2024 |
Luckner, Marcin; Łysak, Agnieszka; Archanowicz-Kudelska, Katarzyna Modelling 15-Minute City Work and Education Amenities Using Surveys and Simulations Inproceedings Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings), University of Gdańsk, 2024. Abstract | Links | BibTeX | Tags: 15-minute city, behaviour modelling, survey analytics, transport simulation @inproceedings{Luckner2024a, title = {Modelling 15-Minute City Work and Education Amenities Using Surveys and Simulations}, author = {Marcin Luckner and Agnieszka Łysak and Katarzyna Archanowicz-Kudelska}, doi = {10.62036/isd.2024.77}, year = {2024}, date = {2024-01-01}, booktitle = {Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings)}, journal = {Proceedings of the 32nd International Conference on Information Systems Development}, publisher = {University of Gdańsk}, abstract = {Modern cities, against global plans promoting sustainability, are still being designed and built with a primary focus on the needs of drivers. Planning concepts, such as a 15-minute city, aim to minimise car usage by assuring quick access to vital urban functions within walking distance. However, their application needs information about achievability and viability. This work presents a model that combines qualitative and quantitative studies on travel duration from home to school and work. The survey data are a base for a model that calculates connections between the actual locations visited by the respondents and calculates travel parameters. The study performed among parents from three primary schools showed that over 56% of travel to schools can be covered by public transport in less than 15 minutes and that the benefits of using a car on longer travel to work are limited. }, keywords = {15-minute city, behaviour modelling, survey analytics, transport simulation}, pubstate = {published}, tppubtype = {inproceedings} } Modern cities, against global plans promoting sustainability, are still being designed and built with a primary focus on the needs of drivers. Planning concepts, such as a 15-minute city, aim to minimise car usage by assuring quick access to vital urban functions within walking distance. However, their application needs information about achievability and viability. This work presents a model that combines qualitative and quantitative studies on travel duration from home to school and work. The survey data are a base for a model that calculates connections between the actual locations visited by the respondents and calculates travel parameters. The study performed among parents from three primary schools showed that over 56% of travel to schools can be covered by public transport in less than 15 minutes and that the benefits of using a car on longer travel to work are limited. |
Łysak, Agnieszka; Luckner, Marcin Deep Learning Residential Building Segmentation for Evaluation of Suburban Areas Development Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 103–117, Springer Nature Switzerland, 2024, ISSN: 16113349. Abstract | Links | BibTeX | Tags: Computer vision, Deep learning, SegFormer, Semantic segmentation, Transformers @inproceedings{ysak2024, title = {Deep Learning Residential Building Segmentation for Evaluation of Suburban Areas Development}, author = {Agnieszka Łysak and Marcin Luckner}, url = {http://dx.doi.org/10.1007/978-3-031-63783-4_9}, doi = {10.1007/978-3-031-63783-4_9}, issn = {16113349}, year = {2024}, date = {2024-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {14838 LNCS}, pages = {103--117}, publisher = {Springer Nature Switzerland}, abstract = {Deep neural network models are commonly used in computer vision problems, e.g., image segmentation. Convolutional neural networks have been state-of-the-art methods in image processing, but new architectures, such as Transformer-based approaches, have started outperforming previous techniques in many applications. However, those techniques are still not commonly used in urban analyses, mostly performed manually. This paper presents a framework for the residential building semantic segmentation architecture as a tool for automatic urban phenomena monitoring. The method could improve urban decision-making processes with automatic city analysis, which is predisposed to be faster and even more accurate than those made by human researchers. The study compares the application of new deep network architectures with state-of-the-art solutions. The analysed problem is urban functional zone segmentation for the urban sprawl evaluation using targeted land cover map construction. The proposed method monitors the expansion of the city, which, uncontrolled, can cause adverse effects. The method was tested on photos from three residential districts. The first district has been manually segmented by functional zones and used for model training and evaluation. The other two districts have been used for automated segmentation by models' inference to test the robustness of the methodology. The test resulted in 98.2% accuracy.}, keywords = {Computer vision, Deep learning, SegFormer, Semantic segmentation, Transformers}, pubstate = {published}, tppubtype = {inproceedings} } Deep neural network models are commonly used in computer vision problems, e.g., image segmentation. Convolutional neural networks have been state-of-the-art methods in image processing, but new architectures, such as Transformer-based approaches, have started outperforming previous techniques in many applications. However, those techniques are still not commonly used in urban analyses, mostly performed manually. This paper presents a framework for the residential building semantic segmentation architecture as a tool for automatic urban phenomena monitoring. The method could improve urban decision-making processes with automatic city analysis, which is predisposed to be faster and even more accurate than those made by human researchers. The study compares the application of new deep network architectures with state-of-the-art solutions. The analysed problem is urban functional zone segmentation for the urban sprawl evaluation using targeted land cover map construction. The proposed method monitors the expansion of the city, which, uncontrolled, can cause adverse effects. The method was tested on photos from three residential districts. The first district has been manually segmented by functional zones and used for model training and evaluation. The other two districts have been used for automated segmentation by models' inference to test the robustness of the methodology. The test resulted in 98.2% accuracy. |
Luckner, Marcin; Wrona, Przemysław; Grzenda, Maciej; Łysak, Agnieszka Analysing Urban Transport Using Synthetic Journeys Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 118–132, Springer Nature Switzerland, 2024, ISSN: 16113349. Abstract | Links | BibTeX | Tags: public transport, synthetic journeys, Travel mode choice @inproceedings{Luckner2024, title = {Analysing Urban Transport Using Synthetic Journeys}, author = {Marcin Luckner and Przemysław Wrona and Maciej Grzenda and Agnieszka Łysak}, url = {http://dx.doi.org/10.1007/978-3-031-63783-4_10}, doi = {10.1007/978-3-031-63783-4_10}, issn = {16113349}, year = {2024}, date = {2024-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {14838 LNCS}, pages = {118--132}, publisher = {Springer Nature Switzerland}, abstract = {Travel mode choice models make it possible to learn under what conditions people decide to use different means of transport. Typically, such models are based on real trip records provided by respondents, e.g. city inhabitants. However, the question arises of how to scale the insights from an inevitably limited number of trips described in their travel diaries to entire cities. To address the limited availability of real trip records, we propose the Urban Journey System integrating big data platforms, analytic engines, and synthetic data generators for urban transport analysis. First of all, the system makes it possible to generate random synthetic journeys linking origin and destination pairs by producing location pairs using an input probability distribution. For each synthetic journey, the system calculates candidate routes for different travel modes (car, public transport (PT), cycling, and walking). Next, the system calculates Level of Service (LOS) attributes such as travel duration, waiting time and distances involved, assuming both planned and real behaviour of the transport system. This allows us to compare travel parameters for planned and real transits. We validate the system with spatial, schedule and GPS data from the City of Warsaw. We analyse LOS attributes and underlying vehicle trajectories over time to estimate spatio-temporal distributions of features such as travel duration, and number of transfers. We extend this analysis by referring to the travel mode choice model developed for the city.}, keywords = {public transport, synthetic journeys, Travel mode choice}, pubstate = {published}, tppubtype = {inproceedings} } Travel mode choice models make it possible to learn under what conditions people decide to use different means of transport. Typically, such models are based on real trip records provided by respondents, e.g. city inhabitants. However, the question arises of how to scale the insights from an inevitably limited number of trips described in their travel diaries to entire cities. To address the limited availability of real trip records, we propose the Urban Journey System integrating big data platforms, analytic engines, and synthetic data generators for urban transport analysis. First of all, the system makes it possible to generate random synthetic journeys linking origin and destination pairs by producing location pairs using an input probability distribution. For each synthetic journey, the system calculates candidate routes for different travel modes (car, public transport (PT), cycling, and walking). Next, the system calculates Level of Service (LOS) attributes such as travel duration, waiting time and distances involved, assuming both planned and real behaviour of the transport system. This allows us to compare travel parameters for planned and real transits. We validate the system with spatial, schedule and GPS data from the City of Warsaw. We analyse LOS attributes and underlying vehicle trajectories over time to estimate spatio-temporal distributions of features such as travel duration, and number of transfers. We extend this analysis by referring to the travel mode choice model developed for the city. |
2023 |
Grzenda, Maciej; Kaźmierczak, Stanisław; Luckner, Marcin; Borowik, Grzegorz; Mańdziuk, Jacek Evaluation of machine learning methods for impostor detection in web applications Journal Article Expert Systems with Applications, 231 (August 2022), pp. 120736, 2023, ISSN: 09574174. Abstract | Links | BibTeX | Tags: Biometrics, Impostor detection, Keystroke dynamics, Machine learning, Multi-factor authentication, Supervised learning @article{Grzenda2023a, title = {Evaluation of machine learning methods for impostor detection in web applications}, author = {Maciej Grzenda and Stanisław Kaźmierczak and Marcin Luckner and Grzegorz Borowik and Jacek Mańdziuk}, url = {https://doi.org/10.1016/j.eswa.2023.120736}, doi = {10.1016/j.eswa.2023.120736}, issn = {09574174}, year = {2023}, date = {2023-01-01}, journal = {Expert Systems with Applications}, volume = {231}, number = {August 2022}, pages = {120736}, publisher = {Elsevier Ltd}, abstract = {Applying machine learning (ML) methods to multi-factor authentication is becoming increasingly popular. However, there is no comprehensive methodology to evaluate biometric systems based on machine learning in the literature. This paper proposes a general methodology for evaluation the ML-based systems for impostor recognition/detection using biometric traits. This includes creation of learning and testing sets with appropriate size balance (proportion) between these sets, selecting the number of instances coming from different users, evaluation of the influence of the impostors number on their detection rate, and the impact of the number of records representing user's behavior. In addition, we propose how the real data (possibly affected by account takeover attempts) could be used to extend the enrollment data to support the impostor detection. The proposed approach was used for a systematic comparison of an extensive set of ML and statistical methods. For some of them, the false acceptance rate (FAR) close to zero and false rejection rate (FRR) smaller than 0.05 in a supervised experiment were accomplished, proving the merit of certain ML-based approaches. Moreover, using the method proposed in the paper, a classifier trained on experimental data achieved FAR below 0.05 on the real-world data collected at an actual financial web page.}, keywords = {Biometrics, Impostor detection, Keystroke dynamics, Machine learning, Multi-factor authentication, Supervised learning}, pubstate = {published}, tppubtype = {article} } Applying machine learning (ML) methods to multi-factor authentication is becoming increasingly popular. However, there is no comprehensive methodology to evaluate biometric systems based on machine learning in the literature. This paper proposes a general methodology for evaluation the ML-based systems for impostor recognition/detection using biometric traits. This includes creation of learning and testing sets with appropriate size balance (proportion) between these sets, selecting the number of instances coming from different users, evaluation of the influence of the impostors number on their detection rate, and the impact of the number of records representing user's behavior. In addition, we propose how the real data (possibly affected by account takeover attempts) could be used to extend the enrollment data to support the impostor detection. The proposed approach was used for a systematic comparison of an extensive set of ML and statistical methods. For some of them, the false acceptance rate (FAR) close to zero and false rejection rate (FRR) smaller than 0.05 in a supervised experiment were accomplished, proving the merit of certain ML-based approaches. Moreover, using the method proposed in the paper, a classifier trained on experimental data achieved FAR below 0.05 on the real-world data collected at an actual financial web page. |
Grzenda, Maciej; Luckner, Marcin; Wrona, Przemysław Urban Traveller Preference Miner: Modelling Transport Choices with Survey Data Streams Proceeding 13718 LNAI , 2023, ISSN: 16113349. Abstract | Links | BibTeX | Tags: Feature engineering, public transport, Stream mining @proceedings{Grzenda2023, title = {Urban Traveller Preference Miner: Modelling Transport Choices with Survey Data Streams}, author = {Maciej Grzenda and Marcin Luckner and Przemysław Wrona}, doi = {10.1007/978-3-031-26422-1_50}, issn = {16113349}, year = {2023}, date = {2023-01-01}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {13718 LNAI}, pages = {654--657}, abstract = {The unprecedented interest in sustainable transport modes for urban areas raises the question of what makes citizens select environmentally friendly transport modes such as public transport rather than private cars. While travel surveys are conducted to document real transport mode choices, they can also shed light on how these choices are made. In this paper, we demonstrate a system combining survey data with complex information documenting public transport features, as perceived by individual respondents. The system relies on a combination of big data modules to collect vehicle location records and travel planning engines to calculate candidate connection features, including disruptions faced by individuals. Hence a combination of streaming and batch modules is used to transform survey data into instances used to learn classification models. This takes place while taking into account concept drift. Real-life data from the city of Warsaw, including recently collected survey data, location records of trams and buses, and planned and true schedules, are used to demonstrate the system. A video related to this paper is available at https://youtu.be/fTcxUxEMGlk.}, keywords = {Feature engineering, public transport, Stream mining}, pubstate = {published}, tppubtype = {proceedings} } The unprecedented interest in sustainable transport modes for urban areas raises the question of what makes citizens select environmentally friendly transport modes such as public transport rather than private cars. While travel surveys are conducted to document real transport mode choices, they can also shed light on how these choices are made. In this paper, we demonstrate a system combining survey data with complex information documenting public transport features, as perceived by individual respondents. The system relies on a combination of big data modules to collect vehicle location records and travel planning engines to calculate candidate connection features, including disruptions faced by individuals. Hence a combination of streaming and batch modules is used to transform survey data into instances used to learn classification models. This takes place while taking into account concept drift. Real-life data from the city of Warsaw, including recently collected survey data, location records of trams and buses, and planned and true schedules, are used to demonstrate the system. A video related to this paper is available at https://youtu.be/fTcxUxEMGlk. |
Guerra-Manzanares, Alejandro; Bahsi, Hayretdin; Luckner, Marcin Springer Paris, 2023, ISSN: 22638733. Abstract | Links | BibTeX | Tags: Android, Concept drift, Machine learning, Malware detection, Mobile security, Permission @book{Guerra-Manzanares2023, title = {Leveraging the first line of defense: a study on the evolution and usage of android security permissions for enhanced android malware detection}, author = {Alejandro Guerra-Manzanares and Hayretdin Bahsi and Marcin Luckner}, url = {https://doi.org/10.1007/s11416-022-00432-3}, doi = {10.1007/s11416-022-00432-3}, issn = {22638733}, year = {2023}, date = {2023-01-01}, booktitle = {Journal of Computer Virology and Hacking Techniques}, volume = {19}, number = {1}, pages = {65--96}, publisher = {Springer Paris}, abstract = {Android security permissions are built-in security features that constrain what an app can do and access on the system, that is, its privileges. Permissions have been widely used for Android malware detection, mostly in combination with other relevant app attributes. The available set of permissions is dynamic, refined in every new Android OS version release. The refinement process adds new permissions and deprecates others. These changes directly impact the type and prevalence of permissions requested by malware and legitimate applications over time. Furthermore, malware trends and benign apps' inherent evolution influence their requested permissions. Therefore, the usage of these features in machine learning-based malware detection systems is prone to concept drift issues. Despite that, no previous study related to permissions has taken into account concept drift. In this study, we demonstrate that when concept drift is addressed, permissions can generate long-lasting and effective malware detection systems. Furthermore, the discriminatory capabilities of distinct set of features are tested. We found that the initial set of permissions, defined in Android 1.0 (API level 1), are sufficient to build an effective detection model, providing an average 0.93 F1 score in data that spans seven years. In addition, we explored and characterized permissions evolution using local and global interpretation methods. In this regard, the varying importance of individual permissions for malware and benign software recognition tasks over time are analyzed.}, keywords = {Android, Concept drift, Machine learning, Malware detection, Mobile security, Permission}, pubstate = {published}, tppubtype = {book} } Android security permissions are built-in security features that constrain what an app can do and access on the system, that is, its privileges. Permissions have been widely used for Android malware detection, mostly in combination with other relevant app attributes. The available set of permissions is dynamic, refined in every new Android OS version release. The refinement process adds new permissions and deprecates others. These changes directly impact the type and prevalence of permissions requested by malware and legitimate applications over time. Furthermore, malware trends and benign apps' inherent evolution influence their requested permissions. Therefore, the usage of these features in machine learning-based malware detection systems is prone to concept drift issues. Despite that, no previous study related to permissions has taken into account concept drift. In this study, we demonstrate that when concept drift is addressed, permissions can generate long-lasting and effective malware detection systems. Furthermore, the discriminatory capabilities of distinct set of features are tested. We found that the initial set of permissions, defined in Android 1.0 (API level 1), are sufficient to build an effective detection model, providing an average 0.93 F1 score in data that spans seven years. In addition, we explored and characterized permissions evolution using local and global interpretation methods. In this regard, the varying importance of individual permissions for malware and benign software recognition tasks over time are analyzed. |
2022 |
Guerra-Manzanares, Alejandro; Luckner, Marcin; Bahsi, Hayretdin Android malware concept drift using system calls: Detection, characterization and challenges Journal Article Expert Systems with Applications, 206 , pp. 117200, 2022, ISSN: 0957-4174. Abstract | Links | BibTeX | Tags: Android malware, Concept drift, Malware behavior, Malware characterization, Malware detection, Malware evolution, Mobile malware, System calls @article{Guerra2022a, title = {Android malware concept drift using system calls: Detection, characterization and challenges}, author = {Alejandro Guerra-Manzanares and Marcin Luckner and Hayretdin Bahsi}, url = {https://www.sciencedirect.com/science/article/pii/S0957417422005863}, doi = {https://doi.org/10.1016/j.eswa.2022.117200}, issn = {0957-4174}, year = {2022}, date = {2022-01-01}, journal = {Expert Systems with Applications}, volume = {206}, pages = {117200}, abstract = {The majority of Android malware detection solutions have focused on the achievement of high performance in old and short snapshots of historical data, which makes them prone to lack the generalization and adaptation capabilities needed to discriminate effectively new malware trends in an extended time span. These approaches analyze the phenomenon from a stationary point of view, neglecting malware evolution and its degenerative impact on detection models as new data emerge, the so-called concept drift. This research proposes a novel method to detect and effectively address concept drift in Android malware detection and demonstrates the results in a seven-year-long data set. The proposed solution manages to keep high-performance metrics over a long period of time and minimizes model retraining efforts by using data sets belonging to short periods. Different timestamps are evaluated in the experimental setup and their impact on the detection performance is compared. Additionally, the characterization of concept drift in Android malware is performed by leveraging the inner workings of the proposed solution. In this regard, the discriminatory properties of the important features are analyzed at various time horizons.}, keywords = {Android malware, Concept drift, Malware behavior, Malware characterization, Malware detection, Malware evolution, Mobile malware, System calls}, pubstate = {published}, tppubtype = {article} } The majority of Android malware detection solutions have focused on the achievement of high performance in old and short snapshots of historical data, which makes them prone to lack the generalization and adaptation capabilities needed to discriminate effectively new malware trends in an extended time span. These approaches analyze the phenomenon from a stationary point of view, neglecting malware evolution and its degenerative impact on detection models as new data emerge, the so-called concept drift. This research proposes a novel method to detect and effectively address concept drift in Android malware detection and demonstrates the results in a seven-year-long data set. The proposed solution manages to keep high-performance metrics over a long period of time and minimizes model retraining efforts by using data sets belonging to short periods. Different timestamps are evaluated in the experimental setup and their impact on the detection performance is compared. Additionally, the characterization of concept drift in Android malware is performed by leveraging the inner workings of the proposed solution. In this regard, the discriminatory properties of the important features are analyzed at various time horizons. |
Guerra-Manzanares, Alejandro; Luckner, Marcin; Bahsi, Hayretdin Concept drift and cross-device behavior: Challenges and implications for effective android malware detection Journal Article Computers & Security, 120 , pp. 102757, 2022, ISSN: 0167-4048. Abstract | Links | BibTeX | Tags: Android, Android emulator, Concept drift, Malware detection, Mobile security, Real device, Smartphone @article{Guerra2022, title = {Concept drift and cross-device behavior: Challenges and implications for effective android malware detection}, author = {Alejandro Guerra-Manzanares and Marcin Luckner and Hayretdin Bahsi}, url = {https://www.sciencedirect.com/science/article/pii/S0167404822001523}, doi = {https://doi.org/10.1016/j.cose.2022.102757}, issn = {0167-4048}, year = {2022}, date = {2022-01-01}, journal = {Computers & Security}, volume = {120}, pages = {102757}, abstract = {The large body of Android malware research has demonstrated that machine learning methods can provide high performance for detecting Android malware. However, the vast majority of studies underestimate the evolving nature of the threat landscape, which requires the creation of a model life-cycle to ensure effective continuous detection in real-world settings over time. In this study, we modeled the concept drift issue of Android malware detection, encompassing the years between 2011 and 2018, using dynamic feature sets (i.e., system calls) derived from Android apps. The relevant studies in the literature have not focused on the timestamp selection approach and its critical impact on effective drift modeling. We evaluated and compared distinct timestamp alternatives. Our experimental results show that a widely used timestamp in the literature yields poor results over time and that enhanced concept drift handling is achieved when an app internal timestamp was used. Additionally, this study sheds light on the usage of distinct data sources and their impact on concept drift modeling. We identified that dynamic features obtained for individual apps from different data sources (i.e., emulator and real device) show significant differences that can distort the modeling results. Therefore, the data sources should be considered and their fusion preferably avoided while creating the training and testing data sets. Our analysis is supported using a global interpretation method to comprehend and characterize the evolution of Android apps throughout the years from a data source-related perspective.}, keywords = {Android, Android emulator, Concept drift, Malware detection, Mobile security, Real device, Smartphone}, pubstate = {published}, tppubtype = {article} } The large body of Android malware research has demonstrated that machine learning methods can provide high performance for detecting Android malware. However, the vast majority of studies underestimate the evolving nature of the threat landscape, which requires the creation of a model life-cycle to ensure effective continuous detection in real-world settings over time. In this study, we modeled the concept drift issue of Android malware detection, encompassing the years between 2011 and 2018, using dynamic feature sets (i.e., system calls) derived from Android apps. The relevant studies in the literature have not focused on the timestamp selection approach and its critical impact on effective drift modeling. We evaluated and compared distinct timestamp alternatives. Our experimental results show that a widely used timestamp in the literature yields poor results over time and that enhanced concept drift handling is achieved when an app internal timestamp was used. Additionally, this study sheds light on the usage of distinct data sources and their impact on concept drift modeling. We identified that dynamic features obtained for individual apps from different data sources (i.e., emulator and real device) show significant differences that can distort the modeling results. Therefore, the data sources should be considered and their fusion preferably avoided while creating the training and testing data sets. Our analysis is supported using a global interpretation method to comprehend and characterize the evolution of Android apps throughout the years from a data source-related perspective. |
Wrona, Przemysław; Grzenda, Maciej; Luckner, Marcin Streaming Detection of Significant Delay Changes in Public Transport Systems Inproceedings Derek, Groen; de Mulatier, Clélia; Maciej, Paszynski; V, Krzhizhanovskaya Valeria; J, Dongarra Jack; A, Sloot Peter M (Ed.): Computational Science – ICCS 2022, pp. 486–499, Springer International Publishing, Cham, 2022, ISBN: 978-3-031-08760-8. @inproceedings{Wrona2022, title = {Streaming Detection of Significant Delay Changes in Public Transport Systems}, author = {Przemysław Wrona and Maciej Grzenda and Marcin Luckner}, editor = {Groen Derek and Clélia de Mulatier and Paszynski Maciej and Krzhizhanovskaya Valeria V and Dongarra Jack J and Sloot Peter M A}, isbn = {978-3-031-08760-8}, year = {2022}, date = {2022-01-01}, booktitle = {Computational Science – ICCS 2022}, pages = {486--499}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Public transport systems are expected to reduce pollution and contribute to sustainable development. However, disruptions in public transport such as delays may negatively affect mobility choices. To quantify delays, aggregated data from vehicle location systems are frequently used. However, delays observed at individual stops are caused inter alia by fluctuations in running times and the knock-on effects of delays occurring in other locations. Hence, in this work, we propose both a method detecting significant delays and a reference architecture, relying on the stream processing engines in which the method is implemented. The method can complement the calculation of delays defined as deviation from schedules. This provides both online rather than batch identification of significant and repetitive delays, and resilience to the limited quality of location data. The method we propose can be used with different change detectors, such as ADWIN, applied to a location data stream shuffled to individual edges of a transport graph. It can detect in an online manner at which edges statistically significant delays are observed and at which edges delays arise and are reduced. Such detections can be used to model mobility choices and quantify the impact of regular rather than random disruptions on feasible trips with multimodal trip modelling engines. The evaluation performed with the public transport data of over 2000 vehicles confirms the merits of the method and reveals that a limited-size subgraph of a transport system graph causes statistically significant delays.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Public transport systems are expected to reduce pollution and contribute to sustainable development. However, disruptions in public transport such as delays may negatively affect mobility choices. To quantify delays, aggregated data from vehicle location systems are frequently used. However, delays observed at individual stops are caused inter alia by fluctuations in running times and the knock-on effects of delays occurring in other locations. Hence, in this work, we propose both a method detecting significant delays and a reference architecture, relying on the stream processing engines in which the method is implemented. The method can complement the calculation of delays defined as deviation from schedules. This provides both online rather than batch identification of significant and repetitive delays, and resilience to the limited quality of location data. The method we propose can be used with different change detectors, such as ADWIN, applied to a location data stream shuffled to individual edges of a transport graph. It can detect in an online manner at which edges statistically significant delays are observed and at which edges delays arise and are reduced. Such detections can be used to model mobility choices and quantify the impact of regular rather than random disruptions on feasible trips with multimodal trip modelling engines. The evaluation performed with the public transport data of over 2000 vehicles confirms the merits of the method and reveals that a limited-size subgraph of a transport system graph causes statistically significant delays. |
Luckner, Marcin; Krzemińska, Izabella; Wawrzyniak, Piotr; Legierski, Jarosław Estimating Population Density Without Contravening Citizen's Privacy: Warsaw Use Case Journal Article IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52 (7), pp. 4494–4506, 2022. @article{Luckner2022, title = {Estimating Population Density Without Contravening Citizen's Privacy: Warsaw Use Case}, author = {Marcin Luckner and Izabella Krzemińska and Piotr Wawrzyniak and Jarosław Legierski}, year = {2022}, date = {2022-01-01}, journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems}, volume = {52}, number = {7}, pages = {4494--4506}, publisher = {IEEE}, abstract = {Spatial data on a cellular network load can be used to develop commercial and public services. However, such data is calculated based on individual users’ behavior and can contravene their privacy rights. Moreover, direct tracking of individual devices violates the European Union’s regulations. To solve this issue, we propose to use data aggregated in individual cells of the public land mobile network without tracking an individual mobile device in the entire process. To prove that the proposed data collection method is useful, we compared the obtained results with a closed-circuit television system in an estimation of the number of people. The proposed system is sensitive enough to detect untypical global events in an urban area and distinguish transport demand zones of various types as we showed on real data from the City of Warsaw. }, keywords = {}, pubstate = {published}, tppubtype = {article} } Spatial data on a cellular network load can be used to develop commercial and public services. However, such data is calculated based on individual users’ behavior and can contravene their privacy rights. Moreover, direct tracking of individual devices violates the European Union’s regulations. To solve this issue, we propose to use data aggregated in individual cells of the public land mobile network without tracking an individual mobile device in the entire process. To prove that the proposed data collection method is useful, we compared the obtained results with a closed-circuit television system in an estimation of the number of people. The proposed system is sensitive enough to detect untypical global events in an urban area and distinguish transport demand zones of various types as we showed on real data from the City of Warsaw. |
2021 |
Wachulec, Małgorzata; Luckner, Marcin Fault detection of jet engine heat sensor Journal Article Procedia Computer Science, 192 , pp. 844–852, 2021, ISSN: 18770509. Abstract | Links | BibTeX | Tags: Anomaly detection, Oil temperature sensor, Outlier detection, Sister engines, Time series @article{Wachulec2021, title = {Fault detection of jet engine heat sensor}, author = {Małgorzata Wachulec and Marcin Luckner}, url = {https://doi.org/10.1016/j.procs.2021.08.087}, doi = {10.1016/j.procs.2021.08.087}, issn = {18770509}, year = {2021}, date = {2021-01-01}, journal = {Procedia Computer Science}, volume = {192}, pages = {844--852}, publisher = {Elsevier B.V.}, abstract = {This paper presents an algorithm predicting oil level and temperature sensor (OLTS) failure to replace it before it carries serious costs. OLTS sensor showing too high oil temperature cockpit indications is a driver of significant air turnback events and commanded in-flight shutdown (IFSD). A prediction of sensor malfunction is possible, but an operator requires at least 11 months of historical data. The developed algorithm automates the process of identifying potential failures using a data-driven, dissimilarity based model. It calculates the rolling mean of the oil temperature difference between sister engines for short-term and long-term periods (counted in flights). If the difference between the short-term and long-term means is greater than a set threshold at least confirmation window times, it sets an alert. The proposed model requires less than three months of data to detect the malfunction, with the final F1 score measured on the test set equal to 0.71.}, keywords = {Anomaly detection, Oil temperature sensor, Outlier detection, Sister engines, Time series}, pubstate = {published}, tppubtype = {article} } This paper presents an algorithm predicting oil level and temperature sensor (OLTS) failure to replace it before it carries serious costs. OLTS sensor showing too high oil temperature cockpit indications is a driver of significant air turnback events and commanded in-flight shutdown (IFSD). A prediction of sensor malfunction is possible, but an operator requires at least 11 months of historical data. The developed algorithm automates the process of identifying potential failures using a data-driven, dissimilarity based model. It calculates the rolling mean of the oil temperature difference between sister engines for short-term and long-term periods (counted in flights). If the difference between the short-term and long-term means is greater than a set threshold at least confirmation window times, it sets an alert. The proposed model requires less than three months of data to detect the malfunction, with the final F1 score measured on the test set equal to 0.71. |
Luckner, Marcin; Krzemińska, Izabella; Wawrzyniak, Piotr; Legierski, Jarosław Contravening Citizen's Privacy : Warsaw Use Case Journal Article IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1–13, 2021. Abstract | Links | BibTeX | Tags: Data models, Data privacy, Estimation, Privacy, Probes, Trajectory, Urban areas @article{Luckner2021, title = {Contravening Citizen's Privacy : Warsaw Use Case}, author = {Marcin Luckner and Izabella Krzemińska and Piotr Wawrzyniak and Jarosław Legierski}, url = {https://ieeexplore.ieee.org/document/9497518}, year = {2021}, date = {2021-01-01}, journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems}, pages = {1--13}, publisher = {IEEE}, abstract = {Spatial data on a cellular network load can be used to develop commercial and public services. However, such data is calculated based on individual users' behavior and can contravene their privacy rights. Moreover, direct tracking of individual devices violates the European Union's regulations. To solve this issue, we propose to use data aggregated in individual cells of the public land mobile network without tracking an individual mobile device in the entire process. To prove that the proposed data collection method is useful, we compared the obtained results with a closed-circuit television system in an estimation of the number of people. The proposed system is sensitive enough to detect untypical global events in an urban area and distinguish transport demand zones of various types as we showed on real data from the City of Warsaw.}, keywords = {Data models, Data privacy, Estimation, Privacy, Probes, Trajectory, Urban areas}, pubstate = {published}, tppubtype = {article} } Spatial data on a cellular network load can be used to develop commercial and public services. However, such data is calculated based on individual users' behavior and can contravene their privacy rights. Moreover, direct tracking of individual devices violates the European Union's regulations. To solve this issue, we propose to use data aggregated in individual cells of the public land mobile network without tracking an individual mobile device in the entire process. To prove that the proposed data collection method is useful, we compared the obtained results with a closed-circuit television system in an estimation of the number of people. The proposed system is sensitive enough to detect untypical global events in an urban area and distinguish transport demand zones of various types as we showed on real data from the City of Warsaw. |
2020 |
Luckner, Marcin; Grzenda, MacIej; Kunicki, Robert; Legierski, Jaroslaw IoT Architecture for Urban Data-Centric Services and Applications Journal Article ACM Transactions on Internet Technology, 20 (3), 2020, ISSN: 15576051. Abstract | Links | BibTeX | Tags: big data, data processing, Data stream, public transport @article{Luckner2020ab, title = {IoT Architecture for Urban Data-Centric Services and Applications}, author = {Marcin Luckner and MacIej Grzenda and Robert Kunicki and Jaroslaw Legierski}, doi = {10.1145/3396850}, issn = {15576051}, year = {2020}, date = {2020-01-01}, journal = {ACM Transactions on Internet Technology}, volume = {20}, number = {3}, abstract = {In this work, we describe an urban Internet of Things (IoT) architecture, grounded in big data patterns and focused on the needs of cities and their key stakeholders. First, the architecture of the dedicated platform USE4IoT (Urban Service Environment for the Internet of Things), which gathers and processes urban big data and extends the Lambda architecture, is proposed. We describe how the platform was used to make IoT an enabling technology for intelligent transport planning. Moreover, key data processing components vital to provide high-quality IoT data streams in a near-real-time manner are defined. Furthermore, tests showing how the IoT platform described in this study provides a low-latency analytical environment for smart cities are included.}, keywords = {big data, data processing, Data stream, public transport}, pubstate = {published}, tppubtype = {article} } In this work, we describe an urban Internet of Things (IoT) architecture, grounded in big data patterns and focused on the needs of cities and their key stakeholders. First, the architecture of the dedicated platform USE4IoT (Urban Service Environment for the Internet of Things), which gathers and processes urban big data and extends the Lambda architecture, is proposed. We describe how the platform was used to make IoT an enabling technology for intelligent transport planning. Moreover, key data processing components vital to provide high-quality IoT data streams in a near-real-time manner are defined. Furthermore, tests showing how the IoT platform described in this study provides a low-latency analytical environment for smart cities are included. |
Luckner, Marcin; ł, Rafa Automatic detection of changes in signal strength characteristics in a wi-fi network for an indoor localisation system Journal Article Sensors (Switzerland), 20 (7), pp. 1–13, 2020, ISSN: 14248220. Abstract | Links | BibTeX | Tags: Fingerprinting, Indoor localisation system, Quality of Service, System deployment and maintenance, Wi-Fi network @article{Luckner2020c, title = {Automatic detection of changes in signal strength characteristics in a wi-fi network for an indoor localisation system}, author = {Marcin Luckner and Rafa{ł} Górak}, doi = {10.3390/s20071828}, issn = {14248220}, year = {2020}, date = {2020-01-01}, journal = {Sensors (Switzerland)}, volume = {20}, number = {7}, pages = {1--13}, abstract = {This paper faces the issue of changing the received signal strength (RSS) from an observed access point (AP). Such a change can reduce the Quality of Service (QoS) of a Wi-Fi-based Indoor Localisation System. We have proposed a dynamic system based on an estimator of RSS using the readings from other APs. Using an optimal threshold, the algorithm recognises an AP that has changed its characteristics. Next, the system rebuilds the localisation model excluding the changed AP to keep QoS. For the tests, we simulated a change in the analysed Wi-Fi network by replacing the measured RSS by an RSS obtained from the same AP model that lies in another place inside the same multi-floor building. The algorithm was evaluated in simulations of an isolated single-floor building, a single-floor building and a multi-floor building. The mean increase of the localisation error obtained by the system varies from 0.25 to 0.61 m after the RSS changes, whereas the error increase without using the system is between 1.21 and 1.98 m. The system can be applied to any service based on a Wi-Fi network for various kinds of changes like a reconfiguration of the network, a local malfunction or ageing of the infrastructure.}, keywords = {Fingerprinting, Indoor localisation system, Quality of Service, System deployment and maintenance, Wi-Fi network}, pubstate = {published}, tppubtype = {article} } This paper faces the issue of changing the received signal strength (RSS) from an observed access point (AP). Such a change can reduce the Quality of Service (QoS) of a Wi-Fi-based Indoor Localisation System. We have proposed a dynamic system based on an estimator of RSS using the readings from other APs. Using an optimal threshold, the algorithm recognises an AP that has changed its characteristics. Next, the system rebuilds the localisation model excluding the changed AP to keep QoS. For the tests, we simulated a change in the analysed Wi-Fi network by replacing the measured RSS by an RSS obtained from the same AP model that lies in another place inside the same multi-floor building. The algorithm was evaluated in simulations of an isolated single-floor building, a single-floor building and a multi-floor building. The mean increase of the localisation error obtained by the system varies from 0.25 to 0.61 m after the RSS changes, whereas the error increase without using the system is between 1.21 and 1.98 m. The system can be applied to any service based on a Wi-Fi network for various kinds of changes like a reconfiguration of the network, a local malfunction or ageing of the infrastructure. |
Luckner, Marcin; ł, Rafa Automatic detection of changes in signal strength characteristics in a wi-fi network for an indoor localisation system Journal Article Sensors (Switzerland), 20 (7), pp. 1–13, 2020, ISSN: 14248220. Abstract | Links | BibTeX | Tags: Fingerprinting, Indoor localisation system, Quality of Service, System deployment and maintenance, Wi-Fi network @article{Luckner2020b, title = {Automatic detection of changes in signal strength characteristics in a wi-fi network for an indoor localisation system}, author = {Marcin Luckner and Rafa{ł} Górak}, doi = {10.3390/s20071828}, issn = {14248220}, year = {2020}, date = {2020-01-01}, journal = {Sensors (Switzerland)}, volume = {20}, number = {7}, pages = {1--13}, abstract = {This paper faces the issue of changing the received signal strength (RSS) from an observed access point (AP). Such a change can reduce the Quality of Service (QoS) of a Wi-Fi-based Indoor Localisation System. We have proposed a dynamic system based on an estimator of RSS using the readings from other APs. Using an optimal threshold, the algorithm recognises an AP that has changed its characteristics. Next, the system rebuilds the localisation model excluding the changed AP to keep QoS. For the tests, we simulated a change in the analysed Wi-Fi network by replacing the measured RSS by an RSS obtained from the same AP model that lies in another place inside the same multi-floor building. The algorithm was evaluated in simulations of an isolated single-floor building, a single-floor building and a multi-floor building. The mean increase of the localisation error obtained by the system varies from 0.25 to 0.61 m after the RSS changes, whereas the error increase without using the system is between 1.21 and 1.98 m. The system can be applied to any service based on a Wi-Fi network for various kinds of changes like a reconfiguration of the network, a local malfunction or ageing of the infrastructure.}, keywords = {Fingerprinting, Indoor localisation system, Quality of Service, System deployment and maintenance, Wi-Fi network}, pubstate = {published}, tppubtype = {article} } This paper faces the issue of changing the received signal strength (RSS) from an observed access point (AP). Such a change can reduce the Quality of Service (QoS) of a Wi-Fi-based Indoor Localisation System. We have proposed a dynamic system based on an estimator of RSS using the readings from other APs. Using an optimal threshold, the algorithm recognises an AP that has changed its characteristics. Next, the system rebuilds the localisation model excluding the changed AP to keep QoS. For the tests, we simulated a change in the analysed Wi-Fi network by replacing the measured RSS by an RSS obtained from the same AP model that lies in another place inside the same multi-floor building. The algorithm was evaluated in simulations of an isolated single-floor building, a single-floor building and a multi-floor building. The mean increase of the localisation error obtained by the system varies from 0.25 to 0.61 m after the RSS changes, whereas the error increase without using the system is between 1.21 and 1.98 m. The system can be applied to any service based on a Wi-Fi network for various kinds of changes like a reconfiguration of the network, a local malfunction or ageing of the infrastructure. |
Luckner, Marcin; Grzenda, MacIej; Kunicki, Robert; Legierski, Jaroslaw IoT Architecture for Urban Data-Centric Services and Applications Journal Article ACM Transactions on Internet Technology, 20 (3), 2020, ISSN: 15576051. Abstract | Links | BibTeX | Tags: big data, data processing, Data stream, public transport @article{Luckner2020a, title = {IoT Architecture for Urban Data-Centric Services and Applications}, author = {Marcin Luckner and MacIej Grzenda and Robert Kunicki and Jaroslaw Legierski}, doi = {10.1145/3396850}, issn = {15576051}, year = {2020}, date = {2020-01-01}, journal = {ACM Transactions on Internet Technology}, volume = {20}, number = {3}, abstract = {In this work, we describe an urban Internet of Things (IoT) architecture, grounded in big data patterns and focused on the needs of cities and their key stakeholders. First, the architecture of the dedicated platform USE4IoT (Urban Service Environment for the Internet of Things), which gathers and processes urban big data and extends the Lambda architecture, is proposed. We describe how the platform was used to make IoT an enabling technology for intelligent transport planning. Moreover, key data processing components vital to provide high-quality IoT data streams in a near-real-time manner are defined. Furthermore, tests showing how the IoT platform described in this study provides a low-latency analytical environment for smart cities are included.}, keywords = {big data, data processing, Data stream, public transport}, pubstate = {published}, tppubtype = {article} } In this work, we describe an urban Internet of Things (IoT) architecture, grounded in big data patterns and focused on the needs of cities and their key stakeholders. First, the architecture of the dedicated platform USE4IoT (Urban Service Environment for the Internet of Things), which gathers and processes urban big data and extends the Lambda architecture, is proposed. We describe how the platform was used to make IoT an enabling technology for intelligent transport planning. Moreover, key data processing components vital to provide high-quality IoT data streams in a near-real-time manner are defined. Furthermore, tests showing how the IoT platform described in this study provides a low-latency analytical environment for smart cities are included. |
2019 |
Luckner, Marcin Practical web spam lifelong machine learning system with automatic adjustment to current lifecycle phase Journal Article Security and Communication Networks, 2019 , 2019, ISSN: 19390122. Abstract | Links | BibTeX | Tags: @article{Luckner2019ab, title = {Practical web spam lifelong machine learning system with automatic adjustment to current lifecycle phase}, author = {Marcin Luckner}, doi = {10.1155/2019/6587020}, issn = {19390122}, year = {2019}, date = {2019-01-01}, journal = {Security and Communication Networks}, volume = {2019}, abstract = {Machine learning techniques are a standard approach in spam detection. Their quality depends on the quality of the learning set, and when the set is out of date, the quality of classification falls rapidly. The most popular public web spam dataset that can be used to train a spam detector-WEBSPAM-UK2007-is over ten years old. Therefore, there is a place for a lifelong machine learning system that can replace the detectors based on a static learning set. In this paper, we propose a novel web spam recognition system. The system automatically rebuilds the learning set to avoid classification based on outdated data. Using a built-in automatic selection of the active classifier the system very quickly attains productive accuracy despite a limited learning set. Moreover, the system automatically rebuilds the learning set using external data from spam traps and popular web services. A test on real data from Quora, Reddit, and Stack Overflow proved the high recognition quality. Both the obtained average accuracy and the F-measure were 0.98 and 0.96 for semiautomatic and full-Automatic mode, respectively.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Machine learning techniques are a standard approach in spam detection. Their quality depends on the quality of the learning set, and when the set is out of date, the quality of classification falls rapidly. The most popular public web spam dataset that can be used to train a spam detector-WEBSPAM-UK2007-is over ten years old. Therefore, there is a place for a lifelong machine learning system that can replace the detectors based on a static learning set. In this paper, we propose a novel web spam recognition system. The system automatically rebuilds the learning set to avoid classification based on outdated data. Using a built-in automatic selection of the active classifier the system very quickly attains productive accuracy despite a limited learning set. Moreover, the system automatically rebuilds the learning set using external data from spam traps and popular web services. A test on real data from Quora, Reddit, and Stack Overflow proved the high recognition quality. Both the obtained average accuracy and the F-measure were 0.98 and 0.96 for semiautomatic and full-Automatic mode, respectively. |
Bukowski, Mateusz; Luckner, Marcin; Kunicki, Robert Estimation of Free Space on Car Park Using Computer Vision Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 316–325, 2019, ISSN: 21945357. Abstract | Links | BibTeX | Tags: @inproceedings{Bukowski2019b, title = {Estimation of Free Space on Car Park Using Computer Vision Algorithms}, author = {Mateusz Bukowski and Marcin Luckner and Robert Kunicki}, doi = {10.1007/978-3-030-13273-6_30}, issn = {21945357}, year = {2019}, date = {2019-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {920}, pages = {316--325}, abstract = {A system for monitoring of vacant parking spots can save drivers a lot of time and costs. Other citizens can benefit from a reduction of pollutions too. In our work, we proposed the computer vision system that estimates free space in a car park. The system uses three separate estimation methods based on various approaches to the estimation issue. The free car park area is recognised on a video frame by as the broadest cohesive area, the largest group of pixels with similar colours, and background for parked cars. The raw results of the estimations are aggregated by a Multi-Layer Perceptron to obtain the final estimate. The test on real data from the City of Warsaw showed that the system reaches 95% accuracy. Moreover, the results were compared with the registers from the parking machines to estimate a gap between covered payment and the accurate number of parked cars.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } A system for monitoring of vacant parking spots can save drivers a lot of time and costs. Other citizens can benefit from a reduction of pollutions too. In our work, we proposed the computer vision system that estimates free space in a car park. The system uses three separate estimation methods based on various approaches to the estimation issue. The free car park area is recognised on a video frame by as the broadest cohesive area, the largest group of pixels with similar colours, and background for parked cars. The raw results of the estimations are aggregated by a Multi-Layer Perceptron to obtain the final estimate. The test on real data from the City of Warsaw showed that the system reaches 95% accuracy. Moreover, the results were compared with the registers from the parking machines to estimate a gap between covered payment and the accurate number of parked cars. |
Wilkowski, Artur; Mykhalevych, Ihor; Luckner, Marcin City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 326–336, 2019, ISSN: 21945357. Abstract | Links | BibTeX | Tags: Computer vision, Detection, Tracking, Traffic monitoring @inproceedings{Wilkowski2019b, title = {City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms}, author = {Artur Wilkowski and Ihor Mykhalevych and Marcin Luckner}, doi = {10.1007/978-3-030-13273-6_31}, issn = {21945357}, year = {2019}, date = {2019-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {920}, pages = {326--336}, abstract = {In this paper there are proposed methods and algorithms supporting city traffic controllers in effective perception and analysis of the visual information from the public transport monitoring system implemented in the City of Warsaw. To achieve this goal, public transport vehicles must be recognised and tracked in camera view. In this work, we describe a structure and give preliminary results for the detection and tracking system proposed. The algorithms discussed in this paper uses background subtraction to extract moving vehicles from the scene and the classification system to reject objects that are not city buses. Furthermore, a custom tracking module is utilized to enable labeling of city buses instances. During the test performed in the City of Warsaw the system was able to successfully detect 89% bus instances giving less than 15% erroneous detections.}, keywords = {Computer vision, Detection, Tracking, Traffic monitoring}, pubstate = {published}, tppubtype = {inproceedings} } In this paper there are proposed methods and algorithms supporting city traffic controllers in effective perception and analysis of the visual information from the public transport monitoring system implemented in the City of Warsaw. To achieve this goal, public transport vehicles must be recognised and tracked in camera view. In this work, we describe a structure and give preliminary results for the detection and tracking system proposed. The algorithms discussed in this paper uses background subtraction to extract moving vehicles from the scene and the classification system to reject objects that are not city buses. Furthermore, a custom tracking module is utilized to enable labeling of city buses instances. During the test performed in the City of Warsaw the system was able to successfully detect 89% bus instances giving less than 15% erroneous detections. |
Grzenda, Maciej; Kunicki, Robert; ł, Jaros; Luckner, Marcin Big data w analizie funkcjonowania systemu komunikacji miejskiej Incollection Ocena wpływu miejskich projektów transportowych Programu Operacyjnego Infrastruktura i Środowisko, pp. 116–137, Centrum Unijnych Projektów Transportowych, 2019. BibTeX | Tags: @incollection{Grzenda2019b, title = {Big data w analizie funkcjonowania systemu komunikacji miejskiej}, author = {Maciej Grzenda and Robert Kunicki and Jaros{ł}aw Legierski and Marcin Luckner}, year = {2019}, date = {2019-01-01}, booktitle = {Ocena wpływu miejskich projektów transportowych Programu Operacyjnego Infrastruktura i Środowisko}, pages = {116--137}, publisher = {Centrum Unijnych Projektów Transportowych}, keywords = {}, pubstate = {published}, tppubtype = {incollection} } |
Luckner, Marcin; Gad, Michal; Sobkowiak, Pawel Antyscam-Practical web spam classifier Journal Article International Journal of Electronics and Telecommunications, 65 (4), pp. 713–722, 2019, ISSN: 23001933. Abstract | Links | BibTeX | Tags: Automatic classification, Imbalanced sets classification, Machine learning, Spam detection, Web spam detection @article{Luckner2019c, title = {Antyscam-Practical web spam classifier}, author = {Marcin Luckner and Michal Gad and Pawel Sobkowiak}, doi = {10.24425/ijet.2019.130255}, issn = {23001933}, year = {2019}, date = {2019-01-01}, journal = {International Journal of Electronics and Telecommunications}, volume = {65}, number = {4}, pages = {713--722}, abstract = {To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting-up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period.}, keywords = {Automatic classification, Imbalanced sets classification, Machine learning, Spam detection, Web spam detection}, pubstate = {published}, tppubtype = {article} } To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting-up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period. |
Luckner, Marcin; Gad, Michal; Sobkowiak, Pawel Antyscam-Practical web spam classifier Journal Article International Journal of Electronics and Telecommunications, 65 (4), pp. 713–722, 2019, ISSN: 23001933. Abstract | Links | BibTeX | Tags: Automatic classification, Imbalanced sets classification, Machine learning, Spam detection, Web spam detection @article{Luckner2019b, title = {Antyscam-Practical web spam classifier}, author = {Marcin Luckner and Michal Gad and Pawel Sobkowiak}, doi = {10.24425/ijet.2019.130255}, issn = {23001933}, year = {2019}, date = {2019-01-01}, journal = {International Journal of Electronics and Telecommunications}, volume = {65}, number = {4}, pages = {713--722}, abstract = {To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting-up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period.}, keywords = {Automatic classification, Imbalanced sets classification, Machine learning, Spam detection, Web spam detection}, pubstate = {published}, tppubtype = {article} } To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting-up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period. |
Bukowski, Mateusz; Luckner, Marcin; Kunicki, Robert Estimation of Free Space on Car Park Using Computer Vision Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 316–325, 2019, ISSN: 21945357. Abstract | Links | BibTeX | Tags: @inproceedings{Bukowski2019, title = {Estimation of Free Space on Car Park Using Computer Vision Algorithms}, author = {Mateusz Bukowski and Marcin Luckner and Robert Kunicki}, doi = {10.1007/978-3-030-13273-6_30}, issn = {21945357}, year = {2019}, date = {2019-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {920}, pages = {316--325}, abstract = {A system for monitoring of vacant parking spots can save drivers a lot of time and costs. Other citizens can benefit from a reduction of pollutions too. In our work, we proposed the computer vision system that estimates free space in a car park. The system uses three separate estimation methods based on various approaches to the estimation issue. The free car park area is recognised on a video frame by as the broadest cohesive area, the largest group of pixels with similar colours, and background for parked cars. The raw results of the estimations are aggregated by a Multi-Layer Perceptron to obtain the final estimate. The test on real data from the City of Warsaw showed that the system reaches 95% accuracy. Moreover, the results were compared with the registers from the parking machines to estimate a gap between covered payment and the accurate number of parked cars.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } A system for monitoring of vacant parking spots can save drivers a lot of time and costs. Other citizens can benefit from a reduction of pollutions too. In our work, we proposed the computer vision system that estimates free space in a car park. The system uses three separate estimation methods based on various approaches to the estimation issue. The free car park area is recognised on a video frame by as the broadest cohesive area, the largest group of pixels with similar colours, and background for parked cars. The raw results of the estimations are aggregated by a Multi-Layer Perceptron to obtain the final estimate. The test on real data from the City of Warsaw showed that the system reaches 95% accuracy. Moreover, the results were compared with the registers from the parking machines to estimate a gap between covered payment and the accurate number of parked cars. |
Wilkowski, Artur; Mykhalevych, Ihor; Luckner, Marcin City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 326–336, 2019, ISSN: 21945357. Abstract | Links | BibTeX | Tags: Computer vision, Detection, Tracking, Traffic monitoring @inproceedings{Wilkowski2019, title = {City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms}, author = {Artur Wilkowski and Ihor Mykhalevych and Marcin Luckner}, doi = {10.1007/978-3-030-13273-6_31}, issn = {21945357}, year = {2019}, date = {2019-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {920}, pages = {326--336}, abstract = {In this paper there are proposed methods and algorithms supporting city traffic controllers in effective perception and analysis of the visual information from the public transport monitoring system implemented in the City of Warsaw. To achieve this goal, public transport vehicles must be recognised and tracked in camera view. In this work, we describe a structure and give preliminary results for the detection and tracking system proposed. The algorithms discussed in this paper uses background subtraction to extract moving vehicles from the scene and the classification system to reject objects that are not city buses. Furthermore, a custom tracking module is utilized to enable labeling of city buses instances. During the test performed in the City of Warsaw the system was able to successfully detect 89% bus instances giving less than 15% erroneous detections.}, keywords = {Computer vision, Detection, Tracking, Traffic monitoring}, pubstate = {published}, tppubtype = {inproceedings} } In this paper there are proposed methods and algorithms supporting city traffic controllers in effective perception and analysis of the visual information from the public transport monitoring system implemented in the City of Warsaw. To achieve this goal, public transport vehicles must be recognised and tracked in camera view. In this work, we describe a structure and give preliminary results for the detection and tracking system proposed. The algorithms discussed in this paper uses background subtraction to extract moving vehicles from the scene and the classification system to reject objects that are not city buses. Furthermore, a custom tracking module is utilized to enable labeling of city buses instances. During the test performed in the City of Warsaw the system was able to successfully detect 89% bus instances giving less than 15% erroneous detections. |
Grzenda, Maciej; Kunicki, Robert; Legierski, Jarosław; Luckner, Marcin Big data w analizie funkcjonowania systemu komunikacji miejskiej Incollection Ocena wpływu miejskich projektów transportowych Programu Operacyjnego Infrastruktura i Środowisko, pp. 116–137, Centrum Unijnych Projektów Transportowych, 2019. BibTeX | Tags: @incollection{Grzenda2019, title = {Big data w analizie funkcjonowania systemu komunikacji miejskiej}, author = {Maciej Grzenda and Robert Kunicki and Jarosław Legierski and Marcin Luckner}, year = {2019}, date = {2019-01-01}, booktitle = {Ocena wpływu miejskich projektów transportowych Programu Operacyjnego Infrastruktura i Środowisko}, pages = {116--137}, publisher = {Centrum Unijnych Projektów Transportowych}, keywords = {}, pubstate = {published}, tppubtype = {incollection} } |
Luckner, Marcin Practical web spam lifelong machine learning system with automatic adjustment to current lifecycle phase Journal Article Security and Communication Networks, 2019 , 2019, ISSN: 19390122. Abstract | Links | BibTeX | Tags: @article{Luckner2019a, title = {Practical web spam lifelong machine learning system with automatic adjustment to current lifecycle phase}, author = {Marcin Luckner}, doi = {10.1155/2019/6587020}, issn = {19390122}, year = {2019}, date = {2019-01-01}, journal = {Security and Communication Networks}, volume = {2019}, abstract = {Machine learning techniques are a standard approach in spam detection. Their quality depends on the quality of the learning set, and when the set is out of date, the quality of classification falls rapidly. The most popular public web spam dataset that can be used to train a spam detector-WEBSPAM-UK2007-is over ten years old. Therefore, there is a place for a lifelong machine learning system that can replace the detectors based on a static learning set. In this paper, we propose a novel web spam recognition system. The system automatically rebuilds the learning set to avoid classification based on outdated data. Using a built-in automatic selection of the active classifier the system very quickly attains productive accuracy despite a limited learning set. Moreover, the system automatically rebuilds the learning set using external data from spam traps and popular web services. A test on real data from Quora, Reddit, and Stack Overflow proved the high recognition quality. Both the obtained average accuracy and the F-measure were 0.98 and 0.96 for semiautomatic and full-Automatic mode, respectively.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Machine learning techniques are a standard approach in spam detection. Their quality depends on the quality of the learning set, and when the set is out of date, the quality of classification falls rapidly. The most popular public web spam dataset that can be used to train a spam detector-WEBSPAM-UK2007-is over ten years old. Therefore, there is a place for a lifelong machine learning system that can replace the detectors based on a static learning set. In this paper, we propose a novel web spam recognition system. The system automatically rebuilds the learning set to avoid classification based on outdated data. Using a built-in automatic selection of the active classifier the system very quickly attains productive accuracy despite a limited learning set. Moreover, the system automatically rebuilds the learning set using external data from spam traps and popular web services. A test on real data from Quora, Reddit, and Stack Overflow proved the high recognition quality. Both the obtained average accuracy and the F-measure were 0.98 and 0.96 for semiautomatic and full-Automatic mode, respectively. |
2018 |
ł, Rafa; Luckner, Marcin Automatic detection of missing access points in indoor positioning system Journal Article Sensors (Switzerland), 18 (11), 2018, ISSN: 14248220. Abstract | Links | BibTeX | Tags: Fingerprinting, Indoor localisation system, System deployment and maintenance @article{Gorak2018b, title = {Automatic detection of missing access points in indoor positioning system}, author = {Rafa{ł} Górak and Marcin Luckner}, url = {https://doi.org/10.3390/s18113595}, doi = {10.3390/s18113595}, issn = {14248220}, year = {2018}, date = {2018-10-01}, journal = {Sensors (Switzerland)}, volume = {18}, number = {11}, abstract = { The paper presents a Wi-Fi-based indoor localisation system. It consists of two main parts, the localisation model and an Access Points (APs) detection module. The system uses a received signal strength (RSS) gathered by multiple mobile terminals to detect which AP should be included in the localisation model and whether the model needs to be updated (rebuilt). The rebuilding of the localisation model prevents the localisation system from a significant loss of accuracy. The proposed automatic detection of missing APs has a universal character and it can be applied to any Wi-Fi localisation model which was created using the fingerprinting method. The paper considers the localisation model based on the Random Forest algorithm. The system was tested on data collected inside a multi-floor academic building. The proposed implementation reduced the mean horizontal error by 5.5 m and the classification error for the floor's prediction by 0.26 in case of a serious malfunction of a Wi-Fi infrastructure. Several simulations were performed, taking into account different occupancy scenarios as well as different numbers of missing APs. The simulations proved that the system correctly detects missing and present APs in the Wi-Fi infrastructure. },keywords = {Fingerprinting, Indoor localisation system, System deployment and maintenance}, pubstate = {published}, tppubtype = {article} } <p>The paper presents a Wi-Fi-based indoor localisation system. It consists of two main parts, the localisation model and an Access Points (APs) detection module. The system uses a received signal strength (RSS) gathered by multiple mobile terminals to detect which AP should be included in the localisation model and whether the model needs to be updated (rebuilt). The rebuilding of the localisation model prevents the localisation system from a significant loss of accuracy. The proposed automatic detection of missing APs has a universal character and it can be applied to any Wi-Fi localisation model which was created using the fingerprinting method. The paper considers the localisation model based on the Random Forest algorithm. The system was tested on data collected inside a multi-floor academic building. The proposed implementation reduced the mean horizontal error by 5.5 m and the classification error for the floor's prediction by 0.26 in case of a serious malfunction of a Wi-Fi infrastructure. Several simulations were performed, taking into account different occupancy scenarios as well as different numbers of missing APs. The simulations proved that the system correctly detects missing and present APs in the Wi-Fi infrastructure.</p> |
ł, Rafa; Luckner, Marcin Automatic detection of missing access points in indoor positioning system Journal Article Sensors (Switzerland), 18 (11), 2018, ISSN: 14248220. Abstract | Links | BibTeX | Tags: Fingerprinting, Indoor localisation system, System deployment and maintenance @article{Gorak2018, title = {Automatic detection of missing access points in indoor positioning system}, author = {Rafa{ł} Górak and Marcin Luckner}, url = {https://doi.org/10.3390/s18113595}, doi = {10.3390/s18113595}, issn = {14248220}, year = {2018}, date = {2018-10-01}, journal = {Sensors (Switzerland)}, volume = {18}, number = {11}, abstract = {textlessptextgreaterThe paper presents a Wi-Fi-based indoor localisation system. It consists of two main parts, the localisation model and an Access Points (APs) detection module. The system uses a received signal strength (RSS) gathered by multiple mobile terminals to detect which AP should be included in the localisation model and whether the model needs to be updated (rebuilt). The rebuilding of the localisation model prevents the localisation system from a significant loss of accuracy. The proposed automatic detection of missing APs has a universal character and it can be applied to any Wi-Fi localisation model which was created using the fingerprinting method. The paper considers the localisation model based on the Random Forest algorithm. The system was tested on data collected inside a multi-floor academic building. The proposed implementation reduced the mean horizontal error by 5.5 m and the classification error for the floor's prediction by 0.26 in case of a serious malfunction of a Wi-Fi infrastructure. Several simulations were performed, taking into account different occupancy scenarios as well as different numbers of missing APs. The simulations proved that the system correctly detects missing and present APs in the Wi-Fi infrastructure.textless/ptextgreater}, keywords = {Fingerprinting, Indoor localisation system, System deployment and maintenance}, pubstate = {published}, tppubtype = {article} } textlessptextgreaterThe paper presents a Wi-Fi-based indoor localisation system. It consists of two main parts, the localisation model and an Access Points (APs) detection module. The system uses a received signal strength (RSS) gathered by multiple mobile terminals to detect which AP should be included in the localisation model and whether the model needs to be updated (rebuilt). The rebuilding of the localisation model prevents the localisation system from a significant loss of accuracy. The proposed automatic detection of missing APs has a universal character and it can be applied to any Wi-Fi localisation model which was created using the fingerprinting method. The paper considers the localisation model based on the Random Forest algorithm. The system was tested on data collected inside a multi-floor academic building. The proposed implementation reduced the mean horizontal error by 5.5 m and the classification error for the floor's prediction by 0.26 in case of a serious malfunction of a Wi-Fi infrastructure. Several simulations were performed, taking into account different occupancy scenarios as well as different numbers of missing APs. The simulations proved that the system correctly detects missing and present APs in the Wi-Fi infrastructure.textless/ptextgreater |
Epperlein, J; Legierski, J; Luckner, M; č, Mare J; Nair, R The use of presence data in modelling demand for transportation Miscellaneous 2018. @misc{Epperlein2018b, title = {The use of presence data in modelling demand for transportation}, author = {J Epperlein and J Legierski and M Luckner and J Mare{č}ek and R Nair}, year = {2018}, date = {2018-01-01}, booktitle = {arXiv}, abstract = {Copyright textcopyright 2018, arXiv, All rights reserved. We consider the applicability of the data from operators of cellular systems to modelling demand for transportation. While individual-level data may contain precise paths of movement, stringent privacy rules prohibit their use without consent. Presence data aggregate the individual-level data to information on the numbers of transactions at each base transceiver station (BTS) per each time period. Our work is aimed at demonstrating value of such aggregate data for mobility management while maintaining privacy of users. In particular, given mobile subscriber activity aggregated to short time intervals for a zone, a convex optimisation problem estimates most likely transitions between zones. We demonstrate the method on presence data from Warsaw, Poland, and compare with official demand estimates obtained with classical econometric methods.}, keywords = {}, pubstate = {published}, tppubtype = {misc} } Copyright textcopyright 2018, arXiv, All rights reserved. We consider the applicability of the data from operators of cellular systems to modelling demand for transportation. While individual-level data may contain precise paths of movement, stringent privacy rules prohibit their use without consent. Presence data aggregate the individual-level data to information on the numbers of transactions at each base transceiver station (BTS) per each time period. Our work is aimed at demonstrating value of such aggregate data for mobility management while maintaining privacy of users. In particular, given mobile subscriber activity aggregated to short time intervals for a zone, a convex optimisation problem estimates most likely transitions between zones. We demonstrate the method on presence data from Warsaw, Poland, and compare with official demand estimates obtained with classical econometric methods. |
Epperlein, J; Legierski, J; Luckner, M; č, Mare J; Nair, R The use of presence data in modelling demand for transportation Miscellaneous 2018. @misc{Epperlein2018, title = {The use of presence data in modelling demand for transportation}, author = {J Epperlein and J Legierski and M Luckner and J Mare{č}ek and R Nair}, year = {2018}, date = {2018-01-01}, booktitle = {arXiv}, abstract = {Copyright textcopyright 2018, arXiv, All rights reserved. We consider the applicability of the data from operators of cellular systems to modelling demand for transportation. While individual-level data may contain precise paths of movement, stringent privacy rules prohibit their use without consent. Presence data aggregate the individual-level data to information on the numbers of transactions at each base transceiver station (BTS) per each time period. Our work is aimed at demonstrating value of such aggregate data for mobility management while maintaining privacy of users. In particular, given mobile subscriber activity aggregated to short time intervals for a zone, a convex optimisation problem estimates most likely transitions between zones. We demonstrate the method on presence data from Warsaw, Poland, and compare with official demand estimates obtained with classical econometric methods.}, keywords = {}, pubstate = {published}, tppubtype = {misc} } Copyright textcopyright 2018, arXiv, All rights reserved. We consider the applicability of the data from operators of cellular systems to modelling demand for transportation. While individual-level data may contain precise paths of movement, stringent privacy rules prohibit their use without consent. Presence data aggregate the individual-level data to information on the numbers of transactions at each base transceiver station (BTS) per each time period. Our work is aimed at demonstrating value of such aggregate data for mobility management while maintaining privacy of users. In particular, given mobile subscriber activity aggregated to short time intervals for a zone, a convex optimisation problem estimates most likely transitions between zones. We demonstrate the method on presence data from Warsaw, Poland, and compare with official demand estimates obtained with classical econometric methods. |
2017 |
Luckner, Marcin; ł, Pawe; ł, Pawe Public transport stops state detection and propagation warsaw use case Inproceedings SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, pp. 235–241, 2017, ISBN: 9789897582417. Abstract | Links | BibTeX | Tags: Data mining, Events detection, Extract informations, Geographic information systems, Geography, Markup languages @inproceedings{Luckner2017cb, title = {Public transport stops state detection and propagation warsaw use case}, author = {Marcin Luckner and Pawe{ł} Kobojek and Pawe{ł} Zawistowski}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025476306&partnerID=40&md5=794077ac781c41cadefc7b7173a8a979}, isbn = {9789897582417}, year = {2017}, date = {2017-01-01}, booktitle = {SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems}, pages = {235--241}, abstract = {Publication of information on public transport in a form acceptable to third-party developers can improve a quality of services offered to the citizens. Usually, published data are limited to localisations of the stops and the schedules. However, a public transport model based on these data is incomplete without information about a current state of the stops. In this paper, we present a system that observes public sources of information on public transport such as Twitter feeds and official web pages hosted by the City of Warsaw. The incoming messages are parsed to extract information on events that concern public transport lines and stops. Extracted information allows us to detect a current state of the stops and to create linguistically independent and spatial oriented information in Geography Markup Language format that can be published using a web service. The system has been tested on real data from Warsaw district and the suburban zones. textcopyright 2017 by SCITEPRESS Science and Technology Publications, Lda. All Rights Reserved.}, keywords = {Data mining, Events detection, Extract informations, Geographic information systems, Geography, Markup languages}, pubstate = {published}, tppubtype = {inproceedings} } Publication of information on public transport in a form acceptable to third-party developers can improve a quality of services offered to the citizens. Usually, published data are limited to localisations of the stops and the schedules. However, a public transport model based on these data is incomplete without information about a current state of the stops. In this paper, we present a system that observes public sources of information on public transport such as Twitter feeds and official web pages hosted by the City of Warsaw. The incoming messages are parsed to extract information on events that concern public transport lines and stops. Extracted information allows us to detect a current state of the stops and to create linguistically independent and spatial oriented information in Geography Markup Language format that can be published using a web service. The system has been tested on real data from Warsaw district and the suburban zones. textcopyright 2017 by SCITEPRESS Science and Technology Publications, Lda. All Rights Reserved. |
ń, Kamil Bre; ł, Maciej Cho; Luckner, Marcin Evil-AP - Mobile man-in-the-middle threat Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 617–627, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Brenski2017b, title = {Evil-AP - Mobile man-in-the-middle threat}, author = {Kamil Bre{ń}ski and Maciej Cho{ł}uj and Marcin Luckner}, doi = {10.1007/978-3-319-59105-6_53}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10244 LNCS}, pages = {617--627}, abstract = {textcopyright IFIP International Federation for Information Processing 2017. Clients of public hotspots are exposed to various threats including a man-in-the-middle attacks. To stress existing threats we created the Evil-AP application for demonstrating a man-in-the-middle attack. The application, installed on an Android phone with root permissions, turns on hotspot services and performs network redirection. We tested as the proposed techniques can be used to eavesdrop, redirect, inject, and strip the Internet traffic. A mobility of the created solution together with the wide functionality creates an extremely dangerous tool. Therefore, we concluded our work with good practices that allow the users to avoid similar threats as described in our work.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } textcopyright IFIP International Federation for Information Processing 2017. Clients of public hotspots are exposed to various threats including a man-in-the-middle attacks. To stress existing threats we created the Evil-AP application for demonstrating a man-in-the-middle attack. The application, installed on an Android phone with root permissions, turns on hotspot services and performs network redirection. We tested as the proposed techniques can be used to eavesdrop, redirect, inject, and strip the Internet traffic. A mobility of the created solution together with the wide functionality creates an extremely dangerous tool. Therefore, we concluded our work with good practices that allow the users to avoid similar threats as described in our work. |
Luckner, Marcin; Karwowski, Jan Estimation of Delays for Individual Trams to Monitor Issues in Public Transport Infrastructure Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 518–527, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2017bb, title = {Estimation of Delays for Individual Trams to Monitor Issues in Public Transport Infrastructure}, author = {Marcin Luckner and Jan Karwowski}, doi = {10.1007/978-3-319-67074-4_50}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10448 LNAI}, pages = {518--527}, abstract = {From the Publisher: "Does Collective Intelligence (CI) exist and if so, how can it be characterized quantified, and harnessed? Questions such as these continue to be hotly debated within both the scientific and philosophical communities. Yet few researchers working in the fields of artificial intelligence or distributed computing doubt CI's enormous potential value to the future of computing. Unfortunately, for lack of a rigorous, formal theory of Collective Intelligence, most attempts to analyze CI systems have been disappointing, at best. In Computational Collective Intelligence, Professor Tadeusz Szuba does much to rectify that situation by developing, for the first time, both a formal definition of CI and practical guidelines for its assessment and applications." "Working from the ground up, Dr. Szuba begins with a stimulating and insightful discussion of the types of intelligence - including individual, artificial and collective - into which he brings ideas from AI, information theory, and distributed computing, as well as psychology, sociology, animal behavior, cognitive science, and other relevant disciplines. He tackles the problem of computational models for simulating and measuring CI. He explores all theoretically feasible of CI computations and presents a groundbreaking, nondeterministic approach using the Random PROLOG Processor (RPP) as a CI modeling and evaluation tool. He then introduces the Collective Intelligence Quotient (IQS) and develops clear-cut guidelines for measuring it. In the final chapters, he lays the foundation for a dynamic new discipline, Collective Intelligence Engineering (CIE), and considers its potential applications as an organizational restructuring tool."-BOOK JACKET.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } From the Publisher: "Does Collective Intelligence (CI) exist and if so, how can it be characterized quantified, and harnessed? Questions such as these continue to be hotly debated within both the scientific and philosophical communities. Yet few researchers working in the fields of artificial intelligence or distributed computing doubt CI's enormous potential value to the future of computing. Unfortunately, for lack of a rigorous, formal theory of Collective Intelligence, most attempts to analyze CI systems have been disappointing, at best. In Computational Collective Intelligence, Professor Tadeusz Szuba does much to rectify that situation by developing, for the first time, both a formal definition of CI and practical guidelines for its assessment and applications." "Working from the ground up, Dr. Szuba begins with a stimulating and insightful discussion of the types of intelligence - including individual, artificial and collective - into which he brings ideas from AI, information theory, and distributed computing, as well as psychology, sociology, animal behavior, cognitive science, and other relevant disciplines. He tackles the problem of computational models for simulating and measuring CI. He explores all theoretically feasible of CI computations and presents a groundbreaking, nondeterministic approach using the Random PROLOG Processor (RPP) as a CI modeling and evaluation tool. He then introduces the Collective Intelligence Quotient (IQS) and develops clear-cut guidelines for measuring it. In the final chapters, he lays the foundation for a dynamic new discipline, Collective Intelligence Engineering (CIE), and considers its potential applications as an organizational restructuring tool."-BOOK JACKET. |
Luckner, Marcin; ł, Aneta Ros; ń, Izabela Krzemi; ł, Jaros; Kunicki, Robert Clustering of Mobile Subscriber's Location Statistics for Travel Demand Zones Diversity Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 315–326, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2017f, title = {Clustering of Mobile Subscriber's Location Statistics for Travel Demand Zones Diversity}, author = {Marcin Luckner and Aneta Ros{ł}an and Izabela Krzemi{ń}ska and Jaros{ł}aw Legierski and Robert Kunicki}, url = {http://link.springer.com/10.1007/978-3-319-59105-6_27}, doi = {10.1007/978-3-319-59105-6_27}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10244 LNCS}, pages = {315--326}, abstract = {textcopyright IFIP International Federation for Information Processing 2017. Current knowledge on travel demand is necessary to keep a travel demand model up to date. However, the data gathering is a laborious and costly task. One of the approaches to this issues can be the utilisation of mobile data. In this work, we used mobile subscriber's location statistics to define a daily characteristic of mobile events occurrences registered by Base Transceiver Stations (BTS). For types of preprocessed data were tested to create stable clusters of BTS according to registered routines. The obtained results were used to find similar travel demand zones from the Warsaw public transport demand model according to a daily activity of the citizens. The obtained results can be used to update the model or to plan a cohesive strategy of public transport development.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } textcopyright IFIP International Federation for Information Processing 2017. Current knowledge on travel demand is necessary to keep a travel demand model up to date. However, the data gathering is a laborious and costly task. One of the approaches to this issues can be the utilisation of mobile data. In this work, we used mobile subscriber's location statistics to define a daily characteristic of mobile events occurrences registered by Base Transceiver Stations (BTS). For types of preprocessed data were tested to create stable clusters of BTS according to registered routines. The obtained results were used to find similar travel demand zones from the Warsaw public transport demand model according to a daily activity of the citizens. The obtained results can be used to update the model or to plan a cohesive strategy of public transport development. |
Luckner, Marcin; Topolski, Bartosz; Mazurek, Magdalena Application of XGboost algorithm in fingerprinting localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 661–671, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2017ab, title = {Application of XGboost algorithm in fingerprinting localisation task}, author = {Marcin Luckner and Bartosz Topolski and Magdalena Mazurek}, doi = {10.1007/978-3-319-59105-6_57}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10244 LNCS}, pages = {661--671}, abstract = {An Indoor Positioning System (IPS) issues regression and classification challenges in form of an horizontal localisation and a floor detection. We propose to apply the XGBoost algorithm for both tasks. The algorithm uses vectors of Received Signal Strengths from Wi–Fi access points to map the obtained fingerprints into horizontal coordinates and a current floor number. The original application schema for the algorithm to create IPS was proposed. The algorithm was tested using real data from an academic building. The testing data were split into two datasets. The first data set contains signals from all observed access points. The second dataset consist of signals from the academic network infrastructure. The second dataset was created to eliminate temporary hotspots and to improve a stability of the positioning system. The tested algorithm got similar results as reference methods on the wider set of access points. On the limited set the algorithm obtained the best results.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } An Indoor Positioning System (IPS) issues regression and classification challenges in form of an horizontal localisation and a floor detection. We propose to apply the XGBoost algorithm for both tasks. The algorithm uses vectors of Received Signal Strengths from Wi–Fi access points to map the obtained fingerprints into horizontal coordinates and a current floor number. The original application schema for the algorithm to create IPS was proposed. The algorithm was tested using real data from an academic building. The testing data were split into two datasets. The first data set contains signals from all observed access points. The second dataset consist of signals from the academic network infrastructure. The second dataset was created to eliminate temporary hotspots and to improve a stability of the positioning system. The tested algorithm got similar results as reference methods on the wider set of access points. On the limited set the algorithm obtained the best results. |
Luckner, Marcin; ł, Pawe; ł, Pawe Public transport stops state detection and propagation warsaw use case Inproceedings SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, pp. 235–241, 2017, ISBN: 9789897582417. Abstract | Links | BibTeX | Tags: Data mining, Events detection, Extract informations, Geographic information systems, Geography, Markup languages @inproceedings{Luckner2017c, title = {Public transport stops state detection and propagation warsaw use case}, author = {Marcin Luckner and Pawe{ł} Kobojek and Pawe{ł} Zawistowski}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025476306&partnerID=40&md5=794077ac781c41cadefc7b7173a8a979}, isbn = {9789897582417}, year = {2017}, date = {2017-01-01}, booktitle = {SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems}, pages = {235--241}, abstract = {Publication of information on public transport in a form acceptable to third-party developers can improve a quality of services offered to the citizens. Usually, published data are limited to localisations of the stops and the schedules. However, a public transport model based on these data is incomplete without information about a current state of the stops. In this paper, we present a system that observes public sources of information on public transport such as Twitter feeds and official web pages hosted by the City of Warsaw. The incoming messages are parsed to extract information on events that concern public transport lines and stops. Extracted information allows us to detect a current state of the stops and to create linguistically independent and spatial oriented information in Geography Markup Language format that can be published using a web service. The system has been tested on real data from Warsaw district and the suburban zones. textcopyright 2017 by SCITEPRESS Science and Technology Publications, Lda. All Rights Reserved.}, keywords = {Data mining, Events detection, Extract informations, Geographic information systems, Geography, Markup languages}, pubstate = {published}, tppubtype = {inproceedings} } Publication of information on public transport in a form acceptable to third-party developers can improve a quality of services offered to the citizens. Usually, published data are limited to localisations of the stops and the schedules. However, a public transport model based on these data is incomplete without information about a current state of the stops. In this paper, we present a system that observes public sources of information on public transport such as Twitter feeds and official web pages hosted by the City of Warsaw. The incoming messages are parsed to extract information on events that concern public transport lines and stops. Extracted information allows us to detect a current state of the stops and to create linguistically independent and spatial oriented information in Geography Markup Language format that can be published using a web service. The system has been tested on real data from Warsaw district and the suburban zones. textcopyright 2017 by SCITEPRESS Science and Technology Publications, Lda. All Rights Reserved. |
Luckner, Marcin; Karwowski, Jan Estimation of Delays for Individual Trams to Monitor Issues in Public Transport Infrastructure Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 518–527, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2017b, title = {Estimation of Delays for Individual Trams to Monitor Issues in Public Transport Infrastructure}, author = {Marcin Luckner and Jan Karwowski}, doi = {10.1007/978-3-319-67074-4_50}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10448 LNAI}, pages = {518--527}, abstract = {From the Publisher: "Does Collective Intelligence (CI) exist and if so, how can it be characterized quantified, and harnessed? Questions such as these continue to be hotly debated within both the scientific and philosophical communities. Yet few researchers working in the fields of artificial intelligence or distributed computing doubt CI's enormous potential value to the future of computing. Unfortunately, for lack of a rigorous, formal theory of Collective Intelligence, most attempts to analyze CI systems have been disappointing, at best. In Computational Collective Intelligence, Professor Tadeusz Szuba does much to rectify that situation by developing, for the first time, both a formal definition of CI and practical guidelines for its assessment and applications." "Working from the ground up, Dr. Szuba begins with a stimulating and insightful discussion of the types of intelligence - including individual, artificial and collective - into which he brings ideas from AI, information theory, and distributed computing, as well as psychology, sociology, animal behavior, cognitive science, and other relevant disciplines. He tackles the problem of computational models for simulating and measuring CI. He explores all theoretically feasible of CI computations and presents a groundbreaking, nondeterministic approach using the Random PROLOG Processor (RPP) as a CI modeling and evaluation tool. He then introduces the Collective Intelligence Quotient (IQS) and develops clear-cut guidelines for measuring it. In the final chapters, he lays the foundation for a dynamic new discipline, Collective Intelligence Engineering (CIE), and considers its potential applications as an organizational restructuring tool."-BOOK JACKET.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } From the Publisher: "Does Collective Intelligence (CI) exist and if so, how can it be characterized quantified, and harnessed? Questions such as these continue to be hotly debated within both the scientific and philosophical communities. Yet few researchers working in the fields of artificial intelligence or distributed computing doubt CI's enormous potential value to the future of computing. Unfortunately, for lack of a rigorous, formal theory of Collective Intelligence, most attempts to analyze CI systems have been disappointing, at best. In Computational Collective Intelligence, Professor Tadeusz Szuba does much to rectify that situation by developing, for the first time, both a formal definition of CI and practical guidelines for its assessment and applications." "Working from the ground up, Dr. Szuba begins with a stimulating and insightful discussion of the types of intelligence - including individual, artificial and collective - into which he brings ideas from AI, information theory, and distributed computing, as well as psychology, sociology, animal behavior, cognitive science, and other relevant disciplines. He tackles the problem of computational models for simulating and measuring CI. He explores all theoretically feasible of CI computations and presents a groundbreaking, nondeterministic approach using the Random PROLOG Processor (RPP) as a CI modeling and evaluation tool. He then introduces the Collective Intelligence Quotient (IQS) and develops clear-cut guidelines for measuring it. In the final chapters, he lays the foundation for a dynamic new discipline, Collective Intelligence Engineering (CIE), and considers its potential applications as an organizational restructuring tool."-BOOK JACKET. |
ń, Kamil Bre; ł, Maciej Cho; Luckner, Marcin Evil-AP - Mobile man-in-the-middle threat Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 617–627, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Brenski2017, title = {Evil-AP - Mobile man-in-the-middle threat}, author = {Kamil Bre{ń}ski and Maciej Cho{ł}uj and Marcin Luckner}, doi = {10.1007/978-3-319-59105-6_53}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10244 LNCS}, pages = {617--627}, abstract = {textcopyright IFIP International Federation for Information Processing 2017. Clients of public hotspots are exposed to various threats including a man-in-the-middle attacks. To stress existing threats we created the Evil-AP application for demonstrating a man-in-the-middle attack. The application, installed on an Android phone with root permissions, turns on hotspot services and performs network redirection. We tested as the proposed techniques can be used to eavesdrop, redirect, inject, and strip the Internet traffic. A mobility of the created solution together with the wide functionality creates an extremely dangerous tool. Therefore, we concluded our work with good practices that allow the users to avoid similar threats as described in our work.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } textcopyright IFIP International Federation for Information Processing 2017. Clients of public hotspots are exposed to various threats including a man-in-the-middle attacks. To stress existing threats we created the Evil-AP application for demonstrating a man-in-the-middle attack. The application, installed on an Android phone with root permissions, turns on hotspot services and performs network redirection. We tested as the proposed techniques can be used to eavesdrop, redirect, inject, and strip the Internet traffic. A mobility of the created solution together with the wide functionality creates an extremely dangerous tool. Therefore, we concluded our work with good practices that allow the users to avoid similar threats as described in our work. |
Luckner, Marcin; Topolski, Bartosz; Mazurek, Magdalena Application of XGboost algorithm in fingerprinting localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 661–671, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2017a, title = {Application of XGboost algorithm in fingerprinting localisation task}, author = {Marcin Luckner and Bartosz Topolski and Magdalena Mazurek}, doi = {10.1007/978-3-319-59105-6_57}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10244 LNCS}, pages = {661--671}, abstract = {An Indoor Positioning System (IPS) issues regression and classification challenges in form of an horizontal localisation and a floor detection. We propose to apply the XGBoost algorithm for both tasks. The algorithm uses vectors of Received Signal Strengths from Wi–Fi access points to map the obtained fingerprints into horizontal coordinates and a current floor number. The original application schema for the algorithm to create IPS was proposed. The algorithm was tested using real data from an academic building. The testing data were split into two datasets. The first data set contains signals from all observed access points. The second dataset consist of signals from the academic network infrastructure. The second dataset was created to eliminate temporary hotspots and to improve a stability of the positioning system. The tested algorithm got similar results as reference methods on the wider set of access points. On the limited set the algorithm obtained the best results.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } An Indoor Positioning System (IPS) issues regression and classification challenges in form of an horizontal localisation and a floor detection. We propose to apply the XGBoost algorithm for both tasks. The algorithm uses vectors of Received Signal Strengths from Wi–Fi access points to map the obtained fingerprints into horizontal coordinates and a current floor number. The original application schema for the algorithm to create IPS was proposed. The algorithm was tested using real data from an academic building. The testing data were split into two datasets. The first data set contains signals from all observed access points. The second dataset consist of signals from the academic network infrastructure. The second dataset was created to eliminate temporary hotspots and to improve a stability of the positioning system. The tested algorithm got similar results as reference methods on the wider set of access points. On the limited set the algorithm obtained the best results. |
Luckner, Marcin; ł, Aneta Ros; ń, Izabela Krzemi; ł, Jaros; Kunicki, Robert Clustering of Mobile Subscriber's Location Statistics for Travel Demand Zones Diversity Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 315–326, 2017, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2017, title = {Clustering of Mobile Subscriber's Location Statistics for Travel Demand Zones Diversity}, author = {Marcin Luckner and Aneta Ros{ł}an and Izabela Krzemi{ń}ska and Jaros{ł}aw Legierski and Robert Kunicki}, url = {http://link.springer.com/10.1007/978-3-319-59105-6_27}, doi = {10.1007/978-3-319-59105-6_27}, issn = {16113349}, year = {2017}, date = {2017-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {10244 LNCS}, pages = {315--326}, abstract = {textcopyright IFIP International Federation for Information Processing 2017. Current knowledge on travel demand is necessary to keep a travel demand model up to date. However, the data gathering is a laborious and costly task. One of the approaches to this issues can be the utilisation of mobile data. In this work, we used mobile subscriber's location statistics to define a daily characteristic of mobile events occurrences registered by Base Transceiver Stations (BTS). For types of preprocessed data were tested to create stable clusters of BTS according to registered routines. The obtained results were used to find similar travel demand zones from the Warsaw public transport demand model according to a daily activity of the citizens. The obtained results can be used to update the model or to plan a cohesive strategy of public transport development.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } textcopyright IFIP International Federation for Information Processing 2017. Current knowledge on travel demand is necessary to keep a travel demand model up to date. However, the data gathering is a laborious and costly task. One of the approaches to this issues can be the utilisation of mobile data. In this work, we used mobile subscriber's location statistics to define a daily characteristic of mobile events occurrences registered by Base Transceiver Stations (BTS). For types of preprocessed data were tested to create stable clusters of BTS according to registered routines. The obtained results were used to find similar travel demand zones from the Warsaw public transport demand model according to a daily activity of the citizens. The obtained results can be used to update the model or to plan a cohesive strategy of public transport development. |
2016 |
ł, Rafa; Luckner, Marcin Modified random forest algorithm for Wi–Fi indoor localization system Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9876 LNCS (208921), pp. 147–157, 2016, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @article{Gorak2016e, title = {Modified random forest algorithm for Wi–Fi indoor localization system}, author = {Rafa{ł} Górak and Marcin Luckner}, doi = {10.1007/978-3-319-45246-3_14}, issn = {16113349}, year = {2016}, date = {2016-01-01}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {9876 LNCS}, number = {208921}, pages = {147--157}, abstract = {The paper presents a modification of Random Forest approach to the indoor localization problem. The localization solution is based on RSS (Received Signal Strength) from multiple sources of Wi–Fi signal. We analyze two localization models. The first one is built using a straightforward application of a random forest method. The second model is a combination of localization models built for each Access Point from the building's network using similar technique (Random Forests) as for the first model. The modification proposed in the second model gives us a substantial accuracy improvement when compared to the first model. We test also the solution against a network malfunction when some Access Points are turned off as the malfunction immunity is another important feature of the presented localization solution.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The paper presents a modification of Random Forest approach to the indoor localization problem. The localization solution is based on RSS (Received Signal Strength) from multiple sources of Wi–Fi signal. We analyze two localization models. The first one is built using a straightforward application of a random forest method. The second model is a combination of localization models built for each Access Point from the building's network using similar technique (Random Forests) as for the first model. The modification proposed in the second model gives us a substantial accuracy improvement when compared to the first model. We test also the solution against a network malfunction when some Access Points are turned off as the malfunction immunity is another important feature of the presented localization solution. |
Wilkowski, Artur; Luckner, Marcin Low-cost canoe counting system for application in a natural environment Inproceedings Advances in Intelligent Systems and Computing, pp. 705–715, 2016, ISSN: 21945357. Abstract | Links | BibTeX | Tags: Classification with rejection, Computer vision, Pattern recognition @inproceedings{Wilkowski2016b, title = {Low-cost canoe counting system for application in a natural environment}, author = {Artur Wilkowski and Marcin Luckner}, doi = {10.1007/978-3-319-29357-8_61}, issn = {21945357}, year = {2016}, date = {2016-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {440}, pages = {705--715}, abstract = {? Springer International Publishing Switzerland 2016.This paper presents low-cost system for counting canoes and canoeists to control cannoning tourist routes. The created system was implemented on Raspberry Pi 2 and the total cost of the tracking device is less than 200$. The proposed algorithmuses background subtraction and Support Vector Machines to track vessels and recognize canoes among them. The obtained results are rewarding as for low-cost solution. Depending on considered group of objects the accuracy of the algorithm reaches 84, 89.5, and 96% for canoes, vessels, and all objects respectively.}, keywords = {Classification with rejection, Computer vision, Pattern recognition}, pubstate = {published}, tppubtype = {inproceedings} } ? Springer International Publishing Switzerland 2016.This paper presents low-cost system for counting canoes and canoeists to control cannoning tourist routes. The created system was implemented on Raspberry Pi 2 and the total cost of the tracking device is less than 200$. The proposed algorithmuses background subtraction and Support Vector Machines to track vessels and recognize canoes among them. The obtained results are rewarding as for low-cost solution. Depending on considered group of objects the accuracy of the algorithm reaches 84, 89.5, and 96% for canoes, vessels, and all objects respectively. |
ł, Rafa; Luckner, Marcin Long term analysis of the localization model based on Wi-Fi network Inproceedings Studies in Computational Intelligence, pp. 87–96, 2016, ISSN: 1860949X. Abstract | Links | BibTeX | Tags: @inproceedings{Gorak2016bc, title = {Long term analysis of the localization model based on Wi-Fi network}, author = {Rafa{ł} Górak and Marcin Luckner}, doi = {10.1007/978-3-319-31277-4_8}, issn = {1860949X}, year = {2016}, date = {2016-01-01}, booktitle = {Studies in Computational Intelligence}, volume = {642}, pages = {87--96}, abstract = {The paper presents the analysis of long term accuracy of the localization solution based on Wi-Fi signals. The localization model is built using random forest algorithm and it was tested using data collected between years 2012–2014 inside of a six floor building.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The paper presents the analysis of long term accuracy of the localization solution based on Wi-Fi signals. The localization model is built using random forest algorithm and it was tested using data collected between years 2012–2014 inside of a six floor building. |
Luckner, Marcin; ł, Rafa Hybrid algorithm for floor detection using GSM signals in indoor localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 730–741, 2016, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2016ab, title = {Hybrid algorithm for floor detection using GSM signals in indoor localisation task}, author = {Marcin Luckner and Rafa{ł} Górak}, doi = {10.1007/978-3-319-32034-2_61}, issn = {16113349}, year = {2016}, date = {2016-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {9648}, pages = {730--741}, abstract = {The expression of flavin-containing monooxygenases (FMOs) in dog liver microsomes was suggested by a high methimazole S- oxidase activity. When the reaction was catalyzed by dog liver microsomes, apparent Vmax and Km values were 6.3 nmol/min/mg and 14 ? M, respectively. This reaction was highly inhibited (73%) in the presence of imipramine, but it was also weakly affected by trimethylamine, suggesting the involvement of different isoforms. The sequences of dog FMO1 and FMO3 were obtained by reverse transcription-polymerase chain reaction and 5?/3? terminal exten- sion. The cDNAs of dog FMO1 and dog FMO3 encode proteins of 532 amino acids, which contain the NADPH- and FAD-binding sites. The dog FMO1 amino acid sequence is 88, 86, and 89% identical to sequences of human, rabbit, and pig FMO1, respec- tively. The dog FMO3 amino acid sequence is 83, 84, and 82% identical to sequences of human, rabbit, and rat FMO3, respec- tively. Dog FMO1 and dog FMO3 exhibited only 56% identities. The FMO1 and FMO3 recombinant proteins and the FMO1 and FMO3 microsomal proteins migrated with the same mobility (56 kDa), as determined in SDS-polyacrylamide gel electrophoresis and immu- noblotting. By Western blotting, dog FMO1 and dog FMO3 were detected in microsomes from liver and lung but not in kidney microsomes. By Northern blotting, the probe for FMO1 specifically hybridized a 2.6-kilobase (kb) transcript in liver and lung samples only. The probe for FMO3 hybridized two transcripts of approxi- mately 3 and 4.2 kb in the liver and lung samples}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The expression of flavin-containing monooxygenases (FMOs) in dog liver microsomes was suggested by a high methimazole S- oxidase activity. When the reaction was catalyzed by dog liver microsomes, apparent Vmax and Km values were 6.3 nmol/min/mg and 14 ? M, respectively. This reaction was highly inhibited (73%) in the presence of imipramine, but it was also weakly affected by trimethylamine, suggesting the involvement of different isoforms. The sequences of dog FMO1 and FMO3 were obtained by reverse transcription-polymerase chain reaction and 5?/3? terminal exten- sion. The cDNAs of dog FMO1 and dog FMO3 encode proteins of 532 amino acids, which contain the NADPH- and FAD-binding sites. The dog FMO1 amino acid sequence is 88, 86, and 89% identical to sequences of human, rabbit, and pig FMO1, respec- tively. The dog FMO3 amino acid sequence is 83, 84, and 82% identical to sequences of human, rabbit, and rat FMO3, respec- tively. Dog FMO1 and dog FMO3 exhibited only 56% identities. The FMO1 and FMO3 recombinant proteins and the FMO1 and FMO3 microsomal proteins migrated with the same mobility (56 kDa), as determined in SDS-polyacrylamide gel electrophoresis and immu- noblotting. By Western blotting, dog FMO1 and dog FMO3 were detected in microsomes from liver and lung but not in kidney microsomes. By Northern blotting, the probe for FMO1 specifically hybridized a 2.6-kilobase (kb) transcript in liver and lung samples only. The probe for FMO3 hybridized two transcripts of approxi- mately 3 and 4.2 kb in the liver and lung samples |
Luckner, Marcin; ł, Rafa Comparison of floor detection approaches for suburban area Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 782–791, 2016, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2016c, title = {Comparison of floor detection approaches for suburban area}, author = {Marcin Luckner and Rafa{ł} Górak}, doi = {10.1007/978-3-662-49390-8_76}, issn = {16113349}, year = {2016}, date = {2016-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {9622}, pages = {782--791}, abstract = {? Springer-Verlag Berlin Heidelberg 2016.As a part of smart-buildings, indoor localisation systems ? alternative to Global Positioning System localisation ? bring constantly improving results. Several localisation methods works with a horizontal localisation error less than few meters. However, for small suburban houses, horizontal localisation is not as important as detection of the current floor, which in is still a challenge in multi-storey buildings. This paper compares several approaches that can be used in fingerprintingbased floor detection systems. The tests include the following fingerprints: pressure measures, Wi-Fi signals, and two generations of cellular networks signals. The tests have been done in the suburban 3-storey building with underdeveloped Wi-Fi and cellular infrastructure. Notwithstanding, the floor detection based on Received Signal Strength from both infrastructures reached from 98 to 100%. Additionally, we showed that differences in the number of measures and differences in the number of received signals were not a major factor that influenced on accuracy.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } ? Springer-Verlag Berlin Heidelberg 2016.As a part of smart-buildings, indoor localisation systems ? alternative to Global Positioning System localisation ? bring constantly improving results. Several localisation methods works with a horizontal localisation error less than few meters. However, for small suburban houses, horizontal localisation is not as important as detection of the current floor, which in is still a challenge in multi-storey buildings. This paper compares several approaches that can be used in fingerprintingbased floor detection systems. The tests include the following fingerprints: pressure measures, Wi-Fi signals, and two generations of cellular networks signals. The tests have been done in the suburban 3-storey building with underdeveloped Wi-Fi and cellular infrastructure. Notwithstanding, the floor detection based on Received Signal Strength from both infrastructures reached from 98 to 100%. Additionally, we showed that differences in the number of measures and differences in the number of received signals were not a major factor that influenced on accuracy. |
Homenda, Wladyslaw; Luckner, Marcin; Pedrycz, Witold Classification with rejection: Concepts and evaluations Inproceedings Advances in Intelligent Systems and Computing, pp. 413–425, 2016, ISSN: 21945357. Abstract | Links | BibTeX | Tags: Binary classifiers ensemble, Reclassification, Rejection rule @inproceedings{Homenda2016b, title = {Classification with rejection: Concepts and evaluations}, author = {Wladyslaw Homenda and Marcin Luckner and Witold Pedrycz}, doi = {10.1007/978-3-319-19090-7_31}, issn = {21945357}, year = {2016}, date = {2016-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {364}, pages = {413--425}, abstract = {? Springer International Publishing Switzerland 2016.Standard classification process allocates all processed elements to given classes. Such type of classification assumes that there are only native and no foreign elements, i.e., all processed elements are included in given classes. The quality of standard classification can be measured by two factors: numbers of correctly and incorrectly classified elements, called True Positives and False Positives. Admitting foreign elements in standard classification process increases False Positives and, in this way, deteriorates quality of classification. In this context, it is desired to reject foreign elements, i.e., not to assign them to any of given classes. Rejecting foreign elements will reduce the number of false positives, but can also reject native elements reducing True Positives as side effect. Therefore, it is important to build well-designed rejection, which will reject significant part of foreigners and only few natives. In this paper, evaluations of classification with rejection concepts are presented. Three main models: a classification without rejection, a classification with rejection, and a classification with reclassification are presented. The concepts are illustrated by flexible ensembles of binary classifiers with evaluations of eachmodel. The proposed models can be used, in particular, as classifiers working with noised data, where recognized input is not limited to elements of known classes.}, keywords = {Binary classifiers ensemble, Reclassification, Rejection rule}, pubstate = {published}, tppubtype = {inproceedings} } ? Springer International Publishing Switzerland 2016.Standard classification process allocates all processed elements to given classes. Such type of classification assumes that there are only native and no foreign elements, i.e., all processed elements are included in given classes. The quality of standard classification can be measured by two factors: numbers of correctly and incorrectly classified elements, called True Positives and False Positives. Admitting foreign elements in standard classification process increases False Positives and, in this way, deteriorates quality of classification. In this context, it is desired to reject foreign elements, i.e., not to assign them to any of given classes. Rejecting foreign elements will reduce the number of false positives, but can also reject native elements reducing True Positives as side effect. Therefore, it is important to build well-designed rejection, which will reject significant part of foreigners and only few natives. In this paper, evaluations of classification with rejection concepts are presented. Three main models: a classification without rejection, a classification with rejection, and a classification with reclassification are presented. The concepts are illustrated by flexible ensembles of binary classifiers with evaluations of eachmodel. The proposed models can be used, in particular, as classifiers working with noised data, where recognized input is not limited to elements of known classes. |
Luckner, Marcin; ł, Rafa Hybrid algorithm for floor detection using GSM signals in indoor localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 730–741, 2016, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2016a, title = {Hybrid algorithm for floor detection using GSM signals in indoor localisation task}, author = {Marcin Luckner and Rafa{ł} Górak}, doi = {10.1007/978-3-319-32034-2_61}, issn = {16113349}, year = {2016}, date = {2016-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {9648}, pages = {730--741}, abstract = {The expression of flavin-containing monooxygenases (FMOs) in dog liver microsomes was suggested by a high methimazole S- oxidase activity. When the reaction was catalyzed by dog liver microsomes, apparent Vmax and Km values were 6.3 nmol/min/mg and 14 ? M, respectively. This reaction was highly inhibited (73%) in the presence of imipramine, but it was also weakly affected by trimethylamine, suggesting the involvement of different isoforms. The sequences of dog FMO1 and FMO3 were obtained by reverse transcription-polymerase chain reaction and 5?/3? terminal exten- sion. The cDNAs of dog FMO1 and dog FMO3 encode proteins of 532 amino acids, which contain the NADPH- and FAD-binding sites. The dog FMO1 amino acid sequence is 88, 86, and 89% identical to sequences of human, rabbit, and pig FMO1, respec- tively. The dog FMO3 amino acid sequence is 83, 84, and 82% identical to sequences of human, rabbit, and rat FMO3, respec- tively. Dog FMO1 and dog FMO3 exhibited only 56% identities. The FMO1 and FMO3 recombinant proteins and the FMO1 and FMO3 microsomal proteins migrated with the same mobility (56 kDa), as determined in SDS-polyacrylamide gel electrophoresis and immu- noblotting. By Western blotting, dog FMO1 and dog FMO3 were detected in microsomes from liver and lung but not in kidney microsomes. By Northern blotting, the probe for FMO1 specifically hybridized a 2.6-kilobase (kb) transcript in liver and lung samples only. The probe for FMO3 hybridized two transcripts of approxi- mately 3 and 4.2 kb in the liver and lung samples}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The expression of flavin-containing monooxygenases (FMOs) in dog liver microsomes was suggested by a high methimazole S- oxidase activity. When the reaction was catalyzed by dog liver microsomes, apparent Vmax and Km values were 6.3 nmol/min/mg and 14 ? M, respectively. This reaction was highly inhibited (73%) in the presence of imipramine, but it was also weakly affected by trimethylamine, suggesting the involvement of different isoforms. The sequences of dog FMO1 and FMO3 were obtained by reverse transcription-polymerase chain reaction and 5?/3? terminal exten- sion. The cDNAs of dog FMO1 and dog FMO3 encode proteins of 532 amino acids, which contain the NADPH- and FAD-binding sites. The dog FMO1 amino acid sequence is 88, 86, and 89% identical to sequences of human, rabbit, and pig FMO1, respec- tively. The dog FMO3 amino acid sequence is 83, 84, and 82% identical to sequences of human, rabbit, and rat FMO3, respec- tively. Dog FMO1 and dog FMO3 exhibited only 56% identities. The FMO1 and FMO3 recombinant proteins and the FMO1 and FMO3 microsomal proteins migrated with the same mobility (56 kDa), as determined in SDS-polyacrylamide gel electrophoresis and immu- noblotting. By Western blotting, dog FMO1 and dog FMO3 were detected in microsomes from liver and lung but not in kidney microsomes. By Northern blotting, the probe for FMO1 specifically hybridized a 2.6-kilobase (kb) transcript in liver and lung samples only. The probe for FMO3 hybridized two transcripts of approxi- mately 3 and 4.2 kb in the liver and lung samples |
ł, Rafa; Luckner, Marcin Long term analysis of the localization model based on Wi-Fi network Inproceedings Studies in Computational Intelligence, pp. 87–96, 2016, ISSN: 1860949X. Abstract | Links | BibTeX | Tags: @inproceedings{Gorak2016bb, title = {Long term analysis of the localization model based on Wi-Fi network}, author = {Rafa{ł} Górak and Marcin Luckner}, doi = {10.1007/978-3-319-31277-4_8}, issn = {1860949X}, year = {2016}, date = {2016-01-01}, booktitle = {Studies in Computational Intelligence}, volume = {642}, pages = {87--96}, abstract = {The paper presents the analysis of long term accuracy of the localization solution based on Wi-Fi signals. The localization model is built using random forest algorithm and it was tested using data collected between years 2012–2014 inside of a six floor building.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The paper presents the analysis of long term accuracy of the localization solution based on Wi-Fi signals. The localization model is built using random forest algorithm and it was tested using data collected between years 2012–2014 inside of a six floor building. |
Luckner, Marcin; ł, Rafa Comparison of floor detection approaches for suburban area Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 782–791, 2016, ISSN: 16113349. Abstract | Links | BibTeX | Tags: @inproceedings{Luckner2016, title = {Comparison of floor detection approaches for suburban area}, author = {Marcin Luckner and Rafa{ł} Górak}, doi = {10.1007/978-3-662-49390-8_76}, issn = {16113349}, year = {2016}, date = {2016-01-01}, booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, volume = {9622}, pages = {782--791}, abstract = {? Springer-Verlag Berlin Heidelberg 2016.As a part of smart-buildings, indoor localisation systems ? alternative to Global Positioning System localisation ? bring constantly improving results. Several localisation methods works with a horizontal localisation error less than few meters. However, for small suburban houses, horizontal localisation is not as important as detection of the current floor, which in is still a challenge in multi-storey buildings. This paper compares several approaches that can be used in fingerprintingbased floor detection systems. The tests include the following fingerprints: pressure measures, Wi-Fi signals, and two generations of cellular networks signals. The tests have been done in the suburban 3-storey building with underdeveloped Wi-Fi and cellular infrastructure. Notwithstanding, the floor detection based on Received Signal Strength from both infrastructures reached from 98 to 100%. Additionally, we showed that differences in the number of measures and differences in the number of received signals were not a major factor that influenced on accuracy.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } ? Springer-Verlag Berlin Heidelberg 2016.As a part of smart-buildings, indoor localisation systems ? alternative to Global Positioning System localisation ? bring constantly improving results. Several localisation methods works with a horizontal localisation error less than few meters. However, for small suburban houses, horizontal localisation is not as important as detection of the current floor, which in is still a challenge in multi-storey buildings. This paper compares several approaches that can be used in fingerprintingbased floor detection systems. The tests include the following fingerprints: pressure measures, Wi-Fi signals, and two generations of cellular networks signals. The tests have been done in the suburban 3-storey building with underdeveloped Wi-Fi and cellular infrastructure. Notwithstanding, the floor detection based on Received Signal Strength from both infrastructures reached from 98 to 100%. Additionally, we showed that differences in the number of measures and differences in the number of received signals were not a major factor that influenced on accuracy. |
Homenda, Wladyslaw; Luckner, Marcin; Pedrycz, Witold Classification with rejection: Concepts and evaluations Inproceedings Advances in Intelligent Systems and Computing, pp. 413–425, 2016, ISSN: 21945357. Abstract | Links | BibTeX | Tags: Binary classifiers ensemble, Reclassification, Rejection rule @inproceedings{Homenda2016, title = {Classification with rejection: Concepts and evaluations}, author = {Wladyslaw Homenda and Marcin Luckner and Witold Pedrycz}, doi = {10.1007/978-3-319-19090-7_31}, issn = {21945357}, year = {2016}, date = {2016-01-01}, booktitle = {Advances in Intelligent Systems and Computing}, volume = {364}, pages = {413--425}, abstract = {? Springer International Publishing Switzerland 2016.Standard classification process allocates all processed elements to given classes. Such type of classification assumes that there are only native and no foreign elements, i.e., all processed elements are included in given classes. The quality of standard classification can be measured by two factors: numbers of correctly and incorrectly classified elements, called True Positives and False Positives. Admitting foreign elements in standard classification process increases False Positives and, in this way, deteriorates quality of classification. In this context, it is desired to reject foreign elements, i.e., not to assign them to any of given classes. Rejecting foreign elements will reduce the number of false positives, but can also reject native elements reducing True Positives as side effect. Therefore, it is important to build well-designed rejection, which will reject significant part of foreigners and only few natives. In this paper, evaluations of classification with rejection concepts are presented. Three main models: a classification without rejection, a classification with rejection, and a classification with reclassification are presented. The concepts are illustrated by flexible ensembles of binary classifiers with evaluations of eachmodel. The proposed models can be used, in particular, as classifiers working with noised data, where recognized input is not limited to elements of known classes.}, keywords = {Binary classifiers ensemble, Reclassification, Rejection rule}, pubstate = {published}, tppubtype = {inproceedings} } ? Springer International Publishing Switzerland 2016.Standard classification process allocates all processed elements to given classes. Such type of classification assumes that there are only native and no foreign elements, i.e., all processed elements are included in given classes. The quality of standard classification can be measured by two factors: numbers of correctly and incorrectly classified elements, called True Positives and False Positives. Admitting foreign elements in standard classification process increases False Positives and, in this way, deteriorates quality of classification. In this context, it is desired to reject foreign elements, i.e., not to assign them to any of given classes. Rejecting foreign elements will reduce the number of false positives, but can also reject native elements reducing True Positives as side effect. Therefore, it is important to build well-designed rejection, which will reject significant part of foreigners and only few natives. In this paper, evaluations of classification with rejection concepts are presented. Three main models: a classification without rejection, a classification with rejection, and a classification with reclassification are presented. The concepts are illustrated by flexible ensembles of binary classifiers with evaluations of eachmodel. The proposed models can be used, in particular, as classifiers working with noised data, where recognized input is not limited to elements of known classes. |
Publications
2024 |
Modelling 15-Minute City Work and Education Amenities Using Surveys and Simulations Inproceedings Harnessing Opportunities: Reshaping ISD in the post-COVID-19 and Generative AI Era (ISD2024 Proceedings), University of Gdańsk, 2024. |
Deep Learning Residential Building Segmentation for Evaluation of Suburban Areas Development Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 103–117, Springer Nature Switzerland, 2024, ISSN: 16113349. |
Analysing Urban Transport Using Synthetic Journeys Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 118–132, Springer Nature Switzerland, 2024, ISSN: 16113349. |
2023 |
Evaluation of machine learning methods for impostor detection in web applications Journal Article Expert Systems with Applications, 231 (August 2022), pp. 120736, 2023, ISSN: 09574174. |
Urban Traveller Preference Miner: Modelling Transport Choices with Survey Data Streams Proceeding 13718 LNAI , 2023, ISSN: 16113349. |
Springer Paris, 2023, ISSN: 22638733. |
2022 |
Android malware concept drift using system calls: Detection, characterization and challenges Journal Article Expert Systems with Applications, 206 , pp. 117200, 2022, ISSN: 0957-4174. |
Concept drift and cross-device behavior: Challenges and implications for effective android malware detection Journal Article Computers & Security, 120 , pp. 102757, 2022, ISSN: 0167-4048. |
Streaming Detection of Significant Delay Changes in Public Transport Systems Inproceedings Derek, Groen; de Mulatier, Clélia; Maciej, Paszynski; V, Krzhizhanovskaya Valeria; J, Dongarra Jack; A, Sloot Peter M (Ed.): Computational Science – ICCS 2022, pp. 486–499, Springer International Publishing, Cham, 2022, ISBN: 978-3-031-08760-8. |
Estimating Population Density Without Contravening Citizen's Privacy: Warsaw Use Case Journal Article IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52 (7), pp. 4494–4506, 2022. |
2021 |
Fault detection of jet engine heat sensor Journal Article Procedia Computer Science, 192 , pp. 844–852, 2021, ISSN: 18770509. |
Contravening Citizen's Privacy : Warsaw Use Case Journal Article IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1–13, 2021. |
2020 |
IoT Architecture for Urban Data-Centric Services and Applications Journal Article ACM Transactions on Internet Technology, 20 (3), 2020, ISSN: 15576051. |
Automatic detection of changes in signal strength characteristics in a wi-fi network for an indoor localisation system Journal Article Sensors (Switzerland), 20 (7), pp. 1–13, 2020, ISSN: 14248220. |
Automatic detection of changes in signal strength characteristics in a wi-fi network for an indoor localisation system Journal Article Sensors (Switzerland), 20 (7), pp. 1–13, 2020, ISSN: 14248220. |
IoT Architecture for Urban Data-Centric Services and Applications Journal Article ACM Transactions on Internet Technology, 20 (3), 2020, ISSN: 15576051. |
2019 |
Practical web spam lifelong machine learning system with automatic adjustment to current lifecycle phase Journal Article Security and Communication Networks, 2019 , 2019, ISSN: 19390122. |
Estimation of Free Space on Car Park Using Computer Vision Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 316–325, 2019, ISSN: 21945357. |
City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 326–336, 2019, ISSN: 21945357. |
Big data w analizie funkcjonowania systemu komunikacji miejskiej Incollection Ocena wpływu miejskich projektów transportowych Programu Operacyjnego Infrastruktura i Środowisko, pp. 116–137, Centrum Unijnych Projektów Transportowych, 2019. |
Antyscam-Practical web spam classifier Journal Article International Journal of Electronics and Telecommunications, 65 (4), pp. 713–722, 2019, ISSN: 23001933. |
Antyscam-Practical web spam classifier Journal Article International Journal of Electronics and Telecommunications, 65 (4), pp. 713–722, 2019, ISSN: 23001933. |
Estimation of Free Space on Car Park Using Computer Vision Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 316–325, 2019, ISSN: 21945357. |
City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms Inproceedings Advances in Intelligent Systems and Computing, pp. 326–336, 2019, ISSN: 21945357. |
Big data w analizie funkcjonowania systemu komunikacji miejskiej Incollection Ocena wpływu miejskich projektów transportowych Programu Operacyjnego Infrastruktura i Środowisko, pp. 116–137, Centrum Unijnych Projektów Transportowych, 2019. |
Practical web spam lifelong machine learning system with automatic adjustment to current lifecycle phase Journal Article Security and Communication Networks, 2019 , 2019, ISSN: 19390122. |
2018 |
Automatic detection of missing access points in indoor positioning system Journal Article Sensors (Switzerland), 18 (11), 2018, ISSN: 14248220. |
Automatic detection of missing access points in indoor positioning system Journal Article Sensors (Switzerland), 18 (11), 2018, ISSN: 14248220. |
The use of presence data in modelling demand for transportation Miscellaneous 2018. |
The use of presence data in modelling demand for transportation Miscellaneous 2018. |
2017 |
Public transport stops state detection and propagation warsaw use case Inproceedings SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, pp. 235–241, 2017, ISBN: 9789897582417. |
Evil-AP - Mobile man-in-the-middle threat Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 617–627, 2017, ISSN: 16113349. |
Estimation of Delays for Individual Trams to Monitor Issues in Public Transport Infrastructure Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 518–527, 2017, ISSN: 16113349. |
Clustering of Mobile Subscriber's Location Statistics for Travel Demand Zones Diversity Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 315–326, 2017, ISSN: 16113349. |
Application of XGboost algorithm in fingerprinting localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 661–671, 2017, ISSN: 16113349. |
Public transport stops state detection and propagation warsaw use case Inproceedings SMARTGREENS 2017 - Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, pp. 235–241, 2017, ISBN: 9789897582417. |
Estimation of Delays for Individual Trams to Monitor Issues in Public Transport Infrastructure Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 518–527, 2017, ISSN: 16113349. |
Evil-AP - Mobile man-in-the-middle threat Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 617–627, 2017, ISSN: 16113349. |
Application of XGboost algorithm in fingerprinting localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 661–671, 2017, ISSN: 16113349. |
Clustering of Mobile Subscriber's Location Statistics for Travel Demand Zones Diversity Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 315–326, 2017, ISSN: 16113349. |
2016 |
Modified random forest algorithm for Wi–Fi indoor localization system Journal Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9876 LNCS (208921), pp. 147–157, 2016, ISSN: 16113349. |
Low-cost canoe counting system for application in a natural environment Inproceedings Advances in Intelligent Systems and Computing, pp. 705–715, 2016, ISSN: 21945357. |
Long term analysis of the localization model based on Wi-Fi network Inproceedings Studies in Computational Intelligence, pp. 87–96, 2016, ISSN: 1860949X. |
Hybrid algorithm for floor detection using GSM signals in indoor localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 730–741, 2016, ISSN: 16113349. |
Comparison of floor detection approaches for suburban area Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 782–791, 2016, ISSN: 16113349. |
Classification with rejection: Concepts and evaluations Inproceedings Advances in Intelligent Systems and Computing, pp. 413–425, 2016, ISSN: 21945357. |
Hybrid algorithm for floor detection using GSM signals in indoor localisation task Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 730–741, 2016, ISSN: 16113349. |
Long term analysis of the localization model based on Wi-Fi network Inproceedings Studies in Computational Intelligence, pp. 87–96, 2016, ISSN: 1860949X. |
Comparison of floor detection approaches for suburban area Inproceedings Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 782–791, 2016, ISSN: 16113349. |
Classification with rejection: Concepts and evaluations Inproceedings Advances in Intelligent Systems and Computing, pp. 413–425, 2016, ISSN: 21945357. |