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  • 1.
    A. Oliveira, Roger
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    S. Salles, Rafael
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Rönnberg, Sarah K.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Deep Learning for Power Quality with Special Reference to Unsupervised Learning2023In: 27th International Conference on Electricity Distribution (CIRED 2023), IEEE, 2023, p. 935-939, article id 10417Conference paper (Refereed)
  • 2.
    Aadan, Mohammed
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Hybrid encryption method to secure distributed data streaming within Apache Kafka2024Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In the progression of the digital world the urgency of securing data becomes increasingly important and the emergence of modern data pipelines has fueled advances in data management and analysis which provides new opportunities for insights. Thus, due to this age of extensive data sharing and andconnectivity leads to ensuring security for sensitive information while in transit is a critical concern. Among modern prominent data pipelines, Apache Kafka stands as a versatile streaming platform with the ability to manage vast data flows and real-time data processing which has allowed the platform to gain traction, though the growth in prominence has resulted in increased demands for data security.

    This thesis, conducted in collaboration with Basalt AB and provides an exploration of the field of data security in the context of Apache Kafka and involves the development, research, and validation of a proposed prototype with a focus on protective measures during data transmission. The thesis presents a strategy and solution to address these challenges and consists of an encryption method and a customized approach suited for the Apache Kafka environment. The contribution includes showcasing the implementation and deployment of the encryption coupled with the presentation of practical suggestions for the proposed model with the aim of outlining measures to access means for protecting confidential information.

    The full text will be freely available from 2024-12-31 22:22
  • 3.
    Aalbers, Anouschka
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Öberg, Linn
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Agil Kravprioritering: En kvalitativ studie om prioriteringsprocesser inom agil mjukvaruutveckling hos Monitor ERP System AB2021Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Prioritizing requirements is one of the most important and influential steps in the creation of a software product. The process is iterative; it takes place during the entire agile software development. Through prioritizing requirements, it is decided which requirements are to be developed, in which order, and why. 

    The aim of this study is to investigate how companies that design software prioritize requirements and to identify which prioritization methods they might use during this process. The purpose of this study is to gain an understanding for why a well-balanced prioritization is important, which specific prioritization factors give value to a product, as well as identifying how these factors are related to the result. The purpose is also to investigate the difficulties that exist in a prioritization process, and to create an overview of some of the most used prioritization methods in agile software development. 

    This study is conducted in collaboration with the software company Monitor ERP in order to analyze the company's prioritization processes used to develop their business management system Monitor. The method used is a qualitative study that consists of observations of meetings about prioritization processes, and semi-structured interviews. Processing of collected material was done by organizing, analyzing, and compiling results according to concepts and categories that emerged from the literature study. The results documents work processes, common goals, prioritization aspects and challenges in the requirements prioritization at Monitor ERP. 

    A well-balanced prioritization proved to be important to be able to deliver the right functionality on time and to be able to provide dependable estimates of development, which in turn leads to customers gaining confidence in both the product and the company. A number of prioritization factors that give value to the Monitor software were identified, many of which contribute to increasing customer satisfaction and product quality. Monitor ERP does not use any specific prioritization methods, but the development philosophy Minimum Viable Product is used as a basis for their prioritization choices. During the prioritization process, challenges such as limited resources, unpredictable tasks, difficulties with time estimation, and a challenge in balancing customer value and customer focus were experienced.

    Download full text (pdf)
    Agil_Kravprioritering_Aalbers_Öberg
  • 4.
    Aalto, Erik
    KTH, School of Computer Science and Communication (CSC).
    Learning Playlist Representations for Automatic Playlist Generation2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Spotify is currently the worlds leading music streaming ser-vice. As the leader in music streaming the task of providing listeners with music recommendations is vital for Spotify. Listening to playlists is a popular way of consuming music, but traditional recommender systems tend to fo-cus on suggesting songs, albums or artists rather than pro-viding consumers with playlists generated for their needs.

    This thesis presents a scalable and generalizeable approach to music recommendation that performs song selection for the problem of playlist generation. The approach selects tracks related to a playlist theme by finding the charac-terizing variance for a seed playlist and projects candidate songs into the corresponding subspace. Quantitative re-sults shows that the model outperforms a baseline which is taking the full variance into account. By qualitative results the model is also shown to outperform professionally curated playlists in some cases.

    Download full text (pdf)
    fulltext
  • 5.
    Aarno, Daniel
    KTH, School of Computer Science and Communication (CSC), Numerical Analysis and Computer Science, NADA.
    Intention recognition in human machine collaborative systems2007Licentiate thesis, monograph (Other scientific)
    Abstract [en]

    Robot systems have been used extensively during the last decades to provide automation solutions in a number of areas. The majority of the currently deployed automation systems are limited in that the tasks they can solve are required to be repetitive and predicable. One reason for this is the inability of today’s robot systems to understand and reason about the world. Therefore the robotics and artificial intelligence research communities have made significant research efforts to produce more intelligent machines. Although significant progress has been made towards achieving robots that can interact in a human environment there is currently no system that comes close to achieving the reasoning capabilities of humans.

    In order to reduce the complexity of the problem some researchers have proposed an alternative to creating fully autonomous robots capable of operating in human environments. The proposed alternative is to allow fusion of human and machine capabilities. For example, using teleoperation a human can operate at a remote site, which may not be accessible for the operator for a number of reasons, by issuing commands to a remote agent that will act as an extension of the operator’s body.

    Segmentation and recognition of operator generated motions can be used to provide appropriate assistance during task execution in teleoperative and human-machine collaborative settings. The assistance is usually provided in a virtual fixture framework where the level of compliance can be altered online in order to improve the performance in terms of execution time and overall precision. Acquiring, representing and modeling human skills are key research areas in teleoperation, programming-by-demonstration and human-machine collaborative settings. One of the common approaches is to divide the task that the operator is executing into several sub-tasks in order to provide manageable modeling.

    This thesis is focused on two aspects of human-machine collaborative systems. Classfication of an operator’s motion into a predefined state of a manipulation task and assistance during a manipulation task based on virtual fixtures. The particular applications considered consists of manipulation tasks where a human operator controls a robotic manipulator in a cooperative or teleoperative mode.

    A method for online task tracking using adaptive virtual fixtures is presented. Rather than executing a predefined plan, the operator has the ability to avoid unforeseen obstacles and deviate from the model. To allow this, the probability of following a certain trajectory sub-task) is estimated and used to automatically adjusts the compliance of a virtual fixture, thus providing an online decision of how to fixture the movement.

    A layered hidden Markov model is used to model human skills. A gestem classifier that classifies the operator’s motions into basic action-primitives, or gestemes, is evaluated. The gestem classifiers are then used in a layered hidden Markov model to model a simulated teleoperated task. The classification performance is evaluated with respect to noise, number of gestemes, type of the hidden Markov model and the available number of training sequences. The layered hidden Markov model is applied to data recorded during the execution of a trajectory-tracking task in 2D and 3D with a robotic manipulator in order to give qualitative as well as quantitative results for the proposed approach. The results indicate that the layered hidden Markov model is suitable for modeling teleoperative trajectory-tracking tasks and that the layered hidden Markov model is robust with respect to misclassifications in the underlying gestem classifiers.

    Download full text (pdf)
    FULLTEXT01
  • 6.
    Aarno, Daniel
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Sommerfeld, Johan
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Kragic, Danica
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Pugeault, Nicolas
    Kalkan, Sinan
    Woergoetter, Florentin
    Krüger, Norbert
    Early reactive grasping with second order 3D feature relations2008In: Recent Progress In Robotics: Viable Robotic Service To Human / [ed] Lee, S; Suh, IH; Kim, MS, 2008, Vol. 370, p. 91-105Conference paper (Refereed)
    Abstract [en]

    One of the main challenges in the field of robotics is to make robots ubiquitous. To intelligently interact with the world, such robots need to understand the environment and situations around them and react appropriately, they need context-awareness. But how to equip robots with capabilities of gathering and interpreting the necessary information for novel tasks through interaction with the environment and by providing some minimal knowledge in advance? This has been a longterm question and one of the main drives in the field of cognitive system development. The main idea behind the work presented in this paper is that the robot should, like a human infant, learn about objects by interacting with them, forming representations of the objects and their categories that are grounded in its embodiment. For this purpose, we study an early learning of object grasping process where the agent, based on a set of innate reflexes and knowledge about its embodiment. We stress out that this is not the work on grasping, it is a system that interacts with the environment based on relations of 3D visual features generated trough a stereo vision system. We show how geometry, appearance and spatial relations between the features can guide early reactive grasping which can later on be used in a more purposive manner when interacting with the environment.

  • 7.
    Aaro, Gustav
    et al.
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Roos, Daniel
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Carlsson, Niklas
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Toolset for Run-time Dataset Collection of Deep-scene Information2020In: Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), Springer, 2020, p. 224-236Conference paper (Refereed)
    Abstract [en]

    Virtual reality (VR) provides many exciting new application opportunities, but also present new challenges. In contrast to 360° videos that only allow a user to select its viewing direction, in fully immersive VR, users can also move around and interact with objects in the virtual world. To most effectively deliver such services it is therefore important to understand how users move around in relation to such objects. In this paper, we present a methodology and software tool for generating run-time datasets capturing a user’s interactions with such 3D environments, evaluate and compare different object identification methods that we implement within the tool, and use datasets collected with the tool to demonstrate example uses. The tool was developed in Unity, easily integrates with existing Unity applications through the use of periodic calls that extracts information about the environment using different ray-casting methods. The software tool and example datasets are made available with this paper. 

  • 8. Aarts, Fides
    et al.
    Jonsson, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Uijen, Johan
    Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction2010In: Testing Software and Systems: ICTSS 2010, Berlin: Springer-Verlag , 2010, p. 188-204Conference paper (Refereed)
  • 9.
    Aarts, Marcel
    Mälardalen University, School of Innovation, Design and Engineering.
    Using Kinect to interact with presentation software2013Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Imagination Studios is a company specialized in motion capturing and animation. Part of their daily business is working at trade shows where they have a booth to keep close contact with existing customers and also to find new ones. However, usually only two to three people will be working at the booth, and frequently, these people will be in meetings with potential customers. During a time like this, nobody is free to attend to other people checking out the booth. This can result in a potential loss of a new customer. This project seeks a way to alleviate that problem.The idea behind this project was to create an application that trade show visitors can interact with in a playful and innovative way while also giving them a feel of what Imagination Studios is all about while looking for information about the company. To do this it was decided to let users interact with the system by using a Microsoft Kinect. The Kinect allows for easy implementation of a user interface based on motion capturing while also being very cost effective. A new user interface was to be designed as well, without copying already existing solutions and without simply expanding a traditional UI with new elements. To achieve this several design sketches were made, and the most interesting ones were then turned into storyboards. These were then used to decide on the final design, which was then elaborated on by use of video sketches and a collage in Adobe Photoshop.Several tools were used during the actual implementation. For the actual visualization and graphical design, the Unreal Engine 3 in combination with UDK was decided upon. To connect Kinect and Unreal Engine 3, a third party addon called NIUI which makes use of the open source SDK OpenNI was used. For ease of debugging and programming in Unrealscript, the programming language used by the Unreal Engine 3, an addon for Microsoft Visual Studio 2010 called nFringe (Pixel Mine, Inc., 2010) was used.

    Download full text (pdf)
    fulltext
  • 10. Aartsen, M. G.
    et al.
    Abbasi, R.
    Ackermann, M.
    Adams, J.
    Aguilar, J. A.
    Ahlers, M.
    Altmann, D.
    Arguelles, C.
    Auffenberg, J.
    Bai, X.
    Baker, M.
    Barwick, S. W.
    Baum, V.
    Bay, R.
    Beatty, J. J.
    Tjus, J. Becker
    Becker, K. -H
    BenZvi, S.
    Berghaus, P.
    Berley, D.
    Bernardini, E.
    Bernhard, A.
    Besson, D. Z.
    Binder, G.
    Bindig, D.
    Bissok, M.
    Blaufuss, E.
    Blumenthal, J.
    Boersma, David J.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Bohm, C.
    Bose, D.
    Boeser, S.
    Botner, Olga
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Brayeur, L.
    Bretz, H. -P
    Brown, A. M.
    Bruijn, R.
    Casey, J.
    Casier, M.
    Chirkin, D.
    Christov, A.
    Christy, B.
    Clark, K.
    Classen, L.
    Clevermann, F.
    Coenders, S.
    Cohen, S.
    Cowen, D. F.
    Silva, A. H. Cruz
    Danninger, M.
    Daughhetee, J.
    Davis, J. C.
    Day, M.
    De Clercq, C.
    De Ridder, S.
    Desiati, P.
    de Vries, K. D.
    de With, M.
    DeYoung, T.
    Diaz-Velez, J. C.
    Dunkman, M.
    Eagan, R.
    Eberhardt, B.
    Eichmann, B.
    Eisch, J.
    Euler, S.
    Evenson, P. A.
    Fadiran, O.
    Fazely, A. R.
    Fedynitch, A.
    Feintzeig, J.
    Feusels, T.
    Filimonov, K.
    Finley, C.
    Fischer-Wasels, T.
    Flis, S.
    Franckowiak, A.
    Frantzen, K.
    Fuchs, T.
    Gaisser, T. K.
    Gallagher, J.
    Gerhardt, L.
    Gladstone, L.
    Glusenkamp, T.
    Goldschmidt, A.
    Golup, G.
    Gonzalez, J. G.
    Goodman, J. A.
    Gora, D.
    Grandmont, D. T.
    Grant, D.
    Gretskov, P.
    Groh, J. C.
    Gross, A.
    Ha, C.
    Ismail, A. Haj
    Hallen, P.
    Hallgren, Allan
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Halzen, F.
    Hanson, K.
    Hebecker, D.
    Heereman, D.
    Heinen, D.
    Helbing, K.
    Hellauer, R.
    Hickford, S.
    Hill, G. C.
    Hoffman, K. D.
    Hoffmann, R.
    Homeier, A.
    Hoshina, K.
    Huang, F.
    Huelsnitz, W.
    Hulth, P. O.
    Hultqvist, K.
    Hussain, S.
    Ishihara, A.
    Jacobi, E.
    Jacobsen, J.
    Jagielski, K.
    Japaridze, G. S.
    Jero, K.
    Jlelati, O.
    Kaminsky, B.
    Kappes, A.
    Karg, T.
    Karle, A.
    Kauer, M.
    Kelley, J. L.
    Kiryluk, J.
    Klaes, J.
    Klein, S. R.
    Koehne, J. -H
    Kohnen, G.
    Kolanoski, H.
    Koepke, L.
    Kopper, C.
    Kopper, S.
    Koskinen, D. J.
    Kowalski, M.
    Krasberg, M.
    Kriesten, A.
    Krings, K.
    Kroll, G.
    Kunnen, J.
    Kurahashi, N.
    Kuwabara, T.
    Labare, M.
    Landsman, H.
    Larson, M. J.
    Lesiak-Bzdak, M.
    Leuermann, M.
    Leute, J.
    Luenemann, J.
    Macias, O.
    Madsen, J.
    Maggi, G.
    Maruyama, R.
    Mase, K.
    Matis, H. S.
    McNally, F.
    Meagher, K.
    Merck, M.
    Merino, G.
    Meures, T.
    Miarecki, S.
    Middell, E.
    Milke, N.
    Miller, J.
    Mohrmann, L.
    Montaruli, T.
    Morse, R.
    Nahnhauer, R.
    Naumann, U.
    Niederhausen, H.
    Nowicki, S. C.
    Nygren, D. R.
    Obertacke, A.
    Odrowski, S.
    Olivas, A.
    Omairat, A.
    O'Murchadha, A.
    Paul, L.
    Pepper, J. A.
    de los Heros, Carlos Perez
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Pfendner, C.
    Pieloth, D.
    Pinat, E.
    Posselt, J.
    Price, P. B.
    Przybylski, G. T.
    Quinnan, M.
    Raedel, L.
    Rae, I.
    Rameez, M.
    Rawlins, K.
    Redl, P.
    Reimann, R.
    Resconi, E.
    Rhode, W.
    Ribordy, M.
    Richman, M.
    Riedel, B.
    Rodrigues, J. P.
    Rott, C.
    Ruhe, T.
    Ruzybayev, B.
    Ryckbosch, D.
    Saba, S. M.
    Sander, H. -G
    Santander, M.
    Sarkar, S.
    Schatto, K.
    Scheriau, F.
    Schmidt, T.
    Schmitz, M.
    Schoenen, S.
    Schoeneberg, S.
    Schoenwald, A.
    Schukraft, A.
    Schulte, L.
    Schultz, D.
    Schulz, O.
    Secke, D.
    Sestayo, Y.
    Seunarine, S.
    Shanidze, R.
    Sheremata, C.
    Smith, M. W. E.
    Soldin, D.
    Spiczak, G. M.
    Spiering, C.
    Stamatikos, M.
    Stanev, T.
    Stanisha, N. A.
    Stasik, A.
    Stezelberger, T.
    Stokstad, R. G.
    Stoessl, A.
    Strahler, E. A.
    Ström, Rickard
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Strotjohann, N. L.
    Sullivan, G. W.
    Taavola, Henric
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, High Energy Physics.
    Taboada, I.
    Tamburro, A.
    Tepe, A.
    Ter-Antonyan, S.
    Tesic, G.
    Tilav, S.
    Toale, P. A.
    Tobin, M. N.
    Toscano, S.
    Tselengidou, M.
    Unger, E.
    Usner, M.
    Vallecorsa, S.
    van Eijndhoven, N.
    van Overloop, A.
    van Santen, J.
    Vehring, M.
    Voge, M.
    Vraeghe, M.
    Walck, C.
    Waldenmaier, T.
    Wallraff, M.
    Weaver, Ch.
    Wellons, M.
    Wendt, C.
    Westerhoff, S.
    Whitehorn, N.
    Wiebe, K.
    Wiebusch, C. H.
    Williams, D. R.
    Wissing, H.
    Wolf, M.
    Wood, T. R.
    Woschnagg, K.
    Xu, D. L.
    Xu, X. W.
    Yanez, J. P.
    Yodh, G.
    Yoshida, S.
    Zarzhitsky, P.
    Ziemann, J.
    Zierke, S.
    Zoll, M.
    The IceProd framework: Distributed data processing for the IceCube neutrino observatory2015In: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 75, p. 198-211Article in journal (Refereed)
    Abstract [en]

    IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, identify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. This paper presents the first detailed description of IceProd, a lightweight distributed management system designed to meet these requirements. It is driven by a central database in order to manage mass production of simulations and analysis of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of computing resources, including grids and batch systems such as CREAM, HTCondor, and PBS. This is accomplished by a set of dedicated daemons that process job submission in a coordinated fashion through the use of middleware plugins that serve to abstract the details of job submission and job management from the framework. (C) 2014 Elsevier Inc. All rights reserved.

  • 11. Aasi, Parisa
    et al.
    Nunes, Ivan
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Rusu, Lazar
    Hodosi, Georg
    Does Organizational Culture Matter in IT Outsourcing Relationships?2015In: 2015 48TH HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS), IEEE Computer Society, 2015, p. 4691-4699Conference paper (Refereed)
    Abstract [en]

    IT Outsourcing (ITO) is used widely by Multinational Companies (MNCs) as a sourcing strategy today. ITO relationship between service buyer and provider then becomes a crucial issue in achieving expected objectives. This research sheds light on the influence of organizational culture (OC) of the buyer company on its ITO relationship with the provider. More specifically, the influence that OC can have on four significant dimensions of trust, cooperation, communication and commitment in ITO is studied through a qualitative analysis. IT managers of six MNCs were interviewed which exposed the connection between OC and ITO relationship factors. An open communication culture, speed of adaption to change, receiving innovative solutions, flat or hierarchical structures and responsibility degree appeared as the most visible differences between OCs of MNCs influencing ITO relationships. The results can be used for improving the ITO by considering the influence of OC to gain more benefits from outsourcing.

  • 12.
    Aayesha, Aayesha
    et al.
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Nouri, Jalal
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Afzaal, Muhammad
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Wu, Yongchao
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Li, Xiu
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    Weegar, Rebecka
    Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
    An Ensemble Approach for Question-Level Knowledge Tracing2021In: Artificial Intelligence in Education: 22nd International Conference, AIED 2021, Utrecht, The Netherlands, June 14–18, 2021, Proceedings, Part II / [ed] Ido Roll; Danielle McNamara; Sergey Sosnovsky; Rose Luckin; Vania Dimitrova, Cham: Springer , 2021, p. 433-437Conference paper (Refereed)
    Abstract [en]

    Knowledge tracing—where a machine models the students’ knowledge as they interact with coursework—is a well-established area in the field of Artificial Intelligence in Education. In this paper, an ensemble approach is proposed that addresses existing limitations in question-centric knowledge tracing and achieves the goal of predicting future question correctness. The proposed approach consists of two models; one is Light Gradient Boosting Machine (LightGBM) built by incorporating all relevant key features engineered from the data. The second model is a Multiheaded-Self-Attention Knowledge Tracing model (MSAKT) that extracts historical student knowledge of future question by calculating their contextual similarity with previously attempted questions. The proposed model’s effectiveness is evaluated by conducting experiments on a big Kaggle dataset achieving an Area Under ROC Curve (AUC) score of 0.84 with 84% accuracy using 10fold cross-validation.

  • 13.
    Abbahaddou, Yassine
    et al.
    LIX, Ecole Polytechnique IP Paris, France.
    Ennadir, Sofiane
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Lutzeyer, Johannes F.
    LIX, Ecole Polytechnique IP Paris, France.
    Vazirgiannis, Michalis
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS. Ecole Polytechnique, IP Paris, Ecole Polytechnique, IP Paris; KTH Stockholm, Sweden.
    Boström, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Bounding The Expected Robustness Of Graph Neural Networks Subject To Node Feature Attacks2024In: 12th International Conference on Learning Representations, ICLR 2024, International Conference on Learning Representations, ICLR , 2024Conference paper (Refereed)
    Abstract [en]

    Graph Neural Networks (GNNs) have demonstrated state-of-the-art performance in various graph representation learning tasks. Recently, studies revealed their vulnerability to adversarial attacks. In this work, we theoretically define the concept of expected robustness in the context of attributed graphs and relate it to the classical definition of adversarial robustness in the graph representation learning literature. Our definition allows us to derive an upper bound of the expected robustness of Graph Convolutional Networks (GCNs) and Graph Isomorphism Networks subject to node feature attacks. Building on these findings, we connect the expected robustness of GNNs to the orthonormality of their weight matrices and consequently propose an attack-independent, more robust variant of the GCN, called the Graph Convolutional Orthonormal Robust Networks (GCORNs). We further introduce a probabilistic method to estimate the expected robustness, which allows us to evaluate the effectiveness of GCORN on several real-world datasets. Experimental experiments showed that GCORN outperforms available defense methods. Our code is publicly available at: https://github.com/Sennadir/GCORN.

  • 14.
    ABBAS, FAHEEM
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Intelligent Container Stacking System at Seaport Container Terminal2016Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Context: The workload at seaport container terminal is increasing gradually. We need to improve the performance of terminal to fulfill the demand. The key section of the container terminal is container stacking yard which is an integral part of the seaside and the landside. So its performance has the effects on both sides. The main problem in this area is unproductive moves of containers. However, we need a well-planned stacking area in order to increase the performance of terminal and maximum utilization of existing resources.

    Objectives: In this work, we have analyzed the existing container stacking system at Helsingborg seaport container terminal, Sweden, investigated the already provided solutions of the problem and find the best optimization technique to get the best possible solution. After this, suggest the solution, test the proposed solution and analyzed the simulation based results with respect to the desired solution.

    Methods: To identify the problem, methods and proposed solutions of the given problem in the domain of container stacking yard management, a literature review has been conducted by using some e-resources/databases. A GA with best parametric values is used to get the best optimize solution. A discrete event simulation model for container stacking in the yard has been build and integrated with genetic algorithm. A proposed mathematical model to show the dependency of cost minimization on the number of containers’ moves.

    Results: The GA has been achieved the high fitness value versus generations for 150 containers to storage at best location in a block with 3 tier levels and to minimize the unproductive moves in the yard. A comparison between Genetic Algorithm and Tabu Search has been made to verify that the GA has performed better than other algorithm or not. A simulation model with GA has been used to get the simulation based results and to show the container handling by using resources like AGVs, yard crane and delivery trucks and container stacking and retrieval system in the yard. The container stacking cost is directly proportional to the number of moves has been shown by the mathematical model.

    Conclusions: We have identified the key factor (unproductive moves) that is the base of other key factors (time & cost) and has an effect on the performance of the stacking yard and overall the whole seaport terminal. We have focused on this drawback of stacking system and proposed a solution that makes this system more efficient. Through this, we can save time and cost both. A Genetic Algorithm is a best approach to solve the unproductive moves problem in container stacking system.

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  • 15.
    Abbas, Gulfam
    et al.
    Blekinge Institute of Technology, School of Computing.
    Asif, Naveed
    Blekinge Institute of Technology, School of Computing.
    Performance Tradeoffs in Software Transactional Memory2010Independent thesis Advanced level (degree of Master (Two Years))Student thesis
    Abstract [en]

    Transactional memory (TM), a new programming paradigm, is one of the latest approaches to write programs for next generation multicore and multiprocessor systems. TM is an alternative to lock-based programming. It is a promising solution to a hefty and mounting problem that programmers are facing in developing programs for Chip Multi-Processor (CMP) architectures by simplifying synchronization to shared data structures in a way that is scalable and compos-able. Software Transactional Memory (STM) a full software approach of TM systems can be defined as non-blocking synchronization mechanism where sequential objects are automatically converted into concurrent objects. In this thesis, we present performance comparison of four different STM implementations – RSTM of V. J. Marathe, et al., TL2 of D. Dice, et al., TinySTM of P. Felber, et al. and SwissTM of A. Dragojevic, et al. It helps us in deep understanding of potential tradeoffs involved. It further helps us in assessing, what are the design choices and configuration parameters that may provide better ways to build better and efficient STMs. In particular, suitability of an STM is analyzed against another STM. A literature study is carried out to sort out STM implementations for experimentation. An experiment is performed to measure performance tradeoffs between these STM implementations. The empirical evaluations done as part of this thesis conclude that SwissTM has significantly higher throughput than state-of-the-art STM implementations, namely RSTM, TL2, and TinySTM, as it outperforms consistently well while measuring execution time and aborts per commit parameters on STAMP benchmarks. The results taken in transaction retry rate measurements show that the performance of TL2 is better than RSTM, TinySTM and SwissTM.

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  • 16.
    Abbas, Haider
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Options-Based Security-Oriented Framework for Addressing Uncerainty Issues in IT Security2010Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Continuous development and innovation in Information Technology introduces novel configuration methods, software development tools and hardware components. This steady state of flux is very desirable as it improves productivity and the overall quality of life in societies. However, the same phenomenon also gives rise to unseen threats, vulnerabilities and security concerns that are becoming more critical with the passage of time. As an implication, technological progress strongly impacts organizations’ existing information security methods, policies and techniques, making obsolete existing security measures and mandating reevaluation, which results in an uncertain IT infrastructure. In order to address these critical concerns, an options-based reasoning borrowed from corporate finance is proposed and adapted for evaluation of security architecture and decision- making to handle them at organizational level. Options theory has provided significant guidance for uncertainty management in several domains, such as Oil & Gas, government R&D and IT security investment projects. We have applied options valuation technique in a different context to formalize optimal solutions in uncertain situations for three specific and identified uncertainty issues in IT security. In the research process, we formulated an adaptation model for expressing options theory in terms useful for IT security which provided knowledge to formulate and propose a framework for addressing uncertainty issues in information security. To validate the efficacy of this proposed framework, we have applied this approach to the SHS (Spridnings- och Hämtningssystem) and ESAM (E-Society) systems used in Sweden. As an ultimate objective of this research, we intend to develop a solution that is amenable to automation for the three main problem areas caused by technological uncertainty in information security: i) dynamically changing security requirements, ii) externalities caused by a security system, iii) obsoleteness of evaluation. The framework is general and capable of dealing with other uncertainty management issues and their solutions, but in this work we primarily deal with the three aforementioned uncertainty problems. The thesis presents an in-depth background and analysis study for a proposed options-based security-oriented framework with case studies for SHS and ESAM systems. It has also been assured that the framework formulation follows the guidelines from industry best practices criteria/metrics. We have also proposed how the whole process can be automated as the next step in development.

  • 17.
    Abbas, Haider
    KTH, School of Information and Communication Technology (ICT), Computer and Systems Sciences, DSV.
    Threats and Security Measures Involved in VoIP-Telephony2006Independent thesis Advanced level (degree of Master (One Year)), 30 credits / 45 HE creditsStudent thesis
  • 18.
    Abbas, Haider
    et al.
    KTH, School of Information and Communication Technology (ICT), Electronic, Computer and Software Systems, ECS.
    Sundkvist, Stefan
    KTH, School of Information and Communication Technology (ICT).
    Increasing the Performance of Crab Linux Router Simulation Package Using XEN2006In: IEEE International Conference on Industrial and Information Systems, Kandy, Sri Lanka, 2006, p. 459-462Conference paper (Refereed)
    Abstract [en]

    Nowadays hardware components are very expensive, especially if the prime purpose is to perform some routing related lab exercises. Physically connected network resources are required to get the desired results. Configuration of network resources in a lab exercise consumes much time of the students and scientists. The router simulation package Crab(1), based on KnoppW, Quagga' and User Mode Linux (UML) is designed for the students to facilitate them in performing lab exercises on a standalone computer where no real network equipment is needed. In addition to that it provides the facility of connection with the real network equipments. Crab also handles the pre configuration of different parts of the simulated networks like automatic IT addressing etc. This paper will describe the performance enhancing of Crab by replacing User Mode Linux virtual machine with XEN capable of providing ten virtual sessions concurrently using a standalone computer.

  • 19.
    Abbas, Haider
    et al.
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Yngström, Louise
    Hemani, Ahmed
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Empowering Security Evaluation of IT Products with Options Theory2009In: 30th IEEE Symposium on Security & Privacy, Oakland, USA, 2009Conference paper (Refereed)
  • 20.
    Abbas, Muhammad
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Requirements-Level Reuse Recommendation and Prioritization of Product Line Assets2021Other (Other academic)
    Abstract [en]

    Software systems often target a variety of different market segments. Targeting varying customer requirements requires a product-focused development process. Software Product Line (SPL) engineering is one possible approach based on reuse rationale to aid quick delivery of quality product variants at scale. SPLs reuse common features across derived products while still providing varying configuration options. The common features, in most cases, are realized by reusable assets. In practice, the assets are reused in a clone-and-own manner to reduce the upfront cost of systematic reuse. Besides, the assets are implemented in increments, and requirements prioritization also has to be done. In this context, the manual reuse analysis and prioritization process become impractical when the number of derived products grows. Besides, the manual reuse analysis process is time-consuming and heavily dependent on the experience of engineers. In this licentiate thesis, we study requirements-level reuse recommendation and prioritization for SPL assets in industrial settings. We first identify challenges and opportunities in SPLs where reuse is done in a clone-and-own manner. We then focus on one of the identified challenges: requirements-based SPL assets reuse and provide automated support for identifying reuse opportunities for SPL assets based on requirements. Finally, we provide automated support for requirements prioritization in the presence of dependencies resulting from reuse.

  • 21.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems. Mälardalens University, Sweden.
    Ferrari, Alessio
    CNR-ISTI, Italy.
    Shatnawi, Anas
    Berget-Levrault, France.
    Enoiu, Eduard
    Mälardalens University, Sweden.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Is Requirements Similarity a Good Proxy for Software Similarity?: An Empirical Investigation in Industry2021In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 27th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2021, 12 April 2021 - 15 April 2021, Springer Science and Business Media Deutschland GmbH , 2021, Vol. 12685, p. 3-18Conference paper (Refereed)
    Abstract [en]

    [Context and Motivation] Content-based recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn identify previously developed code. [Question/problem] Several NLP approaches for similarity computation are available, and there is little empirical evidence on the adoption of an effective technique in recommender systems specifically oriented to requirements-based code reuse. [Principal ideas/results] This study compares different state-of-the-art NLP approaches and correlates the similarity among requirements with the similarity of their source code. The evaluation is conducted on real-world requirements from two industrial projects in the railway domain. Results show that requirements similarity computed with the traditional tf-idf approach has the highest correlation with the actual software similarity in the considered context. Furthermore, results indicate a moderate positive correlation with Spearman’s rank correlation coefficient of more than 0.5. [Contribution] Our work is among the first ones to explore the relationship between requirements similarity and software similarity. In addition, we also identify a suitable approach for computing requirements similarity that reflects software similarity well in an industrial context. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and categorization.

  • 22.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Ferrari, Alessio
    CNR-ISTI, Italy.
    Shatnawi, Anas
    Berger-Levrault, France.
    Enoiu, Eduard
    Mälardalen University, Sweden.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Sundmark, Daniel
    Mälardalen University, Sweden.
    On the relationship between similar requirements and similar software: A case study in the railway domain2023In: Requirements Engineering, ISSN 0947-3602, E-ISSN 1432-010X, Vol. 28, p. 23-47Article in journal (Refereed)
    Abstract [en]

    Recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a stakeholder proposes a new requirement, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn, identify previously developed code. Several NLP approaches for similarity computation between requirements are available. However, there is little empirical evidence on their effectiveness for code retrieval. This study compares different NLP approaches, from lexical ones to semantic, deep-learning techniques, and correlates the similarity among requirements with the similarity of their associated software. The evaluation is conducted on real-world requirements from two industrial projects from a railway company. Specifically, the most similar pairs of requirements across two industrial projects are automatically identified using six language models. Then, the trace links between requirements and software are used to identify the software pairs associated with each requirements pair. The software similarity between pairs is then automatically computed with JPLag. Finally, the correlation between requirements similarity and software similarity is evaluated to see which language model shows the highest correlation and is thus more appropriate for code retrieval. In addition, we perform a focus group with members of the company to collect qualitative data. Results show a moderately positive correlation between requirements similarity and software similarity, with the pre-trained deep learning-based BERT language model with preprocessing outperforming the other models. Practitioners confirm that requirements similarity is generally regarded as a proxy for software similarity. However, they also highlight that additional aspect comes into play when deciding software reuse, e.g., domain/project knowledge, information coming from test cases, and trace links. Our work is among the first ones to explore the relationship between requirements and software similarity from a quantitative and qualitative standpoint. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and change impact analysis.

  • 23.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems. Mälardalens University, Sweden.
    Hamayouni, Ali
    Mälardalens University, Sweden.
    Helali Moghadam, Mahshid
    RISE Research Institutes of Sweden.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Strandberg, Per Erik
    Westermo Network Technologies AB, Sweden.
    Making Sense of Failure Logs in an Industrial DevOps Environment2023In: Advances in Intelligent Systems and Computing book series (AISC,volume 1445): 20th International Conference on Information Technology New Generations, Springer International Publishing , 2023, Vol. 1445, p. 217-226Conference paper (Refereed)
    Abstract [en]

    Processing and reviewing nightly test execution failure logs for large industrial systems is a tedious activity. Furthermore, multiple failures might share one root/common cause during test execution sessions, and the review might therefore require redundant efforts. This paper presents the LogGrouper approach for automated grouping of failure logs to aid root/common cause analysis and for enabling the processing of each log group as a batch. LogGrouper uses state-of-art natural language processing and clustering approaches to achieve meaningful log grouping. The approach is evaluated in an industrial setting in both a qualitative and quantitative manner. Results show that LogGrouper produces good quality groupings in terms of our two evaluation metrics (Silhouette Coefficient and Calinski-Harabasz Index) for clustering quality. The qualitative evaluation shows that experts perceive the groups as useful, and the groups are seen as an initial pointer for root cause analysis and failure assignment.

  • 24.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Inayat, Irum
    National University of Computer& Emerging Sciences, Pakistan.
    Jan, Naila
    National University of Computer& Emerging Sciences, Pakistan.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Enoiu, Eduard Paul
    Mälardalen University, Sweden.
    Sundmark, Daniel
    Mälardalen University, Sweden.
    MBRP: Model-based Requirements Prioritization Using PageRank Algorithm2019In: The 26th Asia-Pacific Software Engineering Conference, IEEE conference proceedings, 2019Conference paper (Refereed)
    Abstract [en]

    Requirements prioritization plays an important role in driving project success during software development. Literature reveals that existing requirements prioritization approaches ignore vital factors such as interdependency between requirements. Existing requirements prioritization approaches are also generally time-consuming and involve substantial manual effort. Besides, these approaches show substantial limitations in terms of the number of requirements under consideration. There is some evidence suggesting that models could have a useful role in the analysis of requirements interdependency and their visualization, contributing towards the improvement of the overall requirements prioritization process. However, to date, just a handful of studies are focused on model-based strategies for requirements prioritization, considering only conflict-free functional requirements. This paper uses a meta-model-based approach to help the requirements analyst to model the requirements, stakeholders, and inter-dependencies between requirements. The model instance is then processed by our modified PageRank algorithm to prioritize the given requirements. An experiment was conducted, comparing our modified PageRank algorithm’s efficiency and accuracy with five existing requirements prioritization methods. Besides, we also compared our results with a baseline prioritized list of 104 requirements prepared by 28 graduate students. Our results show that our modified PageRank algorithm was able to prioritize the requirements more effectively and efficiently than the other prioritization methods.

  • 25.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Inayat, Irum
    National University of Computer & Emerging Sciences, Pakistan.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Jan, Naila
    National University of Computer & Emerging Sciences, Pakistan.
    Requirements dependencies-based test case prioritization for extra-functional properties2019In: IEEE International Conference on Software Testing, Verification and Validation Workshops, IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    The use of requirements’ information in testing is a well-recognized practice in the software development life cycle. Literature reveals that existing tests prioritization and selection approaches neglected vital factors affecting tests priorities, like interdependencies between requirement specifications. We believe that models may play a positive role in specifying these inter-dependencies and prioritizing tests based on these inter-dependencies. However, till date, few studies can be found that make use of requirements inter-dependencies for test case prioritization. This paper uses a meta-model to aid modeling requirements, their related tests, and inter-dependencies between them. The instance of this meta-model is then processed by our modified PageRank algorithm to prioritize the requirements. The requirement priorities are then propagated to related test cases in the test model and test cases are selected based on coverage of extra-functional properties. We have demonstrated the applicability of our proposed approach on a small example case.

  • 26.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Enoiu, Eduard Paul
    Mälardalens University, Sweden.
    Requirements-driven Reuse Recommendation2021In: 25th ACM International Systems and Software Product Line Conference, ACM , 2021, Vol. AConference paper (Refereed)
    Abstract [en]

    This tutorial explores requirements-based reuse recommendation for product line assets in the context of clone-and-own product lines.

  • 27.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems. Mälardalens University, Sweden.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Enoiu, Eduard Paul
    Mälardalens University, Sweden.
    Sundmark, Daniel
    Mälardalens University, Sweden.
    Lindskog, Claes
    Bombardier Transportation AB, Sweden.
    Automated Reuse Recommendation of Product Line Assets based on Natural Language Requirements2020In: Reuse in Emerging Software Engineering Practices, Springer International Publishing , 2020, Vol. 12541, p. 173-189Conference paper (Refereed)
    Abstract [en]

    Software product lines (SPLs) are based on reuse rationale to aid quick and quality delivery of complex products at scale. Deriving a new product from a product line requires reuse analysis to avoid redundancy and support a high degree of assets reuse. In this paper, we propose and evaluate automated support for recommending SPL assets that can be reused to realize new customer requirements. Using the existing customer requirements as input, the approach applies natural language processing and clustering to generate reuse recommendations for unseen customer requirements in new projects. The approach is evaluated both quantitatively and qualitatively in the railway industry. Results show that our approach can recommend reuse with 74% accuracy and 57.4% exact match. The evaluation further indicates that the recommendations are relevant to engineers and can support the product derivation and feasibility analysis phase of the projects. The results encourage further study on automated reuse analysis on other levels of abstractions.

  • 28.
    Abbas, Muhammad Tahir
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Grinnemo, Karl-Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Ferré, G.
    University of Bordeaux, Bordeaux, France.
    Laurent, P.
    University of Liège, Liège, Belgium.
    Alfredsson, Stefan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Rajiullah, Mohammad
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Eklund, Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Towards zero-energy: Navigating the future with 6G in Cellular Internet of Things2024In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 230, article id 103945Article in journal (Refereed)
    Abstract [en]

    The Cellular Internet of Things (CIoT) has seen significant growth in recent years. With the deployment of 5G, it has become essential to reduce the power consumption of these devices for long-term sustainability. The upcoming 6G cellular network introduces the concept of zero-energy CIoT devices, which do not require batteries or manual charging. This paper focuses on these devices, providing insight into their feasibility and practical implementation. The paper examines how CIoT devices use simultaneous wireless information and power transfer, beamforming, and backscatter communication techniques. It also analyzes the potential use of energy harvesting and power management in zero-energy CIoT devices. Furthermore, the paper explores how low-power transceivers can lower energy usage while maintaining dependable communication functions.

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  • 29.
    Abbas, Muhammad Tahir
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Jibran, Muhammad Ali
    Jeju Natl Univ, Dept Comp Engn, Jeju 63243, South Korea..
    Afaq, Muhammad
    Sarhad Univ Sci & Informat Technol, Pakistan..
    Song, Wang-Cheol
    Jeju Natl Univ, South Korea..
    An adaptive approach to vehicle trajectory prediction using multimodel Kalman filter2020In: European transactions on telecommunications, ISSN 1124-318X, E-ISSN 2161-3915, article id e3734Article in journal (Refereed)
    Abstract [en]

    With the aim to improve road safety services in critical situations, vehicle trajectory and future location prediction are important tasks. An infinite set of possible future trajectories can exit depending on the current state of vehicle motion. In this paper, we present a multimodel-based Extended Kalman Filter (EKF), which is able to predict a set of possible scenarios for vehicle future location. Five different EKF models are proposed in which the current state of a vehicle exists, particularly, a vehicle at intersection or on a curve path. EKF with Interacting Multiple Model framework is explored combinedly for mathematical model creation and probability calculation for that model to be selected for prediction. Three different parameters are considered to create a state vector matrix, which includes vehicle position, velocity, and distance of the vehicle from the intersection. Future location of a vehicle is then used by the software-defined networking controller to further enhance the safety and packet delivery services by the process of flow rule installation intelligently to that specific area only. This way of flow rule installation keeps the controller away from irrelevant areas to install rules, hence, reduces the network overhead exponentially. Proposed models are created and tested in MATLAB with real-time global positioning system logs from Jeju, South Korea.

  • 30.
    Abbas, Muhammad Tahir
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Muhammad, Afaq
    Sarhad Univ Sci & Informat Technol, Dept Comp Sci & IT, Peshawar, Pakistan.
    Song, Wang-Cheol
    Jeju Natl Univ, Dept Comp Engn, Jeju, South Korea.
    Road-Aware Estimation Model for Path Duration in Internet of Vehicles (IoV)2019In: Wireless personal communications, ISSN 0929-6212, E-ISSN 1572-834X, Vol. 109, no 2, p. 715-738Article in journal (Refereed)
    Abstract [en]

    In Internet of Vehicles (IoV), numerous routing metrics have been used to assess the performance of routing protocols such as, packet delivery ratio, throughput, end-to-end delay and path duration. Path duration is an influential design parameter, among these routing metrics, that determines the performance of vehicular networks. For instance, in highly dynamic scenarios, it can be used to predict link life time in on-demand routing protocols. In this paper, we propose an infrastructure-assisted hybrid road-aware routing protocol which is capable of enhanced vehicle-to-vehicle and vehicle-to-infrastructure communication. A remarkable aspect of the proposed protocol is that it establishes a link between path duration and fundamental design parameters like vehicular velocity, density, hop count and transmission range. Although, a lot of research has been previously performed, a well defined analytical model for IoV is not available in the literature. Precisely, a relation between path duration and vehicular velocity has not been validated in the previous studies. Experimental results show that the increased packet delivery ratio with reduced end-to-end delay can be achieved by the prediction of path duration. Proposed model for path duration is validated by getting experimental results from network simulator 3 (NS3) and analytical results from MATLAB. In addition, SUMO simulator was used to generate real time traffic on the roads of Gangnam district, South Korea.

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  • 31.
    Abbas, Nadeem
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Designing Self-Adaptive Software Systems with Reuse2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Modern software systems are increasingly more connected, pervasive, and dynamic, as such, they are subject to more runtime variations than legacy systems. Runtime variations affect system properties, such as performance and availability. The variations are difficult to anticipate and thus mitigate in the system design.

    Self-adaptive software systems were proposed as a solution to monitor and adapt systems in response to runtime variations. Research has established a vast body of knowledge on engineering self-adaptive systems. However, there is a lack of systematic process support that leverages such engineering knowledge and provides for systematic reuse for self-adaptive systems development. 

    This thesis proposes the Autonomic Software Product Lines (ASPL), which is a strategy for developing self-adaptive software systems with systematic reuse. The strategy exploits the separation of a managed and a managing subsystem and describes three steps that transform and integrate a domain-independent managing system platform into a domain-specific software product line for self-adaptive software systems.

    Applying the ASPL strategy is however not straightforward as it involves challenges related to variability and uncertainty. We analyzed variability and uncertainty to understand their causes and effects. Based on the results, we developed the Autonomic Software Product Lines engineering (ASPLe) methodology, which provides process support for the ASPL strategy. The ASPLe has three processes, 1) ASPL Domain Engineering, 2) Specialization and 3) Integration. Each process maps to one of the steps in the ASPL strategy and defines roles, work-products, activities, and workflows for requirements, design, implementation, and testing. The focus of this thesis is on requirements and design.

    We validate the ASPLe through demonstration and evaluation. We developed three demonstrator product lines using the ASPLe. We also conducted an extensive case study to evaluate key design activities in the ASPLe with experiments, questionnaires, and interviews. The results show a statistically significant increase in quality and reuse levels for self-adaptive software systems designed using the ASPLe compared to current engineering practices.

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  • 32.
    Abbas, Nadeem
    Umeå universitet.
    Properites of "Good" Java Examples2010Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Example programs are well known as an important tool to learn computer programming. Realizing the signicance of example programs, this study has been conducted with a goalto measure and evaluate the quality of examples used in academia. We make a distinctionbetween good and bad examples, as badly designed examples may prove harmful for novice learners. In general, students differ from expert programmers in their approach to read and comprehend a program. How do students understand example programs is explored in the light of classical theories and models of program comprehension. Key factors that impact program quality and comprehension are identified. To evaluate as well as improve the quality of examples, a set of quality attributes is proposed. Relationship between program complexity and quality is examined. We rate readability as a prime quality attribute and hypothesize that example programs with low readability are difficult to understand. Software Reading Ease Score (SRES), a program readability metric proposed by Börstler et al. is implemented to provide a readability measurement tool. SRES is based on lexical tokens and is easy to compute using static code analysis techniques. To validate SRES metric, results are statistically analyzed in correlation to earlier existing well acknowledged software metrics.

  • 33.
    Abbas, Nadeem
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Towards autonomic software product lines2011In: SPLC '11 Proceedings of the 15th International Software Product Line Conference, Volume 2, ACM Press, 2011, p. 44:1-44:8Conference paper (Refereed)
    Abstract [en]

    We envision an Autonomic Software Product Line (ASPL). The ASPL is a dynamic software product line that supports self adaptable products. We plan to use reflective architecture to model and develop ASPL. To evaluate the approach, we have implemented three autonomic product lines which show promising results. The ASPL approach is at initial stages, and require additional work. We plan to exploit online learning to realize more dynamic software product lines to cope with the problem of product line evolution. We propose on-line knowledge sharing among products in a product line to achieve continuous improvement of quality in product line products.

  • 34.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Andersson, Jesper
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    ASPLe: a methodology to develop self-adaptive software systems with reuse2017Report (Other academic)
    Abstract [en]

    Advances in computing technologies are pushing software systems and their operating environments to become more dynamic and complex. The growing complexity of software systems coupled with uncertainties induced by runtime variations leads to challenges in software analysis and design. Self-Adaptive Software Systems (SASS) have been proposed as a solution to address design time complexity and uncertainty by adapting software systems at runtime. A vast body of knowledge on engineering self-adaptive software systems has been established. However, to the best of our knowledge, no or little work has considered systematic reuse of this knowledge. To that end, this study contributes an Autonomic Software Product Lines engineering (ASPLe) methodology. The ASPLe is based on a multi-product lines strategy which leverages systematic reuse through separation of application and adaptation logic. It provides developers with repeatable process support to design and develop self-adaptive software systems with reuse across several application domains. The methodology is composed of three core processes, and each process is organized for requirements, design, implementation, and testing activities. To exemplify and demonstrate the use of the ASPLe methodology, three application domains are used as running examples throughout the report.

    Download full text (pdf)
    ASPLe2017
  • 35.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Andersson, Jesper
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Harnessing Variability in Product-lines of Self-adaptive Software Systems2015In: Proceedings of the 19th International Conference on Software Product Line: SPLC '15, ACM Press, 2015, p. 191-200Conference paper (Refereed)
    Abstract [en]

    This work studies systematic reuse in the context of self-adaptive software systems. In our work, we realized that managing variability for such platforms is different compared to traditional platforms, primarily due to the run-time variability and system uncertainties. Motivated by the fact that recent trends show that self-adaptation will be used more often in future system generation and that software reuse state-of-practice or research do not provide sufficient support, we have investigated the problems and possibly resolutions in this context. We have analyzed variability for these systems, using a systematic reuse prism, and identified a research gap in variability management. The analysis divides variability handling into four activities: (1) identify variability, (2) constrain variability, (3) implement variability, and (4) manage variability. Based on the findings we envision a reuse framework for the specific domain and present an example framework that addresses some of the identified challenges. We argue that it provides basic support for engineering self-adaptive software systems with systematic reuse. We discuss some important avenues of research for achieving the vision.

  • 36.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Andersson, Jesper
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Löwe, Welf
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Autonomic Software Product Lines (ASPL)2010In: ECSA '10 Proceedings of the Fourth European Conference on Software Architecture: Companion Volume / [ed] Carlos E. Cuesta, ACM Press, 2010, p. 324-331Conference paper (Refereed)
    Abstract [en]

    We describe ongoing work on a variability mechanism for Autonomic Software Product Lines (ASPL). The autonomic software product lines have self-management characteristics that make product line instances more resilient to context changes and some aspects of product line evolution. Instances sense the context, selects and bind the best component variants to variation-points at run-time. The variability mechanism we describe is composed of a profile guided dispatch based on off-line and on-line training processes. Together they form a simple, yet powerful variability mechanism that continuously learns, which variants to bind given the current context and system goals.

  • 37.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Andersson, Jesper
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Löwe, Welf
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Towards Autonomic Software Product Lines (ASPL) - A Technical Report2011Report (Other academic)
    Abstract [en]

    This report describes a work in progress to develop Autonomic Software Product Lines (ASPL). The ASPL is a dynamic software product line approach with a novel variability handling mechanism that enables traditional software product lines to adapt themselves at runtime in response to changes in their context, requirements and business goals. The ASPL variability mechanism is composed of three key activities: 1) context-profiling, 2) context-aware composition, and 3) online learning. Context-profiling is an offline activity that prepares a knowledge base for context-aware composition. The context-aware composition uses the knowledge base to derive a new product or adapts an existing product based on a product line's context attributes and goals. The online learning optimizes the knowledge base to remove errors and suboptimal information and to incorporate new knowledge. The three activities together form a simple yet powerful variability handling mechanism that learns and adapts a system at runtime in response to changes in system context and goals. We evaluated the ASPL variability mechanism on three small-scale software product lines and got promising results. The ASPL approach is, however, is yet at an initial stage and require improved development support with more rigorous evaluation. 

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    fulltext
  • 38.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Andersson, Jesper
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Weyns, Danny
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Knowledge evolution in autonomic software product lines2011In: SPLC '11 Proceedings of the 15th International Software Product Line Conference, Volume 2, New York, NY, USA: ACM Press, 2011, p. 36:1-36:8Conference paper (Refereed)
    Abstract [en]

    We describe ongoing work in knowledge evolution management for autonomic software product lines. We explore how an autonomic product line may benefit from new knowledge originating from different source activities and artifacts at run time. The motivation for sharing run-time knowledge is that products may self-optimize at run time and thus improve quality faster compared to traditional software product line evolution. We propose two mechanisms that support knowledge evolution in product lines: online learning and knowledge sharing. We describe two basic scenarios for runtime knowledge evolution that involves these mechanisms. We evaluate online learning and knowledge sharing in a small product line setting that shows promising results.

  • 39.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Andersson, Jesper
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Weyns, Danny
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Modeling Variability in Product Lines Using Domain Quality Attribute Scenarios2012In: Proceedings of the WICSA/ECSA 2012 Companion Volume, ACM Press, 2012, p. 135-142Conference paper (Refereed)
    Abstract [en]

    The concept of variability is fundamental in software product lines and a successful implementation of a product line largely depends on how well domain requirements and their variability are specified, managed, and realized. While developing an educational software product line, we identified a lack of support to specify variability in quality concerns. To address this problem we propose an approach to model variability in quality concerns, which is an extension of quality attribute scenarios. In particular, we propose domain quality attribute scenarios, which extend standard quality attribute scenarios with additional information to support specification of variability and deriving product specific scenarios. We demonstrate the approach with scenarios for robustness and upgradability requirements in the educational software product line.

  • 40.
    Abbas, Nadeem
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Awais, Mian Muhammad
    Lahore University of Management Sciences, Pakistan.
    Kurti, Arianit
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Smart Forest Observatories Network: A MAPE-K Architecture Based Approach for Detecting and Monitoring Forest Damage2023In: Proceedings of the Conference Digital solutions for detecting and monitoring forest damage: Växjö, Sweden, March 28-29, 2023, 2023Conference paper (Other academic)
    Abstract [en]

    Forests are essential for life, providing various ecological, social, and economic benefits worldwide. However, one of the main challenges faced by the world is the forest damage caused by biotic and abiotic factors. In any case, the forest damages threaten the environment, biodiversity, and ecosystem. Climate change and anthropogenic activities, such as illegal logging and industrial waste, are among the principal elements contributing to forest damage. To achieve the United Nations' Sustainable Development Goals (SDGs) related to forests and climate change, detecting and analyzing forest damages, and taking appropriate measures to prevent or reduce the damages are essential. To that end, we envision establishing a Smart Forest Observatories (SFOs) network, as shown below, which can be either a local area or a wide area network involving remote forests. The basic idea is to use Monitor, Analyze, Plan, Execute, and Knowledge (MAPE-K) architecture from autonomic computing and self-adaptive software systems domain to design and develop the SFOs network. The SFOs are planned to collect, analyze, and share the collected data and analysis results using state-of-the-art methods. The principal objective of the SFOs network is to provide accurate and real-time data to policymakers and forest managers, enabling them to develop effective policies and management strategies for global forest conservation that help to achieve SDGs related to forests and climate change.

  • 41.
    Abbas, Qaisar
    et al.
    Uppsala universitet, Avdelningen för teknisk databehandling.
    Nordström, Jan
    Uppsala universitet, Avdelningen för teknisk databehandling.
    Weak versus strong no-slip boundary conditions for the Navier-Stokes equations2010In: Engineering Applications of Computational Fluid Mechanics, ISSN 1994-2060, Vol. 4, p. 29-38Article in journal (Refereed)
    Download full text (pdf)
    fulltext
  • 42.
    Abbas, Qaisar
    et al.
    Uppsala universitet, Avdelningen för teknisk databehandling.
    Nordström, Jan
    Uppsala universitet, Avdelningen för teknisk databehandling.
    Weak versus Strong No-Slip Boundary Conditions for the Navier-Stokes Equations2008In: Proc. 6th South African Conference on Computational and Applied Mechanics, South African Association for Theoretical and Applied Mechanics , 2008, p. 52-62Conference paper (Other academic)
  • 43.
    Abbas, Qaisar
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Nordström, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Weak versus strong no-slip boundary conditions for the Navier-Stokes equations2010In: Engineering Applications of Computational Fluid Mechanics, ISSN 1994-2060, Vol. 4, p. 29-38Article in journal (Refereed)
  • 44.
    Abbas, Qaisar
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Nordström, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Weak versus Strong No-Slip Boundary Conditions for the Navier-Stokes Equations2008In: Proc. 6th South African Conference on Computational and Applied Mechanics, South African Association for Theoretical and Applied Mechanics , 2008, p. 52-62Conference paper (Other academic)
  • 45.
    Abbas, Qaisar
    et al.
    Uppsala universitet, Avdelningen för teknisk databehandling.
    van der Weide, Edwin
    Nordström, Jan
    Uppsala universitet, Avdelningen för teknisk databehandling.
    Accurate and stable calculations involving shocks using a new hybrid scheme2009In: Proc. 19th AIAA CFD Conference, AIAA , 2009Conference paper (Refereed)
  • 46.
    Abbas, Qaisar
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    van der Weide, Edwin
    Nordström, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Accurate and stable calculations involving shocks using a new hybrid scheme2009In: Proc. 19th AIAA CFD Conference, AIAA , 2009Conference paper (Refereed)
  • 47.
    Abbas, Rashad
    et al.
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Tesfagiorgish, William Issac
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM).
    Enhancing Fairness in Facial Recognition: Balancing Datasets and Leveraging AI-Generated Imagery for Bias Mitigation: A Study on Mitigating Ethnic and Gender Bias in Public Surveillance Systems2024Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Facial recognition technology has become a ubiquitous tool in security and personal identification. However, the rise of this technology has been accompanied by concerns over inherent biases, particularly regarding ethnic and gender. This thesis examines the extent of these biases by focusing on the influence of dataset imbalances in facial recognition algorithms. We employ a structured methodological approach that integrates AI-generated images to enhance dataset diversity, with the intent to balance representation across ethnics and genders. Using the ResNet and Vgg model, we conducted a series of controlled experiments that compare the performance impacts of balanced versus imbalanced datasets. Our analysis includes the use of confusion matrices and accuracy, precision, recall and F1-score metrics to critically assess the model’s performance. The results demonstrate how tailored augmentation of training datasets can mitigate bias, leading to more equitable outcomes in facial recognition technology. We present our findings with the aim of contributing to the ongoing dialogue regarding AI fairness and propose a framework for future research in the field.

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    fulltext
  • 48.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Al-Shishtawy, Ahmad
    RISE SICS, Stockholm, Sweden.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS. RISE SICS, Stockholm, Sweden..
    Vlassov, Vladimir
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks2018Conference paper (Refereed)
    Abstract [en]

    Short-term traffic prediction allows Intelligent Transport Systems to proactively respond to events before they happen. With the rapid increase in the amount, quality, and detail of traffic data, new techniques are required that can exploit the information in the data in order to provide better results while being able to scale and cope with increasing amounts of data and growing cities. We propose and compare three models for short-term road traffic density prediction based on Long Short-Term Memory (LSTM) neural networks. We have trained the models using real traffic data collected by Motorway Control System in Stockholm that monitors highways and collects flow and speed data per lane every minute from radar sensors. In order to deal with the challenge of scale and to improve prediction accuracy, we propose to partition the road network into road stretches and junctions, and to model each of the partitions with one or more LSTM neural networks. Our evaluation results show that partitioning of roads improves the prediction accuracy by reducing the root mean square error by the factor of 5. We show that we can reduce the complexity of LSTM network by limiting the number of input sensors, on average to 35% of the original number, without compromising the prediction accuracy.

  • 49.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Kalavri, Vasiliki
    Systems Group, ETH, Zurich, Switzerland.
    Carbone, Paris
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Vlassov, Vladimir
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Streaming Graph Partitioning: An Experimental Study2018In: Proceedings of the VLDB Endowment, E-ISSN 2150-8097, Vol. 11, no 11, p. 1590-1603Article in journal (Refereed)
    Abstract [en]

    Graph partitioning is an essential yet challenging task for massive graph analysis in distributed computing. Common graph partitioning methods scan the complete graph to obtain structural characteristics offline, before partitioning. However, the emerging need for low-latency, continuous graph analysis led to the development of online partitioning methods. Online methods ingest edges or vertices as a stream, making partitioning decisions on the fly based on partial knowledge of the graph. Prior studies have compared offline graph partitioning techniques across different systems. Yet, little effort has been put into investigating the characteristics of online graph partitioning strategies.

    In this work, we describe and categorize online graph partitioning techniques based on their assumptions, objectives and costs. Furthermore, we employ an experimental comparison across different applications and datasets, using a unified distributed runtime based on Apache Flink. Our experimental results showcase that model-dependent online partitioning techniques such as low-cut algorithms offer better performance for communication-intensive applications such as bulk synchronous iterative algorithms, albeit higher partitioning costs. Otherwise, model-agnostic techniques trade off data locality for lower partitioning costs and balanced workloads which is beneficial when executing data-parallel single-pass graph algorithms.

  • 50.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Sottovia, Paolo
    Huawei Munich Research Centre, Munich, Germany.
    Hassan, Mohamad Al Hajj
    Huawei Munich Research Centre, Munich, Germany.
    Foroni, Daniele
    Huawei Munich Research Centre, Munich, Germany.
    Bortoli, Stefano
    Huawei Munich Research Centre, Munich, Germany.
    Real-time Traffic Jam Detection and Congestion Reduction Using Streaming Graph Analytics2020In: 2020 IEEE International Conference on Big Data (Big Data), Institute of Electrical and Electronics Engineers (IEEE) , 2020, p. 3109-3118Conference paper (Refereed)
    Abstract [en]

    Traffic congestion is a problem in day to day life, especially in big cities. Various traffic control infrastructure systems have been deployed to monitor and improve the flow of traffic across cities. Real-time congestion detection can serve for many useful purposes that include sending warnings to drivers approaching the congested area and daily route planning. Most of the existing congestion detection solutions combine historical data with continuous sensor readings and rely on data collected from multiple sensors deployed on the road, measuring the speed of vehicles. While in our work we present a framework that works in a pure streaming setting where historic data is not available before processing. The traffic data streams, possibly unbounded, arrive in real-time. Moreover, the data used in our case is collected only from sensors placed on the intersections of the road. Therefore, we investigate in creating a real-time congestion detection and reduction solution, that works on traffic streams without any prior knowledge. The goal of our work is 1) to detect traffic jams in real-time, and 2) to reduce the congestion in the traffic jam areas.In this work, we present a real-time traffic jam detection and congestion reduction framework: 1) We propose a directed weighted graph representation of the traffic infrastructure network for capturing dependencies between sensor data to measure traffic congestion; 2) We present online traffic jam detection and congestion reduction techniques built on a modern stream processing system, i.e., Apache Flink; 3) We develop dynamic traffic light policies for controlling traffic in congested areas to reduce the travel time of vehicles. Our experimental results indicate that we are able to detect traffic jams in real-time and deploy new traffic light policies which result in 27% less travel time at the best and 8% less travel time on average compared to the travel time with default traffic light policies. Our scalability results show that our system is able to handle high-intensity streaming data with high throughput and low latency.

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