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  • 1.
    A. Oliveira, Roger
    et al.
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Energivetenskap.
    S. Salles, Rafael
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Energivetenskap.
    Rönnberg, Sarah K.
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Energivetenskap.
    Deep Learning for Power Quality with Special Reference to Unsupervised Learning2023Inngår i: 27th International Conference on Electricity Distribution (CIRED 2023), IEEE, 2023, s. 935-939, artikkel-id 10417Konferansepaper (Fagfellevurdert)
  • 2.
    Aalbers, Anouschka
    et al.
    Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för datavetenskap och samhällsbyggnad, Datavetenskap.
    Öberg, Linn
    Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för datavetenskap och samhällsbyggnad, Datavetenskap.
    Agil Kravprioritering: En kvalitativ studie om prioriteringsprocesser inom agil mjukvaruutveckling hos Monitor ERP System AB2021Independent thesis Basic level (professional degree), 10 poäng / 15 hpOppgave
    Abstract [sv]

    Kravprioritering är ett av de viktigaste och mest inflytelserika stegen vid tillverkning av en mjukvaruprodukt. Processen är iterativ; den sker under hela produktens agila mjukvaruutvecklingsprocess. Genom kravprioritering beslutas det om vilka krav som ska utvecklas, i vilken ordning och varför. 

    Målet med denna studie är att undersöka hur mjukvaruutvecklande företag gör för att kravprioritera, samt identifiera vilka prioriteringsmetoder de eventuellt använder sig av. Studiens syfte är att få en förståelse för varför en väl avvägd prioritering är viktig, vilka särskilda prioriteringsfaktorer som ger värde till en produkt och att se hur dessa faktorer är relaterade till resultatet. Syftet är även att undersöka vilka svårigheter som finns i en prioriteringsprocess, samt att skapa en översikt över några av de mest vedertagna prioriteringsmetoderna inom agil mjukvaruutveckling. 

    Studien utförs i samarbete med mjukvaruföretaget Monitor ERP för att analysera företagets prioriteringsprocesser som används för att utveckla deras affärssystem Monitor. Metoden som används är en kvalitativ undersökning som består av observationer av möten kring prioriteringsarbete och semi-strukturerade intervjuer. Bearbetning av insamlat material skedde genom att organisera, analysera och sammanställa resultat enligt begrepp och kategorier som framkom utifrån litteraturstudien. Resultatet redovisar arbetsprocesser, gemensamma mål, prioriteringsaspekter och utmaningar i prioriteringsarbetet hos Monitor ERP.

    En väl avvägd prioritering visade sig vara viktigt för att kunna leverera rätt funktionalitet i tid, för att kunna ge trovärdiga estimeringar om utvecklingen och det i sin tur leder till att kunder får förtroende för både produkten och företaget. En rad olika prioriteringsfaktorer som ger värde till programvaran Monitor identifierades, varav många bidrar till att öka kundnöjdheten och kvaliteten på produkten. Monitor ERP använder inte några särskilda prioriteringsmetoder, utan utvecklingsfilosofin Minimum Viable Product används som grund till deras prioriteringsval. Under prioriteringsarbetet upplevdes utmaningar såsom begränsade resurser, oförutsägbara uppgifter, svårigheter med tidsestimering och en utmaning i balansen mellan kundnytta och kundfokus.  

    Fulltekst (pdf)
    Agil_Kravprioritering_Aalbers_Öberg
  • 3.
    Aalto, Erik
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Learning Playlist Representations for Automatic Playlist Generation2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    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.

    Fulltekst (pdf)
    fulltext
  • 4.
    Aarno, Daniel
    KTH, Skolan för datavetenskap och kommunikation (CSC), Numerisk Analys och Datalogi, NADA.
    Intention recognition in human machine collaborative systems2007Licentiatavhandling, monografi (Annet vitenskapelig)
    Abstract [sv]

    Robotsystem har använts flitigt under de senaste årtiondena för att skapa automationslösningar i ett flertal områden. De flesta nuvarande automationslösningarna är begränsade av att uppgifterna de kan lösa måste vara repetitiva och förutsägbara. En av anledningarna till detta är att dagens robotsystem saknar förmåga att förstå och resonera om omvärlden. På grund av detta har forskare inom robotik och artificiell intelligens försökt att skapa intelligentare maskiner. Trots att stora framsteg har gjorts då det gäller att skapa robotar som kan fungera och interagera i en mänsklig miljö så finns det för nuvarande inget system som kommer i närheten av den mänskliga förmågan att resonera om omvärlden.

    För att förenkla problemet har vissa forskare föreslagit en alternativ lösning till helt självständiga robotar som verkar i mänskliga miljöer. Alternativet är att kombinera människors och maskiners förmågor. Exempelvis så kan en person verka på en avlägsen plats, som kanske inte är tillgänglig för personen i fråga på grund av olika orsaker, genom att använda fjärrstyrning. Vid fjärrstyrning skickar operatören kommandon till en robot som verkar som en förlängning av operatörens egen kropp.

    Segmentering och identifiering av rörelser skapade av en operatör kan användas för att tillhandahålla korrekt assistans vid fjärrstyrning eller samarbete mellan människa och maskin. Assistansen sker ofta inom ramen för virtuella fixturer där eftergivenheten hos fixturen kan justeras under exekveringen för att tillhandahålla ökad prestanda i form av ökad precision och minskad tid för att utföra uppgiften.

    Den här avhandlingen fokuserar på två aspekter av samarbete mellan människa och maskin. Klassificering av en operatörs rörelser till ett på förhand specificerat tillstånd under en manipuleringsuppgift och assistans under manipuleringsuppgiften baserat på virtuella fixturer. Den specifika tillämpningen som behandlas är manipuleringsuppgifter där en mänsklig operatör styr en robotmanipulator i ett fjärrstyrt eller samarbetande system.

    En metod för att följa förloppet av en uppgift medan den utförs genom att använda virtuella fixturer presenteras. Istället för att följa en på förhand specificerad plan så har operatören möjlighet att undvika oväntade hinder och avvika från modellen. För att möjliggöra detta estimeras kontinuerligt sannolikheten att operatören följer en viss trajektorie (deluppgift). Estimatet används sedan för att justera eftergivenheten hos den virtuella fixturen så att ett beslut om hur rörelsen ska fixeras kan tas medan uppgiften utförs.

    En flerlagers dold Markovmodell (eng. layered hidden Markov model) används för att modellera mänskliga färdigheter. En gestemklassificerare som klassificerar en operatörs rörelser till olika grundläggande handlingsprimitiver, eller gestemer, evalueras. Gestemklassificerarna används sedan i en flerlagers dold Markovmodell för att modellera en simulerad fjärrstyrd manipuleringsuppgift. Klassificeringsprestandan utvärderas med avseende på brus, antalet gestemer, typen på den dolda Markovmodellen och antalet tillgängliga träningssekvenser. Den flerlagers dolda Markovmodellen tillämpas sedan på data från en trajektorieföljningsuppgift i 2D och 3D med en robotmanipulator för att ge både kvalitativa och kvantitativa resultat. Resultaten tyder på att den flerlagers dolda Markovmodellen är väl lämpad för att modellera trajektorieföljningsuppgifter och att den flerlagers dolda Markovmodellen är robust med avseende på felklassificeringar i de underliggande gestemklassificerarna.

    Fulltekst (pdf)
    FULLTEXT01
  • 5.
    Aarno, Daniel
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Sommerfeld, Johan
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Kragic, Danica
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Pugeault, Nicolas
    Kalkan, Sinan
    Woergoetter, Florentin
    Krüger, Norbert
    Early reactive grasping with second order 3D feature relations2008Inngår i: Recent Progress In Robotics: Viable Robotic Service To Human / [ed] Lee, S; Suh, IH; Kim, MS, 2008, Vol. 370, s. 91-105Konferansepaper (Fagfellevurdert)
    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.

  • 6.
    Aaro, Gustav
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Roos, Daniel
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Carlsson, Niklas
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Toolset for Run-time Dataset Collection of Deep-scene Information2020Inngår i: Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), Springer, 2020, s. 224-236Konferansepaper (Fagfellevurdert)
    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. 

  • 7. Aarts, Fides
    et al.
    Jonsson, Bengt
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik.
    Uijen, Johan
    Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction2010Inngår i: Testing Software and Systems: ICTSS 2010, Berlin: Springer-Verlag , 2010, s. 188-204Konferansepaper (Fagfellevurdert)
  • 8.
    Aarts, Marcel
    Mälardalens högskola, Akademin för innovation, design och teknik.
    Using Kinect to interact with presentation software2013Independent thesis Basic level (university diploma), 10 poäng / 15 hpOppgave
    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.

    Fulltekst (pdf)
    fulltext
  • 9. 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 universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Högenergifysik.
    Bohm, C.
    Bose, D.
    Boeser, S.
    Botner, Olga
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Högenergifysik.
    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 universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Högenergifysik.
    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 universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Högenergifysik.
    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 universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Högenergifysik.
    Strotjohann, N. L.
    Sullivan, G. W.
    Taavola, Henric
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Högenergifysik.
    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 observatory2015Inngår i: Journal of Parallel and Distributed Computing, ISSN 0743-7315, E-ISSN 1096-0848, Vol. 75, s. 198-211Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 10. Aasi, Parisa
    et al.
    Nunes, Ivan
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Data- och systemvetenskap, DSV.
    Rusu, Lazar
    Hodosi, Georg
    Does Organizational Culture Matter in IT Outsourcing Relationships?2015Inngår i: 2015 48TH HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS), IEEE Computer Society, 2015, s. 4691-4699Konferansepaper (Fagfellevurdert)
    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.

  • 11.
    Aayesha, Aayesha
    et al.
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
    Nouri, Jalal
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
    Afzaal, Muhammad
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
    Wu, Yongchao
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
    Li, Xiu
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
    Weegar, Rebecka
    Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
    An Ensemble Approach for Question-Level Knowledge Tracing2021Inngår i: 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, s. 433-437Konferansepaper (Fagfellevurdert)
    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.

  • 12.
    ABBAS, FAHEEM
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datalogi och datorsystemteknik.
    Intelligent Container Stacking System at Seaport Container Terminal2016Independent thesis Advanced level (degree of Master (One Year)), 10 poäng / 15 hpOppgave
    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.

    Fulltekst (pdf)
    fulltext
  • 13.
    Abbas, Gulfam
    et al.
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Asif, Naveed
    Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation.
    Performance Tradeoffs in Software Transactional Memory2010Independent thesis Advanced level (degree of Master (Two Years))Oppgave
    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.

    Fulltekst (pdf)
    FULLTEXT01
  • 14.
    Abbas, Haider
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Options-Based Security-Oriented Framework for Addressing Uncerainty Issues in IT Security2010Doktoravhandling, monografi (Annet vitenskapelig)
    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.

  • 15.
    Abbas, Haider
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Data- och systemvetenskap, DSV.
    Threats and Security Measures Involved in VoIP-Telephony2006Independent thesis Advanced level (degree of Master (One Year)), 30 poäng / 45 hpOppgave
  • 16.
    Abbas, Haider
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Sundkvist, Stefan
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Increasing the Performance of Crab Linux Router Simulation Package Using XEN2006Inngår i: IEEE International Conference on Industrial and Information Systems, Kandy, Sri Lanka, 2006, s. 459-462Konferansepaper (Fagfellevurdert)
    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.

  • 17.
    Abbas, Haider
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Yngström, Louise
    Hemani, Ahmed
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Empowering Security Evaluation of IT Products with Options Theory2009Inngår i: 30th IEEE Symposium on Security & Privacy, Oakland, USA, 2009Konferansepaper (Fagfellevurdert)
  • 18.
    Abbas, Muhammad
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Requirements-Level Reuse Recommendation and Prioritization of Product Line Assets2021Annet (Annet vitenskapelig)
    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.

  • 19.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system. 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, Digitala system, Industriella system.
    Is Requirements Similarity a Good Proxy for Software Similarity?: An Empirical Investigation in Industry2021Inngår i: 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, s. 3-18Konferansepaper (Fagfellevurdert)
    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.

  • 20.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Ferrari, Alessio
    CNR-ISTI, Italy.
    Shatnawi, Anas
    Berger-Levrault, France.
    Enoiu, Eduard
    Mälardalen University, Sweden.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Sundmark, Daniel
    Mälardalen University, Sweden.
    On the relationship between similar requirements and similar software: A case study in the railway domain2023Inngår i: Requirements Engineering, ISSN 0947-3602, E-ISSN 1432-010X, Vol. 28, s. 23-47Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 21.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system. 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 Environment2023Inngår i: 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, s. 217-226Konferansepaper (Fagfellevurdert)
    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.

  • 22.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    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 Algorithm2019Inngår i: The 26th Asia-Pacific Software Engineering Conference, IEEE conference proceedings, 2019Konferansepaper (Fagfellevurdert)
    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.

  • 23.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    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 properties2019Inngår i: IEEE International Conference on Software Testing, Verification and Validation Workshops, IEEE , 2019Konferansepaper (Fagfellevurdert)
    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.

  • 24.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Enoiu, Eduard Paul
    Mälardalens University, Sweden.
    Requirements-driven Reuse Recommendation2021Inngår i: 25th ACM International Systems and Software Product Line Conference, ACM , 2021, Vol. AKonferansepaper (Fagfellevurdert)
    Abstract [en]

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

  • 25.
    Abbas, Muhammad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system. 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 Requirements2020Inngår i: Reuse in Emerging Software Engineering Practices, Springer International Publishing , 2020, Vol. 12541, s. 173-189Konferansepaper (Fagfellevurdert)
    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.

  • 26.
    Abbas, Muhammad Tahir
    et al.
    Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (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 filter2020Inngår i: European transactions on telecommunications, ISSN 1124-318X, E-ISSN 2161-3915, artikkel-id e3734Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 27.
    Abbas, Muhammad Tahir
    et al.
    Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för matematik och datavetenskap (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)2019Inngår i: Wireless personal communications, ISSN 0929-6212, E-ISSN 1572-834X, Vol. 109, nr 2, s. 715-738Artikkel i tidsskrift (Fagfellevurdert)
    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.

    Fulltekst (pdf)
    fulltext
  • 28.
    Abbas, Nadeem
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Designing Self-Adaptive Software Systems with Reuse2018Doktoravhandling, med artikler (Annet vitenskapelig)
    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.

    Fulltekst (pdf)
    Doctoral Thesis (Comprehensive Summary)
    Download (jpg)
    Front Page
  • 29.
    Abbas, Nadeem
    Umeå universitet.
    Properites of "Good" Java Examples2010Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    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.

  • 30.
    Abbas, Nadeem
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Towards autonomic software product lines2011Inngår i: SPLC '11 Proceedings of the 15th International Software Product Line Conference, Volume 2, ACM Press, 2011, s. 44:1-44:8Konferansepaper (Fagfellevurdert)
    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.

  • 31.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    Andersson, Jesper
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    ASPLe: a methodology to develop self-adaptive software systems with reuse2017Rapport (Annet vitenskapelig)
    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.

    Fulltekst (pdf)
    ASPLe2017
  • 32.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Andersson, Jesper
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Harnessing Variability in Product-lines of Self-adaptive Software Systems2015Inngår i: Proceedings of the 19th International Conference on Software Product Line: SPLC '15, ACM Press, 2015, s. 191-200Konferansepaper (Fagfellevurdert)
    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.

  • 33.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Andersson, Jesper
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Löwe, Welf
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Autonomic Software Product Lines (ASPL)2010Inngår i: ECSA '10 Proceedings of the Fourth European Conference on Software Architecture: Companion Volume / [ed] Carlos E. Cuesta, ACM Press, 2010, s. 324-331Konferansepaper (Fagfellevurdert)
    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.

  • 34.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Andersson, Jesper
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Löwe, Welf
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Towards Autonomic Software Product Lines (ASPL) - A Technical Report2011Rapport (Annet vitenskapelig)
    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. 

    Fulltekst (pdf)
    fulltext
  • 35.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Andersson, Jesper
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Weyns, Danny
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Knowledge evolution in autonomic software product lines2011Inngår i: SPLC '11 Proceedings of the 15th International Software Product Line Conference, Volume 2, New York, NY, USA: ACM Press, 2011, s. 36:1-36:8Konferansepaper (Fagfellevurdert)
    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.

  • 36.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Andersson, Jesper
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Weyns, Danny
    Linnéuniversitetet, Fakultetsnämnden för naturvetenskap och teknik, Institutionen för datavetenskap, fysik och matematik, DFM.
    Modeling Variability in Product Lines Using Domain Quality Attribute Scenarios2012Inngår i: Proceedings of the WICSA/ECSA 2012 Companion Volume, ACM Press, 2012, s. 135-142Konferansepaper (Fagfellevurdert)
    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.

  • 37.
    Abbas, Nadeem
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Awais, Mian Muhammad
    Lahore University of Management Sciences, Pakistan.
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Smart Forest Observatories Network: A MAPE-K Architecture Based Approach for Detecting and Monitoring Forest Damage2023Inngår i: Proceedings of the Conference Digital solutions for detecting and monitoring forest damage: Växjö, Sweden, March 28-29, 2023, 2023Konferansepaper (Annet vitenskapelig)
    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.

  • 38.
    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 equations2010Inngår i: Engineering Applications of Computational Fluid Mechanics, ISSN 1994-2060, Vol. 4, s. 29-38Artikkel i tidsskrift (Fagfellevurdert)
    Fulltekst (pdf)
    fulltext
  • 39.
    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 Equations2008Inngår i: Proc. 6th South African Conference on Computational and Applied Mechanics, South African Association for Theoretical and Applied Mechanics , 2008, s. 52-62Konferansepaper (Annet vitenskapelig)
  • 40.
    Abbas, Qaisar
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    Nordström, Jan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    Weak versus strong no-slip boundary conditions for the Navier-Stokes equations2010Inngår i: Engineering Applications of Computational Fluid Mechanics, ISSN 1994-2060, Vol. 4, s. 29-38Artikkel i tidsskrift (Fagfellevurdert)
  • 41.
    Abbas, Qaisar
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    Nordström, Jan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    Weak versus Strong No-Slip Boundary Conditions for the Navier-Stokes Equations2008Inngår i: Proc. 6th South African Conference on Computational and Applied Mechanics, South African Association for Theoretical and Applied Mechanics , 2008, s. 52-62Konferansepaper (Annet vitenskapelig)
  • 42.
    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 scheme2009Inngår i: Proc. 19th AIAA CFD Conference, AIAA , 2009Konferansepaper (Fagfellevurdert)
  • 43.
    Abbas, Qaisar
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    van der Weide, Edwin
    Nordström, Jan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för teknisk databehandling. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Numerisk analys.
    Accurate and stable calculations involving shocks using a new hybrid scheme2009Inngår i: Proc. 19th AIAA CFD Conference, AIAA , 2009Konferansepaper (Fagfellevurdert)
  • 44.
    Abbas, Zainab
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Al-Shishtawy, Ahmad
    RISE SICS, Stockholm, Sweden.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS. RISE SICS, Stockholm, Sweden..
    Vlassov, Vladimir
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks2018Konferansepaper (Fagfellevurdert)
    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.

  • 45.
    Abbas, Zainab
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Kalavri, Vasiliki
    Systems Group, ETH, Zurich, Switzerland.
    Carbone, Paris
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Vlassov, Vladimir
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Streaming Graph Partitioning: An Experimental Study2018Inngår i: Proceedings of the VLDB Endowment, E-ISSN 2150-8097, Vol. 11, nr 11, s. 1590-1603Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 46.
    Abbas, Zainab
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, 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 Analytics2020Inngår i: 2020 IEEE International Conference on Big Data (Big Data), Institute of Electrical and Electronics Engineers (IEEE) , 2020, s. 3109-3118Konferansepaper (Fagfellevurdert)
    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.

  • 47.
    Abbasi, Azad Ismail
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Coffeepot for Masochists: A Study in User-Centered System Design2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    This master thesis is carried out in the field of “Human-Computer interaction”, more specifically the area “User-centered system design”. The focus has been on “usability” and useful graphical user interfaces. Current theories and definitions in the field have been considered. Literature studies contain well known authors and organisations in domains mentioned above; Jakob Nielsen, Donald A Norman and International Organization for Standardization ISO to mention some.

     Another source for this work from which the theories and way of working have been used is the book “User-Centered System Design” written by Jan Gulliksen and Bengt Göransson.

     The work started with a literature study followed by looking at methods to use. The next step was to do task and user analysis which followed by the development phase. The user has been given a central role in this project and, just as recommended, also been involved through the whole cycle. A useful method to get feedback from users, in addition to interviews and workshops, has been the “Heuristic Evaluation”.

     The final result and conclusion shows that the user-centered system design is a powerful tool to adapt when designing and developing interactive user interface.

    Fulltekst (pdf)
    Azad Abbasi - Master Thesis
  • 48.
    Abbasi, Bushra Qazi
    et al.
    Jönköping University, Tekniska Högskolan, JTH, Avdelningen för datateknik och informatik.
    Awais, Samrah
    Jönköping University, Tekniska Högskolan, JTH, Avdelningen för datateknik och informatik.
    Playing mind gamification: Theoretical evidence of addictive nature of gamification and identification of addictive game elements used in mobile application design2022Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Gamification is a modern concept that makes physical and digital activities engaging and enjoyable just like games. Game elements are added to mobile applications for user retention and engagement. One of the dark sides of gamification i.e., addiction is explored in this novel study in the context of mobile application design. It uses a mixed-method approach to lay the foundation of the relation between gamification and Smartphone Addiction, which is critically explained in a limited literature review using existing theories and studies on gamification. Interviews with behavioral experts confirm the psychological aspects of the research. The study also identifies game elements that contribute to smartphone addiction by a survey analysis of 269 participants. Results reveal Scrolling and Tapping as most addictive game elements. Some elements also show a statistically significant relationship with daily smartphone usage in hours. There are many effective applications of gamification, and in the context of mobile application design, it indeed helps to increase user engagement, however, there is an ethical need to reflect on what the exaggerated form of this engagement can lead to. As future research, a longitudinal study and experiments are suggested to find out this relationship with the use of empirical data.

    Fulltekst (pdf)
    fulltext
  • 49.
    Abbasi, Jasim
    Luleå tekniska universitet, Institutionen för system- och rymdteknik.
    Predictive Maintenance in Industrial Machinery using Machine Learning2021Independent thesis Advanced level (degree of Master (One Year)), 10 poäng / 15 hpOppgave
    Abstract [en]

    Background: The gearbox and machinery faults prediction are expensive both in terms of repair and loss output in production. These losses or faults may lead to complete machinery or plant breakdown. 

    Objective: The goal of this study was to apply advanced machine learning techniques to avoid these losses and faults and replace them with predictive maintenance. To identify and predict the faults in industrial machinery using Machine Learning (ML)  and Deep Learning (DL) approaches. 

    Methods: Our study was based on two types of datasets which includes gearbox and rotatory machinery dataset. These datasets were analyzed to predict the faults using machine learning and deep neural network models. The performance of the model was evaluated for both the datasets with binary and multi-classification problems using the different machine learning models and their statistics.

    Results: In the case of the gearbox fault dataset with a binary classification problem, we observed random forest and deep neural network models performed equally well, with the highest F1-score and AUC score of around 0.98 and with the least error rate of 7%.  In addition to this, in the case of the multi-classification rotatory machinery fault prediction dataset, the random forest model outperformed the deep neural network model with an AUC score of 0.98. 

    Conclusions: In conclusion classification efficiency of the Machine Learning (ML) and Deep Neural Network (DNN) model were tested and evaluated. Our results show Random Forest (RF) and Deep Neural Network (DNN) models have better fault prediction ability to identify the different types of rotatory machinery and gearbox faults as compared to the decision tree and AdaBoost. 

    Keywords: Machine Learning, Deep Learning, Big Data, Predictive Maintenance, Rotatory Machinery Fault Prediction, Gearbox Fault Prediction, Machinery Fault Database, Internet of Things (IoT), Spectra quest machinery fault simulator, Cloud Computing, Industry 4.0

    Fulltekst (pdf)
    Predictive Maintenance in Industrial Machinery using Machine Learning
  • 50. Abbasi, Rosa
    et al.
    Darulova, Eva
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datalogi.
    Modular Optimization-Based Roundoff Error Analysis of Floating-Point Programs2023Inngår i: Static Analysis: 30th International Symposium, SAS 2023 / [ed] Manuel Hermenegildo, Jose F. Morales, 2023Konferansepaper (Fagfellevurdert)
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