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  • 151.
    Herault, Romain Christian
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Lincke, Alisa
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Milrad, Marcelo
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Forsgärde, Elin-Sofie
    Linnéuniversitetet, Fakulteten för Hälso- och livsvetenskap (FHL), Institutionen för hälso- och vårdvetenskap (HV).
    Elmqvist, Carina
    Linnéuniversitetet, Fakulteten för Hälso- och livsvetenskap (FHL), Institutionen för hälso- och vårdvetenskap (HV).
    Svensson, Anders
    Linnéuniversitetet, Fakulteten för Hälso- och livsvetenskap (FHL), Institutionen för hälso- och vårdvetenskap (HV).
    Design and Evaluation of a 360 Degrees Interactive Video System to Support Collaborative Training for Nursing Students in Patient Trauma Treatment2018Ingår i: 26TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION (ICCE 2018) / [ed] Yang, JC Chang, M Wong, LH Rodrigo, MMT, Asia-Pacific Society for Computers in Education, 2018, s. 298-303Konferensbidrag (Refereegranskat)
    Abstract [en]

    Extreme catastrophe situations are rare in Sweden, which makes training opportunities important to secure the competence among emergency personnel that should be actively involved during those situations. There is a need to conceptualize, design and implement interactive learning environments that allow to educate, train and assess these catastrophe situations more often and in different settings, conditions and places. In order to address these challenges, a prototype system has been designed and developed containing immersive interactive 360 degrees educational videos that are available via a web browser. The content of these videos includes simulated learning scenes of a trauma team working at the hospital emergency department. Different types of interaction mechanisms are integrated within the videos in which learners should act upon and respond. The prototype was tested during the fall term 2017 with 17 students from the specialist nursing program, and four medical experts. These activities were assessed in order to get new insights into issues related to the proposed approach and feedback connected to the usefulness, usability and learnability of the suggested prototype. The initial outcomes of the evaluation indicate that the system can provide students with novel interaction mechanisms to improve their skills and it can be applied as a complementary tool to the methods used currently in their education.

  • 152.
    Herault, Romain Christian
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Lundman, Madeleine
    Golub, Koraljka
    Linnéuniversitetet, Fakulteten för konst och humaniora (FKH), Institutionen för kulturvetenskaper (KV).
    Milrad, Marcelo
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Developing Attractive Information Landscapes for the Mapping of Cultural Events Using Web and Mobile Technologies: Uppföljningsseminarium av fakultetsöverskridande project, 22 mars 20182018Övrigt (Övrigt vetenskapligt)
  • 153.
    Heyder, Jakob
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Hierarchical Temporal Memory Software Agent: In the light of general artificial intelligence criteria2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Artificial general intelligence is not well defined, but attempts such as the recent listof “Ingredients for building machines that think and learn like humans” are a startingpoint for building a system considered as such [1]. Numenta is attempting to lead thenew era of machine intelligence with their research to re-engineer principles of theneocortex. It is to be explored how the ingredients are in line with the design princi-ples of their algorithms. Inspired by Deep Minds commentary about an autonomy-ingredient, this project created a combination of Numentas Hierarchical TemporalMemory theory and Temporal Difference learning to solve simple tasks defined in abrowser environment. An open source software, based on Numentas intelligent com-puting platform NUPIC and Open AIs framework Universe, was developed to allowfurther research of HTM based agents on customized browser tasks. The analysisand evaluation of the results show that the agent is capable of learning simple tasksand there is potential for generalization inherent to sparse representations. However,they also reveal the infancy of the algorithms, not capable of learning dynamic com-plex problems, and that much future research is needed to explore if they can createscalable solutions towards a more general intelligent system.

  • 154.
    Hmidi, Mehdi
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Formation Control and UAV Path Finding Under Uncertainty: A contingent and cooperative swarm intelligence approach2020Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Several of our technological breakthroughs are influenced by types of behavior and structures developed in the natural world, including the emulation of swarm in- telligence and the engineering of artificial synapses that function like the human mind. Much like these breakthroughs, this report examines emerging behaviors across swarms of non-communicating, adaptive units that evade obstacles while find- ing a path, to present a swarming algorithm premised on a class of local rule sets re- sulting in a Unmanned Aerial Vehicle (UAV) group navigating together as a unified swarm. Primarily, this method’s important quality is that its rules are local in nature. Thus, the exponential calculations which can be supposed with growing number of drones, their states, and potential tasks are remedied. To this extent, the study tests the algorithmic rules in experiments to replicate the desired behavior in a bounded virtual space filled with simulated units. Simultaneously, in the adaptation of natural flocking rules the study also introduces the rule sets for goal seeking and uncertainty evasion. In effect, the study succeeds in reaching and displaying the desired goals even as the units avoid unknown before flight obstacles and inter-unit collisions with- out the need for a global centralized command nor a leader based hierarchical system.

  • 155.
    Hult, Adam
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    Automatiserad IO-adressering: Ett konfigureringssystem som hanterar maskinunik hårdvaruadressering2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Genom Norden Machinerys förmåga att innovera och skapa har de bland annat lyckats producera maskiner med otroliga kapaciteter. Med det och den höga verkningsgraden maskinerna verkar på har gjort att företaget idag är världsledande inom tubfyllningsindustrin.

     

    Varje maskin som levereras utav Norden har ofta unika kundspecifikationer, detta gör att Nordens elkonstruktionsavdelning behöver tilldela en maskinunik eldokumentation till varje maskin. Detta innebär att IO-konfigurationen är unik och måste då anpassas i maskinens PLC-program. Vid uppstart av maskiner idag måste alla IO-adresser matas in för hand via en operatörspanel. Detta utgör att uppstartsfatsen är både tidskrävande samt att det finns en risk att felaktiga adresser anges.

     

    Denna rapport kommer avhandla och beskriva hur man kan hantera IO-adressering och IO-konfigurering när antalet portar hos en PLC är otillräckliga samt att undersöka möjligheterna till att automatisera den manuella hanteringen utav adresser och IO-konfigurationen.

  • 156.
    Humeniuk, Vladyslav
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Android Architecture Comparison: MVP vs. VIPER2019Självständigt arbete på avancerad nivå (magisterexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Android application development has been of interest since the first Android smartphone was released. Applications are constantly getting more complex as well as smartphone hardware is getting better. New ways of developing Android applications are developed with time. There is Model View Presenter architecture that is the most used for android applications now and new View InteractorPresenter Entity Router architecture that is becoming more popular. But there is no empirical data to compare these architectures to understand what architecture will fit better for developing new applications. This thesis aims to compare the MVP and the VIPER android architectures using a few important metrics like maintainability, modifiability, testability, and performance. Results will answer what architecture is better for developing different types of projects. VIPERarchitecture showed better performance results and maintenance metrics comparison shows that both architectures have advantages and disadvantages.

  • 157.
    Hönel, Sebastian
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Ericsson, Morgan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Löwe, Welf
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Wingkvist, Anna
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    A changeset-based approach to assess source code density and developer efficacy2018Ingår i: ICSE '18 Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, IEEE , 2018, s. 220-221Konferensbidrag (Refereegranskat)
    Abstract [en]

    The productivity of a (team of) developer(s) can be expressed as a ratio between effort and delivered functionality. Several different estimation models have been proposed. These are based on statistical analysis of real development projects; their accuracy depends on the number and the precision of data points. We propose a data-driven method to automate the generation of precise data points. Functionality is proportional to the code size and Lines of Code (LoC) is a fundamental metric of code size. However, code size and LoC are not well defined as they could include or exclude lines that do not affect the delivered functionality. We present a new approach to measure the density of code in software repositories. We demonstrate how the accuracy of development time spent in relation to delivered code can be improved when basing it on net-instead of the gross-size measurements. We validated our tool by studying ca. 1,650 open-source software projects.

  • 158.
    Hönel, Sebastian
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Ericsson, Morgan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Löwe, Welf
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Wingkvist, Anna
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Bayesian Regression on segmented data using Kernel Density Estimation2019Ingår i: 5th annual Big Data Conference: Linnaeus University, Växjö, Sweden, 5-6 December 2019, Zenodo , 2019Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    The challenge of having to deal with dependent variables in classification and regression using techniques based on Bayes' theorem is often avoided by assuming a strong independence between them, hence such techniques are said to be naive. While analytical solutions supporting classification on arbitrary amounts of discrete and continuous random variables exist, practical solutions are scarce. We are evaluating a few Bayesian models empirically and consider their computational complexity. To overcome the often assumed independence, those models attempt to resolve the dependencies using empirical joint conditional probabilities and joint conditional probability densities. These are obtained by posterior probabilities of the dependent variable after segmenting the dataset for each random variable's value. We demonstrate the advantages of these models, such as their nature being deterministic (no randomization or weights required), that no training is required, that each random variable may have any kind of probability distribution, how robustness is upheld without having to impute missing data, and that online learning is effortlessly possible. We compare such Bayesian models against well-established classifiers and regression models, using some well-known datasets. We conclude that our evaluated models can outperform other models in certain settings, using classification. The regression models deliver respectable performance, without leading the field.

  • 159.
    Hönel, Sebastian
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Ericsson, Morgan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Löwe, Welf
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Wingkvist, Anna
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Importance and Aptitude of Source code Density for Commit Classification into Maintenance Activities2019Ingår i: 2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) / [ed] Dr. David Shepherd, IEEE, 2019, s. 109-120Konferensbidrag (Refereegranskat)
    Abstract [en]

    Commit classification, the automatic classification of the purpose of changes to software, can support the understanding and quality improvement of software and its development process. We introduce code density of a commit, a measure of the net size of a commit, as a novel feature and study how well it is suited to determine the purpose of a change. We also compare the accuracy of code-density-based classifications with existing size-based classifications. By applying standard classification models, we demonstrate the significance of code density for the accuracy of commit classification. We achieve up to 89% accuracy and a Kappa of 0.82 for the cross-project commit classification where the model is trained on one project and applied to other projects. Such highly accurate classification of the purpose of software changes helps to improve the confidence in software (process) quality analyses exploiting this classification information.

  • 160.
    Idrizi, Florim
    et al.
    Tetovo State University, Macedonia.
    Rustemi, Avni
    Tetovo State University, Macedonia.
    Dalipi, Fisnik
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). Tetovo State University, Macedonia.
    A new modified sorting algorithm: A comparison with state of the art2017Ingår i: 2017 6th Mediterranean Conference on Embedded Computing (MECO), IEEE, 2017, s. 419-424Konferensbidrag (Refereegranskat)
    Abstract [en]

    Choosing the right method to sort numbers has a huge effect on how quickly a computer can process a task. The most used sorting algorithms today have been discovered years ago, and to this day, they have been the best for the job as there was no other competitive algorithm. Through this paper, we make an analysis and comparison between the state of the art algorithms in sorting and based on their analogy of functionality, we propose a new modified sorting algorithm. We then present a brief description of the new modified algorithm, conduct comparisons with the state of the art, and finally we give conclusions about the performance of the proposed algorithm versus the most popular sorting algorithms. Moreover, we highlight the benefits of using this algorithm in different fields by various business companies or software developers, in cases when they need faster and easier sorting for their data management.

  • 161.
    Iftikhar, Muhammad Usman
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV). Faculty of Engineering Science, Department of Computer Science, KU Leuven, Belgium.
    A Model-Based Approach to Engineer Self-Adaptive Systems with Guarantees2017Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    Modern software systems are increasingly characterized by uncertainties in the operating context and user requirements. These uncertainties are difficult to predict at design time. Achieving the quality goals of such systems depends on the ability of the software to deal with these uncertainties at runtime. A self-adaptive system employs a feedback loop to continuously monitor and adapt itself to achieve particular quality goals (i.e., adaptation goals) regardless of uncertainties. Current research applies formal techniques to provide guarantees for adaptation goals, typically using exhaustive verification techniques. Although these techniques offer strong guarantees for the goals, they suffer from well-known state explosion problem. In this thesis, we take a broader perspective and focus on two types of guarantees: (1) functional correctness of the feedback loop, and (2) guaranteeing the adaptation goals in an efficient manner. To that end, we present ActivFORMS (Active FORmal Models for Self-adaptation), a formally founded model-driven approach for engineering self-adaptive systems with guarantees. ActivFORMS achieves functional correctness by direct execution of formally verified models of the feedback loop using a reusable virtual machine. To efficiently provide guarantees for the adaptation goals with a required level of confidence, ActivFORMS applies statistical model checking at runtime. ActivFORMS supports on the fly changes of adaptation goals and updates of the verified feedback loop models that meet the changed goals. To demonstrate the applicability and effectiveness of the approach, we applied ActivFORMS in several domains: warehouse transportation, oceanic surveillance, tele assistance, and IoT building security monitoring.

  • 162.
    Iftikhar, Muhammad Usman
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Lundberg, Jonas
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Weyns, Danny
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV). Katholieke Univ Leuven, Leuven, Belgium.
    A Model Interpreter for Timed Automata2016Ingår i: Leveraging Applications of Formal Methods, Verification and Validation: Foundational Techniques, PT I, Springer, 2016, s. 243-258Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the model-centric approach to model-driven development, the models used are sufficiently detailed to be executed. Being able to execute the model directly, without any intermediate model-to-code translation, has a number of advantages. The model is always up-to-date and runtime updates of the model are possible. This paper presents a model interpreter for timed automata, a formalism often used for modeling and verification of real-time systems. The model interpreter supports real-time system features like simultaneous execution, system wide signals, a ticking clock, and time constraints. Many existing formal representations can be verified, and many existing DSMLs can be executed. It is the combination of being both verifiable and executable that makes our approach rather unique.

  • 163.
    Iftikhar, Muhammad Usman
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Ramachandran, Gowri Sankar
    KU Leuven, Belgium.
    Bollansée, Pablo
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). KU Leuven, Belgium.
    Weyns, Danny
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). KU Leuven, Belgium.
    Hughes, Danny
    KU Leuven, Belgium.
    DeltaIoT: A Self-Adaptive Internet of Things Exemplar2017Ingår i: Proceedings - 2017 IEEE/ACM 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2017, IEEE, 2017, s. 76-82Konferensbidrag (Refereegranskat)
    Abstract [en]

    Internet of Things (IoT) consists of networked tiny embedded computers (motes) that are capable of monitoring and controlling the physical world. Examples range from building security monitoring to smart factories. A central problem of IoT is minimising the energy consumption of the motes, while guaranteeing high packet delivery performance, regardless of uncertainties such as sudden changes in traffic load and communication interference. Traditionally, to deal with uncertainties the network settings are either hand-tuned or over-provisioned, resulting in continuous network maintenance or inefficiencies. Enhancing the IoT network with self-adaptation can automate these tasks. This paper presents DeltaIoT, an exemplar that enables researchers to evaluate and compare new methods, techniques and tools for self-adaptation in IoT. DeltaIoT is the first exemplar for research on self-adaptation that provides both a simulator for offline experimentation and a physical setup that can be accessed remotely for real-world experimentation. © 2017 IEEE.

  • 164.
    Iftikhar, Muhammad Usman
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Weyns, Danny
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV). Katholieke University Leuven, Belgium.
    ActivFORMS: A Runtime Environment for Architecture-Based Adaptation with Guarantees2017Ingår i: 2017 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE WORKSHOPS (ICSAW), IEEE, 2017, s. 278-281Konferensbidrag (Refereegranskat)
    Abstract [en]

    Modern software systems are exposed to various types of uncertainties, such as dynamics in the available resources that are difficult to predict and goals that may change during operation. Self-adaptation equips a software system with a feedback loop that collects additional knowledge at runtime, monitors the system and adapts it when necessary to maintain its quality goals, regardless of uncertainties. One challenging problem of self-adaptation is to provide guarantees for the goals that are subject of adaptation. In this paper, we present the ActivFORMS runtime environment to realise self- adaptation with guarantees. With ActivFORMS designers model and verify a feedback loop. The verified models can directly be deployed on top of a virtual machine that executes the models to realise adaption. The approach avoids coding of the models, which is an error-prone task. The runtime environment visualises the executing models, the state of the goals, and it supports on the fly updates of the models and goals. We illustrate the approach with an adaptation scenario of an IoT building security example.

  • 165.
    Imran, Ali Shariq
    et al.
    Norwegian University of Science and Technology (NTNU), Norway.
    Dalipi, Fisnik
    University of South-Eastern Norway, Norway.
    Kastrati, Zenun
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Predicting Student Dropout in a MOOC: An Evaluation of a Deep Neural Network Model2019Ingår i: Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence, ACM Publications, 2019, s. 190-195Konferensbidrag (Refereegranskat)
    Abstract [en]

    Massive Open Online Courses (MOOCs) have transformed the way educational institutions deliver high-quality educational material to the onsite and distance learners across the globe. As a result, a new paradigm shifts as to how learners acquire and benefit from the wealth of knowledge provided by a MOOC at their doorstep nowadays in contrast to the brick and mortar settings is visible. Learners are therefore showing a profound interest in the MOOCs offered by top universities and industry giants. They have also attracted a vast number of students from far-flung areas of the world. The massive number of registered students in MOOCs, however, pose one major challenge, i.e., 'the dropouts'. Course planners and content providers are struggling to retain the registered students, which give rise to a new research agenda focusing on predicting and explaining student dropout and low completion rates in a MOOC. Machine learning techniques utilizing deep learning approaches can efficiently predict the potential dropouts and can raise an alert well before time. In this paper, we have focused our study on the application of feed-forward deep neural network architectures to address this problem. Our model achieves not only high accuracy, but also low false negative rate while predicting dropouts on the MOOC data. Moreover, we also provide an in-depth comparison of the proposed architectures concerning precision, recall, and F1 measure.

  • 166.
    Imran, Ali Shariq
    et al.
    Norwegian University of Science and Technology.
    Kastrati, Zenun
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Svendsen, Torbjorn Karl
    Norwegian University of Science and Technology.
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Text-Independent Speaker ID Employing 2D-CNN for Automatic Video Lecture Categorization in a MOOC Setting2019Ingår i: 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), IEEE Computer Society, 2019, s. 273-277Konferensbidrag (Refereegranskat)
    Abstract [en]

    A new form of distance and blended education has hit the market in recent years with the advent of massive open online courses (MOOCs) which have brought many opportunities to the educational sector. Consequently, the availability of learning content to vast demographics of people and across locations has opened up a plethora of possibilities for everyone to gain new knowledge through MOOCs. This poses an immense issue to the content providers as the amount of manual effort required to structure properly and to organize the content automatically for millions of video lectures daily become incredibly challenging. This paper, therefore, addresses this issue as a small part of our proposed personalized content management system by exploiting the voice pattern of the lecturer for identification and for classifying video lectures to the right speaker category. The use of Mel frequency Cepstral coefficients (MFCC) as 2D input features maps to 2D-CNN has shown promising results in contrast to machine learning and deep learning classifiers - making text-independent speaker identification plausible in MOOC setting for automatic video lecture categorization. It will not only help categorize educational videos efficiently for easy search and retrieval but will also promote effective utilization of micro-lectures and multimedia video learning objects (MLO).

  • 167.
    Imran, Ali Shariq
    et al.
    Norwegian University of Science and Technology, Norway.
    Kastrati, Zenun
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Svendsen, Torbjørn Karl
    Norwegian University of Science and Technology (NTNU), Norway.
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Text-Independent Speaker ID for Automatic Video Lecture Classification Using Deep Learning2019Ingår i: Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence, April 19-22, 2019, Bali, Indonesia, ACM Publications, 2019, s. 175-180Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper proposes to use acoustic features employing deep neural network (DNN) and convolutional neural network (CNN) models for classifying video lectures in a massive open online course (MOOC). The models exploit the voice pattern of the lecturer for identification and for classifying the video lecture according to the right speaker category. Filter bank and Mel frequency cepstral coefficient (MFCC) feature along with first and second order derivatives (Δ/ΔΔ) are used as input features to the proposed models. These features are extracted from the speech signal which is obtained from the video lectures by separating the audio from the video using FFmpeg.

    The deep learning models are evaluated using precision, recall, and F1 score and the obtained accuracy is compared for both acoustic features with traditional machine learning classifiers for speaker identification. A significant improvement of 3% to 7% classification accuracy is achieved over the DNN and twice to that of shallow machine learning classifiers for 2D-CNN with MFCC. The proposed 2D-CNN model with an F1 score of 85.71% for text-independent speaker identification makes it plausible to use speaker ID as a classification approach for organizing video lectures automatically in a MOOC setting.

  • 168.
    Jakub, Nilsson
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Pose AR: Assessing Pose Based Input in an AR Context2019Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Despite the rapidly growing adoption of augmented reality (AR) applications, existing methods for interacting with AR content are rated poorly, with surveyors of the area calling for better means of interaction, while researchers strive to create more natural input methods, mainly focusing on gesture input.

    This thesis aims to contribute to the aforementioned efforts by recognizing that technologies for consumer-grade smartphone-based pose estimation have been rapidly improving in recent years and due to their increased accuracy may have untapped potential ready to be utilized for user input. To this end, a rudimentary system for pose based input is integrated into prototype applications, which are constructed with both pose based input and touch input in mind.

    In this work, pose, pose estimation, and posed based input refer to using the distance and orientation of the user (or more precisely, the distance and orientation of their device) in relation to the AR content.

    Using said prototypes within a user interaction study allowed the identification of user preferences which indicate the approaches that future efforts into utilizing pose for input in an AR context ought to adopt. By comparing questionnaire answers and logged positional data across four prototype scenarios, it can be clearly identified that to perceive pose input as intuitive, the AR experiences shouldn’t employ a scale which is so large that it requires substantial shifts in the position of the user, as opposed to merely shifts in the position of the user’s device.

  • 169.
    Jansen, Marc
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). University of Applied Sciences Ruhr West, Germany.
    Kohen-Vacs, Dan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). Holon Institute of Technology (HIT), Israel.
    Otero, Nuno
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM). ISCTE Lisbon University Institute, Portugal.
    Milrad, Marcelo
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    A Complementary View for Better Understanding the Term Computational Thinking2018Ingår i: Proceedings of the International Conference on Computational Thinking Education 2018, Hong Kong: The Education University of Hong Kong , 2018, s. 2-7Konferensbidrag (Refereegranskat)
    Abstract [en]

    The term Computational Thinking is closely related to efforts connected to teach a systematic and well-structured way of problem solving that includes a set of tools and techniques used in Computer Science. While substantial research in this field has shown promising outcomes concerning distinct intervention programs and teaching initiatives, the term Computational Thinking itself requires to be revised in order to get a wider consensus about its meaning and purpose. This paper contributes to the ongoing quest concerning the definition of the term by starting with a fundamental perspective on computational theory and corresponding concepts in order to describe the theoretical building blocks of a systematic view to further elaborate on an approach for teaching and learning about Computational Thinking. Additionally, based on this foundational effort, more advanced concepts are presented and discussed in order to better understand this domain. Finally, the paper identifies and discusses a set of relevant challenges taking a cognitive psychology perspective on Computational Thinking.

  • 170.
    Jansson, Martin
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Petersson, Simon
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Object detection and single-board computers: En förstudie gjord på Saab AB2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Saab använder sig i nuläget av ett utdaterat system för att utföra tester av deras produkter. Systemet filmar ur olika vinklar och sammanfogar videoströmmarna till en slutgiltig video, där de sedan kan analysera resultatet av produkten. Enkortsdatorer är något som på senare år har blivit mer och mer populärt, Saab vill därför undersöka om det går att ersätta det äldre systemet med enkortsdatorer och kameror.Det ska undersökas om enkortsdatorn BeagleBoard klarar av att köra objektidentifiering samtidigt som den filmar och utför operationer som videosynkning, videokodning samt sparar den synkade filmen.Undersökningen visade att BeagleBoardens processor inte är tillräckligt kraftfull för att klara av objektidentifieringen utan hårdvarustöd. Istället behöver det utföras av en dator som bearbetar filmen i efterhand och plockar ut objekt. Det har förslagits en bättre metod för att göra objektidentifieringen smartare och lärande som kommer fungera bättre i Saabs fall.

  • 171.
    Jercic, Petar
    et al.
    Blekinge institute of technology, Sweden.
    Hagelbäck, Johan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Lindley, Craig
    CSIRO, Australia.
    An affective serious game for collaboration between humans and robots2019Ingår i: Entertainment Computing, ISSN 1875-9521, E-ISSN 1875-953X, Vol. 32, s. 1-10, artikel-id 100319Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Elicited physiological affect in humans collaborating with their robot partners was investigated to determine its influence on decision-making performance in serious games. A turn-taking version of the Tower of Hanoi game was used, where physiological arousal and valence underlying such human-robot proximate collaboration were investigated. A comparable decision performance in the serious game was found between human and non-humanoid robot arm collaborator conditions, while higher physiological affect was found in humans collaborating with such robot collaborators. It is suggested that serious games which are carefully designed to take into consideration the elicited physiological arousal might witness a better decision-making performance and more positive valence using non-humanoid robot partners instead of human ones.

  • 172.
    Jercic, Petar
    et al.
    Blekinge Tekniska Högskola.
    Wen, Wei
    Blekinge Tekniska Högskola.
    Hagelbäck, Johan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap (DV).
    Sundstedt, Veronica
    Blekinge Tekniska Högskola.
    The Effect of Emotions and Social Behavior on Performance in a Collaborative Serious Game Between Humans and Autonomous Robots2018Ingår i: International Journal of Social Robotics, ISSN 1875-4791, E-ISSN 1875-4805, Vol. 10, nr 1, s. 115-129Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The aim of this paper is to investigate performance in a collaborative human–robot interaction on a shared serious game task. Furthermore, the effect of elicited emotions and perceived social behavior categories on players’ performance will be investigated. The participants collaboratively played a turn-taking version of the Tower of Hanoi serious game, together with the human and robot collaborators. The elicited emotions were analyzed in regards to the arousal and valence variables, computed from the Geneva Emotion Wheel questionnaire. Moreover, the perceived social behavior categories were obtained from analyzing and grouping replies to the Interactive Experiences and Trust and Respect questionnaires. It was found that the results did not show a statistically significant difference in participants’ performance between the human or robot collaborators. Moreover, all of the collaborators elicited similar emotions, where the human collaborator was perceived as more credible and socially present than the robot one. It is suggested that using robot collaborators might be as efficient as using human ones, in the context of serious game collaborative tasks.

  • 173.
    Jerčić, Petar
    et al.
    Blekinge Tekniska Högskola.
    Hagelbäck, Johan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Lindley, Craig
    CSIRO ICT Centre, Hobart, Australia.
    Physiological Affect and Performance in a Collaborative Serious Game Between Humans and an Autonomous Robot2018Ingår i: Entertainment Computing – ICEC 2018: 17th IFIP TC 14 International Conference, Held at the 24th IFIP World Computer Congress, WCC 2018, Poznan, Poland, September 17–20, 2018 / [ed] Clua E., Roque L., Lugmayr A., Tuomi P., Springer, 2018, s. 127-138Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper sets out to examine how elicited physiological affect influences the performance of human participants collaborating with the robot partners on a shared serious game task; furthermore, to investigate physiological affect underlying such human-robot proximate collaboration. The participants collaboratively played a turn-taking version of a serious game Tower of Hanoi, where physiological affect was investigated in a valence-arousal space. The arousal was inferred from the galvanic skin response data, while the valence was inferred from the electrocardiography data. It was found that the robot collaborators elicited a higher physiological affect in regard to both arousal and valence, in contrast to their human collaborator counterparts. Furthermore, a comparable performance between all collaborators was found on the serious game task.

  • 174.
    Johansson, Albin
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Increasing the robustness of a service in a complex information flow2019Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    In complex information flows where a lot of varied data is transmitted through many companies and divisions, incidents will occur. When Visma Spcs had an incident where invoices sent from Visma to Visma's customers were duplicated and the service meant to receive the transactions did not handle the duplicates properly. They decided that the receiver service was to be upgraded to prevent this incident from happening again, as well as fixing some other issues the service had had. Incidents like this one must be investigated and a solution must be implemented to decrease the likelihood that similar incidents will happen again. In this report, the reader will see examples on how this can be handled and the benefits of tackling technical debt, along with how much more complicated the solutions might get if the service is not allowed to be taken offline.

  • 175.
    Johansson, Daniel
    Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för organisation och entreprenörskap (OE). Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    From products to consumption: changes on the Swedish music market as a result of streaming technologies2013Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Since the year 2009, the Swedish music market has changed drastically. In the first six months of 2013, 75 percent of total revenues to Swedish repertoire owners came from digital distribution. More than 90 percent of those revenues came from streaming. More than half of the population has a streaming subscription, and streaming has become the dominant format for consuming music on this specific market. As a result of this paradigm shift, changes have occurred in the Swedish music industrial system, as well as in user behaviors. This report examines how the Swedish music market has changed as a result of à la carte on demand streaming, explains the streaming model as such and give a picture of what these changes could mean for the future.

  • 176.
    Johansson, Daniel
    Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för organisation och entreprenörskap (OE). Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    Music festivals in Sweden - an analysis of the ten largest commercial festivals 2000 - 20132014Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This study examines the development for commercial music festivals in Sweden during the time period 2000 - 2013. Although it is clear that some legendary Swedish music festivals have disappeared during the latest years, this study indicates that the number of paying visitors of the largest festivals continues to increase. In fact, 2013 was the record year during the studied time frame regarding the number of paying visitors to the ten largest commercial festivals, with official visitor figures validated through STIM data. Nevertheless, the Swedish music festival market has changed considerably. The purpose of the paper is to describe some of these changes as well as provide a quantitative foundation for further research questions to be dealt with in the future.

  • 177.
    Johansson, Elias
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Separation and Extraction of Valuable Information From Digital Receipts Using Google Cloud Vision OCR.2019Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Automatization is a desirable feature in many business areas. Manually extracting information from a physical object such as a receipt is something that can be automated to save resources for a company or a private person. In this paper the process will be described of combining an already existing OCR engine with a developed python script to achieve data extraction of valuable information from a digital image of a receipt. Values such as VAT, VAT%, date, total-, gross-, and net-cost; will be considered as valuable information. This is a feature that has already been implemented in existing applications. However, the company that I have done this project for are interested in creating their own version. This project is an experiment to see if it is possible to implement such an application using restricted resources. To develop a program that can extract the information mentioned above. In this paper you will be guided though the process of the development of the program. As well as indulging in the mindset, findings and the steps taken to overcome the problems encountered along the way. The program achieved a success rate of 86.6% in extracting the most valuable information: total cost, VAT% and date from a set of 53 receipts originated from 34 separate establishments.

  • 178.
    Johansson, Michael
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Internet of things security in healthcare: A test-suite and standard review2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Internet of things is getting more and more popular in healthcare as it comes with benefits that help with efficiency in saving lives and reduce its cost, but it also presents a new attack vector for an attacker to steal or manipulate information sent between them. This report will focus on three properties in the definition of security, confidentiality, integrity and access control. The report will look into what challenges there is in healthcare IoT today through a literature review and from those challenges look into what could minimise these challenges before a device gets into production. The report found that the lack of standardisation has lead to errors that could be easily prevented by following a guideline of tests as those from the European Union Agency for Network and Information Security, or by running a penetration test with the tools brought up in the report on the device to see what vulnerabilities are present.

  • 179.
    Johansson, Oscar
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    Forsman, Max
    Shared computer systems and groupware development: Escaping the personal computer paradigm2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    For the majority of the computers existence, we humans have interacted with them in a similar way, usually with a strict one-to-one relationship between user and machine. This is reflected by the design of most computers, operating systems and user applications on the market today, which are typically intended to only be operated by a single user. When computers are used for teamwork and cooperation, this design philosophy can be restricting and problematic. This paper investigates the development of shared software intended for multiple users and the impact of the single user bias in this context. A prototype software system was developed in order to evaluate different development methods for shared applications and discover potential challenges and limitations with this kind of software. It was found that the development of applications for multiple users can be severely limited by the target operating system and hardware platform. The authors conclude that new platforms are required to develop shared software more efficiently. These platforms should be tailored to provide robust support for multiple concurrent users. This work was carried out together with SAAB Air Traffic Management in Växjö, Sweden and is a bachelor's thesis in computer engineering at Linnaeus University.

  • 180.
    Johansson, Pauline
    et al.
    Linnéuniversitetet, Fakulteten för Hälso- och livsvetenskap (FHL), Institutionen för hälso- och vårdvetenskap (HV).
    Wilde Björling, Camilla
    Kalmar County Council, Sweden.
    Axelsson, Clara
    Linnéuniversitetet, Fakulteten för Hälso- och livsvetenskap (FHL), Institutionen för medicin och optometri (MEO).
    Östlund, Martin
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för medieteknik (ME).
    Widell, Ingela
    Kalmar County Council, Sweden.
    Jonsson, Stefan
    Kalmar County Council, Sweden.
    Tablet computers as a mean to strengthen patients undergoing radiotherapy2015Ingår i: Presented at the 6th International Carers Conference - Care and caring: future proofing the new demographics, Gothenburg, Sweden, September 3-6, 2015, 2015Konferensbidrag (Refereegranskat)
  • 181.
    Jusufi, Ilir
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Memedi, Mevludin
    Örebro University, Sweden.
    Interactive visualization of sensor and self-reported data of patients with Parkinson's disease2019Ingår i: MIRAI AGEING Seminar, November 13-14, 2019, Stockh, 2019Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Advancements in telemedicine have been helpful for frequent monitoring of patients with Parkinson's disease (PD) from remote locations and assessment of their individual symptoms and treatment-related complications. These data can be useful for helping clinicians and patients to interpret symptom states and individually tailor the treatments by visualizing the physiological information collected by sensor-based systems as well as patient self-reported states. Here we present various visualization and interaction techniques to help physicians explore patient’s daily activities, which could be useful for guiding them during the decision-making process. An interface is designed to visualize symptom and medication information, collected by an Internet of Things-based system comprising of a smartphone, electronic dosing device, wrist sensor and a bed sensor.

  • 182.
    Jusufi, Ilir
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Memedi, Mevludin
    Örebro University. Sweden.
    Interactive visualization tools for improving empowerment and treatment of Parkinson's disease patients2019Ingår i: MIRAI AGEING Workshop, June 2-5, 2019, Tokyo, 2019Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Advancements in telemedicine have been helpful for frequent monitoring of patients with Parkinson's disease (PD) from remote locations and assessment of their individual symptoms and treatment-related complications. These data can be useful for helping clinicians and patients to interpret symptom states and individually tailor the treatments by visualizing the physiological information collected by sensor-based systems. Here we present various visualization and interaction techniques developed to help patients track their daily activities. We also present our most recent development to aid physicians in exploring this data in more detailed fashion. Both sets of interfaces are designed to visualize symptom and medication information, collected by an Internet of Things (IoT)-based system comprising of a smartphone, electronic dosing device, wrist sensor and a bed sensor.

  • 183.
    Jusufi, Ilir
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Memedi, Mevludin
    Örebro University.
    Nyholm, Dag
    Uppsala University.
    TapVis: A Data Visualization Approach for Assessment of Alternating Tapping Performance in Patients with Parkinson's Disease2018Ingår i: EuroVis 2018 - Short Papers / [ed] / J. Johansson, F. Sadlo, and T. Schreck, Eurographics - European Association for Computer Graphics, 2018, s. 55-59Konferensbidrag (Refereegranskat)
    Abstract [en]

    Advancements in telemedicine have been helpful for frequent monitoring of patients with Parkinson's disease (PD) from remote locations and assessment of their individual symptoms and treatment-related complications. These data can be useful for helping clinicians to interpret symptom states and individually tailor the treatments by visualizing the physiological information collected by sensor-based systems. In this paper we present a visualization metaphor that represents symptom information of PD patients during tapping tests performed with a smartphone. The metaphor has been developed and evaluated with a clinician. It enabled the clinician to observe fine motor impairments and identify motor fluctuations regarding several movement aspects of patients that perform the tests from their homes.

  • 184. Juziuk, Joanna
    et al.
    Weyns, Danny
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för datavetenskap (DV).
    Holvoet, Tom
    Katholieke Universiteit Leuven, Belgium.
    Design Patterns for Multi-Agent Systems: A Systematic Literature Review2014Ingår i: Agent-Oriented Software Engineering: Reflections on Architectures, Methodologies, Languages, and Frameworks / [ed] Onn Shehory, Arnon Sturm, Berlin/Heidelberg: Springer, 2014, s. 79-99Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Design patterns document a field’s systematic knowledge derived from experiences. Despite the vast body of work in the field of multi-agent systems (MAS), design patterns for MAS are not popular among software practitioners. As MAS have features that are widely considered as key to engineering complex distributed applications, it is important to provide a clear overview of existing patterns to make this knowledge accessible. To that end, we performed a systematic literature review (SLR) covering the main publication venues of the field since 1998, resulting in 206 patterns. The study shows that (1) there is a lack of a standard template for documenting design patterns for MAS, which hampers the use of patterns by practitioners, (2) associations between patterns are poorly described, which results in a lack of overview of the pattern space, (3) patterns for MAS have been used for a variety of application domains, which underpins their high potential for practitioners, and (4) classifications of design patterns for MAS are bounded to specific pattern catalogs, a more holistic view on the pattern space is missing. From our study, we outline a number of guidelines that are important for future work on design patterns for MAS and their adoption in practice.

  • 185.
    Jäderlund, Maria
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Wed 2.0: improving customer experience with wedding service providers through investigation of the ranking mechanism and sentiment analysis of user feedback on Instagram2019Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Instagram is one of the main social platforms for business promotion. Millions of potential customers and endless visual marketing opportunities makes Instagram a perfect place to increase online sales. There are many tools and mechanisms to promote brands on Instagram such as paid advertising or using a pre-generated set of popular hashtags. In this regard, the presence and content of users’ comments becomes an important socio-psychological factor in the motivation to buy or use a product or service. The goal of this degree project is to investigate natural language processing techniques applied to users’ comments on Instagram in order to determine a new algorithm that will include content analysis to the list of feed ranking factors. As it is now, the user has to read through posts on Instagram to get an idea of the quality of a product or service. Therefore, a way to classify and rank products and services is needed. We propose a new algorithm called "Wed 2.0" that can assist consumers in their search of wedding services and products on Instagram. Data mining techniques and sentiment analysis are used to define the mood of the comments and structure user opinions as well as to rank accounts based on this knowledge.

  • 186.
    Karlsson, Axel
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Nordquist, Oscar
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    BabylonJS and Three.js: Comparing performance when it comes to rendering Voronoi height maps in 3D2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    WebGL is a technique that allows the browser to run 3D applications with the help of the GPU. Voronoi diagrams are a set of polygons that can be used to illustrate worlds of islands. In an web-application using Voronoi Polygons to create two dimensional worlds there is a future vision to enable three dimensional behavior. There are multiple frameworks and libraries that can be used to simplify the process of creating 3D applications in the browser. Due to the fact that 3D applications can be performance demanding, an experiment was conducted with BabylonJS and Three.js. In order to evaluate which one of the two performed better, RAM, GPU and CPU were evaluated when translating two dimensional Voronoi heightmaps into a 3D application. The results from this stress test prove that Three.js outperformed BabylonJS.

  • 187.
    Karlsson, Beppe
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Tweeting opinions: How does Twitter data stack up against the polls and betting odds?2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    With the rise of social media, people have gained a platform to express opinions and discuss current subjects with others. This thesis investigates whether a simple sentiment analysis — determining how positive a tweet about a given party is — can be used to predict the results of the Swedish general election and compares the results to betting odds and opinion polls. The results show that while the idea is an interesting one, and sometimes the data can point in the right direction, it is by far a reliable source to predict election outcomes.

  • 188.
    Karlsson, Hanna
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Utformningen av ett videoredigeringsprogram för undervisning i källkritik på lågstadienivå.2019Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Idag finns det ett begränsat utbud av material för källkritiska övningar på lågstadienivå och undervisning i källkritik anses påbörjas i för höga årskurser (Skolverket 2018a; Skolverket 2019a). Detta är två centrala aspekter i denna studie. Syftet med studien är att undersöka om ett videoredigeringsprogram med stöd för interaktivitet kan underlätta dagens undervisning i källkritik på lågstadienivå, samt vilka behov och utmaningar som finns idag. Studien syftar också till att ta reda på hur ett sådant videoredigeringsprogram skulle kunna se ut och fungera. Tanken med studiens tjänst är att eleverna ska lära sig tänka källkritiskt och enklare kunna urskilja vad som är sant eller falskt genom videoredigering där inlagda filmklipp kan manipuleras. För lågstadielärarnas del finns potential för att undervisa eleverna genom skapande av interaktivitet som kan leda till bland annat diskussion i klassrummet. För att ta reda på om tjänsten kan underlätta undervisning i källkritik, vilka behov och utmaningar som finns idag samt önskad funktionalitet och design har flera lärare deltagit i enkätundersökningar och intervjuer. Elever har även observerats vid användning av studiens tjänst för att sedan intervjuas.

    Det som upptäckts i studien är bland annat att lågstadielärare är ovana inom ämnet, de har svårt att hitta material och är i behov av källkritiskt material för lägre åldrar. Eleverna har en vana av digitala verktyg men behöver bland annat tydliga och enkla instruktioner utan ett avancerat språk och god tid på sig att läsa dessa instruktioner. Får att fånga uppmärksamhet av de elever som deltagit i studien behövs också utstickande färger på centrala knappar samt begränsat med valmöjligheter. I studien framkommer även att det finns en önskan om källkritisk undervisning i lägre åldrar, som till exempel i lågstadiet eller förskolan. Det har även framkommit att studiens prototyp eller liknande tjänst möjligtvis kunnat underlätta undervisning i källkritik, detta är dock något som kräver vidare forskning.

  • 189.
    Karlsson, Leif
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Time-synchronized wireless mesh networks using battery-powered nodes2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    This thesis proposes an implementation of battery-powered, time-synchronized wireless nodes that can be deployed in a wireless network topology. Wireless sensor networks are used in a wide variety of scenarios where emphasis is placed on the wireless nodes’ battery life. The main area of focus in this thesis is to examine how wireless nodes can save battery power by utilizing a deep sleep mode and wake up simultaneously using time synchronization to carry out their data communication. This was achieved by deploying five time-synchronized, battery-powered nodes in a wireless network topology. The difference in battery current draw between continuously running nodes and sleep-enabled nodes were measured, as well as the time duration needed by the nodes to successfully send their payloads and route other nodes’ data. The nodes needed between 1502 ms and 3273 ms on average to carry out their data communication, depending on where they were located in the network topology. Measurements show that sleep-enabled nodes on average draw substantially less current than continuously running nodes during a complete data communication cycle. When sleep-enabled nodes were powered by two AA batteries, an increase in battery life of up to 1800% was observed.

  • 190.
    Karlsson, Rasmus
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Exploring a video game AI bot that scans and reacts to its surroundings in real-time.2018Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    The buzz surrounding artificial intelligences continues to grow. They are currently used in a wide variety of systems and appliances, such as video games, virtual personal assistants, and self-driving cars. This paper explores the possibility of a self-learning AI that can play the classic arcade game Q*BERT, using only screenshots as input. It is tested to work on several different screens sizes, and the results are collected and compared to that of a human player, as well as results from previous research. The results are fairly positive. While the AI had a hard time of matching the human player on average score, it did get close to the highest score.

  • 191.
    Karlsson, Viktor
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM), Institutionen för medieteknik (ME).
    Concept of Interactive Video in Job Application: A qualitative research that tests the concept of interactive video and job seekers’ ability creating interactive video resumes.2019Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Interactive video seems to currently be an unpopular field of research. Video resumes however is an increasing trend when applying for jobs and sending out resumes. During this thesis, employers finds interactive video as a new, fun and exciting way of interacting with a resume that simplifies the recruitment process. Also, job seekers find creating interactive video as resumes as an extra nudge in to a company and a better way of marketing themselves for employers. However, conflict occurs between employers and job seekers regarding an interactive video resume. As it simplifies the recruitment process, job seekers have to put down more work when creating an interactive video resume while applying for a job.

    It is shown in this thesis that there are factors that should be investigated, for instance a platform aimed at interactive video resumes seems not have been developed yet as well as what interactive features an interactive video resume should contain. Job seekers find it difficult if creating such resumes took too long, being unaware of how to display interactive visual elements and which aspects to talk about while recording themselves.

    This thesis explores the possibility of employers and former recruitment personnel using an interactive video resume as well as job seekers’ ability of creating an interactive video. The main aims of this thesis are to find guidelines of what an interactive video resume mainly should contain and what job seekers thinks of creating and using an interactive video when applying for jobs.

  • 192.
    Kasianenko, Stanislav
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Predicting Software Defectiveness by Mining Software Repositories2018Självständigt arbete på avancerad nivå (magisterexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    One of the important aims of the continuous software development process is to localize and remove all existing program bugs as fast as possible. Such goal is highly related to software engineering and defectiveness estimation. Many big companies started to store source code in software repositories as the later grew in popularity. These repositories usually include static source code as well as detailed data for defects in software units. This allows analyzing all the data without interrupting programing process. The main problem of large, complex software is impossibility to control everything manually while the price of the error can be very high. This might result in developers missing defects on testing stage and increase of maintenance cost. The general research goal is to find a way of predicting future software defectiveness with high precision. Reducing maintenance and development costs will contribute to reduce the time-to-market and increase software quality.

    To address the problem of estimating residual defects an approach was found to predict residual defectiveness of a software by the means of machine learning. For a prime machine learning algorithm, a regression decision tree was chosen as a simple and reliable solution. Data for this tree is extracted from static source code repository and divided into two parts: software metrics and defect data. Software metrics are formed from static code and defect data is extracted from reported issues in the repository. In addition to already reported bugs, they are augmented with unreported bugs found on “discussions” section in repository and parsed by a natural language processor. Metrics were filtered to remove ones, that were not related to defect data by applying correlation algorithm. Remaining metrics were weighted to use the most correlated combination as a training set for the decision tree. As a result, built decision tree model allows to forecast defectiveness with 89% chance for the particular product. This experiment was conducted using GitHub repository on a Java project and predicted number of possible bugs in a single file (Java class). The experiment resulted in designed method for predicting possible defectiveness from a static code of a single big (more than 1000 files) software version.

  • 193.
    Kastrati, Zenun
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Imran, Ali Shariq
    Norwegian University of Science and Technology, Norway.
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Integrating word embeddings and document topics with deep learning in a video classification framework2019Ingår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 128, s. 85-92Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The advent of MOOC platforms brought an abundance of video educational content that made the selection of best fitting content for a specific topic a lengthy process. To tackle this challenge in this paper we report our research efforts of using deep learning techniques for managing and classifying educational content for various search and retrieval applications in order to provide a more personalized learning experience. In this regard, we propose a framework which takes advantages of feature representations and deep learning for classifying video lectures in a MOOC setting to aid effective search and retrieval. The framework consists of three main modules. The first module called pre-processing concerns with video-to-text conversion. The second module is transcript representation which represents text in lecture transcripts into vector space by exploiting different representation techniques including bag-of-words, embeddings, transfer learning, and topic modeling. The final module covers classifiers whose aim is to label video lectures into the appropriate categories. Two deep learning models, namely feed-forward deep neural network (DNN) and convolutional neural network (CNN) are examined as part of the classifier module. Multiple simulations are carried out on a large-scale real dataset using various feature representations and classification techniques to test and validate the proposed framework.

  • 194.
    Kastrati, Zenun
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Imran, Ali Shariq
    Norwegian University of Science and Technology - NTNU, Norway.
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Transfer Learning to Timed Text Based Video Classification Using CNN2019Ingår i: Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics, Seoul, South Korea: ACM Publications, 2019, artikel-id 23Konferensbidrag (Refereegranskat)
    Abstract [en]

    Open educational video resources are gaining popularity with a growing number of massive open online courses (MOOCs). This has created a niche for content providers to adopt effective solutions in automatically organizing and structuring of educational resources for maximum visibility. Recent advances in deep learning techniques are proving useful in managing and classifying resources into appropriate categories. This paper proposes one such convolutional neural network (CNN) model for classifying video lectures in a MOOC setting using a transfer learning approach. The model uses a time-aligned text transcripts corresponding to video lectures from six broader subject categories. Video lectures and their corresponding transcript dataset is gathered from the Coursera MOOC platform. Two different CNN models are proposed: i) CNN based classification using embeddings learned from our MOOC dataset, ii) CNN based classification using transfer learning. Word embeddings generated from two well known state-of-the-art pre-trained models Word2Vec and GloVe, are used in the transfer learning approach for the second case.

    The proposed CNN models are evaluated using precision, recall, and F1 score and the obtained performance is compared with both conventional and deep learning classifiers. The proposed CNN models have an F1 score improvement of 10-22 percentage points over DNN and conventional classifiers

  • 195.
    Kastrati, Zenun
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Hagelbäck, Johan
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    The Effect of a Flipped Classroom in a SPOC: Students' Perceptions and Attitudes2019Ingår i: ICETC 2019: Proceedings of the 2019 11th International Conference on Education Technology and Computers, ACM Publications, 2019, s. 246-249Konferensbidrag (Refereegranskat)
    Abstract [en]

    The advent of Massive Open Online Courses (MOOCs) and Small Private Online Courses (SPOCs) has brought opportunities to higher education institutions. Despite this, one of the main drawbacks of MOOCs and SPOCs has been relatively low retention rate of the registered students. Having this in mind in this paper we report our research efforts with a SPOC on Applied Machine Learning specifically tailored for professional students. More concretely, we report our findings with regard to the effects of the flipped classroom approach on the students' perceptions and attitudes. The initial results show that flipping the class had direct effects on students' knowledge and skills compared to a fully online class setting. These findings have offered complementary explanations of the survey regression analysis which revealed that course structure/instructional approach followed by course content are the main drivers in accounting for the variance in students' overall perceptions of the course.

  • 196.
    Kastrati, Zenun
    et al.
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Kurti, Arianit
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Imran, Ali Shariq
    Norwegian University of Science and Technology, Norway.
    WET: Word embedding-topic distribution vectors for MOOC video lectures dataset2020Ingår i: Data in Brief, E-ISSN 2352-3409, Vol. 28, artikel-id 105090Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this article, we present a dataset containing word embeddings and document topic distribution vectors generated from MOOCs video lecture transcripts. Transcripts of 12,032 video lectures from 200 courses were collected from Coursera learning platform. This large corpus of transcripts was used as input to two well-known NLP techniques, namely Word2Vec and Latent Dirichlet Allocation (LDA) to generate word embeddings and topic vectors, respectively. We used Word2Vec and LDA implementation in the Gensim package in Python. The data presented in this article are related to the research article entitled “Integrating word embeddings and document topics with deep learning in a video classification framework” [1]. The dataset is hosted in the Mendeley Data repository [2].

  • 197.
    Kautto Ernberg, Nils
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Analyzing Google SERP: Swedish Search Queries2019Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Search Engine Optimization (SEO) is the technique of improving Web sites visibility in search engines. Since the algorithms that search engines are based on become more intelligent each day, there is a constant urge for new knowledge. In collaboration with RankTrail, new research for discovering insights about SEO has been conducted. Hypotheses around alleged ranking factors have been created based on qualitative interviews. Through a quantitative case study these hypotheses have been analyzed. The first part of the analysis consisted of calculating the Spearman’s Rank-Order Correlation. Secondly, these correlations has been visualised using histograms. Additional statistical tests have been performed. Number of images, use of HTTPS and use of a custom meta-description stand out amongst all factors analyzed. All three have a higher mean, but also a higher effect size calculated from Cohen’s d. However, the results of this study show that none of the factors indicate a strong impact on SEO. 

  • 198.
    Kazilas, Panagiotis
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Augmenting MPI Programming Process with Cognitive Computing2019Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Cognitive Computing is a new and quickly advancing technology. In thelast decade Cognitive Computing has been used to assist researchers in theirendeavors in many different scientific fields such as Health & medicine,Education, Marketing, Psychology and Financial Services. On the otherhand, Parallel programming is a more complex concept than sequentialprogramming. The additional complexity of Parallel Programming isintroduced by its nature that requires implementations of more complexalgorithms and it introduces additional concepts to the developers, namelythe communication between the processes (Distributed memory systems)that execute the parallel program and their synchronization (Share memorysystems). As a result of this additional complexity, a lot of novice developersare reserved in their attempts to implement parallel programs. The objectiveof this research project was to investigate whether we can assist parallelprogramming process through cognitive computing solutions. In order toachieve our objective, the MPI Assistant, a Q&A system has been developedand a case study has been carried out to determine our application’s efficiencyin our attempt to assist parallel programming developers. The case studyshowed that our MPI Assistant system indeed helped developers reduce thetime they spend to develop their solutions, but not improve the quality ofthe program or its efficiency as these improvements require features that areout of this research project’s scope. However, the case study had limitednumber of participants, which may affect our results’ reliability. As a nextstep in our attempt to determine if cognitive computing technologies are ableto assist developers in their parallel programming development, we movedto investigate if cognitive solutions can extract better and more completeresponses compared to our manually-created responses that we created forthe MPI Assistant. We have experimented with 2 different approaches to theproblem. An approach where we manually created responses for the MPIAssistant, and an approach where we investigated if cognitive solutions canautomatically extract better and complete responses. We compared the qualityof the latter automatic responses with the quality of the former which weremanually created.

  • 199.
    Keller, Damián
    et al.
    Federal University of Acre, Brazil.
    Otero, Nuno
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för medieteknik (ME).
    Lazzarini, Victor
    National University of Ireland, Ireland.
    Pimenta, Marcelo Soares
    Federal University of Rio Grande do Sul, Brazil.
    de Lima, Maria Helena
    Federal University of Rio Grande do Sul, Brazil.
    Johann, Marcelo
    Federal University of Rio Grande do Sul, Brazil.
    Costalonga, Leandro
    Federal University of Espirito Santo, Brazil.
    Interaction Aesthetics and Ubiquitous Music2015Ingår i: Creativity in the Digital Age / [ed] Nelson Zagalo and Pedro Branco, Springer, 2015, s. 91-105Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    Two recent approaches to interaction design have good potential to address creative practice in everyday settings: interaction aesthetics and ubiquitous music. We discuss the theoretical and methodological issues raised by both perspectives and highlight the similarities and differences among the two approaches. Through the analysis of a series of experiments, a common theme emerges: relational properties may provide a useful target for creativity-oriented experimental work.

  • 200.
    Kerren, Andreas
    Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).
    Special issue on VINCI 2016 best papers2018Ingår i: Journal of Visual Languages and Computing, ISSN 1045-926X, E-ISSN 1095-8533, Vol. 48, s. 9-9Artikel i tidskrift (Övrigt vetenskapligt)
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