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  • 1.
    Abdelraheem, Mohamed Ahmed
    et al.
    SICS Swedish ICT AB, SWE.
    Gehrmann, Christian
    SICS Swedish ICT AB, SWE.
    Lindström, Malin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Nordahl, Christian
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Executing Boolean queries on an encrypted Bitmap index2016In: CCSW 2016 - Proceedings of the 2016 ACM Cloud Computing Security Workshop, co-located with CCS 2016, Association for Computing Machinery (ACM), 2016, p. 11-22Conference paper (Refereed)
    Abstract [en]

    We propose a simple and efficient searchable symmetric encryption scheme based on a Bitmap index that evaluates Boolean queries. Our scheme provides a practical solution in settings where communications and computations are very constrained as it offers a suitable trade-off between privacy and performance.

  • 2.
    Abghari, Shahrooz
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Boeva, Veselka
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Casalicchio, Emiliano
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Exner, Peter
    Sony R&D Center Lund Laboratory, SWE.
    An Inductive System Monitoring Approach for GNSS Activation2022In: IFIP Advances in Information and Communication Technology / [ed] Maglogiannis, I, Iliadis, L, Macintyre, J, Cortez, P, Springer Science+Business Media B.V., 2022, Vol. 647, p. 437-449Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a Global Navigation Satellite System (GNSS) component activation model for mobile tracking devices that automatically detects indoor/outdoor environments using the radio signals received from Long-Term Evolution (LTE) base stations. We use an Inductive System Monitoring (ISM) technique to model environmental scenarios captured by a smart tracker via extracting clusters of corresponding value ranges from LTE base stations’ signal strength. The ISM-based model is built by using the tracker’s historical data labeled with GPS coordinates. The built model is further refined by applying it to additional data without GPS location collected by the same device. This procedure allows us to identify the clusters that describe semi-outdoor scenarios. In that way, the model discriminates between two outdoor environmental categories: open outdoor and semi-outdoor. The proposed ISM-based GNSS activation approach is studied and evaluated on a real-world dataset contains radio signal measurements collected by five smart trackers and their geographical location in various environmental scenarios.

  • 3.
    Adamov, Alexander
    et al.
    Kharkiv Natl Univ Radio Elect, NioGuard Secur Lab, Kharkov, Kharkiv Oblast, Ukraine..
    Carlsson, Anders
    Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
    A Sandboxing Method to Protect Cloud Cyberspace2015In: PROCEEDINGS OF 2015 IEEE EAST-WEST DESIGN & TEST SYMPOSIUM (EWDTS), IEEE Communications Society, 2015Conference paper (Refereed)
    Abstract [en]

    This paper addresses the problem of protecting cloud environments against targeted attacks, which have become a popular mean of gaining access to organization's confidential information and resources of cloud providers. Only in 2015 eleven targeted attacks have been discovered by Kaspersky Lab. One of them - Duqu2 - successfully attacked the Lab itself. In this context, security researchers show rising concern about protecting corporate networks and cloud infrastructure used by large organizations against such type of attacks. This article describes a possibility to apply a sandboxing method within a cloud environment to enforce security perimeter of the cloud.

  • 4.
    Ahmadi Mehri, Vida
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Tutschku, Kurt
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Privacy and trust in cloud-based marketplaces for AI and data resources2017In: IFIP Advances in Information and Communication Technology, Springer New York LLC , 2017, Vol. 505, p. 223-225Conference paper (Refereed)
    Abstract [en]

    The processing of the huge amounts of information from the Internet of Things (IoT) has become challenging. Artificial Intelligence (AI) techniques have been developed to handle this task efficiently. However, they require annotated data sets for training, while manual preprocessing of the data sets is costly. The H2020 project “Bonseyes” has suggested a “Market Place for AI”, where the stakeholders can engage trustfully in business around AI resources and data sets. The MP permits trading of resources that have high privacy requirements (e.g. data sets containing patient medical information) as well as ones with low requirements (e.g. fuel consumption of cars) for the sake of its generality. In this abstract we review trust and privacy definitions and provide a first requirement analysis for them with regards to Cloud-based Market Places (CMPs). The comparison of definitions and requirements allows for the identification of the research gap that will be addressed by the main authors PhD project. © IFIP International Federation for Information Processing 2017.

  • 5.
    Angelova, Milena
    et al.
    Technical University of Sofia-branch Plovdiv, BUL.
    Vishnu Manasa, Devagiri
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boeva, Veselka
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    Lavesson, Niklas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    An expertise recommender system based on data from an institutional repository (DiVA)2018In: Proceedings of the 22nd edition of the International Conference on ELectronic PUBlishing: From Projects to Sustainable Infrastructure, ELPUB 2018 / [ed] Chan L.,Mounier P., OpenEdition Press , 2018Conference paper (Refereed)
    Abstract [en]

    Finding experts in academics is an important practical problem, e.g. recruiting reviewersfor reviewing conference, journal or project submissions, partner matching for researchproposals, finding relevant M. Sc. or Ph. D. supervisors etc. In this work, we discuss anexpertise recommender system that is built on data extracted from the Blekinge Instituteof Technology (BTH) instance of the institutional repository system DiVA (DigitalScientific Archive). DiVA is a publication and archiving platform for research publicationsand student essays used by 46 publicly funded universities and authorities in Sweden andthe rest of the Nordic countries (www.diva-portal.org). The DiVA classification system isbased on the Swedish Higher Education Authority (UKÄ) and the Statistic Sweden's (SCB)three levels classification system. Using the classification terms associated with studentM. Sc. and B. Sc. theses published in the DiVA platform, we have developed a prototypesystem which can be used to identify and recommend subject thesis supervisors inacademy.

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  • 6.
    Angelova, Milena
    et al.
    Technical University of sofia, BUL.
    Vishnu Manasa, Devagiri
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Boeva, Veselka
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    Lavesson, Niklas
    An Expertise Recommender System based on Data from an Institutional Repository (DiVA)2019In: Connecting the Knowledge Common from Projects to sustainable Infrastructure: The 22nd International conference on Electronic Publishing - Revised Selected Papers / [ed] Leslie Chan, Pierre Mounier, OpenEdition Press , 2019, p. 135-149Chapter in book (Refereed)
    Abstract [en]

    Finding experts in academics is an important practical problem, e.g. recruiting reviewersfor reviewing conference, journal or project submissions, partner matching for researchproposals, finding relevant M. Sc. or Ph. D. supervisors etc. In this work, we discuss anexpertise recommender system that is built on data extracted from the Blekinge Instituteof Technology (BTH) instance of the institutional repository system DiVA (DigitalScientific Archive). DiVA is a publication and archiving platform for research publicationsand student essays used by 46 publicly funded universities and authorities in Sweden andthe rest of the Nordic countries (www.diva-portal.org). The DiVA classification system isbased on the Swedish Higher Education Authority (UKÄ) and the Statistic Sweden's (SCB)three levels classification system. Using the classification terms associated with studentM. Sc. and B. Sc. theses published in the DiVA platform, we have developed a prototypesystem which can be used to identify and recommend subject thesis supervisors in academy.

  • 7.
    Bangabash, Subhasish
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Panda, Srimanta
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Machine Learning - Managerial Perspective: A Study to define concepts and highlight challenges in a product-based IT Organization2019Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The purpose of this research is to understand the main managerial challenges that arise in the context of Machine Learning. This research aims to explore the core concepts of Machine Learning and provide the same conceptual foundation to managers to overcome possible obstacles while implementing Machine Learning. Therefore, the main research question is: 

    What are the phases and the main challenges while managing Machine Learning project in a product based IT organization? 

     The focus is on the main concepts of Machine Learning and identifying challenges during each phase through literature review and qualitative data collected from interviews conducted with professionals. The research aims to position itself in the field of research which looks for inputs from consultants and management professionals either associated with Machine Learning or they are planning to start such initiatives. In this research paper we introduce ACDDT (Agile-Customer-Data-Domain-Technology) model framework for managers. This framework is centered on the main challenges in Machine Learning project phases while dealing with customer, data, domain and technology. In addition, the frame work also provides key inputs to managers for managing those challenges and possibly overcome them.

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    Machine Learning
  • 8.
    Brodka, Piotr
    et al.
    Wroclaw Univ Technol, Inst Informat, PL-50370 Wroclaw, Poland..
    Sobas, Mateusz
    Wroclaw Univ Technol, Inst Informat, PL-50370 Wroclaw, Poland..
    Johnson, Henric
    Blekinge Institute of Technology, School of Computing.
    Profile Cloning Detection in Social Networks2014In: 2014 EUROPEAN NETWORK INTELLIGENCE CONFERENCE (ENIC), IEEE Computer Society, 2014, p. 63-68Conference paper (Refereed)
    Abstract [en]

    Profile cloning is a severe security issue in social networks since it is used to make a profile identical to existing ones. Profile cloning detection creates a possibility to detect frauds that would use people's trust to gather social information. This paper proposes two novel methods of profile cloning detection and also presents state-of-the-art research. The first method is based on the similarity of attributes from both profiles and the second method is based on the similarity of relationship networks. The methods are further evaluated with experiments and the results clearly describes that the proposed methods are useful and efficient compared to existing methods. The paper also stress that profile cloning in Facebook is not only possible but also fairly easy to perform.

  • 9.
    Clementson, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Augustsson, John
    User Study of Quantized MIP Level Data In Normal Mapping Techniques2017Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

     The standard MIP mapping technique halves the resolution of textures for each level of the MIP chain. In this thesis the bits per pixel(bpp) is reduced as well. Normal maps are generally used with MIP maps, and todays industry standard for these are usually 24 bpp.The reduction is simulated as there is currently no support for the lower bpp in GPU hardware.

    Objectives: To render images of normal mapped objects with decreasing bpp for each level in a MIP chain and evaluate these against the standard MIP mapping technique using a subjective user study and an objective image comparison method.

    Methods: A custom software is implemented to render the images with quantized normal maps manually placed in a MIP chain. For the subjective experiment a 2AFC test is used, and the objective part consists of a PDIFF test for the images.

    Results: The results indicate that as the MIP level is increased and the bpp is lowered, users can increasingly see a difference.

    Conclusions: The results show that participants can see a difference as the bpp is reduced, which indicates normal mapping as not suitable for this method, however further study is required before this technique can be dismissed as an applicable method

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  • 10.
    Erik, Wikström
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Expected Damage of Projectile-Like Spell Effects in Games2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Background. Many video games make use of particle effects to portray magic abilities known as spells. Different spells may have large variation in behaviour and colour. Aside from their different appearance, the spells often deal a different amount of damage.

    Objectives. The aim of this paper is to evaluate how velocity, scale, and direction, as well as the colour orange and blue affect the expected damage of a projectile-like spell.Methods. A perceptual experiment with a 2AFC was conducted where participants compared various spells with different values of velocity, scale, direction, and colour. The participants were asked to select the spell that they expect to deal the most damage.

    Results. Scale had a larger impact on the expected damage of a spell than velocity. The largest and fastest spells with an added sinus based direction in the x-axis were expected to cause the most damage. However, the difference between these spells and the largest and fastest spells without the added direction was not found to be statistically significant. The orange spells were rated as more damage causing in all cases compared to the blue spells. The difference between the blue and orange preference in two of these cases were however not large enough to be statistically significant.

    Conclusions. The results showed that the visual attributes of a particle-based spell affect its perceived damage with the scale having a greater impact than velocity and orange being the colour most often associated with higher damage. The effect of an added direction could not be evaluated due the result from the direction spells not being statistically significant.

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    BTH2018Wikström
  • 11.
    Fricker, Samuel
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Maksimov, Yuliyan
    Fachhochschule Nordwestschweiz, CHE.
    Pricing of data products in data marketplaces2017In: Lecture Notes in Business Information Processing / [ed] Werder K.,Ojala A.,Holmstrom Olsson H., Springer Verlag , 2017, Vol. 304, p. 49-66Conference paper (Refereed)
    Abstract [en]

    Mobile computing and the Internet of Things promises massive amounts of data for big data analytic and machine learning. A data sharing economy is needed to make that data available for companies that wish to develop smart systems and services. While digital markets for trading data are emerging, there is no consolidated understanding of how to price data products and thus offer data vendors incentives for sharing data. This paper uses a combined keyword search and snowballing approach to systematically review the literature on the pricing of data products that are to be offered on marketplaces. The results give insights into the maturity and character of data pricing. They enable practitioners to select a pricing approach suitable for their situation and researchers to extend and mature data pricing as a topic. © Springer International Publishing AG 2017.

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  • 12.
    Frid Kastrati, Mattias
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Goswami, Prashant
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Selective rasterized ray-traced reflections on the GPU2016In: Eurographics Proceedings STAG 2016 / [ed] Andrea Giachetti and Silvia Biasotti and Marco Tarini, Eurographics - European Association for Computer Graphics, 2016Conference paper (Refereed)
    Abstract [en]

    Ray-tracing achieves impressive effects such as realistic reflections on complex surfaces but is also more computationally expensive than classic rasterization. Rasterized ray-tracing methods can accelerate ray-tracing by taking advantage of the massive parallelization available in the rasterization pipeline on the GPU. In this paper, we propose a selective rasterized raytracing method that optimizes the rasterized ray-tracing by selectively allocating computational resources to reflective regions in the image. Our experiments suggest that the method can speed-up the computation by up to 4 times and also reduce the memory footprint by almost 66% without affecting the image quality. We demonstrate the effectiveness of our method using complex scenes and animations.

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  • 13.
    Hu, Yan
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Jiang, Zeting
    Blekinge Institute of Technology. student.
    Zhu, Kaicheng
    Blekinge Institute of Technology. student.
    An Optimized CNN Model for Engagement Recognition in an E-Learning Environment2022In: Applied Sciences, E-ISSN 2076-3417, Vol. 12, no 16, article id 8007Article in journal (Refereed)
    Abstract [en]

    In the wake of the restrictions imposed on social interactions due to the COVID-19 pandemic, traditional classroom education was replaced by distance education in many universities. Under the changed circumstances, students are required to learn more independently. The challenge for teachers has been to duly ascertain students’ learning efficiency and engagement during online lectures. This paper proposes an optimized lightweight convolutional neural network (CNN) model for engagement recognition within a distance-learning setup through facial expressions. The ShuffleNet v2 architecture was selected, as this model can easily adapt to mobile platforms and deliver outstanding performance compared to other lightweight models. The proposed model was trained, tested, evaluated and compared with other CNN models. The results of our experiment showed that an optimized model based on the ShuffleNet v2 architecture with a change of activation function and the introduction of an attention mechanism provides the best performance concerning engagement recognition. Further, our proposed model outperforms many existing works in engagement recognition on the same database. Finally, this model is suitable for student engagement recognition for distance learning on mobile platforms. © 2022 by the authors.

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  • 14.
    Hu, Yan
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Sundstedt, Veronica
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Exploring Biometrics as an Evaluation Technique for Digital Game Addiction Prevention2018In: Journal of Behavioral Addictions, ISSN 2062-5871, E-ISSN 2063-5303, Vol. 7, p. 15-15Article in journal (Other academic)
  • 15.
    Ishak, Shaik
    et al.
    Blekinge Institute of Technology.
    Jyothsna Chowdary, Anantaneni
    Blekinge Institute of Technology.
    Evaluating Robustness of a CNN Architecture introduced to the Adversarial Attacks2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Abstract:

    Background: From Previous research, state-of-the-art deep neural networks have accomplished impressive results on many images classification tasks. However, adversarial attacks can easily fool these deep neural networks by adding little noise to the input images. This vulnerability causes a significant concern in deploying deep neural network-based systems in real-world security-sensitive situations. Therefore, research in attacking and the architectures with adversarial examples has drawn considerable attention. Here, we use the technique for image classification called Convolutional Neural Networks (CNN), which is known for determining favorable results in image classification.

    Objectives: This thesis reviews all types of adversarial attacks and CNN architectures in the present scientific literature. Experiment to build a CNN architecture to classify the handwritten digits in the MNIST dataset. And they are experimenting with adversarial attacks on the images to evaluate the accuracy fluctuations in categorizing images. This study also includes an experiment using the defensive distillation technique to improve the architecture's performance under adversarial attacks. 

    Methods: This thesis includes two methods; the systematic literature review method involved finding the best performing CNN architectures and best performing adversarial attack techniques. The experimentation method consists in building a CNN model based on modified LeNet architecture with two convolutional layers, one max-pooling layer, and two dropouts. The model is trained and tested with the MNIST dataset. Then applying adversarial attacks FGSM, IFGSM, MIFGSM on the input images to evaluate the model's performance. Later this model will be modified a little by defensive distillation technique and then tested towards adversarial attacks to evaluate the architecture's performance.

    Results: An experiment is conducted to evaluate the robustness of the CNN architecture in classifying the handwritten digits. The graphs show the accuracy before and after implementing adversarial attacks on the test dataset. The defensive distillation mechanism is applied to avoid adversarial attacks and achieve robust architecture.

    Conclusions: The results showed that FGSM, I-FGSM, MI-FGSM attacks reduce the test accuracy from 95% to around 35%. These three attacks to the proposed network successfully reduced ~70% of the test accuracy in all three cases for maximum epsilon 0.3. By the defensive distillation mechanism, the test accuracy reduces from 90% to 88% for max epsilon 0.3. The proposed defensive distillation process is successful in defending the adversarial attacks. 

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  • 16.
    Javadi, Mohammad Saleh
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Computer Vision Algorithms for Intelligent Transportation Systems Applications2018Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    In recent years, Intelligent Transportation Systems (ITS) have emerged as

    an efficient way of enhancing traffic flow, safety and management. These

    goals are realized by combining various technologies and analyzing the acquired

    data from vehicles and roadways. Among all ITS technologies, computer

    vision solutions have the advantages of high flexibility, easy maintenance

    and high price-performance ratio that make them very popular for

    transportation surveillance systems. However, computer vision solutions

    are demanding and challenging due to computational complexity, reliability,

    efficiency and accuracy among other aspects.

     

    In this thesis, three transportation surveillance systems based on computer

    vision are presented. These systems are able to interpret the image

    data and extract the information about the presence, speed and class of

    vehicles, respectively. The image data in these proposed systems are acquired

    using Unmanned Aerial Vehicle (UAV) as a non-stationary source

    and roadside camera as a stationary source. The goal of these works is to

    enhance the general performance of accuracy and robustness of the systems

    with variant illumination and traffic conditions.

     

    This is a compilation thesis in systems engineering consisting of three

    parts. The red thread through each part is a transportation surveillance

    system. The first part presents a change detection system using aerial images

    of a cargo port. The extracted information shows how the space is

    utilized at various times aiming for further management and development

    of the port. The proposed solution can be used at different viewpoints and

    illumination levels e.g. at sunset. The method is able to transform the images

    taken from different viewpoints and match them together. Thereafter,

    it detects discrepancies between the images using a proposed adaptive local

    threshold. In the second part, a video-based vehicle's speed estimation

    system is presented. The measured speeds are essential information for law

    enforcement and they also provide an estimation of traffic flow at certain

    points on the road. The system employs several intrusion lines to extract

    the movement pattern of each vehicle (non-equidistant sampling) as an input

    feature to the proposed analytical model. In addition, other parameters such as camera sampling rate and distances between intrusion lines are also

    taken into account to address the uncertainty in the measurements and to

    obtain the probability density function of the vehicle's speed. In the third

    part, a vehicle classification system is provided to categorize vehicles into

    \private car", \light trailer", \lorry or bus" and \heavy trailer". This information

    can be used by authorities for surveillance and development of

    the roads. The proposed system consists of multiple fuzzy c-means clusterings using input features of length, width and speed of each vehicle. The

    system has been constructed by using prior knowledge of traffic regulations

    regarding each class of vehicle in order to enhance the classification performance.

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  • 17.
    Jerčić, Petar
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Sennersten, Charlotte
    CSIRO Mineral Resources, AUS.
    Lindley, Craig
    Intelligent Sensing and Systems Laboratory, CSIRO ICT Centre, AUS .
    Modeling cognitive load and physiological arousal through pupil diameter and heart rate2020In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 79, no 5-6, p. 3145-3159Article in journal (Refereed)
    Abstract [en]

    This study investigates individuals’ cognitive load processing abilities while engaged on a decision-making task in serious games, to explore how a substantial cognitive load dominates over the physiological arousal effect on pupil diameter. A serious game was presented to the participants, which displayed the on–line biofeedback based on physiological measurements of arousal. In such dynamic decision-making environment, the pupil diameter was analyzed in relation to the heart rate, to evaluate if the former could be a useful measure of cognitive abilities of individuals. As pupil might reflect both cognitive activity and physiological arousal, the pupillary response will show an arousal effect only when the cognitive demands of the situation are minimal. Evidence shows that in a situation where a substantial level of cognitive activity is required, only that activity will be observable on the pupil diameter, dominating over the physiological arousal effect indicated by the pupillary response. It is suggested that it might be possible to design serious games tailored to the cognitive abilities of an individual player, using the proposed physiological measurements to observe the moment when such dominance occurs. © 2018, The Author(s).

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  • 18.
    Karlsson, Christoffer
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies. 1987.
    The performance impact from processing clipped triangles in state-of-the-art games.2018Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Background. Modern game applications pressures hardware to its limits, and affects how graphics hardware and APIs are designed. In games, rendering geometry plays a vital role, and the implementation of optimization techniques, such as view frustum culling, is generally necessary to meet the quality expected by the customers. Failing to optimize a game application can potentially lead to higher system requirements or less quality in terms of visual effects and content. Many optimization techniques, and studies of the performance of such techniques exist. However, no research was found where the utilization of computational resources in the GPU, in state-of-the-art games, was analyzed.

    Objectives. The aim of this thesis was to investigate the potential problem of commercial game applications wasting computational resources. Specifically, the focus was set on the triangle data processed in the geometry stage of the graphics pipeline, and the amount of triangles discarded through clipping.

    Methods. The objectives were met by conducting a case study and an empirical data analysis of the amount triangles and entire draw calls that were discarded through clipping, as well as the vertex data size and the time spent on processing these triangles, in eight games. The data was collected using Triangelplockaren, a tool which collects the triangle data that reaches the rasterizer stage. This data was then analyzed and discussed through relational findings in the results.

    Results. The results produced consisted of 30 captures of benchmark and gameplay sessions. The average of each captured session was used to make observations and to draw conclusions.

    Conclusions. This study showed evidence of noteworthy amounts of data being processed in the GPU which is discarded through clipping later in the graphics pipeline. This was seen in all of the game applications included in this study. While it was impossible to draw conclusions regarding the direct impact on performance, it was safe to say that the performance relative to the geometry processed was significant in each of the analyzed cases, and in many cases extreme.

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    BTH2018CKarlsson
  • 19.
    Karlsson, Christoffer
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Schachtschabel, Lukas
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Legible Tone Mapping: An evaluation of text processed by tone mapping operators2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Context. Tone mapping operators (TMO) are designed to reduce the dynamicrange of high dynamic range images so that they can be presented onstandard dynamic range display devices. Many operators focus on creatingperceptually similar images.

    Objectives. This thesis aims to investigate how dierent TMOs reproducephotographed text. The underlying reason being to test the contrast reproductionof each TMO.

    Methods. An experiment has been performed in order to investigate thelegibility of photographed and tone mapped text. A user study was conducted,in which 18 respondents partook, where respondents were to ratehow much of the text in each photograph that they found to be legible.

    Results. Due to low participation, the results of the experiment are mostlyinconclusive. However, some tendencies have been observed and analyzedand they fall in line with previous work within the area.

    Conclusions. The main conclusion that can be drawn from the results isthat the TMO presented by Kuang [11] is rated as better than the TMOsby Fattal [7] and Kim and Kautz [10].

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  • 20.
    Karlsson, Julia
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Using graphical attributes to influence the perception of safety in a 3D environment2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Context. Most games make use of graphics to create an environment that fits the mood they wish to convey. To use a game's graphical attributes such as colour, shape and texture to their utmost ability, knowing how these are perceived could help.

    Objective. This paper tries to determine how graphical attributes such as colour, texture, and shapes affect the perceived safety of a path inside a 3d environment.

    Method. To reach the objective, an experiment was conducted with 20 participants. The experiment was a two-alternative forced-choice (2AFC) test of 38 pairs of images, where each pair contained two versions of a tunnel entrance scene rendered using different graphical attributes. Each difference was based around either colour (warm and cold colour schemes), shape (round, wide, angular and thin), or texture (rugged, neutral and sterile).

    Results. The experiment generated results that varied compared to the expected results. For instance, the wider shapes were seen as safer compared to the thinner shapes, as was the same result with rounder shapes being perceived safer than angular shapes. Although a few preferred the cold colour scheme, the warmer colour scheme was seen as safer by the majority. While expected to be perceived as less safe than neutral textures but more than the rugged ones, the sterile texture was actually most commonly seen as safe.

    Conclusions. The main conclusion that was made is that colour, texture and shape can be applied to change the perception of safety in a scene. However, when opposing attributes are used in combination, the result might be based on how dominant the attribute is. The dominance of the graphical attributes could be an interesting topic for future work.

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  • 21.
    Khambhammettu, Mahith
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Persson, Marie
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Analyzing a Decision Support System for Resource Planning and Surgery Scheduling2016In: Procedia Computer Science / [ed] Martinho R.,Rijo R.,Cruz-Cunha M.M.,Bjorn-Andersen N.,Quintela Varajao J.E., Elsevier, 2016, Vol. 100, p. 532-538Conference paper (Refereed)
    Abstract [en]

    This study aims to propose a decision support system based on optimization modelling for operating room resource planning and sequence dependent scheduling of surgery operations. We conduct a simulation experiment using real world data collected from the local hospital to evaluate the proposed model. The obtained results are compared with real surgery schedules, planned at the local hospital. The experiment shows that the efficiency of schedules produced by the proposed model are significantly improved, in terms of less surgery turnover time, increased utilization of operating rooms and minimized make-span, compared to the real schedules. Moreover, the proposed optimization based decision support system enables analysis of surgery scheduling in relation to resource planning.

  • 22.
    Kim, Jinhan
    et al.
    Korea Adv Inst Sci & Technol, KOR..
    Feldt, Robert
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering. Chalmers Univ, Dept Comp Sci & Engn, Gothenburg, Sweden.;Blekinge Inst Technol, Dept Software Engn, Karlskrona, Sweden..
    Yoo, Shin
    Korea Adv Inst Sci & Technol, KOR.
    Guiding Deep Learning System Testing Using Surprise Adequacy2019In: International Conference on Software Engineering, IEEE , 2019, p. 1039-1049Conference paper (Refereed)
    Abstract [en]

    Deep Learning (DL) systems are rapidly being adopted in safety and security critical domains, urgently calling for ways to test their correctness and robustness. Testing of DL systems has traditionally relied on manual collection and labelling of data. Recently, a number of coverage criteria based on neuron activation values have been proposed. These criteria essentially count the number of neurons whose activation during the execution of a DL system satisfied certain properties, such as being above predefined thresholds. However, existing coverage criteria are not sufficiently fine grained to capture subtle behaviours exhibited by DL systems. Moreover, evaluations have focused on showing correlation between adversarial examples and proposed criteria rather than evaluating and guiding their use for actual testing of DL systems. We propose a novel test adequacy criterion for testing of DL systems, called Surprise Adequacy for Deep Learning Systems (SADL), which is based on the behaviour of DL systems with respect to their training data. We measure the surprise of an input as the difference in DL system's behaviour between the input and the training data (i.e., what was learnt during training), and subsequently develop this as an adequacy criterion: a good test input should be sufficiently but not overtly surprising compared to training data. Empirical evaluation using a range of DL systems from simple image classifiers to autonomous driving car platforms shows that systematic sampling of inputs based on their surprise can improve classification accuracy of DL systems against adversarial examples by up to 77.5% via retraining.

  • 23.
    Komu, Miika
    et al.
    Ericsson Res, FIN.
    Morabito, Roberto
    Ericsson Res, FIN.
    Kauppinen, Tero
    Ericsson Res, FIN.
    Kjallman, Jimmy
    Ericsson Res, FIN.
    Yao, Yong
    Blekinge Institute of Technology, Faculty of Computing, Department of Communication Systems.
    Power Consumption in Remote Gaming: an Empirical Evaluation2016In: 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    The thin-client approach for gaming is becoming more popular. For instance, Nvidia Shield, Valve Steam and Shinra technologies have offerings based on the concept. In remote cloud gaming, the game is being executed and processed in the cloud while the user receives a video and audio stream of the game, in a very similar way as with remote desktop clients. At the same time, clouds are moving towards the end-users as "edge clouds" with different standardization bodies, such Open Mobile Edge Cloud and Open Fog Consortium, giving momentum for the efforts. Were remote gaming approaches to utilize edge clouds, the games could be played without installing any infrastructure at the homes of end-users while keeping network delays to the latency-sensitive games low. While waiting for such edge-cloud deployments to substantiate, even regional clouds could be utilized for the purpose. In such environments, remote cloud gaming can already now be utilized by game companies as an alternative to traditional download-and-install games in order to support, e.g., anti-piracy protection. While the incentives for the game companies are relatively clear, the end-user experience has been investigated mainly from the viewpoint of latency. In this paper, we fill a research gap related to energy efficiency by showing that mobile phone users can save between 12 and 32 % power by utilizing remote gaming instead of playing with a native app. Our prototype is based on GamingAnywhere open-source software for which we have also integrated a gamepad for easier controls. We show power measurements both with a 2D and 3D games, and also additional measurements with a smart TV-stick.

  • 24.
    Kusetogullari, Hüseyin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Yavariabdi, Amir
    Karatay University, TUR.
    Evolutionary multiobjective multiple description wavelet based image coding in the presence of mixed noise in images2018In: Applied Soft Computing, ISSN 1568-4946, E-ISSN 1872-9681, Vol. 73, p. 1039-1052Article in journal (Refereed)
    Abstract [en]

    In this paper, a novel method for generation of multiple description (MD) wavelet based image coding is proposed by using Multi-Objective Evolutionary Algorithms (MOEAs). Complexity of the multimedia transmission problem has been increased for MD coders if an input image is affected by any type of noise. In this case, it is necessary to solve two different problems which are designing the optimal side quantizers and estimating optimal parameters of the denoising filter. Existing MD coding (MDC) generation methods are capable of solving only one problem which is to design side quantizers from the given noise-free image but they can fail reducing any type of noise on the descriptions if they applied to the given noisy image and this will cause bad quality of multimedia transmission in networks. Proposed method is used to overcome these difficulties to provide effective multimedia transmission in lossy networks. To achieve it, Dual Tree-Complex Wavelet Transform (DT-CWT) is first applied to the noisy image to obtain the subbands or set of coefficients which are used as a search space in the optimization problem. After that, two different objective functions are simultaneously employed in the MOEA to find pareto optimal solutions with the minimum costs by evolving the initial individuals through generations. Thus, optimal quantizers are created for MDCs generation and obtained optimum parameters are used in the image filter to remove the mixed Gaussian impulse noise on the descriptions effectively. The results demonstrate that proposed method is robust to the mixed Gaussian impulse noise, and offers a significant improvement of optimal side quantizers for balanced MDCs generation at different bitrates. © 2018 Elsevier B.V.

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  • 25.
    Larsson-Ståhl, Jennifer
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    A Study on the Perceived Realism Of Strand-based Hair Simulated By Style: Evaluating Real-time Hair-simulation in Unreal Engine 42020Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Background. In order to increase the visual fidelity of characters in video games, strand-based hair rendering within Unreal Engine 4 is explored in this thesis. Because of the complex nature of hair, explicit hair models can be very costly to render and simulate. It is theorized that utilizing customized hair and simulation settings, tailored to specific types of hairstyles could alleviate this issue while preserving visual fidelity.

    Objectives. The aim of this thesis is to provide an insight into what can be done to increase visual appeal and computer performance of physical simulation for different types of hairstyles and determine if customized settings may cause a significant impact on the perceived level of realism. The objectives of this thesis are to acquire a set of different strand-based hairstyles, determine a set of customized hair and simulation settings which can be applied to them, create a test scene inside of Unreal Engine 4 and render out a set of images and videos to be used in a user experiment, measure the performance of each customized setting and finally synthesize the acquired data.

    Methods. In order to achieve the aims and objectives of this thesis, a user experiment that utilizes the 2AFC method to let participants compare image- and video-pairs is performed as well as a performance experiment using the built-in profiling tools in Unreal Engine 4. In addition, a pilot experiment was performed in order to ascertain that the experiments would be feasible on the available hardware. Results. The results show that there was a significant difference in the perceived level of realism when different simulation settings was applied to the hairstyles, with customized settings being preferred to the default setting. The voting results on the image-pairs showed a preference for fine hair strands while the strand count did not have as much of an impact. It was shown that participants could easier distinguish between the different simulation- and hair-settings in long hair compared to short hair. The performance experiment showed that the amount of hair strands had the biggest impact on computer performance.

    Conclusions. Customizing hair and simulation settings to different types of hairstyles could provide a heightened perceived level of realism and a limited performance boost, from what could be derived from these experiments. Lowering the hair strand count was determined to be the most effective method of increasing performance. The performance of strand-based hair is currently not quite reaching a consistent 60 frames per second on the tested hardware, but with further optimizations it is believed that this could be acquired, especially on more powerful graphics cards. Future work should keep focus on increasing the stability of real-time strand-based hair simulation.

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    A Study on the Perceived Realism Of Strand-based Hair Simulated By Style - Evaluating Real-time Hair-simulation in Unreal Engine 4
  • 26.
    Lewenhagen, Kenneth
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Boldt, Martin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Borg, Anton
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Gerell, Manne
    Malmö University, SWE.
    Dahlen, Johan
    Region South Swedish Police, SWE.
    An Interdisciplinary Web-based Framework for Data-driven Placement Analysis of CCTV Cameras2021In: Proceedings of the 2021 Swedish Workshop on Data Science, SweDS 2021, Institute of Electrical and Electronics Engineers Inc. , 2021Conference paper (Refereed)
    Abstract [en]

    This paper describes work in progress of an interdisciplinary research project that focuses on the placement and analysis of public close-circuit television (CCTV) cameras using data-driven analysis of crime data. A novel web-based prototype that acts as a framework for the camera placement analysis with regards to historical crime occurrence is presented. The web-based prototype enables various analyses involving public CCTV cameras e.g., to determine suitable locations for both stationary CCTV cameras as well as temporary cameras that are moved around after a few months to address crime seasonality. The framework also opens up for other analyses, e.g. automatically highlighting crimes that are carried out closed by at least one camera. The research also investigates to what extent it is possible to generate estimates on the amount of detail captured by a camera given the distance to the crime light conditions. The research project includes interdisciplinary competences from various areas such as criminology, computer and data science as well as the Swedish Police. © 2021 IEEE.

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  • 27.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about Research Funding: December 20162016Other (Other (popular science, discussion, etc.))
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  • 28.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about research funding: December 20172017Other (Other (popular science, discussion, etc.))
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    fulltext
  • 29.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about Research Funding: June 20162016Other (Other (popular science, discussion, etc.))
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    fulltext
  • 30.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about research funding: June 20172017Other (Other (popular science, discussion, etc.))
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    fulltext
  • 31.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about research funding: March 20172017Other (Other (popular science, discussion, etc.))
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    fulltext
  • 32.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH newsletter on science Publishing and Information about Research Funding: September 20162016Other (Other (popular science, discussion, etc.))
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    fulltext
  • 33.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about research funding: September 20172017Other (Other (popular science, discussion, etc.))
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  • 34.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    Hur ser forskningssamarbetet ut på BTH?: Samförfattarskap, nyckelord, tidskrifter och organisationer2016Other (Other (popular science, discussion, etc.))
    Abstract [sv]

    Jag med hjälp av data från ISI Web of Science mellan åren 2013-mars 2016 samt data från vår egen publiceringsdatabas under samma tidsperiod, gjort visualiseringar av samförfattande, nyckelord och citerade tidskrifter samt medförfattares affilieringar för att få ledtrådar hur forskningssamarbete och -publiceringar ser ut den aktuella perioden.

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  • 35.
    Linde, Peter
    Blekinge Institute of Technology, The Library.
    Statistik över nedladdade fulltextfiler och mest besökta publikationer i BTHs DiVA-databas juni-nov. 20152015Other (Other (popular science, discussion, etc.))
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  • 36.
    Linde, Peter
    et al.
    Blekinge Institute of Technology, The Library.
    Ahnström, Eva-Lisa
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about Research Funding: March 20162016Other (Other (popular science, discussion, etc.))
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  • 37.
    Linde, Peter
    et al.
    Blekinge Institute of Technology, The Library.
    Eva-Lisa, Ahnström
    Blekinge Institute of Technology, The Library.
    BTH Newsletter on Science Publishing and Information about research funding: December 20152015Other (Other (popular science, discussion, etc.))
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  • 38.
    Linde, Peter
    et al.
    Blekinge Institute of Technology, The Library.
    Simson, Olivia
    Ahnström, Eva-Lisa
    Pettersson, Anette
    Riktlinjer för hantering av forskningsdata vid Blekinge Tekniska Högskola2019Other (Other (popular science, discussion, etc.))
  • 39.
    Lindholm, Emil
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Procedurally generating an initial character state for interesting role-playing game experiences2020Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
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    Procedurally generating an initial character state for interesting role-playing game experiences
  • 40.
    Liu, Fengming
    et al.
    Shandong Normal University, CHI.
    Zhu, Xiaoqian
    Shandong Normal University, CHI.
    Hu, Yuxi
    UC Davis, USA.
    Ren, Lehua
    Shandong Normal University, CHI.
    Johnson, Henric
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    A cloud theory-based trust computing model in social networks2017In: Entropy, ISSN 1099-4300, Vol. 19, no 1, article id 11Article in journal (Refereed)
    Abstract [en]

    How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node's comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved. © 2016 by the authors.

  • 41.
    Ljungberg, Alexander
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Smedberg, Simon
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Discovering and masking environmental features in modern sandboxes2022Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Background. The awareness of cyber attacks in businesses is increasing with the rising number of cyber incidents for businesses. With nearly 350 000 new malware detected per day, there is a big incentive to allocate resources to company infrastructure to mitigate malware. These solutions require scalability not to become bottlenecks and expensive. Therefore, to combat malware, automated solutions have been developed. The automated solutions comprises isolated virtual environments (sandbox), automated analysis, and reports. As a response from malware developers, malware has evolved to become aware of its environment, which has led to an arms race between malware developers and analysts.

    Objectives. In this thesis, we study how malware can identify sandbox environments and attempt to find appropriate values for masking system information (features).

    Methods. First, we research previous techniques to identify sandbox environments and consult with Windows environment experts from Truesec. We found 179 features to examine. Then, we gather a dataset of 2448 non-sandbox samples and 77 sandbox samples with a probing method. We use the statistical test Mann-Whitney U-test to identify features that differ between the dataset's groups. We conduct masking on a dataset level and evaluate it with a method similar to k-fold cross-validation using a random forest classifier. Furthermore, we analyze each feature's ability to detect sandboxes with the feature importance calculated by the Mean Decrease in Impurity (MDI).

    Results. We found 156 out of 179 features that reveal sandbox environments. Which seven out of those features could independently expose sandboxes, i.e., it was possible to classify all sandboxes and non-sandboxes with only one of them. The masking evaluation indicates that our proposed methods are effective at masking the sandboxes. The results of the feature importance showed that Windows Management Instrumentation (WMI) is an ideal source of information when it comes to exposing sandbox environments.

    Conclusions. Based on the result, we conclude that various values can expose a sandbox. Furthermore, we conclude that our method to find masking values is adequate and the proposed masking methods successfully masks sandbox samples. Lastly, we conclude that there needs to be a change of focus from evasion techniques to masking implementations in the research field.  

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  • 42.
    Lopez-Rojas, Edgar
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Elmir, Ahmad
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Axelsson, Stefan
    Norges Teknisk-Naturvitenskapelige Universitet, NOR.
    Paysim: A financial mobile money simulator for fraud detection2016In: 28th European Modeling and Simulation Symposium, EMSS 2016 / [ed] Bruzzone A.G.,Jimenez E.,Louca L.S.,Zhang L.,Longo F., Dime University of Genoa , 2016, p. 249-255Conference paper (Refereed)
    Abstract [en]

    The lack of legitimate datasets on mobile money transactions to perform research on in the domain of fraud detection is a big problem today in the scientific community. Part of the problem is the intrinsic private nature of financial transactions, that leads to no public available data sets. This will leave the researchers with the burden of first harnessing the dataset before performing the actual research on it. This paper propose an approach to such a problem that we named the PaySim simulator. PaySim is a financial simulator that simulates mobile money transactions based on an original dataset. In this paper, we present a solution to ultimately yield the possibility to simulate mobile money transactions in such a way that they become similar to the original dataset. With technology frameworks such as Agent-Based simulation techniques, and the application of mathematical statistics, we show in this paper that the simulated data can be as prudent as the original dataset for research.

  • 43.
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Bibliometric mining of research directions and trends for big data2023In: Journal of Big Data, E-ISSN 2196-1115, Vol. 10, no 1, article id 112Article in journal (Refereed)
    Abstract [en]

    In this paper a program and methodology for bibliometric mining of research trends and directions is presented. The method is applied to the research area Big Data for the time period 2012 to 2022, using the Scopus database. It turns out that the 10 most important research directions in Big Data are Machine learning, Deep learning and neural networks, Internet of things, Data mining, Cloud computing, Artificial intelligence, Healthcare, Security and privacy, Review, and Manufacturing. The role of Big Data research in different fields of science and technology is also analysed. For four geographic regions (North America, European Union, China, and The Rest of the World) different activity levels in Big Data during different parts of the time period are analysed. North America was the most active region during the first part of the time period. During the last years China is the most active region. The citation scores for documents from different regions and from different research directions within Big Data are also compared. North America has the highest average citation score among the geographic regions and the research direction Review has the highest average citation score among the research directions. The program and methodology for bibliometric mining developed in this study can be used also for other large research areas. Now that the program and methodology have been developed, it is expected that one could perform a similar study in some other research area in a couple of days. © 2023, The Author(s).

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  • 44.
    Lundberg, Lars
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Grahn, Håkan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Research Trends, Enabling Technologies and Application Areas for Big Data2022In: Algorithms, E-ISSN 1999-4893, Vol. 15, no 8, article id 280Article in journal (Refereed)
    Abstract [en]

    The availability of large amounts of data in combination with Big Data analytics has transformed many application domains. In this paper, we provide insights into how the area has developed in the last decade. First, we identify seven major application areas and six groups of important enabling technologies for Big Data applications and systems. Then, using bibliometrics and an extensive literature review of more than 80 papers, we identify the most important research trends in these areas. In addition, our bibliometric analysis also includes trends in different geographical regions. Our results indicate that manufacturing and agriculture or forestry are the two application areas with the fastest growth. Furthermore, our bibliometric study shows that deep learning and edge or fog computing are the enabling technologies increasing the most. We believe that the data presented in this paper provide a good overview of the current research trends in Big Data and that this kind of information is very useful when setting strategic agendas for Big Data research.

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  • 45.
    Ma, Liyao
    et al.
    University of Jinan, CHN .
    Sun, Bin
    Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.
    Han, Chunyan
    University of Jinan, CHN .
    Training Instance Random Sampling Based Evidential Classification Forest Algorithms2018In: 2018 21st International Conference on Information Fusion, FUSION 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 883-888Conference paper (Refereed)
    Abstract [en]

    Modelling and handling epistemic uncertainty with belief function theory, different ways to learn classification forests from evidential training data are explored. In this paper, multiple base classifiers are learned on uncertain training subsets generated by training instance random sampling approach. For base classifier learning, with the tool of evidential likelihood function, gini impurity intervals of uncertain datasets are calculated for attribute splitting and consonant mass functions of labels are generated for leaf node prediction. The construction of gini impurity based belief binary classification tree is proposed and then compared with C4.5 belief classification tree. For base classifier combination strategy, both evidence combination method for consonant mass function outputs and majority voting method for precise label outputs are discussed. The performances of different proposed algorithms are compared and analysed with experiments on VCI Balance scale dataset. © 2018 ISIF

  • 46.
    Martin, Eva Garcia
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lavesson, Niklas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Doroud, Mina
    Twitter Inc, San Francisco, CA USA..
    Hashtags and followers: An experimental study of the online social network Twitter2016In: SOCIAL NETWORK ANALYSIS AND MINING, ISSN 1869-5450, Vol. 6, no 1, article id UNSP 12Article in journal (Refereed)
    Abstract [en]

    We have conducted an analysis of data from 502,891 Twitter users and focused on investigating the potential correlation between hashtags and the increase of followers to determine whether the addition of hashtags to tweets produces new followers. We have designed an experiment with two groups of users: one tweeting with random hashtags and one tweeting without hashtags. The results showed that there is a correlation between hashtags and followers: on average, users tweeting with hashtags increased their followers by 2.88, while users tweeting without hashtags increased 0.88 followers. We present a simple, reproducible approach to extract and analyze Twitter user data for this and similar purposes.

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  • 47.
    Moraes, Ana Louiza Dallora
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Eivazzadeh, Shahryar
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Prognosis of Dementia Employing Machine Learning and Microsimulation Techniques: A Systematic Literature Review2016In: Procedia Computer Science / [ed] Martinho R.,Rijo R.,Cruz-Cunha M.M.,Bjorn-Andersen N.,Quintela Varajao J.E., Elsevier, 2016, Vol. 100, p. 480-488Conference paper (Refereed)
    Abstract [en]

    OBJECTIVE: The objective of this paper is to investigate the goals and variables employed in the machine learning and microsimulation studies for the prognosis of dementia. METHOD: According to preset protocols, the Pubmed, Socups and Web of Science databases were searched to find studies that matched the defined inclusion/exclusion criteria, and then its references were checked for new studies. A quality checklist assessed the selected studies, and removed the low quality ones. The remaining ones (included set) had their data extracted and summarized. RESULTS: The summary of the data of the 37 included studies showed that the most common goal of the selected studies was the prediction of the conversion from mild cognitive impairment to Alzheimer's Disease, for studies that used machine learning, and cost estimation for the microsimulation ones. About the variables, neuroimaging was the most frequent used. CONCLUSIONS: The systematic literature review showed clear trends in prognosis of dementia research in what concerns machine learning techniques and microsimulation.

  • 48.
    Nordahl, Christian
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Grahn, Håkan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Persson, Marie
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boeva, Veselka
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Organizing, Visualizing and Understanding Households Electricity Consumption Data through Clustering Analysis.2018In: Organizing, Visualizing and Understanding Households Electricity Consumption Data through Clustering Analysis, https://sites.google.com/view/arial2018/accepted-papersprogram , 2018Conference paper (Refereed)
    Abstract [en]

    We propose a cluster analysis approach for organizing, visualizing and understanding households’ electricity consumption data. We initially partition the consumption data into a number of clusters with similar daily electricity consumption profiles. The centroids of each cluster can be seen as representative signatures of a household’s electricity consumption behaviors. We evaluate the proposed approach by conducting a number of experiments on electricity consumption data of ten selected households. Our results show that the approach is suitable for data analysis, understanding and creating electricity consumption behavior models.

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  • 49.
    Oliveira, Pedro Almir
    et al.
    Federal Institute of Maranhão (IFMA), BRA.
    Santos Neto, Pedro
    Universidade Federal do Piaui, BRA.
    Britto, Ricardo
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Rabêlo, Ricardo De Andrade Lira
    Universidade Federal do Piaui, BRA.
    Braga, Ronyerison
    Universidade Federal do Piaui, BRA.
    Souza, Matheus
    Universidade Federal do Piaui, BRA.
    CIaaS: computational intelligence as a service with Athena2018In: Computer languages, systems & structures, ISSN 1477-8424, E-ISSN 1873-6866, Vol. 54, p. 95-118Article in journal (Refereed)
    Abstract [en]

    Computational Intelligence (CI) is a sub-branch of Artificial Intelligence (AI) that focus on studying adaptive mechanisms to enable intelligent behavior in complex environments. CI techniques have been successful in solving complex problems in many different knowledge areas. However, despite their usefulness, developing solutions based on CI techniques is not a trivial activity, since it involves the codification/adaptation of algorithms to specific context and problems. In this paper, we present and validate through a quasi-experiment a new paradigm to develop CI-based solutions using a more mature version of Athena (2.0): Computational Intelligence as a Service (CIaaS). Using this tool, both researchers and practitioners can design and evaluate CI-based solutions by dragging and dropping components in a visual environment, in a cloud-based platform. The results of the quasi-experiment suggest that our approach can help researchers to design and evaluate CI-based systems in a simple, reliable and fast way. © 2018 Elsevier Ltd

  • 50.
    Olofsdotter Bergström, Annika
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Elovaara, Pirjo
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics. Blekinge Inst Technol, Technosci Studies, S-37435 Karlshamn, Sweden..
    Playing a City2018In: INTERACTIVITY, GAME CREATION, DESIGN, LEARNING, AND INNOVATION / [ed] Brooks, AL Brooks, E Vidakis, N, SPRINGER , 2018, p. 304-313Conference paper (Refereed)
    Abstract [en]

    This paper is based on exploratory interventions in a small city in the south-eastern part of Sweden. The interventions were inspired both by the art movement of Situationists and site-specific games. The activities were also supported by a diversity of theoretical perspectives. During winter 2016 eight women explored by developing playful methods what a city, understood both as a social and material space, could mean for a group of women recently moved to the city. Through the playful approach the project opened up room for participatory design and abled the group to formulate eight rules, also available for other city explorers in other cities.

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