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  • 101.
    PATTA, SIVA VENKATA PRASAD
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Intelligent Decision Support Systems for Compliance Options: A Systematic Literature Review and Simulation2019Independent thesis Advanced level (degree of Master (Two Years)), 80 poäng / 120 hpOppgave
    Abstract [en]

    The project revolves around logistics and its adoption to the new rules. Theobjective of this project is to focus on minimizing data tampering to the lowest level possible.To achieve the set goals in this project, Decision support system and simulation havebeen used. However, to get clear insight about how they can be implemented, a systematicliterature review (Case Study incl.) has been conducted, followed by interviews with personnelat Kakinada port to understand the real-time complications in the field. Then, a simulatedexperiment using real-time data from Kakinada port has been conducted to achieve the set goalsand improve the level of transparency on all sides i.e., shipper, port and terminal.

  • 102.
    Peddireddy, Vidyadhar reddy
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Enhancement of Networking Capabilities in P2P OpenStack2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    In recent times, there’s been a trend towards setting up smaller clouds at the edge of the network and interconnecting them across multiple sites. In these scenarios, the software used for managing the resources should be flexible enough to scale. Considering OpenStack the most widely used cloud software, It is observed that the compute service has shown performance degradation when the deployment reaches fewer hundreds of nodes. Finding out solutions to address the scalability issue in OpenStack, Ericsson has developed a new architecture that supports massive scalability of OpenStack clouds. However, the challenges with multicloud networking in P2P OpenStack remained unsolved. This thesis work as an extension to Ericsson’s P2P OpenStack project investigates various multi-cloud networking techniques and proposes two decentralized designs for cross Neutron networking in P2P OpenStack. The design-1 is based on OpenStack Tricircle project and design-2 is based on VPNaaS. This thesis work implements VPNaaS design to support the automatic interconnection of Virtual machines that belong to the same user but deployed in different OpenStack clouds. We evaluate this thesis for control plane operation under two different scenarios namely single user case and multiple users cases. In both scenarios, request-response time is chosen as an evaluating parameter. Results show that there is an increase in request-response time when users in the system are increased.

  • 103.
    Peng, Cong
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Good Record Keeping for Conducting Research Ethically CorrectManuskript (preprint) (Annet vitenskapelig)
  • 104.
    Peng, Cong
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    What Can Teachers Do to Make the Group Work Learning Effective: a Literature ReviewManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Group work-based learning is encouraged in higher education on account of both ped-agogical benefits and industrial employers’s requirements. However, although a plenty ofstudies have been performed, there are still various factors that will affect students’ groupwork-based learning in practice. It is important for the teachers to understand which fac-tors are influenceable and what can be done to influence. This paper performs a literaturereview to identify the factors that has been investigated and reported in journal articles. Fif-teen journal articles were found relevant and fifteen factors were identified, which could beinfluenced by instructors directly or indirectly. However, more evidence is needed to sup-port the conclusion of some studies since they were performed only in one single course.Therefore, more studies are required on this topic to investigate the factors in differentsubject areas. 

  • 105.
    Peng, Cong
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Goswami, Prashant
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Meaningful Integration of Data from Heterogeneous Health Services and Home Environment Based on Ontology2019Inngår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 19, nr 8, artikkel-id 1747Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The development of electronic health records, wearable devices, health applications and Internet of Things (IoT)-empowered smart homes is promoting various applications. It also makes health self-management much more feasible, which can partially mitigate one of the challenges that the current healthcare system is facing. Effective and convenient self-management of health requires the collaborative use of health data and home environment data from different services, devices, and even open data on the Web. Although health data interoperability standards including HL7 Fast Healthcare Interoperability Resources (FHIR) and IoT ontology including Semantic Sensor Network (SSN) have been developed and promoted, it is impossible for all the different categories of services to adopt the same standard in the near future. This study presents a method that applies Semantic Web technologies to integrate the health data and home environment data from heterogeneously built services and devices. We propose a Web Ontology Language (OWL)-based integration ontology that models health data from HL7 FHIR standard implemented services, normal Web services and Web of Things (WoT) services and Linked Data together with home environment data from formal ontology-described WoT services. It works on the resource integration layer of the layered integration architecture. An example use case with a prototype implementation shows that the proposed method successfully integrates the health data and home environment data into a resource graph. The integrated data are annotated with semantics and ontological links, which make them machine-understandable and cross-system reusable.

  • 106.
    Peng, Cong
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Goswami, Prashant
    Blekinge Tekniska Högskola.
    Bai, Guohua
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    A literature review of current technologies on health data integration for patient-centered health management2019Inngår i: Health Informatics Journal, ISSN 1460-4582, E-ISSN 1741-2811Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Health data integration enables a collaborative utilization of data across different systems. It not only provides a comprehensive view of a patient’s health but can also potentially cope with challenges faced by the current healthcare system. In this literature review, we investigated the existing work on heterogeneous health data integration as well as the methods of utilizing the integrated health data. Our search was narrowed down to 32 articles for analysis. The integration approaches in the reviewed articles were classified into three classifications, and the utilization approaches were classified into five classifications. The topic of health data integration is still under debate and problems are far from being resolved. This review suggests the need for a more efficient way to invoke the various services for aggregating health data, as well as a more effective way to integrate the aggregated health data for supporting collaborative utilization. We have found that the combination of Web Application Programming Interface and Semantic Web technologies has the potential to cope with the challenges based on our analysis of the review result.

  • 107.
    Peng, Rong
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Kylo Data Lakes Configuration deployed in Public Cloud environments in Single Node Mode2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    The master thesis introduces the Kylo Data Lake which deployed in the public cloud environment,provides a perspective of datalake configuration and data ingestion experiment. This paper reveals the underlying architecture of Kylo data lake.

  • 108.
    Pentikäinen, Filip
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Sahlbom, Albin
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Combining Influence Maps and Potential Fields for AI Pathfinding2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    This thesis explores the combination of influence maps and potential fields in two novel pathfinding algorithms, IM+PF and IM/PF, that allows AI agents to intelligently navigate an environment. The novel algorithms are compared to two established pathfinding algorithms, A* and A*+PF, in the real-time strategy (RTS) game StarCraft 2.

    The main focus of the thesis is to evaluate the pathfinding capabilities and real-time performance of the novel algorithms in comparison to the established pathfinding algorithms. Based on the results of the evaluation, general use cases of the novel algorithms are presented, as well as an assessment if the novel algorithms can be used in modern games.

    The novel algorithms’ pathfinding capabilities, as well as performance scalability, are compared to established pathfinding algorithms to evaluate the viability of the novel solutions. Several experiments are created, using StarCraft 2’s base game as a benchmarking tool, where various aspects of the algorithms are tested. The creation of influence maps and potential fields in real-time are highly parallelizable, and are therefore done in a GPGPU solution, to accurately assess all algorithms’ real-time performance in a game environment.

    The experiments yield mixed results, showing better pathfinding and scalability performance by the novel algorithms in certain situations. Since the algorithms utilizing potential fields enable agents to inherently avoid and engage units in the environment, they have an advantage in experiments where such qualities are assessed. Similarly, influence maps enable agents to traverse the map more efficiently than simple A*, giving agents inherent advantages.

    In certain use cases, where multiple agents require pathfinding to the same destination, creating a single influence map is more beneficial than generating separate A* paths for each agent. The main benefits of generating the influence map, compared to A*-based solutions, being the lower total compute time, more precise pathfinding and the possibility of pre-calculating the map.

  • 109.
    Pogén, Tobias
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Asynchronous Particle Calculations on Secondary GPU for Real Time Applications2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
  • 110.
    Qian, Wu
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Cheddad, Abbas
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Segmentation-based Deep Learning Fundus Image Analysis2019Konferansepaper (Fagfellevurdert)
  • 111.
    Roth, Robin
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Lundblad, Martin
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    An Evaluation of Machine Learning Approaches for Hierarchical Malware Classification2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    With an evermore growing threat of new malware that keeps growing in both number and complexity, the necessity for improvement in automatic detection and classification of malware is increasing. The signature-based approaches used by several Anti-Virus companies struggle with the increasing amount of polymorphic malware. The polymorphic malware change some minor aspects of the code to be able to remain undetected. Malware classification using machine learning have been used to try to solve this issue in previous research. In the proposed work, different hierarchical machine learning approaches are implemented to conduct three experiments. The methods utilise a hierarchical structure in various ways to be able to get a better classification performance. A selection of hierarchical levels and machine learning models are used in the experiments to evaluate how the results are affected.

    A data set is created, containing over 90000 different labelled malware samples. The proposed work also includes the creation of a labelling method that can be helpful for researchers in malware classification that needs labels for a created data set.The feature vector used contains 500 n-gram features and 3521 Import Address Table features. In the experiments for the proposed work, the thesis includes the testing of four machine learning models and three different amount of hierarchical levels. Stratified 5-fold cross validation is used in the proposed work to reduce bias and variance in the results.

    The results from the classification approach shows it achieves the highest hF-score, using Random Forest (RF) as the machine learning model and having four hierarchical levels, which got an hF-score of 0.858228. To be able to compare the proposed work with other related work, pure-flat classification accuracy was generated. The highest generated accuracy score was 0.8512816, which was not the highest compared to other related work.

  • 112.
    Sandnes, Carl
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Gehlin Björnberg, Axel
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Cross-platform performance ofintegrated, internal and external GPUs2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    As mobile computers such as laptops and cellphones are becoming more and more powerful, the options for those who traditionally required a more powerful desktop PC, such as video editors or gamers seem to have grown slightly. One of these new options are external Graphics Processing Units (eGPUs). Where a laptop is used along with an external GPU, connected via Intel’s Thunderbolt 3. This is however a rather untested method. This paper discusses the performance of eGPUs in a variety of operating systems (OS’s). For this research, performance benchmarking was used to investigate the performance of GPU intensive tasks in various operating systems. It was possible to determine that the performance across operating systems does indeed differ greatly in some usecases, such as games. While other use cases such as computational and synthetictests perform very similarly independently of which system (OS) is used. It seems that the main limiting factor is the GPU itself. It also appears to be the case that the interface with which the GPU is connected to a computer does indeed impact performance, in a very similar way between different OS’s. Generally, games seem to loose more performance than synthetic and computational tasks when using an externalGPU rather than an internal one. It was also discovered that there are too many variables for any real conclusions to be drawn from the gathered results. This as theresults were sometimes very inconclusive and conflicting. So while the outcomes can be generalized, more research is needed before any definitive conclusions can be made.

  • 113.
    shahzad, Faisal
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Algorithm Development for Source Camera Model Identification2019Independent thesis Advanced level (degree of Master (One Year)), 20 poäng / 30 hpOppgave
  • 114.
    Sharma, Suraj
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Performance comparison of Java and C++ when sorting integers and writing/reading files.2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    This study is conducted to show the strengths and weaknesses of C++ and Java in three areas that are used often in programming; loading, sorting and saving data.Performance and scalability are large factors in software development and choosing the right programming language is often a long process.It is important to conduct these types of direct comparison studies to properly identify strengths and weaknesses of programming languages. Two applications were created, one using C++ and one using Java.Apart from a few syntax and necessary differences, both are as close to being identical as possible.Each application loads three files containing 1000, 10000 and 100000 randomly ordered integers.These files are pre-created and always contain the same values.They are randomly generated by another small application before testing. The test runs three times, once for each file.When the data is loaded, it is sorted using quicksort.The data is reset using the dataset file and sorted again using insertion-sort.The sorted data is then saved to a file.Each test runs 50 times in a large loop and the times for loading, sorting and saving the data are saved.In total, 300 tests are run between the C++ and the Java application. The results show that Java has a total time that is faster than C++ and it is also faster when loading two out of three datasets.C++ was generally faster when sorting the datasets using both algorithms and when saving the data to files. In general Java was faster in this study, but when processing the data and when under heavy load, C++ performed better.The main difference was when loading the files.The way that Java loads the data from a file is very different from C++, even though both applications read the files character by character, Java’s “Scanner” library converts data before it parses it.With some optimization, for example by reading the file line by line and then parsing the data, C++ could be comparable or faster, but for the sake of this study, the input methods that were chosen were seemingly the fairest.

  • 115.
    Sobeh, Abedallah
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Exploration of using Blockchaintechnology for forensically acceptableaudit trails with acceptableperformance impacts2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    In this work, we will test the possibility to use Blockchain to preserve data suchas logs. Data inside Blockchain is preserved to be used as digital evidence. Thestudy will examine if Blockchain technology will satisfy the requirement for digitalevidence in a Swedish court. The study will simulate different test scenarios. Eachscenario will be tested on three different hardware configurations. The test has twomain categories, stream test and batch test. In stream test, we test performanceimpact on different systems in case each log is sent in a separate block. While inbatch test, we have two categories batch with data and batch without data. In thistest, we simulate sending 80GB of data each day. In total we send 80GB of data,but the difference here is that we change the time between each block and adjustthe size of the block. In our tests, we focused on three metrics: CPU load, networkbandwidth usage and storage consumption for each scenario. After the tests, wecollected the data and compared the results of each hardware configuration withinthe same scenario. It was concluded that Blockchain does not scale up in streammode, and it is limited to ten blocks/s regardless of hardware configuration. On theother hand, Blockchain can manage 80GB of data each day without stressing systemresources.

  • 116.
    Spångberg, Felicia
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Schramm, Eva
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Measuring player preference using muscle simulation2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Background: Simulation of physics is something several modern video games use. These simulations are often used to create more believable and realistic environments. Physics-based animations in the form of muscle simulations is one such technique.

    Objectives: The aim of this thesis is to investigate three different stages of full-body muscle deformation and observe which of these are preferred. One using no degree of deformation being the control condition and the other two using different degrees of deformation being the treatments. This study is conducted by creating animationswith three different degrees of muscle simulation. These animations are then rendered in Maya as well as put into a small fighting scenario implemented in Unreal Engine 4. A user experiment will be conducted where a number of participants will be asked to choose between different scenarios using two-alternative forced choice. After the user study is completed, the data will be analyzed and used to form a conclusion.

    Methods: Implementations needed to create the stimulus was first done in Maya where the meshes, muscles and animations were created. Renders were done in Maya of all animations and a scene was also implemented in Unreal Engine 4 simulating a small fighting game using the assets created in Maya. To evaluate player preference,a user experiment was conducted with 13 participants where each participant was asked to watch 27 scenarios containing two side-by-side comparisons with different degrees of muscle deformation. The user experiment stimulus was created using PshycoPy which also collected the data of user preference. The scenarios where presented in an arbitrary order. The study was held in a room where the participant was undisturbed.

    Results: The results showed that no muscle deformation was preferred in all cases where a statistical difference could be found.

    Conclusions: While the results show that the control condition is mostly preferred, most cases did not yield a conclusive result. Thus further research in the area is necessary.

  • 117.
    Strand, Anton
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Gunnarsson, Markus
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Code Reviewer Recommendation: A Context-Aware Hybrid Approach2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Background. Code reviewing is a commonly used practice in software development. It refers to the process of reviewing new code changes, commonly before they aremerged with the code base. However, in order to perform the review, developers need to be assigned to that task. The problems with a manual assignment includes a time-consuming selection process; limited pool of known candidates; risk of high reuse of the same reviewers (high workload).

    Objectives. This thesis aims to attempt to address the above issues with a recommendation system. The idea is to receive feedback from experienced developers in order to expand upon identified reviewer factors; which can be used to determinethe suitability of developers as reviewers for a given change. Also, to develop and implement a solution that uses some of the most promising reviewer factors. The solution can later be deployed and validated through user and reviewer feedback in a real large-scale project. The developed recommendation system is named Carrot.

    Methods. An improvement case study was conducted at Ericsson. The identification of reviewer factors is found through literature review and semi-structured interviews. Validation of Carrot’s usability was conducted through static analysis,user feedback, and static validation.

    Results. The results show that Carrot can help identify adequate non-obvious reviewers and be of great assistance to new developers. There are mixed opinions on Carrot’s ability to assist with workload balancing and decrease of review lead time. The recommendations can be performed in a production environment in less than a quarter of a second.

    Conclusions. The implemented and validated approach indicates possible usefulness in performing recommendations, but could benefit significantly from further improvements. Many of the problems seen with the recommendations seem to be a result of corner-cases that are not handled by the calculations. The problems would benefit considerably from further analysis and testing.

  • 118.
    Talupula, Ashik
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Demand Forecasting Of Outbound Logistics Using Machine learning2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Background: long term volume forecasting is important for logistics service providers for planning their capacity and taking the strategic decisions. At present demand is estimated by using traditional methods of averaging techniques or with their own experiences which often contain some error. This study is focused on filling these gaps by using machine learning approaches. The sample data set is provided by the organization, which is the leading manufacturer of trucks, buses and construction equipment, the organization has customers from more than 190 markets and has production facilities in 18 countries.

    Objectives: This study is to investigate a suitable machine learning algorithm that can be used for forecasting demand of outbound distributed products and then evaluating the performance of the selected algorithms by experimenting to articulate the possibility of using long-term forecasting in transportation.

    Methods: primarily, a literature review was initiated to find a suitable machine learn- ing algorithm and then based on the results of the literature review an experiment is performed to evaluate the performance of the selected algorithms

    Results: Selected CNN, ANN and LSTM models are performing quite well But based on the type and amount of historical data that models were given to learn, models have a very slight difference in performance measures in terms of forecasting performance. Comparisons are made with different measures that are selected by the literature review Conclusions. This study examines the efficacy of using Convolutional Neural Networks (CNN) for performing demand forecasting of outbound distributed products at the country level. The methodology provided uses convolutions on historical loads. The output from the convolutional operation is supplied to fully connected layers together with other relevant data. The presented methodology was implemented on an organization data set of outbound distributed products per month. Results obtained from the CNN were compared to results obtained by Long Short Term Memories LSTM sequence-to-sequence (LSTM S2S) and Artificial Neural Networks (ANN) for the same dataset. Experimental results showed that the CNN outperformed LSTM while producing comparable results to the ANN. Further testing is needed to compare the performances of different deep learning architectures in outbound forecasting.

  • 119.
    Tewolde, Vincent
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Comparison of authentication options forMQTT communication in an IoT basedsmart grid solution2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Background. Smart grid is a new technology that focuses on utilising renewable energyalongside the current infrastructure. It aims to contribute to a sustainable future by implementingIoT devices in the electrical grid to adjust electricity flow and increase energyefficiency. By combining the current infrastructure with information technology manysecurity questions arise. This paper focuses on the authentication of the IoT devicesconnected with the MQTT protocol.Objectives. The study aims to discover a preferable MQTT authentication methodadapted for Techinova’s infrastructure with their requirements in consideration.Methods. A literature review was performed to obtain fundamental authenticationmethods and to distinguish different security approaches. Experiments were executed ina test environment to gather detailed information to gain a deeper understanding anddiscover security vulnerabilities.Results. The results derive from three experiments comparing the selected authenticationoptions security flaws.Conclusions. The results suggests that implementing TLS contributes to a secure authenticationand communication between the IoT devices and the broker without delayingthe transmission. However, further research could obtain other relevant data eventuatingin different results.

  • 120.
    Tkachuk, Roman-Valentyn
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Ilie, Dragos
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Tutschku, Kurt
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Orchestrating Future Service Chains in the Next Generation of Clouds2019Inngår i: Proceedings of SNCNW 2019: The 15th Swedish National Computer Networking Workshop, Luleå, 2019, s. 18-22Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Service Chains have developed into an important concept in service provisioning in today’s and future Clouds. Cloud systems, e.g., Amazon Web Services (AWS), permit the implementation and deployment of new applications, services and service chains rapidly and flexibly. They employ the idea of Infrastructure as Code (IaC), which is the process of managing and provisioning computing infrastructure and its configuration through machine-processable definition files.

    In this paper, we first detail future service chains with particular focus on Network Function Virtualization (NFV) and machine learning in AI. Afterwards, we analyze and summarize the capabilities of today’s IaC tools for orchestrating Cloud infrastructures and service chains. We compare the functionality of the major five IaC tools: Puppet, Chef, SaltStack, Ansible, and Terraform. In addition, we demonstrate how to analyze the functional capabilities of one of the tools. Finally, we give an outlook on future research issues on using IaC tools across multiple operators, data center domains, and different stockholders that collaborate on service chains.

  • 121.
    Tlatlik, Max Lukas
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Volume rendering with Marching cubes and async compute2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    With the addition of the compute shader stage for GPGPU hardware it has becomepossible to run CPU like programs on modern GPU hardware. The greatest benefit can be seen for algorithms that are of highly parallel nature and in the case of volume rendering the Marching cubes algorithm makes for a great candidate due to its simplicity and parallel nature. For this thesis the Marching cubes algorithm was implemented on a compute shader and used in a DirectX 12 framework to determine if GPU frametime performance can be improved by executing the compute command queue parallell to the graphics command queue. Results from performance benchmarks show that a gain is present for each benchmarked configuration and the largest gains are seen for smaller workloads with up to 52%. This information could therefore prove useful for game developers who want to improve framerates or decrease development time but also in other fields such as volume rendering for medical images.

  • 122.
    Tran, Dang Ninh
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Zepernick, Hans-Juergen
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Spherical Light-Weight Data Hiding in 360-Degree Videos with Equirectangular Projection2019Inngår i: International Conference on Advanced Technologies for Communications, IEEE Computer Society , 2019, s. 56-62Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we propose a spherical light-weight data hiding technique for 360-degree videos with equirectangular projection between sphere and plane. In particular, computationally efficient least significant bit (LSB) data hiding is applied to the color encoded equirectangular projection of the sphere. As viewers put more attention to the areas around the equator of a 360-degree video compared to the poles, LSB data hiding may be performed in the regions around the poles without causing perceptually significant quality degradation. In addition, the equirectangular projection induces a huge amount of data redundancy in the areas near the poles which increases the capacity available for LSB data hiding. A performance assessment of the proposed spherical light-weight data hiding technique is conducted using the weighted-to-spherically-uniform peak-signal-to-noise ratio (WS-PSNR) and the Craster parabolic projection PSNR (CPP-PSNR). Because both metrics take the non-linear relationship between samples on the sphere and the samples mapped to the plane into account, they are well suited for assessing the performance of the spherical LSB data hiding technique. Numerical results are provided for scenarios in which a 360-degree cover video carries a secret video using different numbers of bit planes. It is shown that video fidelity in terms of WS-PSNR and CPP-PSNR is indeed kept high in the 360-degree stego-video as long as the LSB data hiding is performed in the areas around the poles. © 2019 IEEE.

  • 123.
    Tran, Dang Ninh
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Zepernick, Hans-Juergen
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Chu, Thi My Chinh
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    On LSB Data Hiding in High-Definition Images Using Morphological Operations2019Inngår i: Proceedings - 2019 19th International Symposium on Communications and Information Technologies, ISCIT 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, s. 386-391Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The aim of steganography is to conceal the presence of communication by way of hiding secret data in perceptually irrelevant parts of a cover object. In this paper, we propose a method for hiding secret images in edge regions of high-definition (HD) images because the human visual system is less sensitive to intensity changes in these regions. In particular, least significant bit substitution is used to embed a secret image in the edge regions of a HD cover image. The edge regions are obtained using a Canny edge detector followed by morphological operations which are used to control the hiding capacity. A performance assessment of the proposed method reveals the trade-off between capacity, detectability, and perceptibility of the hidden data. © 2019 IEEE.

  • 124.
    Tulek, Zerina
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Arnell, Louise
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Facebook Eavesdropping Through the Microphone for Marketing Purpose2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Background. As long as Facebook has existed, advertisements have been present in the application in one way or another. The ads have evolved and become more sophisticated over the years. Today, Facebook creates groups with members having specific attributes and advertisers requests groups for whom Facebook shows the advertisement. Besides this, Facebook receives information from other sources such as browser cookies and ad pixels. All information that Facebook receive or collect is used in their algorithms to target relevant advertisement for each user.

    Objectives. To examine the possibility of Facebook eavesdropping through the microphone for marketing purposes and identify eventual keywords mapped between a spoken conversation and advertisement.

    Methods. Five controlled experiments were performed with two test phones and two control phones. These were treated equally beside the test phones being exposed to spoken conversations containing randomly chosen products, companies and brands. The content of the phones was compared to see whether advertisement was adapted to the spoken conversation in the test phones but not in the control phones.

    Results. No sponsored advertisements were present on the Facebook and Instagram application. Messenger contained ads indicating that Facebook might analyse the content of private messages to adapt advertisement. After adding the Wish application to the research, the results were still the same. Other contents in the Facebook news feed were analysed, however, the content analysed did not contain any evidence that Facebook eavesdrops on spoken conversations for marketing purpose.

    Conclusions. The experiments conducted were not sufficient enough to trigger sponsored advertisement. Therefore, no indications were found that Facebook is eavesdropping through the microphone or not.

  • 125.
    Törnquist Krasemann, Johanna
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Rydergren, Clas
    Linköpings universitet, SWE.
    Passagerar-fokuserad hantering av störningar i den regionala tågtrafiken: En sammanställning av arbete och resultat från den svenska delen av TRANSFORM-projektet2019Rapport (Annet vitenskapelig)
    Abstract [sv]

    Bakgrund och syfte

    Informationstjänster för kollektivtrafikresenärer blir allt bättre, men vid störningar är det fortfarande mycket svårt som resenär att få tillräcklig och aktuell information om hur resan kommer att kunna fullföljas. För planerare och trafikledning är det också en enorm utmaning i att skapa robusta planer som medför flexibilitet i driften, att övervaka trafikläget och att styra systemet på ett proaktivt sätt som balanserar interna prioriteringar med resenärernas. Inom projektet har vi därför studerat två alternativa principer och metoder för att omplanera tågtrafiken vid störningar – där den ena är mer resenärsfokuserad och den andra mer trafiksystem-fokuserad.

    Metodik

    Den förstnämnda metoden inkluderar i omplaneringen av tågen vid störningar även regionala bussar. Metoden beaktar resandeutbyten och alternativa resvägar för att, om möjligt, minska resenärers försening genom att samordna tåg- och/eller bussanslutningar. Här används en matematisk modell som utvecklats i projektet och optimeringsproblemet löses med hjälp av kommersiell mjukvara, Gurobi. Vi använder även anonymiserad, filtrerad, resekortsdata för att modellera passagerarflöden och relevanta anslutningar. Den andra metoden omplanerar tågtrafiken utan hänsyn till annan kollektivtrafik och möjliggör en viktning (dvs. prioritering) av tåg med ett större antal avstigande resenärer. Här används en parallelliserad algoritm som på ett effektivt sätt ska kunna planera om tågen vid störningar baserat på ett antal kvalitetsindikatorer. Båda metoderna har tillämpats i datorbaserade experiment för störningarsscenarier på Blekinge Kustbana och anslutande banor.

    Resultat och slutsatser

    Resultaten från projektet visar på vikten av att utforma beräkningsstöd för tågtrafikledning som inkluderar flera olika målkriterier och kvalitetsindikatorer vid omplaneringen av tåg vid störningar. Vilka kriterier och indikatorer som är mest relevanta att fokusera på i den operativa driften är en bedömning som bör göras dels utifrån ett användarperspektiv, dels baserat på gällande lagstiftning inklusive aktuella operativa regler definierade i järnvägsnätsbeskrivningen för innevarande år.

     

    Preliminära resultaten från studierna visar även på möjligheterna med att samordna den regionala tåg- och busstrafiken i större utsträckning än vad som är praktiskt möjligt idag. Tillgången till data ökar samt olika mer eller mindre avancerade digitala hjälpmedel för resenärer såväl som för trafikledning föreslås och diskuteras av branschen och inom forskarsamhället, men hur man uppnår en effektiv hantering av störningar och säkerställer ändamålsenlig trafikinformation till resenärer är först och främst en organisatorisk fråga, snarare än en teknisk utmaning.

  • 126.
    Uppströmer, Viktor
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Råberg, Henning
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Detecting Lateral Movement in Microsoft Active Directory Log Files: A supervised machine learning approach2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [sv]

    Cyberattacker utgör ett stort hot för dagens företag och organisationer, med engenomsnittlig kostnad för ett intrång på ca 3,86 miljoner USD. För att minimera kostnaden av ett intrång är det viktigt att detektera intrånget i ett så tidigt stadium som möjligt. Avancerande långvariga hot (APT) är en sofistikerad cyberattack som har en lång närvaro i offrets nätverk. Efter attackerarens första intrång kommer fokuset av attacken skifta till att få kontroll över så många enheter som möjligt på nätverket. Detta steg kallas för lateral rörelse och är ett av de mest kritiska stegen i en APT. Syftet med denna uppsats är att undersöka hur och hur väl lateral rörelse kan upptäckas med hjälp av en maskininlärningsmetod. I undersökningen jämförs och utvärderas fem maskininlärningsalgoritmer med upprepad korsvalidering följt av statistisk testning för att bestämma vilken av algoritmerna som är bäst. Undersökningen konkluderar även vilka attributer i det undersökta datasetet som är väsentliga för att detektera laterala rörelser. Datasetet kommer från en Active Directory domänkontrollant där datasetets attributer är skapade av korrelerade loggar med hjälp av datornamn, IP-adress och användarnamn. Datasetet består av en syntetisk, samt, en verklig del vilket skapar ett semi-syntetiskt dataset som innehåller ett multiklass klassifierings problem.

    Experimentet konkluderar att all fem algoritmer klassificerar rätt med en pricksäkerhet (accuracy) på 0.998. Algoritmen RF presterar med den högsta f-measure (0.88) samt recall (0.858), SVM är bäst gällande precision (0.972) och DT har denlägsta inlärningstiden (1237ms). Baserat på resultaten indikerar undersökningenatt algoritmerna RF, SVM och DT presterar bäst i olika scenarier. Till exempel kan SVM användas om en låg mängd falsk positiva larm är viktigt. Om en balanserad prestation av de olika prestanda mätningarna är viktigast ska RF användas. Undersökningen konkluderar även att en stor mängd utav de undersökta attributerna av datasetet kan bortses i framtida experiment, då det inte påverkade prestandan på någon av algoritmerna.

     

  • 127.
    Venishetty, Sai Vineeth
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Machine Learning Approach for Forecasting the Sales of Truck Components2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Context: The context of this research is to forecast the sales of truck componentsusing machine learning algorithms which can help the organization in activity oftrade and business and it also plays a major role for firms in decision-making operationsin the areas corresponding to sales, production, purchasing, finance, and accounting.

    Objectives: This study first investigates to find the suitable machine learning algorithmsthat can be used to forecast the sales of truck components and then theexperiment is performed with the chosen algorithms to forecast the sales and to evaluatethe performances of the chosen machine learning algorithms.

    Methods: Firstly, a Literature review is used to find suitable machine learningalgorithms and then based on the results obtained, an experiment is performed toevaluate the performances of machine learning algorithms.

    Results: Results from the literature review shown that regression algorithms namely Supports Vector Machine Regression, Ridge Regression, Gradient Boosting Regression, and Random Forest Regression are suitable algorithms and results from theexperiment showed that Ridge Regression has performed well than the other machine learning algorithms for the chosen dataset.

    Conclusion: After the experimentation and the analysis, the Ridge regression algorithmhas been performed well when compared with the performances of the otheralgorithms and therefore, Ridge Regression is chosen as the optimal algorithm forperforming the sales forecasting of truck components for the chosen data.

  • 128.
    Vishnubhotla, Sai Datta
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Lundberg, Lars
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Supplementary Material of: "Understanding the Perceived Relevance of Capability Measures: A Survey of Agile Software Development Practitioners"2019Annet (Annet (populærvitenskap, debatt, mm))
    Abstract [en]

    This document contains the supplementary material of the paper titled: "Understanding the Perceived Relevance of Capability Measures: A Survey of Agile Software Development Practitioners" 

  • 129.
    Vishnubhotla, Sai Datta
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Which Abilities and Attitudes Matter Most?: Understanding and Investigating Capabilities in Industrial Agile Contexts2019Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Background: Over the past decades, advancements in the software industry and the prevalence of Agile Software Development (ASD) practices have increased the prominence of individual and interpersonal skills. The humancentric nature of ASD practices makes it imperative to identify and to assign a capable professional to a team. While capabilities of professionals influence team performance and lead the path to a project’s success, the area of capability measurement in ASD remains largely unexplored.

    Objectives: This thesis aims to aggregate evidence from both the state of the art and practice to understand capability measurement in ASD. Further, to support research and practice towards composing agile teams, this thesis also investigates the effects of capability measures on team-level aspects (team performance and team climate) within industrial contexts.

    Method: A mixed-methods approach was employed to address the thesis’ objectives. A Systematic Literature Review (SLR) and an industrial survey were conducted to identify and gather evidence in relation to individual and team capability measures, which are pertinent to ASD context. A case study and another industrial survey were carried out to provide insights and extend support towards agile team composition.

    Results: Our SLR results showed that a major portion of former studies discussed capability measures in relation to affective, communication, interpersonal and personal aspects. Results from our survey also aligned with these findings, where, measures associated with the aforementioned aspects were observed to be widely known to practitioners and were also perceived by them as highly relevant in ASD contexts. Our case study conducted at a small-sized organization revealed multiple professional capability measures to be affecting team performance. Whereas, our survey conducted at a large-sized organization identified an individual’s ability to easily get along with other team members (agreeableness personality trait) to have a significant positive influence on the person’s perceived level of team climate.

    Conclusion: In this thesis, the empirical evidence gathered by employing mixed-methods and examining diverse organizational contexts, contributed towards better realization of capability measurement in ASD. In order to extend support towards team composition in ASD, this thesis presents two approaches. The first approach is based on developing an agile support tool that coordinates capability assessments and team composition. The second approach is based on establishing team climate forecasting models that can provide insights about how the perceived level of climate within a team would vary based on its members’ personalities. However, in order to improve both approaches, it is certainly necessary to examine the effects of diverse capability measures.

  • 130.
    Vishnubhotla, Sai Datta
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Mendes, Emilia
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Lundberg, Lars
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Investigating the relationship between personalities and team climate of software professionals in a telecom companyInngår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    Context: Previous research found that the performance of a team not only depends on the team personality composition, but also on the interactive effects of team climate. Although investigationon personalities associated with software development has been an active research area over the past decades, there has been very limited research in relation to team climate.

    Objective: Our study investigates the association between the five factor model personality traits(openness to experience, conscientiousness, extraversion, agreeableness and neuroticism) and the factors related to team climate (team vision, participative safety, support for innovation and task orientation) within the context of agile teams working in a telecom company.

    Method: A survey was used to gather data on personality characteristics and team climate perceptions of 43 members from eight agile teams. The data was initially used for correlation analysis; then, regression models were developed for predicting the personality traits related toteam climate perception.

    Results: We observed a statistically significant positive correlation between agreeableness and participative safety (r = 0.37), and also between openness to experience and support for innovation(r = 0.31). Additionally, agreeableness was observed to be positively correlated with overall team climate (r = 0.35). Further, from regression models, we observed that personality traits accountedto less than 15% of the variance in team climate.

    Conclusion: A person’s ability to easily get along with team members (agreeableness) has a significant positive influence on the perceived level of team climate. Results from our regression analysis suggest that further data may be needed, and/or there are other human factors, in addition to personality traits, that should also be investigated with regard to their relationship with team climate. Overall, the relationships identified in our study are likely to be applicable to organizations within the telecommunications domain that use scrum methodology for software development.

  • 131.
    Vishnubhotla, Sai Datta
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Mendes, Emilia
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Lundberg, Lars
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Understanding the Perceived Relevance of Capability Measures: A Survey of Agile Software Development PractitionersInngår i: Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    Context: A significant number of studies discussed various human-aspects of software engineers over the past years. However, in the light of swift, incremental and iterative nature of Agile Software Development (ASD) practices, establishing deeper insights into capability measurement is crucial, as both individual and team capability can affect software development performance and project success.

    Objective: Our study investigates how agile practitioners perceive the relevance of individual and team level measures, pertaining to professional, social and innovative aspects, for characterizing the capability of an agile team and its members.

    Method: We undertook a Web-based survey using a questionnaire built based on the capability measures identified from our previous Systematic Literature Review (SLR). This questionnaire sought information about agile practitioners’ perceptions of individual and team capability measures.

    Results: We received 60 usable responses, corresponding to a response rate of 17% from the original sampling frame. Our results indicate that 127 individual and 28 team capability measures were considered as relevant by majority of the practitioners. Our survey also identified seven individual and one team capability measure which have not been previously characterized by our SLR.

    Conclusion: In practitioners’ opinion, an agile team member’s state of being answerable or accountable for things within one's control (responsibility) and the ability to feel or express doubt and raise objections (questioning skills), are the two measures that significantly represent the member’s capability. Overall, the findings from our study shed light on the sparsely explored field of capability measurement in ASD. Our results can be helpful to practitioners in reforming their team composition decisions.

  • 132.
    Warnhag, Oskar
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Wedzinga, Nick
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Evaluating the Effects of Pre-Attentive Processing on Player Performance and Perception in Platform Video Games2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
  • 133.
    Westphal, Florian
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Lavesson, Niklas
    Grahn, Håkan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    A Case for Guided Machine Learning2019Inngår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) / [ed] Andreas Hozinger, Peter Kieseberg, A Min Tjoa and Edgar Weippl, Springer, 2019, Vol. 11713, s. 353-361Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Involving humans in the learning process of a machine learning algorithm can have many advantages ranging from establishing trust into a particular model to added personalization capabilities to reducing labeling efforts. While these approaches are commonly summarized under the term interactive machine learning (iML), no unambiguous definition of iML exists to clearly define this area of research. In this position paper, we discuss the shortcomings of current definitions of iML and propose and define the term guided machine learning (gML) as an alternative.

  • 134.
    Willemsen, Mattias
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Evaluating player performance and usability of graphical FPS interfaces in VR2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Background. When designing video games for Virtual Reality, graphical user interfaces (GUIs) cannot always be designed as they have been for traditional video games. An often recommended approach is to merge the interface with the game world, but it is unclear if this is the best idea in all cases. As the market for Virtual Reality is growing quickly, more research is needed to create an understanding of how GUIs should be designed for Virtual Reality.

    Objectives. The thesis researches existing GUI type classifications and adapts them for VR. A method to compare the GUI types to each other is selected and conclusions are drawn about how they affect player performance, usability, and preference. 

    Methods. A VR FPS game is developed and an experiment is designed using it. The experiment tests the player's performance with each of three distinct GUI types and also presents questionnaires to get their personal preference.

    Results. Both player performance and subjective opinion seems to favour geometric GUI.

    Conclusions. The often recommended approach for designing GUI elements as part of the game world may not always be the best option, as it may sacrifice usability and performance for immersion.

  • 135.
    Wu, Qian
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Segmentation-based Retinal Image Analysis2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Context. Diabetic retinopathy is the most common cause of new cases of legal blindness in people of working age. Early diagnosis is the key to slowing the progression of the disease, thus preventing blindness. Retinal fundus image is an important basis for judging these retinal diseases. With the development of technology, computer-aided diagnosis is widely used.

    Objectives. The thesis is to investigate whether there exist specific regions that could assist in better prediction of the retinopathy disease, it means to find the best region in fundus image that works the best in retinopathy classification with the use of computer vision and machine learning techniques.

    Methods. An experiment method was used as research methods. With image segmentation techniques, the fundus image is divided into regions to obtain the optic disc dataset, blood vessel dataset, and other regions (regions other than blood vessel and optic disk) dataset. These datasets and original fundus image dataset were tested on Random Forest (RF), Support Vector Machines (SVM) and Convolutional Neural Network (CNN) models, respectively.

    Results. It is found that the results on different models are inconsistent. As compared to the original fundus image, the blood vessel region exhibits the best performance on SVM model, the other regions perform best on RF model, while the original fundus image has higher prediction accuracy on CNN model. Conclusions. The other regions dataset has more predictive power than original fundus image dataset on RF and SVM models. On CNN model, extracting features from the fundus image does not significantly improve predictive performance as compared to the entire fundus image.

  • 136.
    Zhang, J.
    et al.
    Zhejiang Normal University, CHI.
    Hu, Yan
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Li, H.
    Zhejiang Normal University, CHI.
    Zheng, H.
    Zhejiang Normal University, CHI.
    Xiang, M.
    Zhejiang Normal University, CHI.
    Wang, Z.
    Zhejiang Normal University, CHI.
    Dong, G.
    Zhejiang Normal University, CHI.
    Altered brain activities associated with cue reactivity during forced break in subjects with Internet gaming disorder2020Inngår i: Addictive Behaviours, ISSN 0306-4603, E-ISSN 1873-6327, Vol. 102, artikkel-id 106203Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background: Studies have proven that forced break can elicit strong psychological cravings for addictive behaviors. This phenomenon could create an excellent situation to study the neural underpinnings of addiction. The current study explores brain features during a cue-reactivity task in Internet gaming disorder (IGD) when participants were forced to stop their gaming behaviors. Methods: Forty-nine IGD subjects and forty-nine matched recreational Internet game users (RGU) were asked to complete a cue-reactivity task when their ongoing gaming behaviors were forced to break. We compared their brain responses to gaming cues and tried to find specific features associated with IGD. Results: Compared with RGU, the IGD subjects showed decreased activation in the anterior cingulate cortex (ACC), parahippocampal gyrus, and dorsolateral prefrontal cortex (DLPFC). Significant negative correlations were observed between self-reported gaming cravings and the baseline activation level (bate value) of the ACC, DLPFC, and parahippocampal gyrus. Conclusions: IGD subjects were unable to suppress their gaming cravings after unexpectedly forced break. This result could also explain why RGU subjects are able to play online games without developing dependence. © 2019 Elsevier Ltd

  • 137.
    Åleskog, Christoffer
    et al.
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Ljungberg Fayyazuddin, Salomon
    Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för datavetenskap.
    Comparing node-sorting algorithms for multi-goal pathfinding with obstacles2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Background. Pathfinding plays a big role in both digital games and robotics, and is used in many different ways. One of them is multi-goal pathfinding (MGPF) which is used to calculate paths from a start position to a destination with the condition that the resulting path goes though a series of goals on the way to the destination. For the most part research on this topic is sparse, and when the complexity is increased through obstacles that are introduced to the scenario, there are only a few articles in the field that relate to the problem.Objectives. The objective in this thesis is to conduct an experiment to compare four algorithms for solving the MGPF problem on six different maps with obstacles, and then analyze and draw conclusions on which of the algorithms is best suited to use for the MGPF problem. The first is the traditional Nearest Neighbor algorithm, the second is a variation on the Greedy Search algorithm, and the third and fourth are variations on the Nearest Neighbor algorithm. Methods. To reach the Objectives all the four algorithms are tested fifty times on six different maps of varying sizes and obstacle layout. Results. The data from the experiment is compiled in graphs for all the different maps, with the time to calculate a path and the path lengths as the metrics. The averages of all the metrics are put in tables to visualize the difference between the results for the four algorithms.Conclusions. The conclusions were that the dynamic version of the Nearest Neighbor algorithm has the best result if both the metrics are taken into account. Otherwise the common Nearest Neighbor algorithm gives the best results in respect to the time taken to calculate the paths and the Greedy Search algorithm creates the shortest paths of all the tested algorithms.

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