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  • Simaremare, Mario
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Edison, Henry
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    AI Assistant to Improve Experimentation in Software Startups Using Large Language Model and Prompt Engineering2024In: CEUR Workshop Proceedings / [ed] Saltan A., Santos R., Wang X., Baiyere A., Peltonen E., Kemell K.-K.Saltan A., Santos R., Wang X., Baiyere A., Peltonen E., Kemell K.-K., Technical University of Aachen , 2024, Vol. 3621Conference paper (Refereed)
    Abstract [en]

    Software startup is a unique type of company with unique characteristics. On the one hand, they must offer innovative products appealing to customers to generate revenue and survive, but on the other hand, they are limited in resources, time, and experience. During the new product development, it is important to experiment with their original ideas. However, doing a meaningful experiment requires resources and challenges. A study on failed software startups shows that, despite its importance, many software startups skipped or did not experiment with their ideas. The study identifies 25 inhibitors spread in five experimentation stages. In the last few years, Large Language Models (LLMs) have become a popular technology. The advancement of LLM has made it adopted into many parts of the software development cycle. Studies show that LLM also has been used to generate new innovative product ideas and to manage innovation. However, there is no investigation into the possibility of utilizing the power of LLM to help software startups do experimentation. Interactions to an LLM are done through prompts. During the interaction or session, a user will send one or more prompts in a zero-, one-, or few-shots to an LLM agent. Unfortunately, learning and using prompts effectively requires time and resources, things that software startups are scarce with. In this project, we aim to help improve the experimentation process and address the inhibitors by leveraging the power of LLMs. There are five initial research questions and studies planned in the project. In the first step, we will investigate current experimentation practices, challenges, inhibitors, and the strategies used to circumvent them. Secondly, we will investigate how AI has been used in today's experimentation. Then, we will investigate the set of measurements available to measure the success of an experiment. The next step is to investigate how to support experimentation using LLMs followed by a validation sequence. The first form of support is a prompt guidebook to help software startups use an LLM agent to help their experimentation. The second form is an LLM-based assistant tailored specifically to guide the experimentation process. © 2006 Gesellschaft für Informatik, Bonn.

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  • Yang, Fan
    et al.
    Universiti Teknologi Malaysia (UTM), Malaysia.
    Ismail, Nor Azman
    Universiti Teknologi Malaysia (UTM), Malaysia.
    Pang, Yee Yong
    Universiti Teknologi Malaysia (UTM), Malaysia.
    Kebande, Victor R.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Al-Dhaqm, Arafat
    Universiti Teknologi PETRONAS, Malaysia.
    Koh, Tieng Wei
    Universiti Teknologi PETRONAS, Malaysia.
    A Systematic Literature Review of Deep Learning Approaches for Sketch-Based Image Retrieval: Datasets, Metrics, and Future Directions2024In: IEEE Access, E-ISSN 2169-3536, Vol. 12, p. 14847-14869Article, review/survey (Refereed)
    Abstract [en]

    Sketch-based image retrieval (SBIR) utilizes sketches to search for images containing similar objects or scenes. Due to the proliferation of touch-screen devices, sketching has become more accessible and therefore has received increasing attention. Deep learning has emerged as a potential tool for SBIR, allowing models to automatically extract image features and learn from large amounts of data. To the best of our knowledge, there is currently no systematic literature review (SLR) of SBIR with deep learning. Therefore, the aim of this review is to incorporate related works into a systematic study, highlighting the main contributions of individual researchers over the years, with a focus on past, present and future trends. To achieve the purpose of this study, 90 studies from 2016 to June 2023 in 4 databases were collected and analyzed using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) framework. The specific models, datasets, evaluation metrics, and applications of deep learning in SBIR are discussed in detail. This study found that Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN) are the most widely used deep learning methods for SBIR. A commonly used dataset is Sketchy, especially in the latest Zero-shot sketch-based image retrieval (ZS-SBIR) task. The results show that Mean Average Precision (mAP) is the most commonly used metric for quantitative evaluation of SBIR. Finally, we provide some future directions and guidance for researchers based on the results of this review. © 2013 IEEE.

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  • Harrison, Peter
    et al.
    Dublin Dental University Hospital, Ireland.
    Madeley, Edward
    Dublin Dental University Hospital, Ireland.
    Nolan, Michael
    Dublin Dental University Hospital, Ireland.
    Renvert, Stefan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Polyzois, Ioannis
    Dublin Dental University Hospital, Ireland.
    A longitudinal analysis of the impact of nonsurgical and surgical treatment of peri-implantitis upon clinical parameters and implant stability quotient values. A 2–3-year follow-up2024In: Clinical and Experimental Dental Research, E-ISSN 2057-4347, Vol. 10, no 1, article id e833Article in journal (Refereed)
    Abstract [en]

    Objectives: In this study, the aim was to investigate the medium- to long-term impact of peri-implantitis treatment upon clinical parameters and implant stability quotient values and to ascertain if magnetic resonance frequency analysis can be used as a diagnostic tool to demonstrate postoperative healing following treatment of peri-implantitis. Materials and Methods: A total of n = 26 patients (n = 86 implants) diagnosed with peri-implantitis were recruited for this prospective cohort study and four different treatment modalities were used. Baseline measurements of a number of clinical parameters as well as implant stability measurements in the form of ISQ were recorded. These measurements were repeated at 6, 12, and 24–36 months following treatment. Analysis of variance was performed for all implants treated as well as separately for each treatment modality. A regression model was also used to determine factors affecting ISQ measurements over time. Results: Treatment of peri-implantitis resulted in significant improvements of both average PPDs and BOP (p <.0001 and p <.01). ISQ values marginally improved initially for all treatment modalities, but improvement was only maintained for 2–3 years in treatment modalities I (+1.28), III (+1.49), and IV (+2.92). There was a statistically significant negative linear correlation between average PPD and the ISQ values recorded both at baseline (r = −.618, p < 0.0001) and at 2/3 years (r = −.604, p < 0.0001). Conclusion: Over the 2–3-year follow-up period, all four treatment modalities led to improved clinical and radiographic peri-implant parameters but implant stability posttreatment, as indicated by the fact that the recorded ISQ scores remained stable. As a result, use of MRFA as an adjunct to the traditionally used periodontal and radiographic tools for the evaluation of postoperative implant stability following the treatment of peri-implant disease cannot be recommended. © 2023 The Authors. Clinical and Experimental Dental Research published by John Wiley & Sons Ltd.

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  • Treidler, Oliver
    et al.
    TP & C GmbH.
    Kunz, Tom-Eric
    TP & C GmbH.
    Capraro, Maximilian
    InnerSource Commons.
    Dorner, Michael
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Sustaining Arm’s Length Cost Allocations for Highly Integrated Development Functions: An Explorative Case Study of Transfer Pricing for InnerSource Communities2024Report (Other academic)
    Abstract [en]

    Most contemporary developments in transfer pricing relate to intangibles. Appropriately coping with increasingly highly integrated value chains constitutes another driving force. This article examines the application of the arm’s length principle in the context of a related-party transaction characterized by integrated collaboration among decentralized business units and the joint utilization and development of intangibles. While the underlying theoretical transfer pricing concepts will be touched upon, we aim to present a case-based application of the arm’s length principle. The pragmatic approach presented in this article aims to support practitioners navigating the tradeoff between finding arm’s length solutions for increasingly complex, digitized organizations and effectively utilizing available internal data for transfer pricing purposes.

    While the OECD recently started tinkering with formulary apportionment approaches for marketing intangibles in the context of the Pillar 1 reforms, day-to-day transfer pricing remains focused on applying transfer prices that are commensurate with the arm’s length principles. As such, Chapter VI of the OECD Transfer Pricing Guidelines of 2017 remains perhaps the most important source of reference for practitioners when it comes to intangibles. The same applies to Chapter VIII when it comes to cost contribution arrangements (CCAs). For this article, it is deemed sufficient to limit the references to Chapter VI and Chapter VIII of the OECD guidelines.

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  • Kroon, Martin
    et al.
    Linnaeus University.
    Görtz, Jakob
    Blekinge Institute of Technology. student.
    Islam, Md. Shafiqul
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Andreasson, Eskil
    Tetra Pak, Lund, Sweden.
    Petersson, Viktor
    Tetra Pak, Lund, Sweden.
    Jutemar Persson, Elin
    Tetra Pak, Lund, Sweden.
    Experimental and theoretical study of stress relaxation in high-density polyethylene2024In: Acta Mechanica, ISSN 0001-5970, E-ISSN 1619-6937Article in journal (Refereed)
    Abstract [en]

    Stress relaxation of high-density polyethylene is addressed both experimentally and theoretically. Two types of stress relaxation testing are carried out: uniaxial tensile testing at constant test specimen length and compression testing of a 3D structure producing inhomogeneous deformation fields and relaxation. A constitutive model for isotropic, semi-crystalline polymers is also proposed. The model has the ability to model stress relaxation at different time scales. The developed model was implemented as a user subroutine in Abaqus (UMAT). The implicit integration scheme including an algorithmic tangent modulus is described in detail. The material model is calibrated by use of the uniaxial tensile tests, and the model is then validated by simulating the compression tests of the 3D structure. The model is able to describe the uniaxial tension tests well, and the comparison between the simulations and experimental testing of the 3D structure shows very good agreement. © 2024, The Author(s).

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  • Nyholm, Joel
    et al.
    student.
    Ghazi, Ahmad Nauman
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Ghazi, Sarah Nauman
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Prediction of dementia based on older adults’ sleep disturbances using machine learning2024In: Computers in Biology and Medicine, ISSN 0010-4825, E-ISSN 1879-0534, Vol. 171, article id 108126Article in journal (Refereed)
    Abstract [en]

    Background: The most common degenerative condition in older adults is dementia, which can be predicted using a number of indicators and whose progression can be slowed down. One of the indicators of an increased risk of dementia is sleep disturbances. This study aims to examine if machine learning can predict dementia and which sleep disturbance factors impact dementia.

    Methods: This study uses five machine learning algorithms (gradient boosting, logistic regression, gaussian naive Bayes, random forest and support vector machine) and data on the older population (60+) in Sweden from the Swedish National Study on Ageing and Care — Blekinge (). Each algorithm uses 10-fold stratified cross-validation to obtain the results, which consist of the Brier score for checking accuracy and the feature importance for examining the factors which impact dementia. The algorithms use 16 features which are on personal and sleep disturbance factors.

    Results: Logistic regression found an association between dementia and sleep disturbances. However, it is slight for the features in the study. Gradient boosting was the most accurate algorithm with 92.9% accuracy, 0.926 f1-score, 0.974 ROC AUC and 0.056 Brier score. The significant factors were different in each machine learning algorithm. If the person sleeps more than two hours during the day, their sex, education level, age, waking up during the night and if the person snores are the variables that most consistently have the highest feature importance in all algorithms.

    Conclusion: There is an association between sleep disturbances and dementia, which machine learning algorithms can predict. Furthermore, the risk factors for dementia are different across the algorithms, but sleep disturbances can predict dementia.

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  • Vishnubhotla, Sai Datta
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Exploring the relation between personality traits and agile team climate: Aggregating results from a twice replicated study in a telecom company2024In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 210, article id 111937Article in journal (Refereed)
    Abstract [en]

    Context: Former literature revealed team performance is contingent on personality composition and interactive effects of team climate. While decades of research on personality prevails in software engineering, team climate remains sparsely researched. Objective: In agile software development, individuals and interactions are key sources of agility. This study replicates a previous study and analyzes the relationship between five-factor-model personality traits and team climate dimensions among agile teams in a telecom company. Method: A Web-based survey was replicated twice, first with 75 professionals from 12 teams in Sweden, followed by 46 professionals from seven teams in India. The data was used for correlation, regression analyses, and meta-analysis. Results: We observed significant negative correlations between neuroticism and all the team climate dimensions. Meta-analysis identified a significant medium-sized negative effect between neuroticism and participative safety. Regression analysis showed personality traits accounted for around 10 % of the variance in team climate dimensions. Conclusions: High neuroticism is not conducive to team climate as emotionally unstable members could impair team cohesion by being reactive and susceptible to stress. Managers assembling Scrum teams ought to mitigate higher neuroticism by counterbalancing it with an elevation of corresponding negatively correlated personality variables and providing support/training towards increasing the aforementioned variables. © 2023

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  • Nawaz, Omer
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Fiedler, Markus
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Khatibi, Siamak
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    QoE-Based Performance Comparison of AVC, HEVC, and VP9 on Mobile Devices with Additional Influencing Factors2024In: Electronics, E-ISSN 2079-9292, Vol. 13, no 2, article id 329Article in journal (Refereed)
    Abstract [en]

    While current video quality assessment research predominantly revolves around resolutions of 4 K and beyond, targeted at ultra high-definition (UHD) displays, effective video quality for mobile video streaming remains primarily within the range of 480 p to 1080 p. In this study, we conducted a comparative analysis of the quality of experience (QoE) for widely implemented video codecs on mobile devices, specifically Advanced Video Coding (AVC), its successor High-Efficiency Video Coding (HEVC), and Google’s VP9. Our choice of 720 p video sequences from a newly developed database, all with identical bitrates, aimed to maintain a manageable subjective assessment duration, capped at 35–40 min. To mimic real-time network conditions, we generated stimuli by streaming original video clips over a controlled emulated setup, subjecting them to eight different packet-loss scenarios. We evaluated the quality and structural similarity of the distorted video clips using objective metrics, including the Video Quality Metric (VQM), Peak Signal-to-Noise Ratio (PSNR), Video Multi-Method Assessment Fusion (VMAF), and Multi-Scale Structural Similarity Index (MS-SSIM). Subsequently, we collected subjective ratings through a custom mobile application developed for Android devices. Our findings revealed that VMAF accurately represented the degradation in video quality compared to other metrics. Moreover, in most cases, HEVC exhibited an advantage over both AVC and VP9 under low packet-loss scenarios. However, it is noteworthy that in our test cases, AVC outperformed HEVC and VP9 in scenarios with high packet loss, based on both subjective and objective assessments. Our observations further indicate that user preferences for the presented content contributed to video quality ratings, emphasizing the importance of additional factors that influence the perceived video quality of end users. © 2024 by the authors.

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  • Mikaelsson Midlöv, Elina
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Lindberg, Terese
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Skär, Lisa
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Relative's suggestions for improvements in support from health professionals before and after a patient's death in general palliative care at home: A qualitative register study2024In: Scandinavian Journal of Caring Sciences, ISSN 0283-9318, E-ISSN 1471-6712Article in journal (Refereed)
    Abstract [en]

    Introduction: The efforts of relatives in providing palliative care (PC) at home are important. Relatives take great responsibility, face many challenges and are at increased risk of poor physical and mental health. Support for these relatives is important, but they often do not receive the support they need. When PC is provided at home, the support for relatives before and after a patient's death must be improved. This study aimed to describe relatives' suggestions to improve the support from health professionals (HPs) before and after a patient's death in general PC at home. Methods: This study had a qualitative descriptive design based on the data from open-ended questions in a survey collected from the Swedish Register of Palliative Care. The respondents were adult relatives involved in general PC at home across Sweden. The textual data were analysed using thematic analysis. Results: The analysis identified four themes: (1) seeking increased access to HPs, (2) needing enhanced information, (3) desiring improved communication and (4) requesting individual support. Conclusions: It is important to understand and address how the support to relatives may be improved to reduce the unmet needs of relatives. The findings of this study offer some concrete suggestions for improvement on ways to support relatives. Further research should focus on tailored support interventions so that HPs can provide optimal support for relatives before and after a patient's death when PC is provided at home. © 2024 The Authors. Scandinavian Journal of Caring Sciences published by John Wiley & Sons Ltd on behalf of Nordic College of Caring Science.

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  • Ahnström, Eva-Lisa
    et al.
    Blekinge Institute of Technology, The Library.
    Brännvall, Evelina
    Lund University.
    Hultman, Ylva
    Royal Institute of Technology.
    Jonsson, Anders
    Uppsala University.
    The profession of research management and administration in Sweden2023In: The Emerald Handbook of Research Management and Administration Around the World / [ed] Simon Kerridge, Susi Poli, Mariko Yang-Yoshihara, Emerald Group Publishing Limited, 2023, p. 751-757Chapter in book (Other academic)
    Abstract [en]

    This chapter outlines the development of the Swedish Higher Education System that led to the evolution of the profession of research management and administration (RMA) in Sweden. Evolution from an informal network towards more formalised and structured work within the Swedish RMA community is highlighted. Discussion on the level of salaries development depending on the education level, gender, experience and roles are elaborated too. The majority of the Swedish RMA community are women, which does not differ from most other RMA communities around the world. Swedish Association of Research Managers and Administrators (SWARMA) is the bridge between national research and innovation funding agencies and researchers. SWARMA selected members actively participate in the reference groups for EU R&I programmes. The future for RMAs in Sweden looks bright!. © 2024 by Eva-Lisa Ahnstrom, Evelina Brannvall, Ylva Hultman and Anders Jonsson. All rights reserved.

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  • Niklasson, Joakim
    et al.
    Linnaeus University.
    Fagerström, Cecilia
    Linnaeus University.
    Backåberg, Sofia
    Linnaeus University.
    Lindberg, Terese
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Bergman, Patrick
    Linnaeus University.
    Daily activity patterns in older adults receiving initial support: the association between daily steps and sitting in bouts of at least 60 min2024In: BMC Geriatrics, E-ISSN 1471-2318, Vol. 24, no 1, article id 88Article in journal (Refereed)
    Abstract [en]

    Background: Aging has a significant impact on health, underlining the importance of maintaining physical function and reducing time spent sitting among older adults. To understand how to reduce prolonged sitting or increase physical activity, factors related to the daily living and observed daily activity patterns should be explored. This study aimed to investigate the association between daily steps, self-rated health, physical activity, sedentary behavior, motivation to exercise and fear of falling among older adults receiving initial support. Method: Cross-sectional design with total population questionnaire data from adults aged ≥ 60 years (n = 917), living at home with initial support from municipal care in southern Sweden. The older adults were offered to participate in a follow-up study measuring daily activity patterns with accelerometers (n = 72). Linear regression was used to analyze associations between daily steps and possible predictors. Results: The linear model ($$ {R}^{2}= $$ 0.478) showed that sitting in unbroken bouts of > 60 min (β = -0.313, p < 0.05), walking independently outdoors (β = 0.301, p < 0.05), intending to increase physical activity (β = -0.294, p < 0.05), sex (β = 0.279, p < 0.05), relative autonomy index (β = 0.258, p < 0.05), fear of falling (β = -0.238, p < 0.05), and self-rated health (β = 0.213, p < 0.05) predicted daily steps. Conclusion: The model of predictors brings new understanding regarding daily steps among community-dwelling older adults. The association between sitting in bouts of > 60 min and daily steps is interesting as 35% of participants had a number of sitting bouts that on average, showed 30% less steps taken. Minimizing long sitting bouts and maintaining physical functioning to promote independence when walking outdoors can be tools for clinical practitioners devising interventions to break prolonged sitting among community-dwelling older adults. Future research should prioritize studying older adults’ outdoor walking independence, including its relation to walking with or without assistive devices and its impact on physical activity and sedentary behavior. © 2024, The Author(s).

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  • Haller, Marc
    et al.
    Karlsruhe University of Applied Sciences, Germany.
    Lenz, Christian
    Karlsruhe University of Applied Sciences, Germany.
    Nachtigall, Robin
    Karlsruhe University of Applied Sciences, Germany.
    Awayshehl, Feras M.
    The University of Tartu, Estonia.
    Alawadi, Sadi
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Handling Non-IID Data in Federated Learning: An Experimental Evaluation Towards Unified Metrics2023In: 2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023, Institute of Electrical and Electronics Engineers (IEEE), 2023, p. 762-770Conference paper (Refereed)
    Abstract [en]

    Recent research has demonstrated that Non-Identically Distributed (Non-IID) data can negatively impact the performance of global models constructed in federated learning. To address this concern, multiple approaches have been developed. Nonetheless, previous research lacks a cohesive overview and fails to uniformly assess these strategies, resulting in challenges when comparing and choosing relevant options for real-world scenarios. This study presents a structured survey of cutting-edge techniques for handling the Non-IID data, accompanied by proposing a metric to develop a standardized approach for assessing data skew and its harmony with the appropriate approach. The findings affirm the metric's suitability as a heuristic for assessing data skew in distributed datasets without having insight into client data, serving both scientific and practical purposes and thus supporting the selection of handling strategies. This preliminary research establishes the foundation for discussing standardizing methodologies for evaluating data heterogeneity in federated learning. © 2023 IEEE.

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  • Eriksson, Mattias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Fe II fluorescence in main-sequence K-dwarfs2024In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 527, no 3, p. 9522-9528Article in journal (Refereed)
    Abstract [en]

    Main-sequence K-dwarfs possess strong emission in the form of the H I Ly α line. There is a close coincidence between the energy corresponding to the transitions H I 1s-2p and Fe II (5D)5s 4D5/2–(5D)5p 4D5/2. Singly ionized iron has been confirmed being pumped by photo-excitation by accidental resonance (PAR) in planetary nebulae, symbiotic stars, K-giants, and active galactic nebulae. I investigate in this work whether PAR can occur in the atmospheres of main-sequence K-dwarfs, which do not possess the large extended atmospheres of the late-type K-giants. Specifically a search for possible Fe II fluorescence lines is conducted. For the case when I can confirm PAR, I estimate the total flux leaving the stars in the form of Fe II fluorescence. I search for emission lines from the Fe II (5D)5p 4D5/2 level. Since those of these lines with the largest branching fractions correspond to lines at wavelengths covered by the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite, a search for archival FUSE spectra from K-dwarfs within 20 ly from the sun is conducted. I retrieve and analyse FUSE spectra for four of these K-dwarfs. In each case I can confirm PAR, I fit the H I Ly α line in Hubble Space Telescope spectra recorded with the Space Telescope Imaging Spectrograph, in order to estimate the efficiency of the PAR mechanism. I can now confirm Fe II fluorescence in the two closest K-dwarfs, Alpha Centauri B, and Epsilon Eridani. The total power leaving as Fe II fluorescence are 4.9 × 1017 and 1.30 × 1018 W respectively. © The Author(s) 2023 Published by Oxford University Press on behalf of Royal Astronomical Society.

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  • Šmite, Darja
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Moe, Nils Brede
    SINTEF Digital, Trondheim.
    Defining a Remote Work Policy: Aligning Actions and Intentions2024In: Agile Processes in Software Engineering and Extreme Programming - Workshops / [ed] Philippe Kruchten, Peggy Gregory, Springer Science+Business Media B.V., 2024, Vol. 489, p. 149-158Conference paper (Refereed)
    Abstract [en]

    After the long period of forced work from home, many knowledge workers have not only developed a strong habit of remote work, but also consider flexibility as their personal right and no longer as a privilege. Existing research suggest that the majority prefers to work two or three days per week from home and are likely to quit or search for a new job if forced to return to full time office work. Given these changes, companies are challenged to alter their work policies and satisfy the employee demands to retain talents. The subsequent decrease in office presence, also calls for transformations in the offices, as the free space opens up opportunities for cutting the rental costs, as well as the other expenses related to office maintenance, amenities, and perks. In this paper, we report our findings from comparing work policies in three Nordic tech and fintech companies and identify the discrepancies in the way the corporate intentions are communicated to the employees. We discuss the need for a more systematic approach to setting the goals behind a revised work policy and aligning the intensions with the company’s actions. Further, we discuss the need to resolve the inherent conflicts of interest between the individual employees (flexibility, individual productivity, and well-being) and the companies (profitability, quality of products and services, employee retention, attractiveness in the job market). © 2024, The Author(s).

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  • Ny, Henrik
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Strategic Sustainable Development.
    Prieto Beaulieu, Martin
    Blekinge Institute of Technology, Faculty of Engineering, Department of Strategic Sustainable Development.
    Ny kärnkraft eller effektivisering och ny förnybar energi för ett kostnadseffektivt svenskt elsystem?: MODELLERING OCH KOSTNADSANALYSER KRING FÖRDUBBLAD ELANVÄNDNING TILL ÅR 20502024Report (Other academic)
    Abstract [sv]

    Sverige och världen är mitt i en omställning till ett ekologiskt, socialt och ekonomiskt hållbart samhälle. I detta förväntas en storskalig elektrifiering spela en stor roll under de närmaste decennierna. 

    Syftet med denna studie var att undersöka om den senaste tidens rapporter om olika energislags samhällskostnader skulle kunna peka på att det blir billigare att möta en ökad elanvändning med ny kärnkraft, i linje med regeringens nya kärnkraftsfärdplan, än med en kombination av effektivisering och ny förnybar energi. 

    Metoden var att ställa upp fem scenarier baserade på Svenska Kraftnäts tidigare analyser och beräkna deras respektive livscykelkostnader, inklusive omkostnader för flexibilitet, utifrån nya data från International Energy Agency:

    ·         Scenario 1a. Planerbart (Svenska kraftnäts planerbartscenario)

    ·         Scenario 1b. Planerbart med ny kärnkraft (Svenska kraftnäts planerbartscenario med variant av Regeringens kärnkraftsfärdplan)

    ·         Scenario 1c. Planerbart med ny kärnkraft och förnybart (Svenska kraftnäts planerbartscenario med variant av Regeringens kärnkraftsfärdplan)

    ·         Scenario 2a. Förnybart (Svenska kraftnäts förnybartscenario)

    ·         Scenario 2b. Förnybart med effektivisering (Svenska kraftnäts förnybartscenario med energieffektivisering)

    Resultatet blev att regeringens billigaste kärnkraftsfärdplansscenario (Sc1c) blir 470 miljarder kr dyrare än det dyraste förnybartscenariot (Sc2a) medan det dyraste kärnkraftsfärdplansscenariot (Sc1b) blir 1070 miljarder kr dyrare än det billigaste förnybartscenariot med effektivisering (Sc2b). Dessutom tillkommer en merkostnad för Regeringens kärnkraftsfärdplansscenarier på minst 2000 till 5000 miljarder kr från år 2050 till 2100. 

    Slutsatsen blir alltså att vi har stärkt de samhällsekonomiska argumenten för att satsa på effektivisering och förnybart snarare än ny kärnkraft för att möta framtidens ökade elenergianvändning. Förnybartscenarierna har även fördelen att de skulle ge mycket mer hanterbara hållbarhetsrisker jämfört med kärnkraftsscenarierna och de skulle, till skillnad från kärnkraftsscenarierna, kunna genomföras tillräckligt snabbt för att bli relevanta för klimatutmaningen. Om vi skulle satsa på effektivisering och ny förnybar energi skulle hela landet också kunna byggas ihop till ett decentraliserat och integrerat energisystem. Ett ‘självspelande piano’ som när det väl är uppbyggt kan förse samhället med billig förnybar energi från eviga flöden. Ett sådant energisystem skulle, till skillnad från dagens centralt styrda system, vara motståndskraftigt mot översvämningar och andra klimatfaktorer samt bli omöjligt för en angripare att slå ut. Det skulle alltså även bli en säkerhetspolitisk fördel i framtiden.

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  • Andersson, Jonathan
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science. student.
    Hu, Yan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Exploring the Impact of Menu Systems, Interaction Methods, and Sitting or Standing Posture on User Experience in Virtual Reality2023Conference paper (Refereed)
    Abstract [en]

    Virtual Reality (VR) has become an increasingly crucial aspect in both commercial and industrial settings. However, the user experience of the user interfaces and interaction methods in the VR environment is often overlooked. This paper aims to explore different menu systems, interaction methods, and the user’s sitting or standing posture on user experience and cybersickness in VR applications. An experiment with two menu systems and two interaction methods in an implemented VR application was conducted with 20 participants. The results found that traditional, top-down, panel menus with motion controls are the best combination regarding the user experience. Sitting posture provides less severe simulator sickness symptoms than standing.

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  • Eklund, Johan
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Thulin, Per
    Entreprenörskapsforum.
    Swedish Competitiveness Scorecard 20212022Report (Other academic)
    Abstract [en]

    I denna rapport, den första inom ramen för ett mångårigt konkurrenskraftsprojekt, presenteras en omfattande genomgång av ekonomiska indikatorer för samtliga OECD länder och en jämförande analys av Sveriges konkurrenskraft i relation till OECD. Swedish Competitiveness Scorecard 2021 omfattar 81 olika indikatorer vilka mäter olika dimensioner av ekonomiska utfall och mer fundamentala konkurrenskraftsförutsättningar – allt ifrån social och miljömässig hållbarhet till forskning och utveckling, arbetsmarknad och infrastruktur.

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  • Braunerhjelm, Pontus
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Donationer till statliga lärosäten – Förslag till förenklingar och förtydliganden2021Report (Other (popular science, discussion, etc.))
    Abstract [sv]

    Högskolesystemets kvalitet och förmåga att positionera sig i den internationella konkurrensen är avgörande för Sveriges tillväxt, välstånd och globala attraktionskraft. Kritik, bland annat av OECD, har dock riktats mot långsiktigheten i politiken, försvagning av tidigare starka forskningsmiljöer, oklara regelverk och otydliga ledningsstrukturer. Flera utredningar har konstaterat att ett sätt att stärka universiteten är en ökad grad av ekonomisk självständighet. Detta skulle kunna uppnås genom att förenkla hanteringen av donationer och att underlätta för lärosäten att själva bilda eller förvalta stiftelser. I Donationer till statliga lärosäten – Förslag till förenklingar och förtydliganden presenteras möjliga vägar och lösningar som förhållandevis enkelt och snabbt skulle kunna lösa nuvarande hinder och begränsningar i donationsprocesserna

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  • Shahzad, Raja Muhammad Khurram
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Automated Malware Detection and Classification Using Supervised Learning2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Malware has been one of the key concerns for Information Technology security researchers for decades. Every year, anti-malware companies release alarming statistics suggesting a continuous increase in the number and types of malware.  This is mainly due to the constant development of new and more sophisticated malicious functionalities, propagation vectors, and infection tactics for malware. To combat this ever-evolving threat, anti-malware companies analyze thousands of malicious samples on a daily basis, either manually or through semi-automated means, to identify their type (whether it's a variant or zero-day) and family. After the analysis, signature databases or rule databases of anti-malware products are updated in order to detect known malware.  However, due to the ever-growing capabilities of malware, the malware analysis process is challenging and requires significant human effort. As a result, researchers are focusing on data-driven approaches based on machine learning to develop intelligent malware detectors with high accuracy. Specifically, they are focused on extracting static features from malware in the form of n-grams for experimental purposes. However, the previous research is inconclusive in terms of optimal feature representation and detection accuracy.

    The primary objective of this thesis is to present state-of-the-art automated techniques for detecting and classifying malware using supervised learning algorithms. In particular, the focus is on two critical aspects of supervised learning-based malware detection: optimal feature representation and improved detection accuracy. Malware detection can be accomplished using two methods: static analysis, which extracts patterns without executing malware, and dynamic analysis, which captures behaviors through executing malware. This thesis focuses on static analysis instead of dynamic analysis because static analysis requires fewer computing resources. An additional benefit of static analysis is that present-day malware cannot evade it. To achieve the goals of this thesis, two new feature representations for static analysis are proposed. Furthermore, three customized ensembles are introduced to enhance malware detection accuracy, and their feasibility is experimentally demonstrated.  

    The experiments incorporate customized malware data sets including Spyware, Adware, Scareware, and Android malware samples, and public malware data sets from Microsoft's having samples from nine distinct malware families. Artificially generated data sets are employed to mitigate class imbalance issues and represent inter-family and intra-family examples. Reverse engineering is performed to transform the data sets as feature data sets using both byte code and assembly language instructions. Further, existing and new feature representations along with various feature selection algorithms and feature fusion techniques are explored. To enhance detection accuracy, different decision theories from social choice theory, such as veto and consensus, are integrated into customized ensembles. The experimental results indicate that the proposed methods are capable of detecting known and zero-day malware. The proposed ensembles are also tested on the UCI public data sets, such as Forest CoverType, and the results demonstrate their effectiveness in classification. Further, these methods are designed to be portable and adaptable to different operating systems, and they can also be scaled for multi-class malware detection.

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  • Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ghazi, Ahmad Nauman
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Noor, Adeeb
    King Abdulaziz University, Saudi Arabia.
    Elmståhl, Sölve
    Lund University.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Breaking barriers: a statistical and machine learning-based hybrid system for predicting dementia2024In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 11, article id 1336255Article in journal (Refereed)
    Abstract [en]

    Introduction: Dementia is a condition (a collection of related signs and symptoms) that causes a continuing deterioration in cognitive function, and millions of people are impacted by dementia every year as the world population continues to rise. Conventional approaches for determining dementia rely primarily on clinical examinations, analyzing medical records, and administering cognitive and neuropsychological testing. However, these methods are time-consuming and costly in terms of treatment. Therefore, this study aims to present a noninvasive method for the early prediction of dementia so that preventive steps should be taken to avoid dementia.

    Methods: We developed a hybrid diagnostic system based on statistical and machine learning (ML) methods that used patient electronic health records to predict dementia. The dataset used for this study was obtained from the Swedish National Study on Aging and Care (SNAC), with a sample size of 43040 and 75 features. The newly constructed diagnostic extracts a subset of useful features from the dataset through a statistical method (F-score). For the classification, we developed an ensemble voting classifier based on five different ML models: decision tree (DT), naive Bayes (NB), logistic regression (LR), support vector machines (SVM), and random forest (RF). To address the problem of ML model overfitting, we used a cross-validation approach to evaluate the performance of the proposed diagnostic system. Various assessment measures, such as accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and Matthew’s correlation coefficient (MCC), were used to thoroughly validate the devised diagnostic system’s efficiency.

    Results: According to the experimental results, the proposed diagnostic method achieved the best accuracy of 98.25%, as well as sensitivity of 97.44%, specificity of 95.744%, and MCC of 0.7535.

    Discussion: The effectiveness of the proposed diagnostic approach is compared to various cutting-edge feature selection techniques and baseline ML models. From experimental results, it is evident that the proposed diagnostic system outperformed the prior feature selection strategies and baseline ML models regarding accuracy.

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