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  • 1.
    Adewumi, Tosin
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Vadoodi, Roshanak
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.
    Tripathy, Aparajita
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Nikolaidou, Konstantina
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Liwicki, Foteini
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Liwicki, Marcus
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idioms2022In: Proceedings of the 13th Language Resources and Evaluation Conference / [ed] Nicoletta Calzolari; Frédéric Béchet; Philippe Blache; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Hélène Mazo; Jan Odijk; Stelios Piperidis, European Language Resources Association (ELRA) , 2022, p. 689-696Conference paper (Refereed)
    Abstract [en]

    We present a fairly large, Potential Idiomatic Expression (PIE) dataset for Natural Language Processing (NLP) in English. The challenges with NLP systems with regards to tasks such as Machine Translation (MT), word sense disambiguation (WSD) and information retrieval make it imperative to have a labelled idioms dataset with classes such as it is in this work. To the best of the authors’ knowledge, this is the first idioms corpus with classes of idioms beyond the literal and the general idioms classification. Inparticular, the following classes are labelled in the dataset: metaphor, simile, euphemism, parallelism, personification, oxymoron, paradox, hyperbole, irony and literal. We obtain an overall inter-annotator agreement (IAA) score, between two independent annotators, of 88.89%. Many past efforts have been limited in the corpus size and classes of samples but this dataset contains over 20,100 samples with almost 1,200 cases of idioms (with their meanings) from 10 classes (or senses). The corpus may also be extended by researchers to meet specific needs. The corpus has part of speech (PoS) tagging from the NLTK library. Classification experiments performed on the corpus to obtain a baseline and comparison among three common models, including the state-of-the-art (SoTA) BERT model, give good results. We also make publicly available the corpus and the relevant codes for working with it for NLP tasks.

  • 2.
    Aehle, Max
    et al.
    University of Kaiserslautern-Landau (RPTU), Germany.
    Tung Nguyen, Xuan
    University of Kaiserslautern-Landau (RPTU), Germany; National Institute for Nuclear Physics (INFN), Italy.
    Novák, Mihály
    European Organization for Nuclear Research (CERN), Switzerland/France.
    Dorigo, Tommaso
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab. National Institute for Nuclear Physics (INFN), Italy.
    Gauger, Nicolas R.
    University of Kaiserslautern-Landau (RPTU), Germany.
    Kieseler, Jan
    Karlsruhe Institute of Technology (KIT), Germany.
    Klute, Markus
    Karlsruhe Institute of Technology (KIT), Germany.
    Vassilev, Vassil
    Princeton University, USA.
    Efficient Forward-Mode Algorithmic Derivatives of Geant4Manuscript (preprint) (Other academic)
  • 3.
    Agües Paszkowsky, Núria
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Data Analysis of Earth Observation Data from Copernicus Satellites2020Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Open Data Cubes are platforms that contain open source satellite data and provide analysis tools for governments or organizations. The Swedish version is known as Swedish Space Data Lab (SSDL) and this master thesis was a part of it, providing the first analysis tools of the SSDL. Within a smaller project in the SSDL a drought analysis was done for the region of Mälardalen. The thesis work consisted on developing data analysis methods using packages for machine learning and statistical analysis in Python and Jupyter Notebooks. The drought analysis consisted of a two-year comparison between 2018 and 2019 due to limitations on the data availability. It was found that first year was drier than the second. However, longer time series would be needed in order to observe trends related to possible changes in the climate.

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  • 4.
    Ashaju, Oluwafemi
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Investigating the Effects of Information Security Awareness in the Third Sector2020Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
    Abstract [en]

    Information security awareness (ISA) focuses on the user’s responsibility and understanding of risk, to ensure that acceptable working practices are adopted under these broad principles, thereby reducing the likelihood of legal, financial and reputational risk related to the organization and individual. However, the third sector organization is behind in the security awareness maturity level. This research aims to understand and evaluate the level of information security awareness (ISA) knowledge in third sector organizations. The study was conducted with mixed-method design, combining the qualitative and quantitative approaches. A semi-structured interview method was used to gather data, transcribe it, and analyse it with a thematic framework analysis. The quantitative approach uses a questionnaire survey method was used to investigate the knowledge of information security awareness. The main findings present a lack of security awareness in the third sector and gaps in good security behaviour. 

     

  • 5.
    Ayanwale, Musa Adekunle
    et al.
    Department of Science and Technology Education, University of Johannesburg, South Africa.
    Sanusi, Ismaila Temitayo
    School of Computing, University of Eastern Finland, P.O.Box 111, 80101, Joensuu, Finland.
    Adelana, Owolabi Paul
    Department of Science and Technology Education, University of Ibadan, Ibadan, Nigeria.
    Aruleba, Kehinde D.
    School of Computing and Mathematical Sciences, University of Leicester, UK.
    Oyelere, Solomon Sunday
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Teachers’ readiness and intention to teach artificial intelligence in schools2022In: Computers and Education: Artificial Intelligence, ISSN 2666-920X, Vol. 3, article id 100099Article in journal (Refereed)
    Abstract [en]

    The emergence of artificial intelligence (AI) as a subject to be incorporated into K-12 educational levels places new demand on relevant stakeholders, especially teachers that drive the teaching and learning process. It is therefore important to understand how ready teachers are to teach the emerging subject as the success of AI education would probably be closely dependent on the readiness of teachers. As a result, this study presents an insight into factors influencing the behavioural intention and readiness of Nigerian in-service teachers to teach artificial intelligence. A total of 368 teachers, from elementary to high school participated in the study. We utilised quantitative methodology using variance-based structural equation modelling to understand the relationship among the eight variables (AI anxiety, perceived usefulness, AI for social good, Attitude towards using AI, perceived confidence in teaching AI, relevance of AI, AI readiness, and behavioural intention) considered in the study. The result indicated that confidence in teaching AI predicts intention to teach AI while AI relevance strongly predicts readiness to teach AI. While other factors influence the teaching of AI, anxiety and social good could not predict teachers' intention and readiness to implement AI in classrooms respectively. We discussed the implication of our findings in relation to AI implementation in schools and highlight future directions.

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  • 6.
    Bergsten, Daniela
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Understanding the Modus Operandi of Advanced Persistent Threats: A comparison of the Modus Operandi of Advanced Persistent Threats and their Impact2020Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
    Abstract [en]

    Since Advanced Persistent Threats (APTs) are the most sophisticated form of cyber weapon to date, previous research has indicated that further knowledge about the actors and their Modus Operandi (MO) is needed as the groups are highly organized, skilled and motivated when engaging in cyberoperations with different aims. This thesis poses the research question: how does the desired impact of an APT affect its MO? To answer the research question, a cross-case study is performed using a qualitative case study design. The method of structured focused comparison is employed where the cases of the Russian attributed APT the Sandworm Team and the North Korean-linked APT the Lazarus Group which have engaged in numerous cyberoperations with multiple impacts are compared against the Russian attributed APT Turla and the North Korean attributed APT Kimsuky which have performed numerous cyberoperations with a single impact. The findings, using the MITRE ATT&CK framework, show that there are similarities across the cases in terms of the techniques used but differences in terms of malwares used. The findings therefore indicate that the malware may be the key determinant of the impact of a cyberoperation by an APT.

  • 7.
    Chowdhury, Ziaul Islam
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Implementation of an abstract module for entity resolution to combine data sources with the same domain information2021Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Increasing digitalization is creating a lot of data every day. Sometimes the same real-world entity is stored in multiple data sources but lacks common reference. This creates a significant challenge on the integration of data sources and may cause duplicates and inconsistencies if not resolved correctly. The core idea of this thesis is to implement an abstract module for entity resolution to combine multiple data sources with similar domain information. 

    CRISP-DM process was used as the methodology in this thesis which started with an understanding of the business and data. Two open datasets containing product details from e-commerce sites are used to conduct the research (Abt-Buy and Amazon-Google). The datasets have similar structures and contain product name, description, manufacturer’s name, price. Both datasets contain gold-standard data to evaluate the performance of the model. In the data exploration phase, various aspects of the datasets are explored such as word-cloud containing important words in the product name and description, bigrams and trigrams of the product name, histograms, standard deviation, mean, min, max length of the product name. Data preparation phases contains NLP based preprocessing pipeline consists of normalization of case, removal of special characters and stop-words, tokenization, and lemmatization. 

    In the modeling phase of the CRISP-DM process, various similarity and distance measures are applied on the product name and/or description and the weighted scores are summed up to form total score of the fuzzy matching. A set of threshold values are applied to the total score and performance of the model is evaluated against the ground truth. The implemented model scored more than 60% F1-score in both datasets. Moreover, the abstract model can be applied to various datasets with similar domain information. The model is not deployed to the production environment which can be a future work. Moreover, blocking or indexing techniques can be also applied in the future with big data technologies which will reduce quadratic nature of entity resolution problem. 

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  • 8. Constantinidis, V.
    et al.
    Zaslavsky, Arkady
    Engineering an ingres active database using conceptual design knowledge1995In: Proceedings / The 7th International Conference on Software Engineering and Knowledge Engineering : SEKE '95 ; technical program, June 22 - 24, 1995, Rockville, Maryland, USA: SEKE '95 ; technical program, June 22 - 24, 1995, Rockville, Maryland, USA, Skokie, Ill: Knowledge Systems Institute, 1995Conference paper (Refereed)
  • 9.
    de Koning, Enrico
    et al.
    Cardiology Department, Leiden University Medical Center, Leiden, Netherlands.
    van der Haas, Yvette
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Stoop, Esmee
    Clinical AI and Research lab, Leiden University Medical Center, Leiden, Netherlands.
    Bosch, Jan
    Research and Development, Regional Ambulance Service Hollands-Midden, Leiden, Netherlands.
    Beeres, Saskia
    Cardiology Department, Leiden University Medical Center, Leiden, Netherlands.
    Schalij, Martin
    Cardiology Department, Leiden University Medical Center, Leiden, Netherlands.
    Boogers, Mark
    Cardiology Department, Leiden University Medical Center, Leiden, Netherlands.
    AI Algorithm to Predict Acute Coronary Syndrome in Prehospital Cardiac Care: Retrospective Cohort Study2023In: JMIR Cardio, E-ISSN 2561-1011, Vol. 7, no 1, article id e51375Article in journal (Refereed)
    Abstract [en]

    Background: Overcrowding of hospitals and emergency departments (EDs) is a growing problem. However, not all ED consultations are necessary. For example, 80% of patients in the ED with chest pain do not have an acute coronary syndrome (ACS). Artificial intelligence (AI) is useful in analyzing (medical) data, and might aid health care workers in prehospital clinical decision-making before patients are presented to the hospital.

    Objective: The aim of this study was to develop an AI model which would be able to predict ACS before patients visit the ED. The model retrospectively analyzed prehospital data acquired by emergency medical services' nurse paramedics.

    Methods: Patients presenting to the emergency medical services with symptoms suggestive of ACS between September 2018 and September 2020 were included. An AI model using a supervised text classification algorithm was developed to analyze data. Data were analyzed for all 7458 patients (mean 68, SD 15 years, 54% men). Specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for control and intervention groups. At first, a machine learning (ML) algorithm (or model) was chosen; afterward, the features needed were selected and then the model was tested and improved using iterative evaluation and in a further step through hyperparameter tuning. Finally, a method was selected to explain the final AI model.

    Results: The AI model had a specificity of 11% and a sensitivity of 99.5% whereas usual care had a specificity of 1% and a sensitivity of 99.5%. The PPV of the AI model was 15% and the NPV was 99%. The PPV of usual care was 13% and the NPV was 94%.

    Conclusions: The AI model was able to predict ACS based on retrospective data from the prehospital setting. It led to an increase in specificity (from 1% to 11%) and NPV (from 94% to 99%) when compared to usual care, with a similar sensitivity. Due to the retrospective nature of this study and the singular focus on ACS it should be seen as a proof-of-concept. Other (possibly life-threatening) diagnoses were not analyzed. Future prospective validation is necessary before implementation.

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  • 10.
    de Lange, Michiel
    et al.
    Utrecht University, Utrecht, The Netherlands.
    Synnes, Kåre
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Leindecker, Gerald
    Institut für Strukturentwicklungsplanung, Wels, Austria.
    Smart Citizens in the Hackable City: On the Datafication, Playfulness, and Making of Urban Public Spaces Through Digital Art2019In: CyberParks – The Interface Between People, Places and Technology: New Approaches and Perspectives / [ed] Carlos Smaniotto Costa, Ina Šuklje Erjavec, Therese Kenna, Michiel de Lange, Konstantinos Ioannidis, Gabriela Maksymiuk, Martijn de Waal, Springer Nature , 2019, p. 157-166Chapter in book (Refereed)
    Abstract [en]

    This contribution explores concepts, approaches and technologies used to make urban public spaces more playful and artful. Through a variety of compelling narratives involving play and art it assists in the design of new cyberparks, public spaces where digitally mediated interactions are an inherent part. How can play and interactive art be used to strengthen urban public spaces by fostering citizen engagement and participation? We propose to not only utilise interactive media for designing urban (public) spaces, but also for social innovation for the benefit of citizens. in cyberparks. The contribution connects urbanity, play and games, as well as concepts of active and passive interactive digital art as part of trends towards pervasive urban interaction, gameful design and artification. We position this as an important part of developing human-centred smart cities where social capital is central, and where citizens engaging in play and art are prerequisites for sustainable communities. Using art, play and games to foster citizen engagement and collaboration is a means to develop social technologies and support the development of collective intelligence in cyberparks. This is studied in concrete cases, such as the Ice Castle in Luleå, Sweden and the Ars Electronica in Linz, from a multi-disciplinary stance involving interaction design, digital art, landscape design, architecture, and health proficiencies. We will analyse two cases of gameful design and one case of digital interactive art being used to address urban issues. Rezone the game is an interactive multimedia game developed to tackle vacancy in the city of Den Bosch in the Netherlands. The Neighbourhood is a board game developed to involve various stakeholders in making their neighbourhood using water as a collective resource.

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  • 11.
    Dehkhoda, Dorna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Combining IRAM2 with Cost-BenefitAnalysis for Risk Management: Creating a hybrid method with traditional and economic aspects2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The aim of this thesis is to contribute to the risk methodology field by introducing a method

    that covers both economic and information security aspects. The aim is to provide a way for

    practitioners to get results that is enough for decision makers to make valid and well-grounded

    decisions. There are a lot of traditional risk assessment methods that focus on information

    security. There are also CBA (Cost-Benefit Analysis) methods that are used to make sure

    investments are cost-effective and provide value for the organization. The aim of this thesis is to

    combine those and see if they can be merged to one risk assessment method to increase the

    value of the result. CBA will be added to a more traditional risk assessment method called

    IRAM2. The thesis will evaluate if they are suited to be used together and if it provides a more

    valuable result when combining them than only using one of them. The research method that

    has been used in this study is ADR. It has been used as a way of working when producing a new

    hybrid method together with some design principles regarding how to combine traditional risk

    management with economic equations.

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  • 12.
    Dibs, Hayder
    et al.
    Department of Water Resources Management Engineering, Faculty of Engineering, Al-Qasim Green University, Babylon, Iraq.
    Al-Ansari, Nadhir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Integrating Highly Spatial Satellite Image for 3D Buildings Modelling Using Geospatial Algorithms and Architecture Environment2023In: Engineering, ISSN 1947-3931, E-ISSN 1947-394X, Vol. 15, no 4, p. 220-233Article in journal (Refereed)
    Abstract [en]

    The growing demand for current and precise geographic information that pertains to urban areas has given rise to a significant interest in digital surface models that exhibit a high level of detail. Traditional methods for creating digital surface models are insufficient to reflect the details of earth’s features. These models only represent three-dimensional objects in a single texture and fail to offer a realistic depiction of the real world. Furthermore, the need for current and precise geographic information regarding urban areas has been increasing significantly. This study proposes a new technique to address this problem, which involves integrating remote sensing, Geographic Information Systems (GIS), and Architecture Environment software environments to generate a detailed three-dimensional model. The processing of this study starts with: 1) Downloading high-resolution satellite imagery; 2) Collecting ground truth datasets from fieldwork; 3) Imaging nose removing; 4) Generating a Two-dimensional Model to create a digital surface model in GIS using the extracted building outlines; 5) Converting the model into multi-patch layers to construct a 3D model for each object separately. The results show that the 3D model obtained through this method is highly detailed and effective for various applications, including environmental studies, urban development, expansion planning, and shape understanding tasks.

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  • 13.
    Dibs, Hayder
    et al.
    Water Resources Management Engineering Department, Faculty of Engineering, Al-Qasim Green University, Babylon, Iraq.
    Al-Ansari, Nadhir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Laue, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques2023In: Engineering, ISSN 1947-3931, E-ISSN 1947-394X, Vol. 15, no 05, p. 328-341Article in journal (Refereed)
    Abstract [en]

    The use of three-dimensional maps is more effective than two-dimensional maps in representing the Earth’s surface. However, the traditional methods used to create digital surface models are not efficient for capturing the details of Earth’s features. This is because they represent only three-dimensional objects in a single texture and do not provide a realistic representation of the real world. Additionally, there is a growing demand for up-to-date and accurate geo-information, particularly in urban areas. To address this challenge, a new technique is proposed in this study that involves integrating remote sensing, Geographic Information System, and Architecture Environment software to generate a highly-detailed three-dimensional model. The method described in this study includes several steps such as acquiring high-resolution satellite imagery, gathering ground truth data, performing radiometric and geometric corrections during image preprocessing, producing a 2D map of the region of interest, constructing a digital surface model by extending the building outlines, and transforming the model into multi-patch layers to create a 3D model for each object individually. The research findings indicate that the digital surface model obtained with comprehensive information is suitable for different purposes, such as environmental research, urban development and expansion planning, and shape recognition tasks.

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  • 14.
    Ekström, Karl
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Sandin, Fredrik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Fault Severity Estimation using Weak Supervision with Language Based Labels and Condition Monitoring Data2020Conference paper (Refereed)
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    SAIS
  • 15.
    Erhard, Annalena
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    The Cost of Algorithmic decisions: A Systematic Literature Review2021Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Decisions have been automated since the early days. Ever since the rise of AI, ML and DataAnalytics, algorithmic decision-making has experienced a boom time. Nowadays, using AI withina company is said to be critical to the success of a company. Considering the point that it can bequite costly to develop AI/ ML and integrating it into decision-making, it is striking how littleresearch was put into the identification and analysis of its cost drivers by now. This thesis is acontribution to raise and the awareness of possible cost drivers to algorithmic decisions. Thetopic was divided in two subgroups. That is solely algorithms and hybrid decision-making. Asystematic literature review was conducted to create a theoretical base for further research. Thecost drivers for algorithms to make decisions without human interaction, the identified costdrivers identified can be found at Data Storage (including initial, floor rent, energy, service,disposal, and environmental costs), Data Processing, Transferring and Migrating. Additionally,social costs and the ones related to fairness as well as the ones related to algorithms themselves(Implementation and Design, Execution and Maintenance) could be found. Business Intelligenceused for decision making raises costs in Data quality, Update delays of cloud systems, Personneland Personnel training, Hardware, Software, Maintenance and Data Storage. Moreover, it isimportant to say that the recurrence of some costs was detected. Further research should go inthe direction of applicability of the theoretical costs in practice.

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    theCostOfAlgorithmicDecisions_thesis
  • 16.
    Fúska, Róbert
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Implementation of ISO27001 standard in startups2022Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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  • 17.
    Hossain, Mohammad Shahadat
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh.
    Ahmed, Mumtahina
    Port City International University, Dhaka, Bangladesh.
    Raihan, S. M. Shafkat
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh.
    Sharma, Angel
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System to Diagnose Schizophrenia Using Whole Blood DNA Methylation Data2023In: Machine Intelligence and Emerging Technologies - First International Conference, MIET 2022, Proceedings, part 2 / [ed] Md. Shahriare Satu; Mohammad Ali Moni; M. Shamim Kaiser; Mohammad Shamsul Arefin; Mohammad Shamsul Arefin, Springer Science and Business Media Deutschland GmbH , 2023, Vol. 1, p. 271-282Conference paper (Refereed)
    Abstract [en]

    Schizophrenia is a severe neurological disease where a patient’s perceptions of reality are disrupted. Its symptoms include hallucinations, delusions, and profoundly strange thinking and behavior, which make the patient’s daily functions difficult. Despite identifying genetic variations linked to Schizophrenia, causative genes involved in pathogenesis and expression regulations remain unknown. There is no particular way in life sciences for diagnosing Schizophrenia. Commonly used machine learning and deep learning are data-oriented. They lack the ability to deal with uncertainty in data. Belief Rule Based Expert System (BRBES) methodology addresses various categories of uncertainty in data with evidential reasoning. Previous researches showed the association of DNA methylation (DNAm) with risk of Schizophrenia. Whole blood DNAm data, hence, is useful for smart diagnosis of Scizophrenia. However, to our knowledge, no previous studies have investigated the performance of BRBES to diagnose Schizophrenia. Therefore, in this study, we explore BRBES’ performance in diagnosing Schizophrenia using whole blood DNAm data. BRBES was optimized by gradient-free algorithms due to the limitations of gradient-based optimization. Classification thresholds were optimized to yield better results. Finally, we compared performance to two machine learning models after 5-fold cross-validation where our model achieved the highest average sensitivity (76.8%) among the three.

  • 18.
    Kabir, Sami
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Shahadat Hossain, Mohammad
    Department of Computer Science & Engineering, University of Chittagong, Chattogram 4331, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    An Integrated Approach of Belief Rule Base and Convolutional Neural Network to Monitor Air Quality in Shanghai2022In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 206, article id 117905Article in journal (Refereed)
    Abstract [en]

    Accurate monitoring of air quality can reduce its adverse impact on earth. Ground-level sensors can provide fine particulate matter (PM2.5) concentrations and ground images. But, such sensors have limited spatial coverage and require deployment cost. PM2.5 can be estimated from satellite-retrieved Aerosol Optical Depth (AOD) too. However, AOD is subject to uncertainties associated with its retrieval algorithms and constrain the spatial resolution of estimated PM2.5. AOD is not retrievable under cloudy weather as well. In contrast, satellite images provide continuous spatial coverage with no separate deployment cost. Accuracy of monitoring from such satellite images is hindered due to uncertainties of sensor data of relevant enviromental parameters, such as, relative humidity, temperature, wind speed and wind direction . Belief Rule Based Expert System (BRBES) is an efficient algorithm to address these uncertainties. Convolutional Neural Network (CNN) is suitable for image analytics. Hence, we propose a novel model by integrating CNN with BRBES to monitor air quality from satellite images with improved accuracy. We customized CNN and optimized BRBES to increase monitoring accuracy further. An obscure image has been differentiated between polluted air and cloud in our model. Valid environmental data (temperature, wind speed and wind direction) have been adopted to further strengthen the monitoring performance of our proposed model. Three-year observation data (satellite images and environmental parameters) from 2014 to 2016 of Shanghai have been employed to analyze and design our proposed model. The results conclude that the accuracy of our model to monitor PM2.5 of Shanghai is higher than only CNN and other conventional Machine Learning methods. Real-time validation of our model on near real-time satellite images of April-2021 of Shanghai shows average difference between our calculated PM2.5 concentrations and the actual one within ±5.51.

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  • 19.
    Keller, Pascal
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering. Julius-Maximilians-Universität Würzburg.
    A New Application for Texture Mapping using 2D-3D Correspondences2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This master thesis describes the development of an application for texture mapping. Itspurpose is to simplify quality assurance for carbon fiber workpieces. Thermographic images are captured of the same and mapped to a 3D model, this way it can be examined ina convenient and interactive manner. The Direct Linear Transformation (DLT) is used for2D-3D assignments. Contents are the mathematical background of the DLT, the graphicalvisualization via OpenGL and the detailed explanation of the mapping process. The visualization part dives deep into the components of a graphics engine and explains how toimplement decent and efficient scene rendering. CUDA and OpenCL are addressed as wellto demonstrate the possibilities of performance improving for highly parallelized tasks. Aconcluding experiment is conducted, proving operational reliability and only small deviations. The reasons for some deviations between the mapped images are discussed andrecommendations for solving them are offered.

  • 20.
    Kietzmann, Jan
    et al.
    University of Victoria, Victoria, BC, V8P 5C2, Canada.
    Demetis, Dionysios S.
    Hull University Business School, Hull, HU6 7RX, U.K..
    Eriksson, Maria Theresa
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.
    Dabirian, Amir
    California State University, Fullerton, CA, 90802, USA.
    Hello Quantum! How Quantum Computing Will Change the World2021In: IT Professional Magazine, ISSN 1520-9202, E-ISSN 1941-045X, Vol. 23, no 4, p. 106-111Article in journal (Refereed)
  • 21.
    Kovács, László
    et al.
    Savaria Department of Business Administration, Faculty of Social Sciences, Eötvös Loránd University, Szombathely, Hungary.
    Bota, András
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Hajdu, László
    Innorenew CoE, Izola, Slovenia; Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Koper, Slovenia; Gyula Juhász Faculty of Education, University of Szeged, Szeged, Hungary.
    Krész, Miklós
    Innorenew CoE, Izola, Slovenia; Andrej Marušič Institute, University of Primorska, Koper, Slovenia; Gyula Juhász Faculty of Education, University of Szeged, Szeged, Hungary.
    Brands, networks, communities: How brand names are wired in the mind2022In: PLOS ONE, E-ISSN 1932-6203, Vol. 17, no 8, article id e0273192Article in journal (Refereed)
    Abstract [en]

    Brands can be defined as psychological constructs residing in our minds. By analyzing brand associations, we can study the mental constructs around them. In this paper, we study brands as parts of an associative network based on a word association database. We explore the communities–closely-knit groups in the mind–around brand names in this structure using two community detection algorithms in the Hungarian word association database ConnectYourMind. We identify brand names inside the communities of a word association network and explain why these brand names are part of the community. Several detected communities contain brand names from the same product category, and the words in these categories were connected either to brands in the category or to words describing the product category. Based on our findings, we describe the mental position of brand names. We show that brand knowledge, product knowledge and real word knowledge interact with each other. We also show how the meaning of a product category arises and how this meaning is related to brand meaning. Our results suggest that words sharing the same community with brand names can be used in brand communication and brand positioning.

  • 22.
    Lindskog, Viktor
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    The Need for Accreditation Speed2022Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Security requirements on information systems needs a way to be verified for fulfilment. Accreditation is a tool to measure the level of compliance of the security requirements. Unfortunately, the accreditation process also comes with challenges. To be able to complete the whole accreditation process the practitioners need to have a rigorous time plan and a generous budget, something that are not always available. The aim of this research is to identify challenges with time and costs in the accreditation process. Thereafter, building upon the identified challenges, aspects that could address time and costs are then proposed as a new model for accreditation. The theory presents the importance of accreditations and known challenges of today. The theory also justifies the need of reducing these challenges. This research collaborated with a company that has experience in accreditation. The company was used to gather empirical data to widen the view of accreditation in a qualitative way. The chosen method for this research was Design Science Research. The method was performed in two iterations and the demonstration- and evaluation-step was performed with an expert-panel consisted of employees from the collaborated company. The conclusion of the research is that the identified challenges can be assessed in a qualitative way to be handled with the new accreditation model developed in this research. The new accreditation model is based on a meticulous analysis on the identified challenges and the different steps in the risk management framework from National Institute of Standards and Technology.

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    The Need for Accreditation Speed
  • 23.
    Lugnet, Johan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Ericson, Åsa
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Scenarios as a Tool for Professional Training in Information Security Dialogues2022In: International Journal of Technology, Knowledge and Society, ISSN 1832-3669, Vol. 18, no 2, p. 65-77Article in journal (Refereed)
    Abstract [en]

    This article presents scenarios designed to support abstract and reflective thinking necessary to inculcate information security awareness among IT service designers. Data for the study was obtained in empirical interventions and through an action research approach in cooperation with an IT company. The findings highlight the need for training that, in combination with traditional contents, also integrates organizational, business, and social aspects into information security awareness. Rethinking a strategy for training to be grounded in scenarios from day-to-day business activities is one implication of the study; another is the suggestion to frame the scenarios as dilemmas, that is, problematic and realistic situations having multiple solutions depending on interpretations and perspectives, and a final conclusion is the importance of enabling structured in-depth dialogues among employees.

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  • 24.
    Magnusson, Jens
    Luleå University of Technology, Department of Engineering Sciences and Mathematics.
    Training Neural Network Potentials for Atomistic Calculations on Carbon Materials: An initial study on diamond structures2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Machine Learning (ML) and especially implementations of  Neural Networks (NNs) is growing in popularity  across numerous application areas. One of which is the use of a trained NN as an interatomic potential in Atomistic Simulations (AS), a NN applied in this manner is referred to as a Neural Network Potential (NNP).

    A well established method of atomistic calculations is the use of the first principle Density Functional Theory (DFT). DFT can very precisely model properties of nanomaterials, but for large systems of atoms DFT is not a feasible method because of its heavy computational load. The use of NNPs enables accurate simulations of big systems of atoms with a reasonable low computational cost.

    Previous work by students at Luleå University of Technology (LTU) where NNs were trained on fullerenes and carbon nanotubes (CNTs) demonstrated promising results. The NNs trained by the use of Atomistic Machine-Learning Package (AMP) managed to predict energies with considerable accuracy (100 meV/atom), but the force predictions were problematic and did not reach desired accuracy (the force RMSE reached was 6 eV/Å). Attempts made to run AS such as Molecular Dynamics (MD) and Geometry Optimization (GO) were unsuccessful, likely due to a poor representation of forces. 

    This work aims to improve the performance of NNs on carbon materials by studying diamond structures using AMP, such that working AS can be achieved.This was done in two stages, first a feasibility study was made to find appropriate hyperparameters. Moreover a study was made, where NNs was trained with the hyperparameters found. Two types of feature mapping descriptors were considered here, Gaussian and Zernike.The NNs trained was used as NNPs to perform MD and GO simulations as a mean of evaluation. The NNPs were also used to calculate the phonon dispersion curve of diamond.The trained NNPs in this work managed to perform AS and calculate the phonon dispersion curve with varying success. The best performing NN trained on 333 super-cells of diamond reached an accuracy of 120 meV/atom when predicting energies, and 640 meV/Å predicting forces. A NNP trained with Gaussian descriptors turned out to be 10 times faster than the reference simulation done with DFT, compared while performing a single step in a GO. The phonon dispersion curve produced by the Gaussian NNP displayed a striking resemblance to the reference produced by using DFT. Phonon dispersion curves produced by the Zernike NNP was distorted and involved a great deal of imaginary frequencies, but the correct amplitude was reached.The Gaussian NNPs trained in this work turned out to be faster and better in almost all regards compared to the Zernike alternative. The only time Zernike outperformed Gaussian descriptors were in the total energy reached in a GO simulation applying the NNPs from the study. Compared to DFT results the Zernike error was 0.26 eV (0.05%) and the Gaussian error was 0.855 eV (0.17%). MD simulations where the NNPs was used worked well for the Gaussian variant but not for the Zernike.With the AS up and running (at least for the Gaussian NNP) the following step is either to improve the performance on diamond structures. Or to include more carbon materials in the studies such as CNT and fullerenes.

  • 25.
    Marinakis, Yannis
    et al.
    Technical University of Crete, School of Production Engineering and Management, Chania, Greece.
    Marinakis, Magdalene
    Technical University of Crete, School of Production Engineering and Management, Chania, Greece.
    Migdalas, Athanasios
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering. Aristotle University of Thessaloniki, Department of Civil Engineering, Thessaloniki, Central Macedonia, Greece.
    Variants and Formulations of the Vehicle Routing Problem2018In: Open Problems in Optimization and Data Analysis / [ed] Panos M. Pardalos, Athanasios Migdalas, Springer Nature , 2018, p. 91-127Chapter in book (Refereed)
    Abstract [en]

    The vehicle routing problem is one of the most important problems in the field of supply chain management, of logistics, of combinatorial optimization, and, in general, of operational research. The interest in this problem has been recently increased both from theoretical and practical aspects. In this chapter, a number of the most important variants of the vehicle routing problem are presented. In some of them, the basic formulation of the problem is, also, given.

  • 26.
    Michel, Hannes
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Visualizing audit log events at the Swedish Police Authority to facilitate its use in the judicial system2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Within the Swedish Police Authority, physical users’ actions within all systems that manage sensitive information, are registered and sent to an audit log. The audit log contains log entries that consist of information regarding the events that occur by the performing user. This means that the audit log continuously manages massive amounts of data which is collected, processed and stored. For the police authority, the audit log may be useful for proving a digital trail of something that has occurred.

    An audit log is based upon the collected data from a security log. Security logs can collect datafrom most of the available systems and applications. It provides the availability for the organizationto implement network surveillance over the digital assets where logs are collected in real-time whichenables the possibility to detect any intrusion over the network. Furthermore, additional assets thatlog events are generated from are security software, firewalls, operating systems, workstations,networking equipment, and applications.

    The actors in a court of law usually don’t possess the technical knowledge required to interpret alog events since they can contain variable names, unparsed data or undefined values. Thisemphasizes the need for a user-friendly artifact of the audit log events that facilitates its use.

    Researching a way of displaying the current data format and displaying it in an improvedpresentable manner would be beneficial as an academic research by producing a generalizablemodel. In addition, it would prove useful for the internal investigations of the police authority sinceit was formed by their needs.

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  • 27.
    Michel, Hannes
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Christensson, Emil
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Framework For Enabling Structured Communication of Security Vulnerabilities in the Production Domain in Industry 4.02021Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    As industries are increasingly adapting to new technological trends for data collection and production efficiency, they are fulfilling the description of being part of the industry 4.0 (I4.0) paradigm. This swift development has led to unforeseen consequences concerning managerial and strategic aspects of security. In addition, threats and sophisticated attacks have increased, emphasizing a greater demand for information security management in the industrial setting.

    For smaller industrial manufacturers, information security management is not always available due the cost of resources, placing them in a challenging position. In addition, I4.0 introduces the area of OT/IT (Operational Technology and Information Technology) convergence, which is often heavily complex, creating the need for cross-competence. Furthermore, consequences from cyber attacks in the production domain can be catastrophic as they may endanger the safety and health of personnel. Thus, smaller manufacturing industries need to utilize existing resources to enable the prerequisites of managing security issues that may come with I4.0. Structuring and effectivizing the communication of security issues is needed to ensure that suitable competence can address security issues in a timely manner. The aspects of communication and competence are not addressed by current security standards and frameworks in the industrial context, nor are they equally applicable for smaller industrial organizations. 

    This study aims to contribute to the research field of information security in I4.0 by investigating how security vulnerabilities should be communicated at a smaller manufacturing industry that does not have an information security management system. The framework is based on a traditional incident response information flow and was designed at a Swedish manufacturing industry through the narrative of OT or production personnel. 

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    Framework for Enabling Structured Communication of Security Vulnerabilities in the Production Domain in Industry 4.0 - Hannes and Emil
  • 28.
    Mitra, Karan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Åhlund, Christer
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Ranjan, Rajiv
    Newcastle University.
    ALPINE: A Bayesian System For Cloud Performance Diagnosis And Prediction2017In: 2017 IEEE International Conference on Services Computing (SCC), Piscataway, NJ: IEEE, 2017, p. 281-288, article id 8034996Conference paper (Refereed)
    Abstract [en]

    Cloud performance diagnosis and prediction is a challenging problem due to the stochastic nature of the cloud systems. Cloud performance is affected by a large set of factors such as virtual machine types, regions, workloads, wide area network delay and bandwidth. Therefore, necessitating the determination of complex relationships between these factors. The current research in this area does not address the challenge of modeling the uncertain and complex relationships between these factors. Further, the challenge of cloud performance prediction under uncertainty has not garnered sufficient attention. This paper proposes, develops and validates ALPINE, a Bayesian system for cloud performance diagnosis and prediction. ALPINE incorporates Bayesian networks to model uncertain and complex relationships between several factors mentioned above. It handles missing, scarce and sparse data to diagnose and predict stochastic cloud performance efficiently. We validate our proposed system using extensive real data and show that it predicts cloud performance with high accuracy of 91.93%.

  • 29.
    Nikolakopoulos, George
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Autonomy as an enabler for the Next Generation of Space Robotics Exploration Missions2022In: 2022 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC) / [ed] Luís Louro, Pedro Fonseca, Pedro Neto, Rodrigo Ventura, IEEE, 2022, p. 1-1Conference paper (Refereed)
  • 30.
    Nilsson, Jacob
    Luleå University of Technology, Department of Engineering Sciences and Mathematics.
    Improving the Security of the Android Pattern Lock using Biometrics and Machine Learning2017Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the increased use of Android smartphones, the Android Pattern Lock graphical password has become commonplace. The Android Pattern Lock is advantageous in that it is easier to remember and is more complex than a five digit numeric code. However, it is susceptible to a number of attacks, both direct and indirect. This fact shows that the Android Pattern Lock by itself is not enough to protect personal devices. Other means of protection are needed as well.

    In this thesis I have investigated five methods for the analysis of biometric data as an unnoticable second verification step of the Android Pattern Lock. The methods investigated are the euclidean barycentric anomaly detector, the dynamic time warping barycentric anomaly detector, a one-class support vector machine, the local outlier factor anomaly detector and a normal distribution based anomaly detector. The models were trained using an online training strategy to enable adaptation to changes in the user input behaviour. The model hyperparameters were fitted using a data set with 85 users. The models are then tested with other data sets to illustrate how different phone models and patterns affect the results.       

    The euclidean barycentric anomaly detector and dynamic time warping (DTW) barycentric anomaly detector have a sub 10 \% equal error rate in both mean and median, while the other three methods have an equal error rate between 15 \% and 20 \% in mean and median. The higher performance of the euclidean and DTW barycentric anomaly detector is likely because they account for the time series nature of the data, while the other methods do not. Each user in the data set have provided each pattern at most 50 times, meaning that the long-term effects of user adaptation could not be studied.

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  • 31.
    Nilsson, Jacob
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Sandin, Fredrik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Delsing, Jerker
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Interoperability automation considered as machine learning tasks2019Conference paper (Other academic)
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  • 32.
    Pardalos, Panos
    et al.
    Industrial and Systems, Engineering Department, University of Florida, Center For Applied Optimization, Gainesville, USA.
    Migdalas, AthanasiosLuleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    Open Problems in Optimization and Data Analysis2018Collection (editor) (Refereed)
    Abstract [en]

    Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book.  Each contribution provides the fundamentals  needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline.

  • 33.
    Parnes, Peter
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Integrerad AI i undervisningen: Ett experimentellt steg mot dynamiskt och studentcentrerat lärande2024Conference paper (Refereed)
    Abstract [sv]

    Stora språkmodeller som GPT och Llama 2 samt tjänster som ChatGPT och KhanMigo visar på möjligheterna att föra samtal med en AI i ett lärandesyfte. Tillgången till AI-tjänster påverkar hur undervisning bör utformas och kan potentiellt leda till stora positiva effekter på studenternas lärande (Parnes 2023). AI-modeller samt deras tillhörande tjänster ger oss inte bara möjligheten att få svar på frågor utan de kan också hjälpa studenter genom sokratiskt lärande där AI-tjänsten ställer frågor till studenten i stället för att ge svaret direkt vilket hjälper studenten att komma fram till svaret själv.

    Här presenteras ett experimentellt högskolepedagogiskt utvecklingsarbete runt skapandet av AI-assistenter för att stötta studenter i en individanpassad och sokratisk undervisningsmiljö. Målet är att ge studenten tillgång till specifikt utbildningsmaterial där möjligheten undersöks till hur en egen utbildningsplan som utvecklas kontinuerligt kan skapas. Undervisningen anpassas till studentens eget lärande och tidigare prestationer vävs in samtidigt som systemet ger återkoppling till den lärande i realtid med målet att göra studenten mer aktiv i sitt eget lärande (Felder & Brent, 2009). Med hjälp av AI kan kortare föreläsningar skapas automatiskt utifrån lärarens beskrivningar för varje student där både lärarens röst och fysiska gestalt återskapas digitalt. AI kan också hjälpa till i bedömningen och ge snabb och kontinuerlig återkoppling till studenten vilket är positivt för lärandet (Wisniewski et al. 2020). 

    Samtidigt är interaktion och diskussion viktigt för lärandet och genom nyttjandet av AI-verktyg kan läraren få mer tid för de djupare diskussionerna. Frågan är om det kommer att leda till att studenterna lär sig effektivare, mer långsiktigt och om det ökar genomströmningen. I (Klingberg, 2023) föreslås att genom användning av AI-verktyg så kan studietakten ökas och att studietiden, i alla fall i grundskolan minskas med flera år. 

    AI har stor potential att förändra högre utbildning för alla inblandade inklusive studenter, lärare och administrativ personal. En av många utmaningar är den historiskt långsamma förändringen av högre utbildning. I slutändan handlar det om hur vi kan hjälpa våra studenter att lära sig mer och vad vi ska undervisa.

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  • 34.
    Parnes, Peter
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hedenström, Agneta
    Luleå University of Technology, Professional Support.
    Breddad rekrytering till Datateknik och relaterade IT-utbildningar genom #include@LTU och långsiktig rekrytering genom Makerspacerörelsen för ökad jämställdhet2023Conference paper (Refereed)
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  • 35.
    Parnes, Peter
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hedenström, Agneta
    Luleå University of Technology, University Pedagogy Centre.
    Creating interest for STEM through Computer Game Making in an Informal Makerspace Learning Environment: Luleå Game Create2021In: Abstracts 7th International Designs for Learning conference: Remediation of Learning, 2021, p. 49-50Conference paper (Refereed)
    Abstract [en]

    This abstract presents the results from an informal learning process called Luleå Game Create where children, ages 7-15 and accompanying adults got a gentle introduction to computer game creation in a Makerspace [1] setting at Luleå Makerspace where special focus is given to gender equality [2].

    Luleå Makerspace was founded in 2013 with the goal to provide an open learning environment [3] for people of any gender and background to realize their ideas, i.e. go from idea to prototype using modern tools and learn from each other. The Makerspace provides a creative environment where learning is done through either unstructured personal interactions or via organized workshops [4].

    Luleå Game Create

    Luleå Game Create is a series of informal workshops run during 2019-2020 where the participants learned how to create computer games. The format is based on that a workshop leader shows how to create different types of games and the participants get to make the games their own via various choices. The technical platform used is Unity, a professional game development engine [5].

    Material for each workshop is designed with two parts; 1: pre-made digital libraries to help game creation, and 2: detailed instructions on how to create the game and highlights different features. The instructions are shared openly and can be used by the participants after the workshop [6].

    The length of each workshop is 2.5 - 3 hours and the participants can either loan pre-setup computers at the makerspace or bring their own devices which they have to pre-configure at home. During the workshop much focus is placed on that everybody can follow along and participants are encouraged to help each other. Some of the children participate on their own and some together with an accompanying adult. Each workshop has between 10 and 15 participants and the workshops do not build on each other even though they might be divided up over two sessions.

    Focus is placed on gender equality with the long-term goal of raising interest for studying STEM and Computer Science subjects among young girls [7]. All workshops where open to both genders except one where together with the company Star Stable, a horse game was created.

    Discussion and Conclusions

    Luleå Game Create has run during 2019 and 2020 and so far about 75 participants attended the workshops. The feedback has been very positive with an overall grade of 4.5 out of 5 and 9 out of 10 say that they have gotten an increased interest in creating computer games and want to learn more.

    Requests for future topics include various details related to creating games but also other maker skills such as modelling for physical fabrication using 3D-printing and laser cutting.

    For the non-girl specific workshops, the gender balance is about equal between the children but surprisingly biased towards women among the adults (i.e. mothers and relatives) which has led to that a specific workshop for adult women is being planned. This is very positive as adult role models are important.

    During the pandemic the series moved online using Zoom instead but unfortunately with less interest from the earlier participants.

  • 36.
    Pilipiec, Patrick
    et al.
    Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden; School of Business and Economics, Maastricht University, Maastricht, The Netherlands.
    Samsten, Isak
    Department of Computer and Systems Sciences, Stockholm University, Kista, Sweden.
    Bota, András
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Surveillance of communicable diseases using social media: A systematic review2023In: PLOS ONE, E-ISSN 1932-6203, Vol. 18, no 2, article id e0282101Article, review/survey (Refereed)
    Abstract [en]

    Background

    Communicable diseases pose a severe threat to public health and economic growth. The traditional methods that are used for public health surveillance, however, involve many drawbacks, such as being labor intensive to operate and resulting in a lag between data collection and reporting. To effectively address the limitations of these traditional methods and to mitigate the adverse effects of these diseases, a proactive and real-time public health surveillance system is needed. Previous studies have indicated the usefulness of performing text mining on social media.

    Objective

    To conduct a systematic review of the literature that used textual content published to social media for the purpose of the surveillance and prediction of communicable diseases.MethodologyBroad search queries were formulated and performed in four databases. Both journal articles and conference materials were included. The quality of the studies, operationalized as reliability and validity, was assessed. This qualitative systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

    Results

    Twenty-three publications were included in this systematic review. All studies reported positive results for using textual social media content to surveille communicable diseases. Most studies used Twitter as a source for these data. Influenza was studied most frequently, while other communicable diseases received far less attention. Journal articles had a higher quality (reliability and validity) than conference papers. However, studies often failed to provide important information about procedures and implementation.

    Conclusion

    Text mining of health-related content published on social media can serve as a novel and powerful tool for the automated, real-time, and remote monitoring of public health and for the surveillance and prediction of communicable diseases in particular. This tool can address limitations related to traditional surveillance methods, and it has the potential to supplement traditional methods for public health surveillance.

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  • 37.
    Porras, Jari
    et al.
    Lappeenranta University of Technology, Lappeenranta, Finland.
    Rondeau, Eric
    University of Lorraine, Nancy, France.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Silva, Victoria Maria Palacin
    Lappeenranta University of Technology, Lappeenranta, Finland.
    Penzenstadler, Birgit
    California State University Long Beach, Long Beach, USA.
    Experiences from five years of educating sustainability to computer science students2019In: Engineering Education for Sustainability / [ed] Davim, João Paulo, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1-34Chapter in book (Refereed)
  • 38.
    Raghavendran, Krishnaraj
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Analysis Of Fastlane For Digitalization Through Low-Code ML Platforms2022Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Even a professional photographer sometimes uses automatic default settings that come up with the camera to take a photo. One can debate the quality of outcome from manual vs automatic mode. Until and unless we have a professional level of competence in taking a photo, updating our skills/knowledge as per the latest market trends and having enough time to try out different settings manually, it is worthwhile to use Auto-mode. As camera manufacturers, after several iterations of testing, comes up with the list of ideal parameter values, which is embedded as a factory default setting when we choose auto-mode. For non-professional photographers or amateurs recommend using the auto-mode that comes with the camera for not missing the moment. Similarly, in the context of developing machine learning models, until and unless we have the required data-engineering and ML development competence, time to train and test different ML models and tune different hyper parameter settings, it is worth to try out to Automatic Machine learning feature provided out-of-shelf by all the Cloud-based and Cloud-agnostic ML platforms. This thesis deep dives into evaluating possibility of generating automatic machine learning models with no-code/low-code experience provided by GCP, AWS, Azure and Databricks. We have made a comparison between different ML platforms on generating automatic ML model and presenting the results. It also covers the lessons learnt by developing automatic ML models from a sample dataset across all four ML platforms. Later, we have outlined machine learning subject matter expert’s viewpoints about using Automatic Machine learning models. From this research, we found automatic machine learning can come handy for many off-the-shelf analytical use-cases, this can be highly beneficial especially for time-constrained projects, when resource competence or staffing is a bottleneck and even when competent data scientists want a second-opinion or compare AutoML results with the custom ML model built. 

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  • 39.
    Raihan, S. M. Shafkat
    et al.
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh.
    Ahmed, Mumtahina
    Port City International University, Chittagong, Bangladesh.
    Sharma, Angel
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, 4331, Bangladesh.
    Islam, Raihan Ul
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A Belief Rule Based Expert System to Diagnose Alzheimer’s Disease Using Whole Blood Gene Expression Data2022In: Brain Informatics: 15th International Conference, BI 2022, Padua, Italy, July 15–17, 2022, Proceedings / [ed] Mufti Mahmud, Jing He, Stefano Vassanelli, André van Zundert, Ning Zhong, Springer, 2022, p. 301-315Conference paper (Refereed)
    Abstract [en]

    Alzheimer’s disease (AD) is a degenerative neurological disease that is the most common cause of dementia. It is also the fifth-greatest reason for death in adults aged 65 and over. However, there is no accurate way of diagnosing neurological Alzheimer’s disorders in medical research. Blood gene expression analysis offers a realistic option for identifying those at risk of AD. Blood gene expression patterns have previously proved beneficial in diagnosing several brain disorders, despite the blood-brain barrier’s restricted permeability. The most extensively used statistical machine learning and deep learning algorithms are data-driven and do not address data uncertainty. Belief Rule-Based Expert System (BRBES) is an approach that can identify various forms of uncertainty in data and reason using evidential reasoning. No previous research studies have examined BRBES’ performance in diagnosing AD. As a result, this study aims to identify how effective BRBES is at diagnosing Alzheimer’s disease from blood gene expression data. We used a gradient-free technique to optimize the BRBES because prior research had shown the limits of gradient-based optimization. We have also attempted to address the class imbalance problem using BRBES’ consequent utility parameters. Finally, after 5-fold cross-validation, we compared our model to three classic ML models, finding that our model had a greater specificity than the other three models across all folds. The average specificity of our models for all folds was 32%

  • 40.
    Shahzad, Muhammad Faisal
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    The Privacy And Security Challenges Of Crowdsourcing Activities A Systematic Literature Review2024Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
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  • 41.
    Sharma, Priyanka
    et al.
    Department of Electronics and Telecommunication, IET-Devi Ahilya University, Indore, India.
    Neema, Vaibhav
    Department of Electronics and Telecommunication, IET-Devi Ahilya University, Indore, India.
    Vishvakarma, Santosh Kumar
    Electrical Engineering Department, Indian Institute of Technology Indore, Indore, India.
    Chouhan, Shailesh Singh
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    MPEG/H256 video encoder with 6T/8T hybrid memory architecture for high quality output at lower supply2023In: Memories - Materials, Devices, Circuits and Systems, ISSN 2773-0646, Vol. 4, article id 100028Article in journal (Refereed)
    Abstract [en]

    The use of Multimedia video content is increased rapidly in the past decade, and most multimedia video content is used by mobile phone users. Multimedia video processing consumes significant power during video compression, and thus low power multimedia video compression is essential for battery operated devices. Moving Picture Experts Group (MPEG) Video encoding is giving a higher compression rate and low bandwidth requirement. Conventional MPEG Video encoding architecture uses the conventional 6T memory cells to store video frames for further compression processing. The failure probability of 6T cells is significantly large (0.0988 at 600 mV supply voltage), leading to a decrease in the output quality of the encoded video. From the hybrid memory matrix formulation, it is calculated that storing higher-order MSB bits in highly stable memory cells will provide high-quality video encoding processing as compared to the conventional technique because the human eye is more susceptible to higher-order luminance bits. Hence, in this research work instant of using conventional 6T memory cells during video encoding processing, a unique Hybrid 6T/8T memory architecture is proposed, where the 8-bit Luminance pixels are stored favourably in consonance with their effect on the output quality. The higher order luminance bits (MSB’s) require high stability and thus these bits are stored in the 8T bit cells and the remaining bits (LSB’s) are stored in the conventional 6T bit cells for high-quality video encoding processing. This research article also proposes a separate memory peripheral circuitry for hybrid memory architecture for video encoding techniques. In addition, this article proposes a unique architecture for parallel video processing with the use of a hybrid pixel memory array. The failure probability of 6T and 8T at the worst failure corner (FS corner for read and SF corner for write) is simulated for 30000 Monte-Carlo simulations points at 45 nm CMOS technology node using CADENCE EDA tool. For the simulation work here, a standard Common Intermediate Format/Quarter Common Intermediate Format (CIF/QCIF) Coastguard video sample is used and for output quality here average PSNR method is used and simulation work is performed using the MATLAB tool.

    The worst PSNR for conventional 6T memory array and Hybrid memory array at 600 mV supply voltage shows improvement in worst minimum PSNR as 6.43 dB is calculated. 30% less power consumption to conventional memory architecture.

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  • 42.
    Shi, Junchuan
    et al.
    Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA.
    Peng, Dikang
    School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
    Peng, Zhongxiao
    School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
    Zhang, Ziyang
    Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA.
    Goebel, Kai
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics. Palo Alto Research Center, Palo Alto, CA 94034, USA.
    Wu, Dazhong
    Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA.
    Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks2022In: Mechanical systems and signal processing, ISSN 0888-3270, E-ISSN 1096-1216, Vol. 162, article id 107996Article in journal (Refereed)
    Abstract [en]

    Gearbox fault diagnosis is expected to significantly improve the reliability, safety and efficiency of power transmission systems. However, planetary gearbox fault diagnosis remains a challenge due to complex responses caused by multiple planetary gears. Model-based gearbox fault diagnosis techniques extract hand-crafted features from sensor data based on underlying physics and statistical analysis, which are not effective in extracting spatial and temporal features automatically. While deep learning methods such as convolutional neural network (CNN) enable automatic feature extraction from multiple sensor sources, they are not capable of extracting spatial and temporal features simultaneously without losing critical feature information. To address this issue, we introduce a novel deep neural network based on bidirectional-convolutional long short-term memory (BiConvLSTM) networks to determine the type, location, and direction of planetary gearbox faults by extracting spatial and temporal features from both vibration and rotational speed measurements automatically and simultaneously. In particular, a CNN determines spatial correlations between two measurements within one time step automatically by combining signals collected from three accelerometers and one tachometer. Long short-term memory (LSTM) networks identify temporal dependencies between two adjacent time steps. By replacing input-to-state and state-to-state operations in the LSTM cell with convolutional operations, the BiConvLSTM can learn spatial correlations and temporal dependencies without losing critical features. Experimental results have shown that the BiConvLSTM network can detect the type, location, and direction of gearbox faults with higher accuracy than conventional deep learning approaches such as CNN, LSTM, and CNN-LSTM.

  • 43.
    Synnes, Kåre
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Artopoulos, Georgios
    The Cyprus Institute, Nicosia, Cyprus.
    Smaniotto Costa, Carlos
    Universidade Lusófona, Lisbon, Portugal.
    Menezes, Marluci
    National Laboratory for Civil Engineering – LNEC, Lisbon, Portugal.
    Redaelli, Gaia
    Politecnico di Milano, Milan, Italy.
    CyberParks Songs and Stories: Enriching Public Spaces with Localized Culture Heritage Material such as Digitized Songs and Stories2019In: CyberParks - The Interface Between People, Places and Technology: New Approaches and Perspectives / [ed] Carlos Smaniotto Costa, Springer, 2019, p. 224-237Chapter in book (Refereed)
    Abstract [en]

    This chapter offers theoretical considerations and reflections on technological solutions that contribute to digitally supported documentation, access and reuse of localised heritage content in public spaces. It addresses immaterial cultural heritage, including informal stories that could emerge and be communicated by drawing hyperlinks between digitised assets, such as songs, images, drawings, texts and more, and not yet documented metadata, as well as augmenting interaction opportunities with interactive elements that relate to multiple media stored in databases and archives across Europe. The aim is to enable cultural heritage to be experienced in novel ways, supported by the proliferation of smartphones and ubiquitous Internet access together with new technical means for user profiling, personalisation, localisation, contextawareness and gamification. The chapter considers cyberparks as digitally enhanced public spaces for accessing and analyzing European cultural heritage and for enriching the interpretation of the past, along with theoretical ramifications and technological limitations. It identifies the capacities of a proposed digital environment together with design guidelines for interaction with cultural heritage assets in public spaces. The chapter concludes with describing a taxonomy of digital content that can be used in order to enhance association and occupation conditions of public spaces, and with discussing technological challenges associated with enriching public spaces with localized cultural heritage material.

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  • 44.
    Tadaros, Marduch
    et al.
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering. Linköping University, Department of Science and Technology, Norrköping, Sweden.
    Kyriakakis, Nikolaos A.
    Technical University of Crete, School of Production Engineering and Management, University Campus, Chania, 73100, Greece.
    A Hybrid Clustered Ant Colony Optimization Approach for the Hierarchical Multi-Switch Multi-Echelon Vehicle Routing Problem with Service Times2024In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, no 190, article id 110040Article in journal (Refereed)
    Abstract [en]

    In this paper, the Hierarchical Multi Switch Multi Echelon Vehicle Routing Problem with Service Times (HMSME-VRP-ST) is presented. This novel problem considers distribution applications in which goods are delivered either directly from a central depot or through intermediate facilities called switch points. Commodities are loaded into interchangeable containers called swap bodies at the central depot, and can be transferred from one vehicle to another at the switch points. The goal is to minimize fixed and variable costs of the vehicle fleet and swap-bodies while serving a predetermined set of customers. The routes are constrained by time and swap bodies by loading capacity. A mathematical model of the HMSME-VRP-ST is presented, and a Hybrid Clustered Ant Colony Optimization (HCACO) algorithm is proposed to address the complexity of the problem. The approach utilizes the ant-based clustering algorithm, combining the density and connectivity properties of clustering for creating promising neighborhoods with the solution construction methodology and pheromone-based memory of the Ant Colony Optimization framework. Additionally, two local search schemes based on Variable Neighborhood Descent are incorporated to further improve the generated solutions. The behavior of each HCACO variant is analyzed, and their results are compared to a Greedy Randomized Adaptive Search Procedure metaheuristic in 36 newly generated benchmarks comprising of clustered, uniformly random, and mixed clustered-random instances.

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  • 45.
    Tadaros, Marduch
    et al.
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.
    Sifaleras, Angelo
    University of Macedonia.
    Migdalas, Athanasios
    Luleå University of Technology, Department of Social Sciences, Technology and Arts, Business Administration and Industrial Engineering.
    A Variable Neighborhood Search Approach for Solving a Real-World Hierarchical Multi-Echelon Vehicle Routing Problem Involving HCT VehiclesManuscript (preprint) (Other academic)
  • 46.
    Taxidou, Andromachi
    et al.
    Technical University of Crete, Chania, Greece.
    Karafyllidis, Ioannis
    Technical University of Crete, Chania, Greece.
    Marinaki, Magdalene
    Technical University of Crete, Chania, Greece.
    Marinakis, Yannis
    School of Production Engineering and Management, Technical University of Crete, Chania, Greece.
    Migdalas, Athanasios
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
    A Hybrid Firefly - VNS Algorithm for the Permutation Flowshop Scheduling Problem2019In: Variable Neighborhood Search: 6th International Conference, ICVNS 2018, Sithonia, Greece, October 4–7, 2018, Revised Selected Papers / [ed] Angelo Sifaleras, Prof. Said Salhi, Jack Brimberg, Springer, 2019, Vol. 11328, p. 274-286Conference paper (Refereed)
    Abstract [en]

    In this paper a Permutation Flowshop Scheduling Problem is solved using a hybridization of the Firefly algorithm with Variable Neighborhood Search algorithm. The Permutation Flowshop Scheduling Problem (PFSP) is one of the most computationally complex problems. It belongs to the class of combinatorial optimization problems characterized as NP-hard. In order to find high quality solutions in reasonable computational time, heuristic and metaheuristic algorithms have been used for solving the problem. The proposed method, Hybrid Firefly Variable Neighborhood Search algorithm, uses in the local search phase of the algorithm a number of local search algorithms, 1-0 relocate, 1-1 exchange and 2-opt. In order to test the effectiveness and efficiency of the proposed method we used a set of benchmark instances of different sizes from the literature.

  • 47.
    Tinkler, Elias
    et al.
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences.
    Westlin, Patrik
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences.
    Fostering Continuous Improvement and Innovation Through the Complaints Process: A case study at a global manufacturing company2020Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Quality and innovation are central elements in a successful business, where organizations are not

    solely looking to satisfy existing customers with high quality but to create novel solutions for future

    customers as well. As a result, addressing both concepts are vital for sustaining business longterm,

    which has led to a conflict regarding where companies should allocate their efforts. This study

    analyzed a global manufacturing company’s complaints management (CM) process, where quality and

    innovation were addressed with the study questions: How can the CM process be improved to reduce

    recurring complaints? and How can the CM process be improved to foster innovation?. To answer

    these, a qualitative approach was used in forms of unstructured and semi-structured interviews as

    well as quality management & control tools. The variables analyzed were partly constructed from the

    extensive literature review and partly from the employees involved with the CM process. The results

    showcased negligence towards the CM process, where process description and governance as well as

    knowledge management were lacking. Practical implications of the study indicates that if the CM

    process receives more focus in regards to the mentioned factors, the quality and its ability to foster

    innovation as well innovation will be improved. Theoretical implications of the study indicates a

    misalignment between the perception of the CM process and the actions of the company. Employees

    found it essential to the company’s strategy whereas the process, despite this received attention.

    These implications are limited to large manufacturing companies and in order to generalize the results,

    further research is required.

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  • 48.
    Tossavainen, Timo
    Luleå University of Technology, Department of Health, Learning and Technology, Education, Language, and Teaching.
    Matemaattisia keskusteluja tekoälyn kanssa – Onko ChatGPT:stä oppaaksi matematiikan oppimisessa?2023In: Tieteessä tapahtuu, ISSN 0781-7916, Vol. 41, no 2, p. 39-46Article in journal (Other academic)
    Abstract [fi]

    Tekoäly on tulossa osaksi oppimisen arkea. Kävin keskusteluja tekoälyn kanssa muun muassa eräiden matemaattisten lauseiden todistamisesta selvittääkseni, miten tekoälyä voisi käyttää matematiikan oppimisen tukena. Millaisia mahdollisuuksia tai uhkakuvia tekoälyn käyttöön liittyy?

  • 49.
    Tsanakas, Efstathios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
    Open Banking: Application difficulties & API security, under PSD2.2023Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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  • 50.
    Zorraquino, Alicia
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Digital Services and Systems.
    Social media and business: balancing risks and opportunities: A literature review2020Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
    Abstract [en]

    Purpose

    This thesis analyses what are the current information security risks and opportunities of social media in a business context based on publications from 2015 to 2020.

    Design/methodology/approach

    This papers follows a qualitative method, particularly a Systematic Literature Review guided by Okoli and and Schabram (2010), the concept-centric approach described by Webster and Watson (2002) and thematic analysis described by Braun and Clarke (2006).

    Findings

    Data leaks, non-compliance and reputational risks seem to be the most significant corporate social media risks. Adopting social media policies and providing employees social media security education, training and awareness are the most mentioned controls by the reviewed literature.

    Social media are more and more used as a threat intelligence source and for cyber security prediction and detection. Furthermore, social media may be used for InfoSec discussion, as a tool for Information Security Training and Awareness, for internal cyber threat sharing and for incident response handling.

    Originality/value

    This thesis provides an overall view of the risks, controls and opportunities that social media use implies for private organizations. Further research is needed that focuses primarily on the opportunities that social media offer to strengthen business Information Security.

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