In Sweden, the principle of “Digital First”, as proposed by the Agency for Digital Government, stipulates that contacts between citizens and public agencies ought to take place primarily via digital means. Following this principle, welfare provision has increasingly become an online practice, which does not only change the forms of welfare provision, but also, and significantly, demand specific resources and skills from the citizens. This development is important to highlight in relation to senior citizens (aged 65+), as research has made it clear how this is a heterogenic but also digitally vulnerable group. In a highly digitalized country as Sweden, about 10 percent of this group lack access of technical devices for using the internet and 15 percent state that they never use the Internet at all (Olsson & Viscovi, 2023). This paper focuses on Swedish digital user interfaces, with an aim of understanding how their semiotic composition in different ways demands responsibility of senior citizens. Theoretically, it centers on the concept of responsibilization (Koksvik, 2020) and on critical discussions on digital citizenship (Schou & Hjelholt, 2018). Empirically, the paper draws on a multimodal discourse analysis of Swedish digital welfare user interfaces, which explores how the interfaces, in their layout, use of different semiosis, language use and affordances, multimodally serve to shift responsibility from the welfare state to the citizen. The paper critically discusses the implication of this shift for senior citizens, as a digitally vulnerable group.

This report concerns the implementation of a simulation framework to evaluate an emerging peer-to-peer network topology scheme using 8-point hypercircles, entitled HyperCircle. This topology was proposed in order to alleviate some of the drawbacks of current P2P systems evolving in an uncontrolled manner, such as scalability issues, network overload and long search times. The framework is supposed to be used to evaluate the advantages of this new topology. The framework has been built on top of an existing simulator software solution, the selection of which was an important part of the development. Weighing different variables such as scalability and API usability, the selection fell on OverSim, an open-source discreet-event simulator based on OMNET++.

After formalizing the protocol for easier implementation, as well as extending it for better performance, implementation followed using C++ with OverSim’s API and simulation library. Implemented as a module (alongside other stock modules providing their own protocols such as Chord and Kademlia), it can be used in OverSim to simulate a user-defined network using one of the simulation routine applications provided (or using a custom application written by the user). For the purposes of this thesis, the standard application KBRTestApp was used; an application sending test messages between randomly selected nodes, while adding and removing nodes at specific time intervals. The adding and removing of nodes can be configured with probability parameters.

Tentative testing shows that this implementation of the HyperCircle protocol has a certain performance gain over the OverSim implementations of the Chord and Kademlia protocols, measurable in the time it takes a message to get from sender to recipient. Further testing is outside the scope of this thesis.

Serious games (SGs), are gaining prominence as a tool for early education at home as well as in school settings. Given the mixed effects of gamification on various aspects of users' lives, it is pertinent to study its broader effects on a child's pre-school and school years. Given the lack of consensus on a comprehensive measure that encapsulates these effects on an individual's routine functioning, the present study examined whether various engagement states in SGs use influence a relatively broader measure of users' functioning across significant life domains such as Quality of Life (QoL). It is argued that it would serve scholars, teachers, and parents better to understand the broader implications of SGs on children's overall QoL rather than isolated physiological and behavioral effects. Consequently, utilizing structural equation modeling, results from 335 parents of 2-10-year-olds in a developing country showed that cognitive and behavioral engagement in gamified applications appear to influence the child's QoL, but not affective engagement. Results are discussed in terms of the consequences of using game-based technology for a child's development, with far-reaching academic, personal, physical, and social implications not only for the school-going ages, but also for early teenage years. The results are promising in relation to QoL. The findings indicate the role modern technology plays in improving individuals' lives. The findings provide scholars, parents, and creators of SGs important information for their plan of action regarding children's exposure to SGs and making SGs a frequent aspect of the learning experience early in life.

Gamification is a modern concept that makes physical and digital activities engaging and enjoyable just like games. Game elements are added to mobile applications for user retention and engagement. One of the dark sides of gamification i.e., addiction is explored in this novel study in the context of mobile application design. It uses a mixed-method approach to lay the foundation of the relation between gamification and Smartphone Addiction, which is critically explained in a limited literature review using existing theories and studies on gamification. Interviews with behavioral experts confirm the psychological aspects of the research. The study also identifies game elements that contribute to smartphone addiction by a survey analysis of 269 participants. Results reveal Scrolling and Tapping as most addictive game elements. Some elements also show a statistically significant relationship with daily smartphone usage in hours. There are many effective applications of gamification, and in the context of mobile application design, it indeed helps to increase user engagement, however, there is an ethical need to reflect on what the exaggerated form of this engagement can lead to. As future research, a longitudinal study and experiments are suggested to find out this relationship with the use of empirical data.

Software-Defined Networking (SDN) är en framväxande teknik inom nätverksdomänen. Konceptet är baserat på att frikoppla och abstrahera kontrollplan och dataplan för de traditionella nätverksenheterna. Separationen underlättar nätverksdrift och ger många fördelar såsom, snabbare leverans, bättre segmentering, skalbarhet, förbättrade kvalitet på tjänsten och kvalitet på upplevelsen. Trots många fördelar har SDN också utmaningar.

Syftet med denna studie är att utforska de största utmaningarna med att implementera SDN-arkitektur i svenska organisationer. Fokus ligger på kunskapsklyftan som är en av de tidigare identifierade huvudutmaningarna, och hur svenska organisationer har hanterat dessa.

En kvalitativ metod har valts för att genomföra denna studie med hjälp av semistrukturerade intervjuer för att samla in data från sju olika organisationer, med hjälp av en blandning av målinriktat och snöbollsurval. En tematisk metod användes sedan för att generera kategorier och teman från den insamlade datan.

Resultaten överensstämmer med tidigare studier när det gäller tekniska, ekonomiska och säkerhetsmässiga utmaningar. De tekniska utmaningarna var dock färre jämfört med tidigare studier. Ett nytt arbetssätt presenterades som en ny utmaning vid implementering av en SDN-lösning. Dessutom, nämndes kunskapsklyftan som en central utmaning inom svenska organisationer vid implementering och drift av SDN. Slutligen presenterades tydliga rekommendationer för att övervinna utmaningen med kunskapsgapet, från att konsultera en tredje part, att ha en tydlig plan, använda en flerfasprocess för SDN-implementering samt att ha en digital utbildningsplattform tillgänglig för IT-teamet.

Konkurrensen är stor inom dagens affärsmarknad vilket medför att företag ständigt måste vara uppdaterade och förändra deras affärsverksamhet för att kunna överleva och vara konkurrenskraftiga på marknaden. Dagens marknadssituation erfodrar att företag snabbt kan reagera på marknadsförändringar och nya kundkrav vid allt kortare produktlivscyklar. För att företag skall kunna hantera denna nya marknadssituation måste företagen bli integrerade med varandra inom deras affärsområde. Denna integrering underlättar företagens förmåga att snabbt kunna anpassa sig till nya marknadssituationer och överleva på en snabbt föränderlig marknad. Ett utav de största grundläggande koncepten för denna integrering är flödeshantering (Supply Chain Management). Flödeshanteringen integrerar och koordinerar företagets processer både internt som externt. Informationsteknologi (IT) kan förbättra effektiviteten av flödeshanteringen. IT-lösningar skapar effektivare affärsprocesser och förbättrar integrationen med andra aktörer inom företagets försörjningskedja. Syftet med uppsatsen är att beskriva och förklara effekter för affärsverksamheten samt konsekvenser för dess affärsprocesser, vid en implementering av en realtidslogistiklösning. Uppsatsen syftar vidare till att identifiera framgångsfaktorer vid en sådan implementering. Uppsatsarbetet har genomförts genom en litteraturstudie där teori om flödeshantering, affärsförändring och implementationseffekter har behandlats. En fallstudie i uppsatsen har använts där tre aktörer har blivit intervjuade; en tillverkare (Volvo Powertrain), en underleverantör (Metallfabriken Ljunghäll) och en systemutvecklare (PipeChain). Analysen av litteraturstudien och den empiriska undersökningen har bidragit till en identifiering av huvudeffekter samt konsekvenser vid en implementering av en IT-logistiklösning. Några av dessa effekter är: lagerreducering, högre leveranssäkerhet, förbättrade relationer samt ökad flexibilitet. Exempel på konsekvenser dessa effekter har orsakat är: precisare planering och produktion, effektivare produktionsprocesser samt förbättrad leveransprocess. Vidare så har framgångsfaktorer för lyckad implementering identifierats så som ömsesidig tillit, förståelse för förändring samt utvärdering.

Access to the internet is more available than ever before for small children and adolescents, along with an increasing number of channels for using Generative Artificial Intelligence (GAI). For parents of children and teens, this is a new frontier with innovative tools, terminology, and effects that test the integrity of existing parental mediation strategies for modern media. The lack of research aimed at parental awareness of GAI or how this tech can influence children’s well-being led us to fill this current gap and gain valuable insights for future use.

The present study explores the current state of parental awareness regarding GAI and its effects on the well-being of children and what mediation strategies parents employ to mitigate these effects. By using the Parental Mediation Theory (PMT) as a theoretical framework, patterns gathered through conducting semi-structured interviews with parents (N=10) are identified with thematic analysis. Through these interviews, themes are uncovered that shed light on how parents perceive GAI in the context of the effects that such technology has on their children, as well as how it could impact their children’s well-being in the future.

The conclusion of this study reveals that while most parents know about GAI, many parents are not aware of the less-familiar effects of this technology being used for media manipulation, chatbot companionship or educational assignments that can have a potentially negative impact on the well-being of their children. Stemming from the PMT, a new parental mediation strategy emerged from an analysis of the collected data. This strategy is called ‘planned mediation’ and it serves to proactively protect children from GAI and its less-familiar effects, rather than responding reactively with the mediation strategies that currently exist.

We propose a higher order mining (HOM) approach for modelling, monitoring and analyzing district heating (DH) substations' operational behaviour and performance. HOM is concerned with mining over patterns rather than primary or raw data. The proposed approach uses a combination of different data analysis techniques such as sequential pattern mining, clustering analysis, consensus clustering and minimum spanning tree (MST). Initially, a substation's operational behaviour is modeled by extracting weekly patterns and performing clustering analysis. The substation's performance is monitored by assessing its modeled behaviour for every two consecutive weeks. In case some significant difference is observed, further analysis is performed by integrating the built models into a consensus clustering and applying an MST for identifying deviating behaviours. The results of the study show that our method is robust for detecting deviating and sub-optimal behaviours of DH substations. In addition, the proposed method can facilitate domain experts in the interpretation and understanding of the substations' behaviour and performance by providing different data analysis and visualization techniques. 

The growth of Internet video and over-the-top transmission techniqueshas enabled online video service providers to deliver highquality video content to viewers. To maintain and improve thequality of experience, video providers need to detect unexpectedissues that can highly affect the viewers’ experience. This requiresanalyzing massive amounts of video session data in order to findunexpected sequences of events. In this paper we combine sequentialpattern mining and clustering to discover such event sequences.The proposed approach applies sequential pattern mining to findfrequent patterns by considering contextual and collective outliers.In order to distinguish between the normal and abnormal behaviorof the system, we initially identify the most frequent patterns. Thena clustering algorithm is applied on the most frequent patterns.The generated clustering model together with Silhouette Index areused for further analysis of less frequent patterns and detectionof potential outliers. Our results show that the proposed approachcan detect outliers at the system level.

Outlier detection has been studied in many domains. Outliers arise due to different reasons such as mechanical issues, fraudulent behavior, and human error. In this paper, we propose an unsupervised approach for outlier detection in a sequence dataset. The proposed approach combines sequential pattern mining, cluster analysis, and a minimum spanning tree algorithm in order to identify clusters of outliers. Initially, the sequential pattern mining is used to extract frequent sequential patterns. Next, the extracted patterns are clustered into groups of similar patterns. Finally, the minimum spanning tree algorithm is used to find groups of outliers. The proposed approach has been evaluated on two different real datasets, i.e., smart meter data and video session data. The obtained results have shown that our approach can be applied to narrow down the space of events to a set of potential outliers and facilitate domain experts in further analysis and identification of system level issues.

This Master’s thesis is aimed at improving the management of artifacts in the context of a joint-project between Jönköping University with the SEMCO project and industrial partner, a company involved in developing software for safety components. Both have a slightly distinct interest but this project can serve both parties.

Nowadays feature modelling is efficient way for domain analysis. The purpose of this master thesis is to analysis existing four popular feature diagrams, to find out commonalities between each of them and conclude results to give suggestions of how to use existing notation systems efficiently and according to situations.

The developed software based on knowledge established from research analysis. Two notation systems which are suggested in research part of the thesis report are implemented in the developed software “NotationManager”. The development procedures are also described and developer choices are mentioned along with the comparisons according to the situations

Scope of the research part as well as development is discussed. Future work for developed solution is also suggested.

eHealth has been adopted by many countries across the globe in response to cut down cost and improve the quality of life. Sweden has been engaged in providing web-based health care services for its citizens for the past decade and county councils have the responsibility to develop them. The main aim of this thesis is to present answers to the following research questions:What strategies (formal and informal) guide the development of web-based health care services provided by the Swedish county councils?What barriers exist in relation to the development and usage of web-based health care services provided by the county councils from the viewpoint of their IT leaders?From the perspective of IT leaders in the county councils and in their capacity to develop, manage and monitor their organizations‘ website content, which web-based health care services are mostly accessed by users and what age group utilize the services most?The thesis is an exploratory research conducted through a survey based on a mail questionnaire that was posted to all 21 county councils in Sweden with 18 councils responding. The results show that all county councils have formally adopted the National eHealth Strategy to guide the development of web-based health care services and some have other informal strategies as well. Technological barriers, resistance to use the web-based services and changing business process to integrate ICTs have been identified by IT leaders as major challenges that impede the development of web-based health care services in Swedish county councils. Swedish citizens more frequently access prescription renewal and booking and cancellation of appointments than other available web-based health care services which depicts a trend towards the use of advanced interactive services than basic information seeking, and people in the ages of 46 to 55 have been identified as the frequent users of web-based health care services according to IT leaders from the county councils.

Telemedicine has been acknowledged to improve the quality of healthcare. However, many telemedicine services fail beyond the pilot phase. A literature review on business model components for telemedicine services was conducted. Based on specified inclusion criteria, 22 publications were included in the review. To facilitate the analysis of literature, a business model framework with value as its central focus was proposed. Improvement in quality, efficiency and accessibility of care were identified to be the outcomes of telemedicine, with patients and healthcare personnel being the main users of the services, which are delivered through home, institutional and community-based care. Patients, health providers, vendors, payers and government agencies are actors involved in the delivery of telemedicine services, which require investments in resources like videoconferencing technologies, home monitoring devices and other IT infrastructure. Subscriptions, reimbursements and pay-per-use revenue streams were identified as feasible for commercializing telemedicine services.

Information technology has been suggested to improve patient health outcomes and reduce the burden of care. In this study, we explored the effects of collaborative innovation between caregivers and patients on healthcare delivery as a consequence of the use of an IT-based device by patients with atrial fibrillation. Two cardiologists and two nurses were interviewed while questionnaires were mailed to 75 patients querying them about the use of a home-based ECG for remote monitoring. Findings indicated that the caregivers considered the device to enhance the quality of clinical decision-making. Patients found the device to be useful and felt more involved in their own care. However, the introduction of the device presented work overload for the caregivers. Thus, the facilitation of timely diagnostics and decision-making were not realized. IT is an enabler through which innovation in healthcare delivery can be realized, but it must be integrated into work practices to realize potential benefits.

Purpose – The aim of this study is to determine if adopting cloud-based knowledge management is a viable way forward for small enterprises and to investigate what are the main factors that might facilitate or inhibit these companies to adopt such solutions.Design/Methodology/Approach - In order to understand the main factors that could influence the adoption of a cloud-based knowledge management solution in small enterprises, I used a qualitative research approach, based on four semi-structured interviews with four small companies from Romania.Findings – The results of the study suggest that implementing knowledge management in the cloud is particularly beneficial for small enterprises, as a lower investment in IT infra-structure can create a competitive advantage and help them implement knowledge man-agement activities as a strategic resource. Moreover, the study suggests that relative ad-vantage, compatibility and technology readiness will influence companies in moving their knowledge to the cloud. Also, the study reveals that companies which did not adopt such a solution had already established systems for managing knowledge and failed to realize its benefits, it was not perceived as needed, they had a low level of awareness or cited security and uncertainty reasons.

The term “Internet of Things” (IoT) was first introduced by a technology pioneer Kevin Ashton in 1999.Although the term is relatively new, the idea of making networks and computers communicate in order totrack and manage devices has been around for many years. As of now IoT is a rising topic in technicalcommunity. Some specialists are anticipating that by 2025 there will be around 100 billion connected IoTdevices with a worldwide economic impact of more than $11 trillion. On the other hand, Internet of Thingsemerges significant challenges. Currently the organization around world use two main approaches whenentering the IoT market. First one is an open platform and is represented by interoperability andcollaboration with devices from different vendors. Second one is a closed platform, or a “walled garden”approach. A “walled garden” approach is characterized by building “fences” around the user. In other words,the service provider has control over applications, content and media and also restricts the non-approvedcontent to reach the customer. Therefore, the research set out to explore these approaches and show thebenefits and limits they can have on an organization. The research was conducted in collaboration with aSwedish manufacturer of outdoor power products called Husqvarna Group. In order to fully acknowledgethe organization’s approach, 4 interviews were conducted with managers, back end developers andconsultants hired by Husqvarna Group. From the findings, some things should be taken in consideration.First, IoT involves big data being collected, therefore security and privacy are crucial when developingdevices and systems. Second, it is essential for an organization to have the same views when taking a newdirection. Third, when discussing Internet of Things, it means that things connect, devices to sensors,sensor to gateways and gateways to system. And there shouldn’t be a delimitation from a vendor to another.Therefore, open platform approach is seen as the way to diversity and innovation.

This thesis represents the ontological model for the Time Aspects for a Healthcare Organization. It provides information about activities which take place at different interval of time at Ryhov Hospital. These activities are series of actions which may be happen in predefined sequence and at predefined times or may be happen at any time in a General ward or in Emergency ward of a Ryhov Hospital.

For achieving above mentioned objective, our supervisor conducts a workshop at the start of thesis. In this workshop, the domain experts explain the main idea of ward activities. From this workshop; the author got a lot of knowledge about activities and time aspects. After this, the author start literature review for achieving valuable knowledge about ward activities, time aspects and also methodology steps which are essentials for ontological model. After developing ontological model for Time Aspects, our supervisor also conducts a second workshop. In this workshop, the author presents the model for evaluation purpose.

The IT consultancy industry is characterized by knowledge intensive implementationprojects related to varying levels of standardized information system software. When faced with a large implementation project at a previously unknown customer various assessmentsis usually conducted to identify the level of fit between the software and organizationin order to plan and structure the implementation process. However, there are several aspects of the customer organization that potentially can affect the end result as well as the implementation process that is unrelated to the fit between the software and the implementation organization as well as the potency of the implementation method. By conducting measurements of these maturity factors within the customer organization the implementing procedure can be modified based on the customer maturity level in order to become more aligned with the capabilities present in the customer organization.

Research question: Which aspects need to be covered by a Customer Maturity Analysis Tool (CMAT) in order to evaluate the pre implementation maturity for potential customersof our case company and how should these aspects be organized and measured? The first task of the research process was to create an underlying model of maturity perspectives and aspects to structure the literature review as well as the empirical data collection. It was decided to adhere to a deductive approach where the theoretical model would be validated and if necessary modified in accordance to feedback from potential users of the CMAT within the case company. This procedure was repeated in the creation of measurements and maturity levels for the aspects to be used in the tool. The research process would therefore transition from a general model based on literature review, through a iterative feedback loop to a final model tailored to the specific requirementsof the case company. The final CMAT ended up containing four main perspectives of customer maturity; ITi nfrastructure, Culture, Process and Business Governance. These four perspectives were in turn divided into subgroups in order to be able to aggregate and compare differentaspects of the perspectives with each other.

Channel charting (CC) is an emerging machine learning method for learning a lower-dimensional representation of channel state information (CSI) in multi-antenna systems while simultaneously preserving spatial relations between CSI samples. The driving objective of CC is to learn these representations or channel charts in a fully unsupervised manner, i.e., without the need for having access to explicit geographical information. Based on recent findings in deep manifold learning, this paper addresses the problem of CC via the "not-too-deep" (N2D) approach for deep manifold learning. According to the proposed approach, an embedding of the global channel chart is first learned using a deep neural network (DNN)-based autoencoder (AE), and this embedding is subsequently searched for the underlying manifold using shallow clustering methods. In this way we are able to counter the problem of collapsing extremities - a well known deficiency of channel charting methods, which in previous research efforts could only be mitigated by introducing side-information in form of distance constraints. To further exploit the ever-increasing spatio-temporal CSI resolution in modern multi-antenna systems, we propose to augment the employed AE with convolutional neural network (CNN) input layers. The resulting convolutional autoencoder (CAE) architecture is able to automatically extract sparsely distributed spatio-temporal features from beamspace domain CSI, yielding a reduced computational complexity of the resulting model.

 Modern autonomous systems should be able to interact with their surroundings in a flexible yet safe manner. To guarantee this behavior, such systems must learn how to approach unseen entities in their environment through the inference of relationships between actions and objects, called affordances. This research project introduces a neuro-symbolic AI system capable of inferring affordances using attribute detection and knowledge representation as its core principles. The attribute detection module employs a visuo-lingual image captioning model to extract the key object attributes of a scene, while the cognitive knowledge module infers the affordances of those attributes using conditional probability. The practical capabilities of the neuro-symbolic AI system are assessed by implementing a simulated robot system that interacts within the problem space of jars and bottles. The neuro-symbolic AI system is evaluated through its caption-inferring capabilities using image captioning and machine translation metrics. The scores registered in the evaluation show a successful attribute captioning rate of more than 71%. The robot simulation is evaluated within a Unity virtual environment by interacting with 50 jars and bottles, equally divided between lifting and twisting affordances. The robot system successfully interacts with all the objects in the scene due to the robustness of the architecture but fails in the inference process 24 out of the 50 iterations. Contrary to previous works approaching the problem as a classification task, this study shows that affordance inference can be successfully implemented using a cognitive visuo-lingual method. The study’s results justify further study into the use of neuro-symbolic AI approaches to affordance inference.

The success of revenue management models depends to a large extent on the quality of historical data used to forecast future bookings. Several theoretical models and best practices of handing historical data have been developed over the years, that all rely on assumptions about underlying distribution and seasonality in the historical data. In this paper, we describe a novel method that compares the fingerprints of the departure to optimise and selects historical departures without making assumptions on data distribution or seasonality. By evaluating the method at the departure level and using the Nemenyi rank test, we show the method’s application in the ferry transportation business and discuss its advantages.

The choice of how much money and resources to spend to understand certain problems is of high interest in many areas. This work illustrates how computational models can be more tightly coupled with experiments to generate decision data at lower cost without reducing the quality of the decision. Several different strategies are explored to illustrate the trade off between lowering costs and quality in decisions.

AUC is used as a performance metric and the number of objects that can be learnt from is constrained. Some of the strategies described reach AUC values over 0.9 and outperforms strategies that are more random. The strategies that use conformal predictor p-values show varying results, although some are top performing.

The application studied is taken from the drug discovery process. In the early stages of this process compounds, that potentially could become marketed drugs, are being routinely tested in experimental assays to understand the distribution and interactions in humans.

In this short paper we describe the implementation of an IoT test-bed in an elementary school. We argue that by adding additional IoT senors to an existing IoT system it is possible to evolve an indoor climate control system into a indoor milieu control system aimed at improving the health and well-being for both pupils and staff who spend their days working in the school environment. Lastly, we call for multidisciplinary action as the domain IoT for health and well-being spans across several different knowledge domains.

The deployment of reconfigurable intelligent surfaces (RISs) in a communication system provides control over the propagation environment, which facilitates the augmentation of a multitude of communication objectives. As these performance gains are highly dependent on the applied phase shifts at the RIS, accurate channel state information at the transceivers is imperative. However, not only do RISs traditionally lack signal processing capabilities, but their end-to-end channels also consist of multiple components. Hence, conventional channel estimation (CE) algorithms become incompatible with RIS-aided communication systems as they fail to provide the necessary information about the channel components, which are essential for a beneficial RIS configuration. To enable the full potential of RISs, we propose to use tensor-decomposition-based CE, which facilitates smart configuration of the RIS by providing the required channel components. We use canonical polyadic (CP) decomposition, that exploits a structured time domain pilot sequence. Compared to other state-of-the-art decomposition methods, the proposed Semi-Algebraic CP decomposition via Simultaneous Matrix Diagonalization (SECSI) algorithm is more time efficient as it does not require an iterative process. The benefits of SECSI for RIS-aided networks are validated with numerical results, which show the improved individual and end-to-end CE accuracy of SECSI.

Theft and Robbery pose serious threats to public safety and society's well-being. There are misconceptions and public believe already in place about the factors that affect these trends. The objective of this thesis is to understand the decline trends in Theft and Robbery  in Sweden between 2008-2022. What has caused the decline of this type of crime between these years? The other objective is to have fruitful recommendations to the authorities for preventing the number of these crimes altogether and to serve as an example for countries experiencing higher rates of theft and robbery. The data in the thesis was gathered from different sources, including public websites, published literature and research, and most importantly law enforcement authorities. Findings from this research confirmed a positive role of education and employment in reducing the crime rate in Sweden. I also found that the increase of youth is also reducing the crime rate whereas increase of immigrant rate increases the crime rate. As a result, the conclusion of this thesis will allow policymakers to understand the factors and provide strategies that affect the decline in the number of Theft and robbery in Sweden. 

Capturing client’s needs and expectations for a product or service is an important problem in software development. Software requirements are normally captured in natural language and mostly they are unstructured which makes it difficult to automate the process of going from software requirements to the executable code. A big hurdle in this process is the lack of consistency and standardization in software requirements representation. Thus, the aim of the thesis is to present a method for transforming natural language requirement text into ontology. It is easy to store and retrieve information from ontology as it is a semantic model, and it is also easy to infer new knowledge from it.

As it is clear from the aim of this work, the main component of our research was software requirements, so there was a need to investigate and decide the types of requirements to define the scope of this research. We selected INCOSE guidelines as a benchmark to scrutinize the properties which we desired in the Natural Language Requirements. These natural language requirements were used in the form of user stories as the input of the transformation process. We selected a combination of two methods for our research i.e. Literature Review and Design Science Research. The reason for selecting these methods was to obtain a good grip on existing work going on in this field and then to combine the knowledge to propose new rules for the requirements to ontology transformation. We studied different domains during literature review such as Requirements Engineering, Ontologies, Natural Language Processing, and Information Extraction. The gathered knowledge was then used to propose the rules and the flow of their implementation. This proposed system was named as “Reqtology”. Reqtology defines the process, from taking the requirements in form of user stories, to extracting the useful information based on the rules and then classifying that information so that it can be used to form ontologies. The workflow consists of a 6-step process which starts from input text in form of user stories and at the end provides us entities which can be used for ontologies formation.

Defective PV panels reduce the efficiency of the whole PV string, causing loss of investment by decreasing its efficiency and lifetime. In this study, firstly, an isolated convolution neural model (ICNM) was prepared from scratch to classify the infrared images of PV panels based on their health, i.e., healthy, hotspot, and faulty. The ICNM occupies the least memory, and it also has the simplest architecture, lowest execution time, and an accuracy of 96% compared to transfer learned pre-trained ShuffleNet, GoogleNet, and SqueezeNet models. Afterward, ICNM, based on its advantages, is reused through transfer learning to classify the defects of PV panels into five classes, i.e., bird drop, single, patchwork, horizontally aligned string, and block with 97.62% testing accuracy. This proposed approach can identify and classify the PV panels based on their health and defects faster with high accuracy and occupies the least amount of the system’s memory, resulting in savings in the PV investment.

This paper examined male engagement towards gender stereotypes online. We specifically sought to address how men engage with gender-stereotyped advertisements on Instagram, and which interactions they utilize to do so. We aimed to understand how men engage with gender stereotypes in Instagram advertisements by answering the following research question:

[RQ1] How do men engage with gender-stereotyped advertisements on Instagram?

Data were collected from 10 male participants through semi-structured interviews using photo elicitation. The data was further obtained through thematic analysis using the Theory of Planned Behaviour. The findings resulted in 26 codes and 6 themes. The results demonstrated that exposure to masculine content receives more attention and recognition than feminine, non-sexualized content. The findings argued that men are hesitant to engage with sexualized and provocative content due to societal norms and fear of being judged by others. In contradiction, men believe that other men are more likely to engage with sexualised, gender-stereotyped content that idealizes masculinity. The study identified the most common engagement interactions utilized when engaging with gender-stereotyped content: liking, visiting the account or website, and sharing content with a friend.

The findings supported previous research claims that accepting a feminine image puts men at risk of violating gender roles, resulting in men preserving a masculine persona by distancing themselves from this type of material (Elliot & Elliot, 2005). Additionally, we concluded that fear of judgement from peers and society results in social pressure to conform to masculine gender norms, which may influence men’s online behaviour.

The results may be delimited by social desirability and sampling bias due to the designated scope. Nevertheless, we have implemented measures to ensure the trustworthiness of this study.

Self-care is important for heart failure patients. However, what are the views of patients on their situation when it comes to realizing self-care? The aim of the paper is to investigate the self-care needs of HF patients, by understanding the issues they embrace in their self-care processes. In this paper we make a review of 17 interviews and make a classification of what the needs are for possible information technology support systems. Based on the analysis of these interviews, we identify the diversity of needs in support of activities related to different background conditions and the dynamics of change of learning and changes in the heart failure condition. The contribution of the paper is a framework for understanding the diversity of needs and the specific situations of this group of patients.

In this paper the nature of user involvement in a co-design process will be explored. The outlines of a research project aiming at developing support systems for self-care inpatients suffering from chronic heart failure will be presented. The project is planned to perform a co-design effort where users (patients and healthcare professionals) will be given the opportunity to influence the development of support systems. We will discuss a number of possibilities and challenges that lie in the design of this kind of project and also some findings from its early stages. This report presents the experiences of users’ input, which are discussed in the context of previous research on benefits of user contributions in systems development.

With many research available on IT governance, this research differs from most of them due to its delimitation. The focus of this research lies in the two domains of value creation and performance measurement. Furthermore, the area of research has been small and medium Enterprises located in the area of Småland, Sweden.

Brisebois, Boyd & Shadid (2001) gave us the following definition of IT governance: “How those persons entrusted with governance of an entity will consider IT in their supervision, monitoring, control, and direction of the entity. How IT is applied will have an immense impact on whether the entity will attain its vision, mission, or strategic goal.”

An objective of IT governance is to align the IT resources of an enterprise in a way that it fast-tracks the business priorities of the enterprise and assures that the investments in IT generates business value and that the IT is performing to its expectations.

The research questions and the outcome of this research paper sheds light on the challenges of both value creation and performance measurement within the SMEs, but it also showcases what the driving forces of IT value creation are and which benefits arise from measuring the IT performance within the SMEs.

Through semi-structured interviews with four SMEs, based in the region of Småland, numerous amounts of challenges and driving forces for IT value creation and challenges and benefits to measuring IT performance have been extracted.

Based on the extracted information from the interviews, an analysis and a conclusion have been formed by the authors. In the end, the authors provide their thoughts for suggestions for further work and how all of this contributes to the field of Informatics.

Over the decades, as organizations begin to move globally there has been a sporadic flow of information in their supply chain. Competition today is forcing companies to integrate tightly with their suppliers and customers, in order to reduce the time available to flex the supply chain (SC) (Koh S.C, Saad S, Arunachalam S, 2006). The integration of firms and departments and information is getting more and more complicated. Regardless of enterprise system solutions being introduced as “integrated suites” they have failed to accomplish application and supply chain integration (Themistocleous, M. Irani, Z. O‟Keefe, and R. 2001). Therefore, this thesis aims to explore, gain better understanding and to explain the balance that may occur between the challenges and benefits gained from integrating enterprise resource planning and supply chain management.Our topic of interest could be view from both developers and user perspective. Developer/consultant‟s perspective is based on the viewpoint of those involved in and responsible for developing enterprise solutions. User‟s perspective, this perspective gives insight to how the integration process is perceived by organisations actually using the solutions. We chose the User perspective because we consider the user to be the direct beneficiary of whatever outcome is gotten from both the business solutions and its integration.In order to achieve a purposeful thesis. We decided to use an interpretive perspective which focus on exploring and gaining insight into issues of integrating enterprise system solution. We used both the inductive and the deductive approaches in our research. This would be advantageous due to the nature of our research topic, as there is little existing knowledge about the integration of enterprise systems solution within supply chain and there are lots of literatures related to the enterprise system solutions (ERP and SCM) been observed. The inductive approach would guide us to choose one or a few specific interactions to explore in-depth, while the deductive approach would aid us when making an hypothesis, since we would be collecting ideas about previous research and theories in order to guide us and make comparison.Conclusively, we found that the balance between challenges and benefits of ERP and SCM are unequivocal, as the benefits surpass the challenges and the effect of challenges on organisation‟s benefit is that it prolongs the short term benefit.

This compilation thesis contributes to a deeper understanding of perceived safety in human-robot interaction (HRI) with a particular focus on social robots. The current understanding of safety in HRI is mostly limited to physical safety, whereas perceived safety has often been neglected and underestimated. However, safe HRI requires a conceptualization of safety that goes beyond physical safety covering also perceived safety of the users. Within this context, this thesis provides a comprehensive analysis of perceived safety in HRI with social robots, considering a diverse set of human-related and robot-related factors.

Two particular challenges for providing perceived safety in HRI are 1) understanding and evaluating human safety perception through direct and indirect measures, and 2) utilizing the measured level of perceived safety for adapting the robot behaviors. The primary contribution of this dissertation is in addressing the first challenge. The thesis investigates perceived safety in HRI by alternating between conducting user studies, literature review, and testing the findings from the literature within user studies.

In this thesis, six main factors influencing perceived safety in HRI are lifted: the context of robot use, the user’s comfort, experience and familiarity with robots, trust, sense of control over the interaction, and transparent and predictable robot behaviors. These factors could provide a common understanding of perceived safety and bridge the theoretical gap in the literature. Moreover, this thesis proposes an experimental paradigm to observe and quantify perceived safety using objective and subjective measures. This contributes to bridging the methodological gap in the literature.

The six factors are reviewed in HRI literature, and the robot features that affect these factors are organized in a taxonomy. Although this taxonomy focuses on social robots, the identified characteristics are relevant to other types of robots and autonomous systems. In addition to the taxonomy, the thesis provides a set of guidelines for providing perceived safety in social HRI. As a secondary contribution, the thesis presents an overview of reinforcement learning applications in social robotics as a suitable learning mechanism for adapting the robots’ behaviors to mitigate psychological harm.

Safety is a fundamental prerequisite that must be addressed before any interaction of robots with humans. Safety has been generally understood and studied as the physical safety of robots in human-robot interaction, whereas how humans perceive these robots has received less attention. Physical safety is a necessary condition for safe human-robot interaction. However, it is not a sufficient condition. A robot that is safe by hardware and software design can still be perceived as unsafe. This article focuses on perceived safety in human-robot interaction. We identified six factors that are closely related to perceived safety based on the literature and the insights obtained from our user studies. The identified factors are the context of robot use, comfort, experience and familiarity with robots, trust, the sense of control over the interaction, and transparent and predictable robot actions. We then made a literature review to identify the robot-related factors that influence perceived safety. Based the literature, we propose a taxonomy which includes human-related and robot-related factors. These factors can help researchers to quantify perceived safety of humans during their interactions with robots. The quantification of perceived safety can yield computational models that would allow mitigating psychological harm.

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency.

This paper examines whether social cues, such as facial expressions, can be used to adapt and tailor a robot-assisted training in order to maximize performance and comfort. Specifically, this paper serves as a basis in determining whether key facial signals, including emotions and facial actions, are common among participants during a physical and cognitive training scenario. In the experiment, participants performed basic arm exercises with a social robot as a guide. We extracted facial features from video recordings of participants and applied a recursive feature elimination algorithm to select a subset of discriminating facial features. These features are correlated with the performance of the user and the level of difficulty of the exercises. The long-term aim of this work, building upon the work presented here, is to develop an algorithm that can eventually be used in robot-assisted training to allow a robot to tailor a training program based on the physical capabilities as well as the social cues of the users.

This paper explores robot-assisted training in a cross-cultural context with older adults. We performed user studies with 28 older adults with two different assistive training robots: an adaptive robot, and a non-adaptive robot, in two countries (Sweden and Israel). In the adaptive robot group, the robot suggested playing music and decreased the number of repetitions based on the participant’s level of engagement. We analyzed the facial expressions of the participants in these two groups. Results revealed that older adults in the adaptive robot group showed more varying facial expressions. The adaptive robot created a distraction for the older adults since it talked more than the non-adaptive robot. This result suggests that a robot designed for older adults should utilize the right amount of communication capabilities. The Israeli participants expressed more positive attitudes towards robots and rated the perceived usefulness of the robot higher than the Swedish participants.

For many applications where interaction between robots and older people takes place, safety and security are key dimensions to consider. ‘Safety’ refers to a perceived threat of physical harm, whereas ‘security’ is a broad term which refers to many aspects related to health, well-being, and aging. This chapter presents a quantitative evaluation tool of the sense of safety and security for robots in elder care. By investigating the literature on measurement of safety and security in human–robot interaction, we propose new evaluation tools specially tailored to assess interaction between robots and older people.

Robot-assisted training, where social robots can be used as motivational coaches, provides an interesting application area. This paper examines how feedback given by a robot agent influences the various facets of participant experience in robot-assisted training. Specifically, we investigated the effects of feedback type on robot acceptance, sense of safety and security, attitude towards robots and task performance. In the experiment, 23 older participants performed basic arm exercises with a social robot as a guide and received feedback. Different feedback conditions were administered, such as flattering, positive and negative feedback. Our results suggest that the robot with flattering and positive feedback was appreciated by older people in general, even if the feedback did not necessarily correspond to objective measures such as performance. Participants in these groups felt better about the interaction and the robot.

Purpose: The main purpose of this study/thesis is to, through an interview with researchers in medical field in Jönköping,  provide an empirical analysis of the link or relationship between medical researcher and patient through social networking sites specifically for collaboration in order to improve relationships, dissemination of information and knowledge sharing.

Background: The importance of social networking websites as a means of interaction between groups of individuals cannot be underestimated. Their impact on daily life activities and activities cannot be underestimated. Because  millions of individuals are making use of Social Network Sites (SNSs) to build or reinforce relationships, connect, disseminate and share information as well as sharing of knowledge whether personal or non-personal experiences with people they already know offline or new people online. Therefore, the authors are interested basically in how social networking web sites are being utilized in terms of collaborations, information and knowledge sharing and particularly in what benefits and challenge are connected to improving inter-groups collaboration in research study between researchers and ordinary citizens.

Method: A review of literature gives us insight about the subject terms, critical and sensitive issues in regards to collaboration through social networking sites designed for research purpose. We apply in general networking theories such as social capital and two of its components couple with Putman´s theory of bonding and bridging social capital as a theoretical framework to synthesize the concept of  ties (strong or weak) . Our analysis based on the empirical data gathered through surveys, interviews and observation provide us with interesting preliminary results and with blueprints to guide the analysis of the thesis.

Conclusion: Social networking platforms are valuable and useful in our generation being part of daily life and activity to keep up with people within our networks. However, the authors discovered that the advantages of involving ordinary citizens to participate in improving researcher-patient collaboration through dynamic social networking actually outweigh the disadvantages despite all odds and sensitive issues such as trust, privacy issues and sceptics of some researchers. In others words, some of the researchers were enthusiastic to collaborate in terms of disseminating useful information and sharing valuable knowledge with ordinary citizens. Overall, the study revealed positive result that despite weak ties relationships, the willingness to collaborate is far more than the obstacles perceived in the course of establishing such collaboration.

Variability in complex systems offering rich set of features is a seriouschallenge to their users in term of flexibility with many possible variants fordifferent application contexts and maintainability. During the long period oftime, much effort has been made to deal with these issues. An effort in thisregard is developing and implementing different variability modelingtechniques.This thesis argues the explanation of three modeling techniques namedconfigurable components, feature models and function-means trees. The maincontribution to the research includes:• A comparison of above mentioned variability modeling techniques in asystematic way,• An attempt to find the integration possibilities of these modelingtechniques based on literature review, case studies, comparison,discussions, and brainstorming.The comparison is based on three case studies each of which is implemented inall above mentioned three modeling techniques and a set of generic aspects ofthese techniques which are further divided into characteristics. At the end, acomprehensive discussion on the comparison is presented and in final sectionsome integration possibility are proposed on the basis of case studies,characteristics, commonalities and experience gained through theimplementation of case studies and literature review.

People with disabilities constitute a big group of Internet users. Due to great advances in adaptive technology for people with disabilities more and more disabled will have access to Internet. For that reason it is extremely important for a web developer to be aware of different disabilities that complicate or prevent using Internet, different adaptive technologies that facilitate using Internet and different methods, both in design and programming, that make Internet accessible for people with disabilities.

In this report we have dealt with three problems:

• Which types of disabilities that complicate or prevent using Internet?

• Which types of adaptive technologies are available concerning using Internet?

• How can a web developer or programmer increase the accessibility to Internet for people with disabilities?To investigate how disabled people use adaptive technologies and which difficulties they experience when using Internet we have interviewed people with various types of disabilities.

The unprecedented pandemic of the infectious coronavirus disease (COVID-19) is still ongoing. Considering the limitations and restrictions imposed by COVID-19, we explored the role of technology and the extent of usage by end-users. In our online survey, we investigated users’ perspectives on their use of technologies in different contexts (e.g., work, entertainment), taking into consideration intrinsic factors such as health consciousness, perceived social isolation, and pandemic-related concerns. Results from 218 respondents show a significant increase in technology use in all investigated contexts after the pandemic occurred. Moreover, the results suggest that different factors may contribute to such increases, depending on the context. It appears that perceived social isolation, concerns about the pandemic, and tracking have the most prominent influence on different use of technology. Furthermore, open-ended responses include beneficial opportunities, concerns & consequences, and behavioral transformations & adaptations due to COVID-19. Our findings provide insights for designing and developing new technologies, especially for communication and entertainment, to support users’ needs during a pandemic.

Software patterns have been proven as a valuable way to storing a repeatable solution to a commonly occurring problem in software design. A pattern is not a finished design that can be directly formed into program code; instead it is a description how to solve a problem that may occur in many situations.

In the ontology community very little research have been made in producing high-level patterns where the solution shows how an architecture of an ontology based software might look like.

In this thesis the results of examining how high-level patterns of this type relates to other types of patterns are given and how these patterns would be described are formulated.

Semantic Web technologies are finally, after a few years of infancy, truly entering the business world to support the growing needs of computer aided information selection and processing. There are already quite well-defined development processes and methods in the software engineering field to handle the construction of large scale and complex enterprise systems, and to reuse knowledge in different software domains patterns are considered to be common practise. Patterns can be described on different levels of abstraction, but the patterns in the focus of this paper are on the software architecture level. In this paper we present a definition of the notion ”ontology application pattern”, as a special form of software architecture patterns describing an ontology-based system. We also show how such patterns, as well as the description of the pattern instantiations, can be described using a modified architecture description language.

Research projects have an inherent risk of failure, and learning howto cope with the risk is an important task for everyone involved. In order to doso it is necessary to share the knowledge of the experiences done during andafter the project. This paper investigates a recently completed enterprisemodeling research project and contributes with lessons learned andrecommendations for future enterprise modeling projects.