This study addresses the issue concerning the relation between information technology (IT) and the negative effects on the environment. A distinct problem is IT suppliers’ unawareness regarding the problematics as well as lack of knowledge concerning sustainable solutions. Green IT is a systematic application of methods that enables minimization of Information Technology’s environmental impact. Thus, Green IT can be used as a strategy to achieve sustainability goals. The purpose of this study is to develop an approach for IT suppliers to identify drivers, counteract barriers, conduct implementation and achieve benefits through performances of Green IT, to further present directions for future research within the area.   A qualitative research method has formed the base of this study. The theoretical framework is based on literature in Green IT and Green Supply Chain Management (GSCM). Collection of empirical data has been conducted through in-depth interviews with managers at three corporations within the IT supply industry. The collected data has been transcribed and analyzed based on a thematic analysis. Through empirical generalizations from the literature study a theoretical framework was created.  The relevance of this study has been confirmed through the result of the research. The empirical study verifies the need for development of circular models in order to maintain high sustainable standards that permeates the entire value chain. IT suppliers can improve the implementation process of Green IT by implementing a circular approach which enables continuous improvements of Green IT practices in a green value chain.   This study can form the base for further research in the field of development and implementation of Green IT as a part of GSCM. Figure 2 can be used in order to investigate further development of models and frameworks for adoption of Green IT within GSCM. Another suggestion for further research is to investigate if barrier management can improve the implementation process. This thesis focused on internal implementation of Green IT practices. However further research could focus on an external perspective of Green IT implementation.

The purpose of this thesis is to understand the reasons why organizations may or may not be utilizing BI in strategic decision making and to employ the knowledge for developing BI in a way that meets the expectations of the businesses. The research question for this thesis is to identify to what extent Business Intelligence is employed as a decision support tool by organizations when making strategic decisions?  The thesis follows a qualitative method in the form of a case study, where data has been collected from three different companies. The thesis has used a deductive approach which means literature reviews are employed to gather knowledge about the study area. This has also been used to determine how well existing knowledge aligns with the findings from the study. In the study, semi-structured interviews have been used to address the research question as the primary data collection tool. The interview results suggest that BI is employed to varying extent by various organizations when making strategic decisions. This thesis suggests that companies should be much better at using Business Intelligence as a decision-making tool when it comes to making strategic decisions. The results of the study show that companies are well on their way to reaching this goal. But that a lot still needs to be done for example managers at companies need to understand the importance of BI and what it can achieve. There are managers that are very financially oriented who don't understand the value of BI and the benefits of it. They only use BI as a support for carrying financial reports and this is something that prevents the development of BI and also the maturity. This is one of the reasons why companies still have a lot to do when it comes to BI combined with strategic decisions.

This thesis investigates the relationship between technology, specifically machine learning and business value. By incorporating fundamentals of today such as a socio technical perspective and the fourth industrial revolution, commonly referred to as Industry 4.0 and this thesis will explain if machine learning can create business value in the organization as well as what organizational aspects a company needs to obtain in order to create business value from its data.  This was achieved through a qualitative study by conducting semi-structured interviews with a technology industry leader, two experts on the subject and complemented with closely evaluated sources gathered from articles, journals, published literature, websites and case studies.  The analysis of this thesis is based on an analytical framework that concludes five organizational aspects. It shows a clear relationship between the five organizational aspects the analysis is based on in regards to data and internal structure that needs close consideration in order to create business value from data as well as the possibilities of implementing and utilizing machine learning. By having a socio technical perspective in mind the analysis shows and confirms the theories this thesis is based on as well as it gives a nuanced perspective on an industry that primarily focuses on technical factors.  The researchers conclude that apart from the five organizational aspects the analysis is based on, a sixth aspects needs to be incorporated as well. By conducting a study on a large technology industry leader as well as two additional experts on the subject, the researchers conclude that machine learning can benefit large parts of the organization as well as the workforce employed.

Artificial intelligence (AI) shows great potential and has the ability to change and improve numerous domains in society. Thanks to this new technology it is possible to radically improve the learning process and make it more effective for students hence its ability to adapt to students individual flaws, knowledge and needs through so called intelligent tutoring systems (ITS). This, In relation to the many flaws within the school sector in Sweden, where the two utmost highlighted aspects is the high amount of stress teachers experience and the amount of educated and competent teachers that will continue to be a scarce commodity. The research hopes to discover how AI can benefit teachers in the classroom. To better understand the classroom situation this research have conducted a qualitative research process with its focus on teachers. Thus, this research has enabled to identify the teachers challenges, attitudes and needs that exist in order to compare with previous research regarding AI and its potential and capabilities. The research concludes that AI can fulfill some of the needs that teachers express in form of personalized learning within certain areas to enable the students to work at their own pace. AI can also relieve time for teachers and help them with the set up in teaching classes. As far as the teachers' attitudes are concerned, the study's results show that it is generally positive although no one believe a teacher can or should be replaced by AI. AI should instead be used as a complement to the teacher. This is because the teachers care about the human aspect and do not feel that AI can teach the social competencies that the pupils should learn in school. They say that the teaching itself is one thing, but that everything around it requires human contact and relationships between teacher and student as well as student to student.

Due to Covid-19, there has been a rise of uncertainties around the world. One of theuncertainties is how teams and individuals of these teams in agile software developmenthas been affected. The goal of this paper is to see how Covid-19 has affected thesepeople that are WFH (Working from home). In order to collect data for the research paper, a survey of qualitative and quantitativeresponses and semi-structured qualitative interviews are used. In total there were 17 respondents to the survey and two interviews were conducted. The findings of the research show that there have been increased numbers of meetingsand they have also gone to a more online setting compared to before. Goals in generalhave been slightly harder to reach to the extent where communication has been slower.Higher focus has been established by the workers leading to productivity has beenimproved both from the individual perspective and the team perspective. The majorityalso would like to continue to work from home going into the future and going to theoffice is not mandatory but instead optional.

Linköpings hockey club (LHC) arbetar idag tillsammans med Sports Analytics Group vid Linköpings Universitet, de har tillsammans bett oss ta fram ett verktyg för att underlätta LHC:s scoutingprocess. Arbetet inleddes med flera möten tillsammans med LHC där vi diskuterade hur arbetet skulle drivas framåt och vad som behövde göras. Under mötena fick vi reda på att fokus låg på jämförelsen mellan spelarna, dels att hitta liknande spelare för att kunna ta reda på rimliga löner, dels att kunna hitta nya spelare. Electron valdes som ramverk dels på grund av tidigare erfarenheter, dels för att i framtiden ha stöd för många olika enheter. Vi arbetade sedan agilt med kontinuerlig kontakt med LHC varje vecka för att utveckla just den funktionalitet som just de var ute efter. Tillslut fick verktyget funktionalitet såsom att hitta och jämföra spelares löner kontra dess spelarstatistik, en detaljjämförelse där spelares statistik kan jämföras mer noggrant samt en lagbyggesfunktion för att ge en överblick över alla ens valda spelare. Även designen på verktyget arbetades kontinuerlig fram och blev tillslut en minimalistisk sådan. I slutet av arbetet besvarade även personal på LHC på en enkät enligt “The System Usability Scale (SUS)” angående användbarheten, användarvänligheten, och önskvärdheten för verktyget. Svaren blev väldigt positiva och vi anser därför att detta är ett optimerat och näst intill optimalt verktyg för just LHC.

The increased usage of encrypted application layer traffic is making it harder for traditional traffic categorization methods like deep packet inspection to function. Without ways of categorizing traffic, network service providers have a hard time optimizing traffic flows, resulting in worse quality of experience for the end user. Recent solutions to this problem typically apply some statistical measurements on network flows and use the resulting values as features in a machine learning model. However, by utilizing recent advances in multi-fractal analysis, multi-fractal features can be extracted from time-series via wavelet leaders, which can be used as features instead. In this thesis, these features are used exclusively, together with support vector machines, to build a model that categorizes encrypted network traffic into six categories that, according to a report, accounts for over 80% of the mobile traffic composition. The resulting model achieved a F1-score of 0.958 on synthetic traffic while only using multi-fractal features, leading to the conclusion that incorporating multi-fractal features in a traffic categorization framework, implemented at a base station, would be beneficial for the categorization score for such a framework.

Companies offering a service application targeting a broad audience often have difficulties meeting all user requirements since many users have unique needs. Allowing users to define and create content for service applications themselves, which addresses their specific needs, would be a welcomed solution. This would allow developers to focus on the main aspects of the service application, whereas the users themselves can include individual end-user aspects. User-customized content can be used as a selling point for the companies and opens up possibilities for providing a better user experience for each unique end user. This thesis describes the process of creating a prototype system that provides a solution for including user-customized content in a mobile application service system. First, we describe requirement elicitation followed by design and the actual implementation. Furthermore, security is a frequent topic whenever a digital application is discussed today. Therefore, the system creation process is followed up with an investigation of how the resulting application security aspect can be evaluated. After investigating different possibilities, a security evaluation case study on the application is performed. The results show a functioning system that allows customers to customize the content that is rendered inside a cross-platform mobile application. The results from the security evaluation investigation also show that the Open Web Application Security Project (OWASP) Mobile Security Testing Guide (MSTG) framework can be adapted and used for security evaluation of a cross-platform mobile application, even though it targets native applications. The resulting system satisfies most of the requirements for the targeted security level but does not satisfy all requirements for a normal production level mobile application according to the OWASP Mobile Application Security Verification Standard (MASVS). However, the results indicate that there is potential to reach the desired security level by adapting the system to use pure React Native with some native code additions.

The demand for on-demand video streaming has seen an enormous increased usage and is today the main contributor to Internet traffic. Technological developments combined with the accessibility of sufficiently powerful end-user hardware, large bandwidth capacities and significantly reduced storage cost are major contributors to this trend. We have built a simulation environment where multiple clients stream linear and branched video while competing over a shared bottleneck network. We examine how rate caps can be implemented to increase the overall Quality of Experience (QoE). First we present simulation results demonstrating the impact that rate caps have on clients playing linear video and compare and relate the results with prior work. Second we simulate the performance implementation of branched video and consider how its performance is affected by rate caps. Here, we highlight and discuss the trade-off patterns between playback quality and stability observed when a cap is implemented. To derive our conclusions we consider a range of scenarios, in which we vary different variables when a rate cap is set or not and measure the (i) requested encodings, (ii) buffer occupancy, and (iii) the amounts of switches between encodings made by the clients during the playback sequence. The rate cap implementation is shown to generate less switches between encodings, providing an enhanced stability and thus contributing to a better QoE in both the linear and branched environment.

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