En stark motivering till omställning från icke-förnybar till förnybar energi är ökningen av elförbrukning i världen, med målet att minska klimatpåverkan. Denna elförbrukning förväntas stiga från dagens 140 TWh till 190 TWh år 2045 i Sverige. I och med detta etableras nu konceptet Co-Living på den svenska bostadsmarknaden vilket innebär att människor delar på hemmet. I denna studie undersöktes en testbädd på KTH Live-In Lab där olika bostadskonfigurationer har granskats, där den första konfigurationen var singelboenden och den sista är Co-Living. Syftet med studien var att undersöka de boendes beteendeförändringar med avseende på resursförbrukning i hemmet och undersöka om det gick att se en skillnad mellan konfigurationerna. Resurserna som undersöktes var el och vatten. Studien utfördes genom att undersöka data för el- och varmvattenförbrukning samt aktiveringar och användningstid för dusch och tvättställ. Mätperioderna var på tre månader och innefattade fyra boenden i varje konfiguration. Resultatet visar en ökning i Co-Living, av elförbrukning per person på cirka 12,5% under 2021. Vattenförbrukningen per person visade en ökning på ca 56%. Det gick även att se att antalet aktiveringar, per person, för dusch och tvättställ steg med 41%. Sist i resultatet steg användningstiden, per person, för dusch och tvättställ med 132%. Slutsatsen av studien visar en märkbar ökning av resursförbrukning hos boenden i det studerade Co-Living jämfört med singelboenden. Men det finns en osäkerhet om denna förändring var på grund av Co-Living då exempelvis Covid-19 har visat sig kunna ha stor påverkan på resultatet. / One of the strong reasons for converting to renewable energy sources is the increasing amount of resource usage, with the goal to reduce the climate impact of it. The electricity usage is expected to rise from today’s 140 TWh to 190 TWh until year 2045 in Sweden. With this, the concept of Co-Living is now being established on the housing market. The concept is based on people sharing an accommodation. In this study, obtained data from a testbed called Live-In Lab was investigated. The data is obtained from different building configurations of accommodations, where the first one is single households and the last one is Co-Living. The purpose of this study was to examine the resident’s behavioral changes that affected the resource usage, to see if there were differences between the different configurations. The examined resources were electricity and water. The study was conducted by examining data for electricity and water usage, also usage time and activations for shower and basin. Data was collected for periods of three months and there were four tenants in each configuration. The results show that the usage, per person, of electricity increased by 12,5%, and water by 56% in 2021. Noticeable was also that the number of activations, per person, for shower and basin increased by 41%. Lastly the usage time for shower and basin increased by 132% per person. The conclusion for this study is that there is a noticeable increase of resource usage in the investigated Co-Living, comparing with single households. But there is a great uncertainty regarding Co-Living being the main reason for this difference, as Covid-19, for example, also has had a strong impact on resource usage.

Software systems are today a part of more or less every organization. The varieties of software used in organizations are ranging from simple log-keeping applications to advanced decision support systems. The task of a priori valuation of software investments has attracted a lot of research for a long time. One of the main themes of this research has been which types of consequences software investments result in and how these consequences can be incorporated in the a priori valuation of the investment. Much of this research has stated the problem as how to incorporate intangible consequences in the valuation since intangible costs and benefits are assumed to represent a large part of the consequences from a software investment. These consequences are therefore highly relevant in the appraisal of software investments. This thesis is concerned with the question of how intangible consequences can be incorporated in the a priori valuation of a software investment. To answer this question, this thesis presents a theoretical model for the valuation of a software investment based upon a discounted cash flow model in continuous time. The general model argued for in this thesis is that usage results in consequences which must be translated into cash flows to be incorporated in a discounted cash flow model. The software usage is chosen as the underlying value creating function since it is the basic underlying function that creates all consequences specific to the software investment. This thesis develops a stochastic cash flow model to incorporate the uncertainty and characteristics of when the intangible conse quences have an effect on the cash flow by adopting a Brownian motion into the valuation model. To find an analytic model for the problem, the expectations of the future cash flows is transformed into risk-neutral expectations. This allows us to use the risk-free rate of return as a discount factor in the model.

Shared mobility is considered a more sustainable alternative to private modes. Nonetheless, its sudden and sometimes “out of control” emergence poses issues that need to be addressed. Lack of regulations and public space mismanagement cause sidewalks and city roads to be overcrowded with shared vehicles (especially in the case of micromobility). This causes nuisance and safety concerns and hinders the societal benefits shared mobility may provide. Shared mobility hubs have the potential to address these issues. The research was carried out within the context of the SmartHubs project, an EIT Urban Mobility project initiated in 2021 by a diverse consortium of 7 cities, companies, and universities to develop and validate effective and economically viable mobility hub solutions. This degree project aims to improve the Decision-Support-Tool (DST) developed by SmartHubs to identify locations of shared-mobility hubs having high potential in driving sustainable travel usage. To achieve that, the thesis proposes a methodology for determining smart hub locations and their corresponding utilities based on the combination of GIS cluster analysis of free-floating shared mobility parking patterns and a stated-preference study. The potential hub locations were determined from the cluster analysis of free-floating trip characteristics. Using the stated preference survey data, the thesis develops a model to estimate the probability of parking at the hub as a function of explanatory variables, including walking distance, reward policies and the parking situation. The model testing results showed that the proposed methodology can well predict the hub (usage) demand and improve the current DST originally developed in the SmartHubs project.

The main motivation for the study described in this dissertation is to benefit from the development in technology and the huge amount of available data which can be easily captured, stored and maintained electronically. We concentrate on Web usage (i.e., log) mining and Web structure mining. Analysing Web log data will reveal valuable feedback reflecting how effective the current structure of a web site is and to help the owner of a web site in understanding the behaviour of the web site visitors. We developed a framework that integrates statistical analysis, frequent pattern mining, clustering, classification and network construction and analysis. We concentrated on the statistical data related to the visitors and how they surf and pass through the various pages of a given web site to land at some target pages. Further, the frequent pattern mining technique was used to study the relationship between the various pages constituting a given web site. Clustering is used to study the similarity of users and pages. Classification suggests a target class for a given new entity by comparing the characteristics of the new entity to those of the known classes. Network construction and analysis is also employed to identify and investigate the links between the various pages constituting a Web site by constructing a network based on the frequency of access to the Web pages such that pages get linked in the network if they are identified in the result of the frequent pattern mining process as frequently accessed together. The knowledge discovered by analysing a web site and its related data should be considered valuable for online shoppers and commercial web site owners. Benefitting from the outcome of the study, a recommendation system was developed to suggest pages to visitors based on their profiles as compared to similar profiles of other visitors. The conducted experiments using popular datasets demonstrate the applicability and effectiveness of the proposed framework for Web mining and recommendation. As a by product of the proposed method, we demonstrate how it is effective in another domain for feature reduction by concentrating on gene expression data analysis as an application with some interesting results reported in Chapter 5.

Estuarine habitats are considered nursery habitats for fishes and invertebrates, but oligohaline environments are critically understudied. Using a seine net and fyke nets, we sampled Back Bay, Mississippi (USA), a low salinity estuary, once a month for a year to explore the temporal use of the marsh and adjacent submerged landscape by nekton species. We also looked at whether there is evidence of habitat preference in the most numerous nekton species. We used a novel habitat usage index (HUI) to compare seine and fyke net catches of our top 10 species, and evaluated catch size in relation to maturation size. Consequently, we noted marked differences in 48 nekton species in terms of habitat preference; observed, for our top 10 species, transient species were primarily immatures, and resident species mostly occurred in marshes with some exceptions; and detected size patterns consistent with the spawning cycle of the species in question.

This paper offers an inductive, exploratory study on the role of input and individual differences in the early code-mixing of bilingual children. Drawing on data from two German-English bilingual children, aged 2–4, we use the traceback method to check whether their code-mixed utterances can be accounted for with the help of constructional patterns that can be found in their monolingual data and/or in their caregivers’ input. In addition, we apply the tracebackmethod to checkwhether the patterns used by one child can also be found in the input of the other child. Results show that patterns found in the code-mixed utterances could be traced back to the input the children receive, suggesting that children extract lexical knowledge from their environment. Additionally, tracing back patterns within each child was more successful than tracing back to the other child’s corpus, indicating that each child has their own set of patterns which depends verymuch on their individual input. As such, these findings can shed new light on the interplay of the two developing grammars in bilingual children and their individual differences.

This thesis focus on the investigation of material usage in the production processes of electrical motors and generators at ABB Machines, a company based in Västerås, Sweden. The study aims to understand the reasons for the occurrence of excess material after the assembly of a motor or generator and explore possible solutions to minimize its occurrence. In this study, excess material is defined as the components which was intended to be used in the final assembly of a machine but that has for some reason not been used. The components which qualifies as being defined as excess materials are components which are in the same functioning state as when they were delivered from the supplier, in other words components which has not been processed nor damaged. Further, the components defined as excess materials are only the components, after a machine has been fully assembled, which has been gathered by the production personnel working at the final assembly in pallets. For example, this can be components like screws, tube fittings and cap nuts.  The research method employed in this study was a mix of different methodologies. Five methods, a literature review, registration of materials, interviews, observations and focus groups were used to collect information and data. Thereafter, the observations, interviews and focus groups results were processed through a thematic analysis. The collected quantitative data was analysed through a quantitative analysis. With the collected and summarized information, discussions were held and conclusions were drawn regarding the research questions.  The study reveals several reasons for the occurrence of excess material in manufacturing and these include:  Substitution of material in production: Material substitutions during the production process contribute to the generation of excess material. Errors in drawing material and deficiencies in concept generation: Mistakes in the design phase and concept generation lead to the generation of excess material. Least possible order quantity exceeds the actual need: Ordering minimum quantities that exceed the actual requirements result in excess material. Problems with steering in the ERP system: Issues with the Enterprise Resource Planning system affect material management and contribute to excess material. Excess material is not a prioritized area: The management’s lack of focus on minimizing excess material leads to its occurrence. Uncertainties in stock level: Lack of accurate stock level information causes overstocking and results in excess material.  The potential solutions to address excess material in the manufacturing of electrical motors and generators can be grouped into the following categories: storage, order quantity, goods arrival structure, preparations, and general routines.  Storage: Include stocking frequently used materials, reducing the variety of items in stock to minimize substitutions, introducing specific storage locations for large projects, and implementing flexible warehousing. Order quantity: Involve trimming order quantities, improving the handling of "Dummy purchases", and splitting materials upon arrival for multiple machines in a project. Goods arrival structure: Focus on reviewing pick order sizes, establishing clearer loading systems, controlling material allocation, and synchronizing the release of pick orders. Preparations: This solution include facilitating engineering changes in production groups, streamlining part number reduction, and limiting construction items within categories. General routines: Involves checking the usability of remaining materials, collaborating with fitters and production staff to optimize processes and material choices, reporting material substitutions, and systematically tracing excess material in a database. Uncertainties in stock level: Lack of accurate stock level information causes overstocking and results in excess material.

Nowadays, all software projects are based on a large number of libraries, so they do not have to start from scratch. These libraries evolve over time, whether to add functionality or to simplify their use. These updates are necessary to improve their libraries, but can lead to errors in their clients’ code. Developers are thus faced with the problem of breaking changes and need to be able to inform their clients as soon as possible of the arrival of these changes. To limit the impact of these breaking changes, this Master thesis presents UCov. UCov is a static analysis tool that gives library developers a quick overview of the usage coverage of their tests compared with the coverage of their clients. This lets them to compare which elements of their library are being tested with those being used by their clients and also how they are being used. This will enable developers to improve their test suite according to how their clients use their library, to get a better overview of how their library is used, and also to give their clients the best possible warning of changes that may impact their code, thanks to release notes. In this study, we explain the implementation of UCov and test it on various libraries. The results obtained on these libraries are satisfactory. They enable us to highlight potential breaking changes. They also show that there are elements of the libraries’ APIs that are used by clients but never tested. Finally, these results show that UCov offers developers a new tool enabling them to limit the impact of their breaking changes by gaining a better understanding of how clients use their libraries. / Numera baseras alla programvaruprojekt på ett stort antal bibliotek, så att man inte behöver börja från noll. Biblioteksutvecklare ställs därför allt oftare inför problemet med “breaking changes". Dessa är nödvändiga för att förbättra deras bibliotek, men kan leda till fel i deras kunders kod. Utvecklarna måste därför kunna ge sina kunder så mycket förvarning som möjligt om att det kommer att komma inbrytande ändringar. För att begränsa effekterna av dessa förändringar presenterar denna masteruppsats UCov. UCov är ett statiskt analysverktyg som ger biblioteksutvecklare en snabb överblick över användartäckningen för deras tester jämfört med täckningen för deras klienter. Detta gör det möjligt för dem att jämföra vilka element i deras bibliotek som testas med de som används av deras kunder, och även hur de används. Detta gör det möjligt för utvecklare att förbättra sin testsvit enligt hur deras kunder använder deras bibliotek, för att få en bättre överblick över hur deras bibliotek används, och även för att ge sina kunder bästa möjliga varning för ändringar som kan påverka deras kod, tack vare release notes. I den här studien förklarar vi implementeringen av UCov och testar den på olika bibliotek. Resultaten från dessa bibliotek är tillfredsställande. De gör det möjligt för oss att lyfta fram potentiella brytande ändringar. De visar också att det finns delar av bibliotekens API:er som används av klienter men som aldrig testas. Slutligen visar dessa resultat att UCov erbjuder utvecklare ett nytt verktyg som gör det möjligt för dem att begränsa effekterna av sina skadliga ändringar genom att få en bättre förståelse för hur kunderna använder sina bibliotek.

Telehealth and telemedicine have revolutionized the healthcare system in terms of access to information and remote medical treatment. While there is a great deal of literature on current perceptions of telehealth care systems, relatively little is known about perceived user needs and acceptance of future telehealth systems. One way to assess future attitudes is to evaluate anticipated usage of telehealth devices through perceived advantages and disadvantages. Additionally, this study seeks to assess the reliability of a new measure of technology acceptance that capitalizes on human motivation using self-determination theory. An online survey consisted of an original 40-item measure of motivation to use telehealth technology, the Psychosocial Impact of Assistive Devices Scale (PIADS; Jutai & Day, 1996), questions adapted from Edwards et al. (2014) about perceived advantages and disadvantages of telehealth devices, and open-ended questions about advantages, disadvantages, and concerns of interacting with telehealth devices in the future. The open-ended questions were coded for themes. Results also indicated that there was a high reliability between the MUTT and the PIADS, however the MUTT was slightly more reliable. Significant correlations were found between the overall MUTT and subscales of autonomy, competence, relatedness, and goals, as well as moderate correlations between the subscales of the PIADS (i.e., competence, adaptability, self-esteem) and the MUTT. The results of this research will be discussed further.

The current study employs a regional sample in order to investigate the phenomenon of fear-of-missing-out (FoMO), the awareness associated with the fear that other individuals are having a more pleasurable experience that one is not a part of. The current study uniquely examines the role that FoMO plays in viewing patterns associated with news content on social media interfaces. The 10-item scale created by Przybylski, Myrayama, DeHaan, and Gladwell in 2013 was used as a basis to discover the degree of FoMO participants experience while online, while other questions of the survey serve to collect data about participants sociodemographic's, engagement with soft and hard news content, and overall social media usage. (Przybylski, Myrayama, DeHaan, Gladwell 2013). The objective is to demonstrate the influential effects that FoMO poses on media consumer viewing patterns and behaviors.