This study investigates how small and medium-sized enterprises in Sweden implement the EU's NIS Directive through their cybersecurity strategies and policies. The aim is to identify the main challenges and success factors in this process. Interviews with key individuals within these companies reveal that strong leadership engagement is crucial for integrating the NIS Directive requirements into daily operations. The study identifies coercive and mimetic isomorphism as significant factors for adaptation, where companies are influenced both by regulatory demands and by mimicking successful strategies from other firms. The findings show that proactive risk management, including regular training and the use of standards such as ISO 27001 and NIST, enhances companies' resilience against cyber threats. The use of external consultants is an effective strategy, despite the high costs. The study emphasizes the need for tailored cybersecurity strategies that consider each company's unique conditions and needs. 

A high-throughput method for the fabrication of ordered arrays of Au nanoparticles is presented. It is based on pulsed electrodeposition into porous anodic alumina templates. In contrast to many synthesis routes, it is cyanide-free, prior separation of the alumina template from the aluminium substrate is not required, and the use of contaminating surfactants/capping agents often found in colloidal synthesis is avoided. The aspect ratio of the nanoparticles can also be tuned by selecting an appropriate electrodeposition time. We show how to fabricate arrays of nanoparticles, both with branched bases and with hemispherical bases. Furthermore, we compare the different morphologies produced with electron microscopies and grazing-incidence synchrotron X-ray diffraction. We find the nanoparticles are polycrystalline in nature and are compressively strained perpendicular to the direction of growth, and expansively strained along the direction of growth. We discuss how this can produce dislocations and twinning defects that could be beneficial for catalysis.

Det pågår en stor förändring i arbetsliv och samhälle i samband med lansering av olika generativa AI verktyg som skapar innehåll varierande former. Centralt i debatten är ChatGPT, som har väckt mängder av diskussioner i media angående risker för missbruk, särskilt inom utbildningssektorn. Denna studie syftar till att skapa och bidra till förståelse över ChatGPT och dess användbarhet, samt utmaningar genom att analysera acceptansen hos lärare och studenter i högre utbildning. Detta genom att använda teorier från nya vetenskapliga artiklarna angående ChatGPT i högre utbildning, samt jämföra dem med kvalitativa data i form av perspektiv och åsikter från lärare och studenter, och slutligen analysera dem i ett samband med tidigare utbildningsteknologier. Studiens resultat tyder på att ChatGPT har relativt blandad acceptans och delvis haft fördelaktiga effekter på genomförandet av uppgifter i högre utbildning beroende på kunskapsämne. ChatGPT har redan uppvisat anmärkningsvärda förändringar i arbetsprocessen för både lärare och studenter, däremot förekommer det obesvarade frågor och etiska problematik vilket för närvarande förhindrar dess möjligheter som ett potentiellt revolutionerande utbildningsverktyg i högre utbildning.

While solar cell research has traditionally focused on rooftop installations, there aresituations where the roof may not be suitable due to building design or legislativerestrictions. Additionally, shading from surrounding buildings can impact the efficiency ofsolar cells. To overcome these obstacles and maximize efficiency, the study explores solarpanel installations on facades in different densely built areas. The study aims to describehow urban density influences the energy profitability of solar panels on building facades.By employing a combination of quantitative and qualitative methods, including literaturereviews, 3D modeling, and energy calculations, the study analyzes the energy efficiencyand electricity production of facade-mounted solar cells in various densely built areas. Theresults demonstrate that solar panel installations on facades can exhibit varying efficiencyand electricity production, with the building's location in relation to surrounding structuresplaying a significant role. The study seeks to provide an overview of the energyprofitability of solar panels on building facades to support the development of sustainableenergy solutions in urban areas. Considering future urban planning, which is expected tomaintain high density, it becomes crucial to consider existing buildings and solar energyinstallations to ensure their long-term access to solar irradiation. The study is relevant inpromoting sustainability and energy efficiency in both new and existing buildings andexploring the potential of solar panels on building facades. It also highlights the need forfurther research to harness the potential of facades as an alternative energy source. Finally,it concludes that there is no generalized requirement for what the minimum distancebetween buildings needs to be for an efficient solar cell installation to be achieved,emphasizing the importance of considering factors such as the azimuth angle, orientation,and height of neighboring buildings.

This work has been performed at Starke Cycles and its purpose is to analyze the control arm of the MacPherson's suspension system for their new prototype of transport cycles. To analyze the control arm, the work is divided into different parts. The parts consists of mechanical calculations, material production, CAD modulation, structural mechanics and FEM analyzes. Material production is carried out using the material database CES-EduPack. The CAD program Solidworks is used to obtain a CAD model of the control arm. To analyze the control arm, SolidWorks simulation tools are used to obtain stress concentration and are presented.

Starke Cycles is a private bicycle manufacturing company. Their idea is to manufacture and develop environmentally friendly electric bicycles for the transport of goods. A normal way of transporting goods is by means of trucks. The disadvantage of transporting goods in a truck compared to transport cycles is that it causes toxic gases, high risk of traffic accidents and delays because it is restricted in traffic where certain roads and roads prevent it from reaching its destination. These disadvantages are a major reason why Starke Cycles has invested in the production of transport bicycles. The electric motors used in the transport bicycles do not emit exhaust gases. The size of the transport bicycles is considerable smaller, which means more space for fellow drivers on roads and ways and the risk of traffic accidents is reduced. Delays rarely occur because the transport bicycles are allowed to drive on cycle tracks and this makes the transport of goods smoother and faster.

The work results in a 3D model and the control arm reaches the goals that were set at the project. The material selection for the control arm was made of low-alloy steel of the AISI 4340 normalized. FEM analyzes in Solidworks show that the stress concentrations in the link arm can handle the maximum static load with a good safety factor of 200 at maximum load of the transport cycle.

Parkinson's disease (PD) is a progressive, chronic neurodegenerative disorder that impacts patients' quality of life. Hand tremor is a hallmark motor symptom of PD. However, current clinical tremor assessment methods are time-consuming and expensive and may not capture the full extent of tremor fluctuations. The built-in sensors in smartphones offer an accessible and cost-effective alternative for objective tremor assessment.

This study presents a systematic approach to developing a quantitative algorithm for Parkinson's disease tremor assessment using Inertial Measurement Unit (IMU) data. This study begins with a comprehensive data visualisation and understanding phase, leading to the design decision to implement a multiple linear regression model for tremor severity prediction. The IMU data, collected from 10 patients, is pre-processed and normalised to ensure consistency and account for varying degrees of tremor severity.

Feature extraction is conducted based on insights from literature, resulting in 16 unique features. These unique features are extracted for each of the acceleration and rotation rate data, resulting in 582 total features over both hands and all three tremor types. Recursive Feature Elimination with Cross-Validation (RFECV) is employed for feature selection, identifying the most relevant features contributing to tremor severity prediction. A multiple linear regression model is implemented and trained using the Leave-One-Out with Cross-Validation (LOOCV) method.

The model's performance is evaluated resulting in a mean MSE of 0.88, a mean MAE of 0.69, and an R² of 0.88. The results indicate a strong correlation between predicted and actual tremor severity, suggesting the model's high validity. The selected features show a high correlation with the patient's MDS-UPDRS scores, further validating their relevance in predicting tremor severity. Greater results could be achieved, but sample size was the greatest limitation during this study.

This study demonstrates the potential of using IMU data and multiple linear regression modelling for accurate PD tremor assessment within Mobistudy, contributing to the field of quantitative PD analysis.

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.

Studies of parity (P) and time-reversal (T) symmetry violations using molecules are important and attractive because they are complementary to the high-energy tests of physics beyond the Standard Model of elementary particles. The focus of our present work is to surpass the current accuracies of the quantity X, an enhancement factor for the nuclear Schiff moment (Q), and the nucleon electric dipole moments for the (TlF)-Tl-205 molecule. We obtain X = 6856 a.u. using a relativistic coupled-cluster singles and doubles and perturbative triples (CCSD(T)) approach. This new value of X improves the upper limits for Q and the proton EDM by about ten percent over the previous ones. [GRAPHICS] .

To measure physical activity in a wheelchair user is important. Disabled people have been found to be less active and it has negative health implications. By relating to ones own physical activity in concrete form it is easier to reinforce a positive attitude towards being physically active. The aim of this thesis is to show how a system can be built, that is able to collect measurements from sensors, with usability in mind. The system consists of software that integrates an iPhone, Apple Watch and a Tacx rotation sensor mounted on a wheelchair. With the help of a physics model these measurements can estimate energy expenditure of a wheelchair user. The system was tested with four participants performing subjectively decided low, moderate and vigorous physical activity while the system collected data. In terms of absolute energy expenditure the system was inaccurate. On the other hand, correlations were found between the calculated energy expenditures and physical activity. Using measurements from the rotations sensor a correlation of 0.7315 was found between the calculated energy expenditure and physical activity, a correlation of 0.5385 using measurements from the GPS and a correlation of 0.6452 using measurements from Apples own proprietary algorithm. The created system is a promising prototype towards objective measurement of physical activity in wheelchair users.

A mobile stroke unit (MSU) is an advanced ambulance equipped with specialized technology and trained healthcare personnel to provide on-site diagnosis and treatment for stroke patients. Providing efficient access to healthcare (in a viable way) requires optimizing the placement of MSUs. In this study, we propose a time-efficient method based on a genetic algorithm (GA) to find the most suitable ambulance sites for the placement of MSUs (given the number of MSUs and a set of potential sites). We designed an efficient encoding scheme for the input data (the number of MSUs and potential sites) and developed custom selection, crossover, and mutation operators that are tailored according to the characteristics of the MSU allocation problem. We present a case study on the Southern Healthcare Region in Sweden to demonstrate the generality and robustness of our proposed GA method. Particularly, we demonstrate our method's flexibility and adaptability through a series of experiments across multiple settings. For the considered scenario, our proposed method outperforms the exhaustive search method by finding the best locations within 0.16, 1.44, and 10.09 minutes in the deployment of three MSUs, four MSUs, and five MSUs, resulting in 8.75x, 16.36x, and 24.77x faster performance, respectively. Furthermore, we validate the method's robustness by iterating GA multiple times and reporting its average fitness score (performance convergence). In addition, we show the effectiveness of our method by evaluating key hyperparameters, that is, population size, mutation rate, and the number of generations.

Ambulance travel time estimations play a pivotal role in ensuring timely and efficient emergency medical care by predicting the duration for an ambulance to reach a specific location. Overlooking factors such as local traffic situations, day of the week, hour of the day, or the weather may create a risk of inaccurately estimating the ambulance travel times, which might lead to delayed emergency response times, potentially impacting patient outcomes. In the current paper, we propose a novel framework for accurately estimating ambulance travel times using machine learning paradigms, employing real-world spatiotemporal ambulance data from the Skane region, Sweden. Our framework includes data preprocessing and feature engineering, with a focus on variables significantly correlated with travel time. First, through a comprehensive exploratory data analysis, we highlight the main characteristics, patterns, and underlying trends of the considered ambulance data set. Then, we present an extensive empirical analysis comparing the performance of different machine learning models across different ambulance travel trip scenarios and feature sets, revealing insights into the importance of each feature in improving the estimation accuracy. Our experiments indicate that the aforementioned factors play a significant role when estimating the travel time.

This study aims to identify how materialdocumentation is prepared to meet the requirements of the Swedish National Board of Housing, Building and Planning. It also examines which flaws the companies experience with materialdocumentation and informationmanagement. Also, further investigations on BIM are done, to see if it can be a solution to the problems. This study focuses on the materialdocumentation, but only during the project planning. The study was conducted with qualitative methods, literature studies and interviews. Data collected using interviews are used as primary sources. The respondents to the interviews are workers of various kinds and are considered to have enough experience of material documentation. The result of the study has shown that the materialdocumentation is mostly used during production, because the companies buy the most material during that stage. The companies lack knowledge when it comes to documenting and using the material databases. This is because the classification systems are experienced to be complex and overworked. BIM turns out to be a solution to the problems, but it isn’t used to its full potential. This is because there are many who don’t have computer experience and knowledge within BIM.

Concrete is a leading building material due to its durability, strength and carrying capacity etcetera. A weakness of concrete is it´s relatively large carbon dioxide emissions that are released during the production process. At this current time cement production accounts to 5% of the world's GHG emissions. Boverket has set a specific requirement that new buildings must be climate declared as a guide to more sustainable construction.

This  study  aims  to  investigate  and  use  a  model-based  LCA-assessments  where climate- improved concrete is compared to a traditional concrete. This was done by examining a BIM- model.

The  possibility  of  improving  the  environmental  impact  is  answered  by  producing carbon dioxide emissions equivalent for concrete in this property and comparing it with carbon dioxide emissions  equivalent  for  a  climate-improved  concrete  to  show  a potential  carbon  dioxide saving.

A quantitative method is selected for this study using LCA. LCA-assessment is performed using several computer-based BIM programs to be able to produce simulations and calculations. A reference building that represents an ordinary apartment building in Sweden forms the basis of the assessment.

LCA is based on only one environmental indicator which is carbon dioxide emissions. LCA assessment for the two types of concrete include the construction phase A1-A5 as well as the phase B6 operating energy according to Swedish standard SS-EN 15978: 2011. No account is taken of any differences in strength, fire class and sound class when exchanging materials. LCC limits to utility calculation.

Results shows the total price increases by approximately SEK 49,000 if the ordinary concrete is replaced with a climate-improved concrete, and the carbon dioxide emissions is reduced by approximately 57,000 kgCO2e.

Reduction in the climate-impact of concrete partly helps in the climate policy framework 2045 for a climate-neutral Sweden. Climate-improved  concrete  has  limits  within exposure  and  strength  classes.  Surroundingenvironment must therefore be considered.

In the fluctuating wave of digitization, the fourth industrial revolution or Industry 4.0 in the manufacturing industry, has begun that has accelerated industries and companies to adapt and change their whole business to maintain competitive. Industrial Internet of Things (IIoT) has become a central part of this change for manufacturing companies and can be interpreted as companies taking advantage of units to gather real-time data and in turn, lean towards the smart factory. A range of possibilities can be accessed by industries with the rise of IIoT, though the success of this change can differ between different companies depending on size, resources, and economic stability. Parallel to the opportunities, challenges arises for companies, especially small and middle-sized enterprises, that lack the economic resources and scale to redistribute and transform their business. In this paper, the goal has been to distinguish how middle-sized manufacturing companies handle the implementation of IIoT and the smart factory in order to adapt to the ever-changing technical paradigm that Industry 4.0 has introduced. Conclusions have been drawn from the combination of a theoretical framework and interviews with six Swedish middle-sized manufacturing companies. The digitization strategy for manufacturing companies varies from industries. However, there is a consensus that efforts towards a digitized production must take place in order to stay competitive where automation-, monitoring-, and controlling processes within IIoT are main factors to stay competitive. The pace and level of implementation can also differ depending on digital qualification and resistance to change from the staff. Important to note is that the relation between IIoT, digitization and increased competitiveness is not the only factors that are significant as there are more things to consider. The study also shows that competitive advantages are rarely the main reason why companies choose to digitize and implement IIoT.

Climate change has resulted in several actors in various industries starting to take into account how their business activities affect the environment. The Swedish Parliament has set a climate target that is intended to be achieved by 2045. More specifically, the goal means that Sweden should  have no net emissions of greenhouse gases into the atmosphere. In 2019, Sweden's construction and real estate sector accounted for nationwide  greenhouse gas emissions, corresponding to approximately 12 million tonnes of carbon dioxide equivalent, which means that the specified sector can have a major impact on the environment.

Climate declarations are a term used in various contexts that report a building's climate impact. Climate declarations are carried out only for the construction stage, of which it has been divided into  two subcategories:  the product stage (A1-A3) and the construction production stage (A4-A5) (Boverket, 2021).  The study illustrates how the process can be done when producing climate declarations. In addition, a template has been designed  that  shows how  much carbon dioxide equivalents building elements emit.

The study consisted of interview questions that were answered by six different companies with different roles and similar views in sustainable construction. The respondents  that have been interviewed in the study are sales engineer Krister Andersson from the company Ruukki, environmental and sustainability manager Alexandra Rosenqvist from Beijer Byggmaterial, business development manager Linda Hedvall from Lindab,  chief executive officer  Oscar Hoolmé from Jacob Lindh AB and constructor Samir Goralija from Areco Profiles. Furthermore, structured interview questions have been prepared and asked to the above-mentioned companies, such as how do companies stand before the  climate  declaration  act? What measures will be taken to comply with the law? How has the law been affected in the business and what measures will be taken both short- and long-term?

The companies that have been interviewed point out that an EPD is only based on the construction phase of the A-module at present. The companies want a complete EPD with modules from A-D where the entire life cycle analysis is taken into account. This is in order to get a clearer picture of how much carbon dioxide equivalents a hallbuilding generates.

Within the framework of the study, the template has also been tested on an industrial building located in Eslöv municipality.  The template was used to calculate how much carbon dioxide equivalents a hallbuildings climate screen generates.

The results showed that the entire building's climate screen emits 58,065 kilo of carbon dioxide equivalents. Furthermore, it was shown  that both  traditional wall (41  kilo carbon dioxide equivalents per m2) and traditional roof (42 kilo carbon dioxide equivalents per m2) produce lower emissions than sandwich wall (60 kilo carbon dioxide equivalents per m2) and cardboard roof (71 kilo carbon dioxide equivalents per m2).

The  problem with  the production of climate declarations is that today's climate database is unclear and  that  different construction companies  apply  different climate indicators, which makes it hard to compare.  Another  problem  is  that climate declarations only  apply to  the construction phase (A-module). This means that the rest of the building's life cycle assessment has not been taken into account, which delays the process of achieving specified climate goals.

The conclusion  is  thus that the process of producing a climate declaration  is something new since there are no clear guidelines for how inputs  should  be chosen. However,  it was shown that the supplier  can with use of generic values can reduce its carbon dioxide emissions. This is done by choosing the right combination between building elements. 

The development in smart meter technology has made grid operations more efficient based on fine-grained electricity usage data generated at different levels of time granularity. Consequently, machine learning algorithms have benefited from these data to produce useful models for important grid operations. Although machine learning algorithms need historical data to improve predictive performance, these data are not readily available for public utilization due to privacy issues. The existing smart grid data simulation frameworks generate grid data with implicit privacy concerns since the data are simulated from a few real energy consumptions that are publicly available. This paper addresses two issues in smart grid. First, it assesses the level of privacy violation with the individual household appliances based on synthetic household aggregate loads consumption. Second, based on the findings, it proposes two privacy-preserving mechanisms to reduce this risk. Three inference attacks are simulated and the results obtained confirm the efficacy of the proposed privacy-preserving mechanisms.

The benefit associated with the deployment of Internet of Things (IoT) technology is increasing daily. IoT has revolutionized our ways of life, especially when we consider its applications in smart connected homes. Smart devices at home enable the collection of data from multiple sensors for a range of applications and services. Nevertheless, the security and privacy issues associated with aggregating multiple sensors’ data in smart connected homes have not yet been sufficiently prioritized. Along this development, this paper proposes HOMEFUS, a privacy and security-aware model that leverages information theoretic correlation analysis and gradient boosting to fuse multiple sensors’ data at the edge nodes of smart connected homes. HOMEFUS employs federated learning, edge and cloud computing to reduce privacy leakage of sensitive data. To demonstrate its applicability, we show that the proposed model meets the requirements for efficient data fusion pipelines. The model guides practitio ners and researchers on how to setup secure smart connected homes that comply with privacy laws, regulations, and standards. 

Internet of Things (IoT) technology has created a new dimension for data collection, transmission, processing, storage, and service delivery. With the advantages offered by IoT technologies, interest in smart home automation has increased over the years. Nevertheless, smart connected homes are characterized with the security and privacy problems that are associated with aggregating multiple sensors' data and exposing them to the Internet. In this paper, we propose LPM, a lightweight privacy-aware model that leverages information theoretic correlation analysis and gradient boosting to fuse multiple sensors' data at the edge nodes of smart connected homes. LPM employs federated learning, edge and cloud computing to reduce privacy leakages of sensitive data. To demonstrate its applicability, two services, commonly provided by smart homes, i.e., occupancy detection and people count estimation, were experimentally investigated. The results show that LPM can achieve accuracy, F1 score and AUC-ROC of 99.98%, 99.13%, and 99.98% respectively for occupancy detection as well as Mean Squared Error (MSE), Mean Absolute Error (MAE), and R2 of 0.0011,0.0175, and 98.39% respectively for people count estimation. LPM offers the opportunity to each smart connected home to participate in collaborative learning that is achieved through the federated machine learning component of the proposed model.

Progress in the field of Non-Intrusive Load Monitoring (NILM) has been attributed to the rise in the application of artificial intelligence. Nevertheless, the ability of energy disaggregation algorithms to disaggregate different appliance signatures from aggregated smart grid data poses some privacy issues. This paper introduces a new notion of disclosure risk termed energy disaggregation risk. The performance of Sequence-to-Sequence (Seq2Seq) NILM deep learning algorithm along with three activation extraction methods are studied using two publicly available datasets. To understand the extent of disclosure, we study three inference attacks on aggregated data. The results show that Variance Sensitive Thresholding (VST) event detection method outperformed the other two methods in revealing households' lifestyles based on the signature of the appliances. To reduce energy disaggregation risk, we investigate the performance of two privacy-preserving mechanisms based on microaggregation and Discrete Fourier Transform (DFT). Empirically, for the first scenario of inference attack on UK-DALE, VST produces disaggregation risks of 99%, 100%, 89% and 99% for fridge, dish washer, microwave, and kettle respectively. For washing machine, Activation Time Extraction (ATE) method produces a disaggregation risk of 87%. We obtain similar results for other inference attack scenarios and the risk reduces using the two privacy-protection mechanisms.

This study is concerned with digital two-dimensional rivers for games. Specifically the aim is to create a river shape from the basis of a spline curve and make it look like a river with a water flow-rate. This is achieved by developing an artifact capable of river simulations in 2D, with the flow-rate calculated using the necessary hydraulics equations. The scientific process described in Design Science Research Methodology for Information Systems Research is presented and followed. Artifact simulations are demonstrated and evaluated, especially calculations for river mean velocity and discharge are shown to be possible by assuming that the river channel is of trapezoidal shape. Simulations show a type of river not usually seen in games, a river with more accuracy than other game simulations. The artifact river simulations are however limited by a missing smoothness when going between different channel shapes. Also there could be a way of improving the texture used, or possibly use more then one texture in one simulation. The conclusion is that the methods used for river generation by this study could be part of a design tool that targets 2D games.

Since agriculture is a large source of emissions today, changes in our food production and consumption are required to reach EU climate goals. This study aims to find out if nudging combined with knowledge-based system can be used to influence customers’ choice towards more sustainable food. To investigate how the knowledge-based system should be created a quasi-field experiment was performed to measure the effect of re-ordering a menu (with vegetarian options on top). Previous studies have shown that nudging yields result, but without reporting how customers feel about being nudged. To investigate this, a selection of participants with different demographics (age, sex etc.) were presented digital lunch menus and their feelings and thoughts were observed through qualitative research in the shape of think aloud sessions. The participants were presented with three menus that used different nudging tactics. The results were used to create a conceptual model of a digital menu system based which builds upon knowledge-based systems. The system integrated social, label and order nudges as well as profit margin to create a system that is sustainable in the perspective of climate, as well as economy. 

The goal with this thesis is to explore previously used and trusted design guidelines on the new and relatively unexplored platform that is mobile devices. This type of platform is today the most common way for people to access written text, but the typography and design of this text is not always based on research. The thesis is limited to focus on how typefaces and type size affect readability. Based on the definition of readability presented in the thesis both subjective and objective measurements have been produced. These are for example: the reader's personal preference, reading speed, reading comprehension, scroll distance and touch-interactions. Through an analysis of the unique way readers interact with text during reading on a mobile device several objective measurements can be produced. Models for analysing this kind of data have been used and presented in prior studies. The data collection methods utilised in this thesis are: information and literature search, surveys and experiments. The collection of data is mainly conducted through a web application adapted to mobile use which has been published for the participants of the study. The results show that typefaces do not have any significant correlation with readability on text for mobile devices. However, type size has a greater effect on both the subjective and objective measurements of readability. The subjective measurements concerning type size have more of a spread regarding which size was perceived as being the most readable. The type size that generated the best results in the objective measurements was 18pt. When the type size increased so did the reading speed, but the reading comprehension decreased.

The prototype for people with memory impairments This study aims to examine how and if it is possible to use Benyons PACT-analysis together with Gong and Tarasewichs 15 design principles, to make the process from an idea into a final interactive prototype. The prototype is named Skalman. This study focuses on people with memory impairments, specifically those people diagnosed with Alzheimer’s disease. The aim with the PACT-analysis was to analyse the target group through four different subjects, People, Activities, Context and Technologies and to use that to find the needs for Skalman that in the end will help the users to manage and organize their daily lives. Three group interviews were made to collect data from the selected target group for the PACT-analysis. Two group interviews included a person with memory impairments/Alzheimer’s disease and one relative of this person to help and support throughout the interview. Thereafter an interview was made with the chancellors of Alzheimer’s Sweden to gather additional information and to increase the understanding of the disease and its difficulties. The result of the analysis was then used, together with the design principles to develop a LO-FI prototype and was then tested on the target group in order to evaluate the prototype and to improve it to the final result of a HI-FI prototype of Skalman.

The aim of this study is to reduce the energy consumed during manufacturing of parts in manganese steel. This is done by determining the possibility to make changes that shortens the production process of the castings while keeping the material properties similar. The process change that is studied is to see if it is possible to skip the heat treatment process by quenching directly after shake out of the casting. This means that the casted product needs to be shaken out and quenched at an earlier and more specific time. This process is known in the metal industry as direct quenching and is by the time of writing applied on different alloys and manufacturing processes. To determine the possibility to make the aforementioned changes to the casting process, taking the material properties into account, sample bodies are created. These sample bodies are of a predetermined geometry and are manufactured under controlled circumstances. From a total of nine sample bodies six are directly quenched and three are put through a heat treatment process, the later mentioned bodies are used as references. The sample bodies are studied with methods such as microscopy and hardness testing. In this study there are indications that it is possible to introduce direct quencing in the production of details made of austenitic manganese steel. This is because the difference in grain size and fraction of carbides is small between the direct quenched and the heat treated samples in this study. Nevertheless, further studies needs to be made to make a more definitive conclusion.

TikTok is a social media platform where users produce short videos. Today TikTok is used by over 1 billion people. The application offers various features that promotes interaction and knowledge exchange among its users. Entertainment is strongly associated with TikTok, however since 2020 the use of the platform for youth activism has increased. On TikTok, users can express their social values and cooperate with each other. It is also common to use hashtags as a way of linking videos to a specific topic. The aim of this study is to understand how TikTok users experience audiovisual information regarding the topic of feminism. Videos were selected from the platform by using the search word feminism and the hashtag #feminism. This was followed by a content analysis to determine the videos differences and similarities, which enabled the final selection of five videos to be used in the next step of the study. The five videos were then presented during qualitative interviews where the respondents answered questions and expressed their opinions about for example trustworthiness, features and the information itself. The data was compared and analyzed both from a theoretical point of view and regarding different experiences expressed by the respondents. The respondents in this study showed the most interest in an explanatory video which presented them with new information by using pictures, video and speech. 

The respondents showed greatest interest in two explanatory videos who presented new information by using pictures, video and speech. Information presented with pictures were considered to facilitate the understanding of the message, make it more interesting and arouse curiosity. Another video appreciated by the respondents used a narrative to convey entertaining education they could relate to. The recipients’ willingness to engage in the videos were linked to their positive experiences of how the information was presented. This study also shows that previous knowledge, information needs, motivation to use TikTok as well as different processing styles affected the respondents’ experiences.

This is a case study that study the participant culture as well as the community and commitment among the audience at Sveriges Radio Creepypodden. The purpose of the study is to create a deeper understanding of participant culture as a phenomenon and how it creates a space for community by analyzing the listening participation of Sveriges Radios Creepypodden. The aim of the study is to gain a greater understanding of what a mediums historical development can look like and how listeners are allowed to actively participate in the medium.  An interviw with the creator of Creepypodden, Jack Werner and two listeners was conducted. In addition to the interview, an analysis of collected data from four different posts published in ”Creepypodden – Eftersnack” on Facebook has been conducted. 

The theory chapter process the concept of media convergence which gives the reader an understanding of what media convergence means but also how it works in the media world. Participant culture is discussed as a central aspect in the modern media landscape. The study shows that the work Creepypodden does with participant culture is the foundation to the existence of the podcast and that the community among the listeners is perceived as rewarding.

This research paper focuses on analog computers and creating a modular low-cost analog computer system in a single board computer form factor. The single-board analog computer will have the capacity to solve second-order differential equations. The capabilities and possibilities of the single board Analog computer will be explored as well as analog computing in general. The paper follows design science research methodology (DSRM) with the goal of creating and evaluating a working artifact. The artifacts' functionality is evaluated based on a demonstration of its ability to solve Mathieu’s differential equation as well as simulate a spring-mass dampening system. This paper proves that it is possible to create a low-cost analog computer in a modern form factor. The artifact is also placed in a larger contextual setting based on the empirical material provided where its value of it in a digital society is presented. For the world to continue its progression in computational power, but still, limit the already high energy usage, a drastic change is needed. This paper suggests adapting to analog/hybrid technology. To further the progression of analog/hybrid technology it must be made accessible to a wider group of people compared to today. The artifact in this paper offers a solution to this. 

Since the beginning of man, there has been great technological development. Both the industrial revolution and now, industry 4, are good examples of this. This has led to a big change both in our everyday lives as well as for companies and their daily operations. The paper is based on a series of analyses on different documents from the internet, organization documents and documents from public authorities. This will then in turn be combined with a literature review and traditional theories regarding the topic. The paper concludes that customers' changing purchasing behavior has created a need for change in the retail mar. The changing purchasing behavior is attributed to the digitalization of society and customers' new expectations of the companies. To remain relevant in the market, organizations today must meet customers and their expectations through digital portals in a way that did not exist before.

The society is becoming more digitalized which requires companies to adapt in order to survive on the market. A part of such digitalization is the implementation of chatbots in customer services. The purpose of this study is to understand organizations’ and users’ needs in relation to chatbots used in support services and to examine how well chatbots satisfy the needs. Organizations’ and users’ respective needs are thereafter compared. The study is based on two qualitative methods performed through two focus groups and five semi structured interviews. The collected data has been analyzed based on a thematic analyze method. The result shows that the users’ main need was to receive swift and concrete answers to their questions. The organizations’ most central need was to redirect work from their support service staff. The study shows that the most important shared need was the accessibility. The study’s analysis shows that the chatbot has too low competence level to fulfill the users’ and organizations’ needs. Due to the low competence level of the chatbots, the study concludes that a combined customer service, including both chatbots and human support, can be advantageous for both the organizations and the users.

Webbtillgänglighet har blivit allt viktigare med den växande digitaliseringen och de rättsliga krav som ställs på svenska e-handlare. För att uppfylla dessa krav måste e-handlare använda ett användarcentrerat tillvägagångssätt vid webbutveckling för att säkerställa att fler kan interagera med deras digitala plattformar. Dessutom närmar sig tillgänglighetsdirektivet som kräver att e-handlare ska uppfylla tillgänglighetskrav. Vår studie visar att den svenska e-handelssektorn ännu inte är tillräckligt förberedd för att möta dessa krav. Studien syftar till att mäta och utvärdera 100 svenska e-handlare med avseende på problemområden inom webbtillgänglighet enligt WCAG 2.1 på A- och AA-nivå. Baserat på resultaten i mätningen kontaktades och intervjuades e-handlare och tillgänglighetsexperter för att få en djupare förståelse för varför e-handlare har omfattande tillgänglighetsbrister och vilka potentiella lösningar som finns. Resultaten bekräftar att de främsta hindren inkluderar brist på kompetens, teknisk förståelse och ekonomiska resurser. Vi ser att e-handelssektorn agerar reaktivt snarare än proaktivt, vilket inte är tillräckligt för att möta de kommande lagkraven. För att uppnå en överensstämmelse med lagstiftningen kan e-handlare söka extern hjälp, involvera funktionsnedsatta i designprocessen och utnyttja tekniska tillgänglighetsverktyg.

The digitalization develops at a blistering pace all around the world which results in an immense increase of circeling data. This in turn brings new possibilities but at the same time a lot of challenges for companies. They constantly have to be ready and expect the unexpected which was not least noticed when the Covid-19 pandemic hit. Organizations were forced to shut down their offices and work from home instead, which in turn implies even greater risks when it comes to threat and security if you are not prepared. The purpose of this study is to study companies in the information- and cybersecurity industry and how their internal, proactive risk management looks like. With Covid-19 as the foundation we also aim to study the lessons learned by companies as they emerged from the pandemic. To achieve this we have carried out a qualitative study based on 9 interviews with individuals in the industry which have had the opportunity to tell us their thoughts and opinions about proactive cybersecurity and Covid-19. The study has resulted in a compilation of the strategies and methods that are considered central to conducting as successful risk management as possible with a strong focus on the individual and their awareness and knowledge, which is considered to be a central part. For example, companies can work according to the Zero Trust principle to verify and control the assets an individual has, as well as work according to the four most common approaches: employee training, ethical hackers, threat hunting, and proactive monitoring of networks and endpoints, in order to proactively reduce the likelihood of being exposed to unwanted risks.

Bridges in Sweden are in need of improvements, due to increased traffic, altered function or due to degradation. It may also have occurred a mistake during the construction of the bridge which results in the need to reinforce the bridge later. Carbon fiber composite is a suitable reinforcement method that increases the capacity of the bridges. Carbon fiber is not time consuming, it is low in weight and is easy to handle on site. The purpose of the study is to analyze why carbon fiber composite is not used to a greater extent for bridges in the Swedish construction industry, but also to disclose the benefits of carbon fiber composite as reinforcement method. Different cases that have use the CFRP method to improve bridges have been analyzed to illustrate that the method can be applied in real life. Surveys have been sent to people working in the construction industry to get a better insight into how much carbon fiber is actually used in the construction industry. Factors that contribute to the fact that carbon fiber composite is not used to a greater extent can be because of epoxy, meaning that the material is too expensive and that it has a short life span. In some cases carbon fiber composite cannot solve the desired amount of problems in a construction. Although the material is expensive, the reinforcement method is easy to handle and is therefore cheaper in time.

As the number of cities in Europe and the world increasingly prohibit car traffic in the center, there is a demand to replace the vehicles with exhaust-free vehicles. Many times, a van or a truck does not carry more than what you can carry in a heavy cargo bike though it is a better option for several reasons. The work has been done at Starke Cycles, a manufacturing company where they develop heavy cargo bikes based on their work experience from MOVEBYBiKE, which is a freight company. Over the years, they have encountered problems with the ride comfort and that the rear axle has broken off the heavy cargo bikes used today. These problems have occurreddue to that the heavy cargo bikeslack of suspension. During2017, a first prototype has been developed but it is too wide to be approved by the Swedish Transport Agency which is required for a newly manufactured vehicle. The purpose of the work is to solve the problem of the rear axles sustainability and the ride comfort of the heavy cargo bikes that is used today, as well as solving the problem of the first prototypeswidth.The work of developing a suspension has focused on delivering a cost-effective suspension to Starke Cycles to produce and apply on the second prototype that they are developing. The work started with studying and examining the current heavy cargo bikes construction to get an idea of which type of suspensionsare possible to apply to the second prototype. Therefor has the possible suspensions been analyzed and the best suited system chosen with a systematic and objective method, concept evaluation. With the results from the mechanical calculations a double wishbone suspension was developed. The mechanics of materials has been analyzed on chosen components of the suspension in a FEM-simulation in Creo Parametric after a case study in materials selections had been made. The work has not analyzed the constructionslife expectancy against material fatigue.The result is presented as a 3D-model where the goals of the work have been met and drawings on the suspension have been sent to a mechanical workshop for manufacturing. The material selection fell on an aluminumalloy and the FEM-analysis shows that the stress in the analyzed components meet the strength requirements.

The study examines how young people who grow up in a digital world relate to critical information to the information they take on digital platforms, how aware they are about personalization on the internet and how it affects their flow. The purpose of the study is to find out how young people are related to and experience the effects that arise from their use. Furthermore, the study discusses how young people value different types of sources and what their experiences or experiences are from the influenced flow. The survey was conducted with a qualitative method through three focus groups. The empirical data consists of a collection via conversation with focus groups of four participants on three different occasions. Each call lasted between 45 - 60 minutes. The result shows that respondents noticed that their flow was personalized but that they do not know why or how they are. Furthermore, the result shows that all respondents feel that they are very sourcecritical and that they talk a lot about the value of source criticism in school, but then only anchored to the fact-finding requests. In the discussions it was raised how the user may or should have source criticism against influencers, different news sites and individuals.

This study focuses on evaluating and enhancing the user experience of Emely, a conversational agent aimed at improving language skills for second language learners, particularly those who want to increase their chances of securing employment in Sweden. Usability testing was conducted in two test rounds, with the first round providing design implications for the user interface in the second round. However, assessing the effectiveness of the interface improvements was challenging due to low Swedish proficiency among the test groups consisting of potential users of Emely. Although the study did not result in design implications for the user interface, important findings highlight the need to adapt conversational agents, like Emely, for users with low literacy levels and illiteracy, emphasizing the importance of inclusive design for effective language learning support.

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).

In their seminal work on Multidimensional Sorting, Goodman and Pollack introduced the so-called order type, which for each ordered triple of a point set in the plane gives its orientation, clockwise or counterclockwise. This information is sufficient to solve many problems from discrete geometry where properties of point sets do not depend on the exact coordinates of the points but only on their relative positions. Goodman and Pollack showed that an efficient way to store an order type in a matrix λ of quadratic size (w.r.t. the number of points) is to count for every oriented line spanned by two points of the set how many of the remaining points lie to the left of this line. We generalize the concept of order types to bicolored point sets (every point has one of two colors). The bicolored order type contains the orientation of each bicolored triple of points, while no information is stored for monochromatic triples. Similar to the uncolored case, we store the number of blue points that are to the left of an oriented line spanned by two red points or by one red and one blue point in λ_B. Analogously the number of red points is stored in λ_R. As a main result, we show that the equivalence of the information contained in the orientation of all bicolored point triples and the two matrices λ_B and λ_R also holds in the colored case. This is remarkable, as in general the bicolored order type does not even contain sufficient information to determine all extreme points (points on the boundary of the convex hull of the point set).We then show that the information of a bicolored order type is sufficient to determine whether the two color classes can be linearly separated and how one color class can be sorted around a point of the other color class. Moreover, knowing the bicolored order type of a point set suffices to find bicolored plane perfect matchings or to compute the number of crossings of the complete bipartite graph drawn on a bicolored point set in quadratic time.

Let P be a set of n = 2m + 1 points in the plane in general position. We define the graph GM_P whose vertex set is the set of all plane matchings on P with exactly m edges. Two vertices in GM_P are connected if the two corresponding matchings have m − 1 edges in common. In this work we show that GM_P is connected.

Unmanned aerial vehicles (UAVs) are used in many areas where their usage is increasing constantly. Their popularity, therefore, maintains its importance in the technology world. Parallel to the development of technology, human standards, and surroundings should also improve equally. This study is developed based on the possibility of timely delivery of urgent medical requests in emergency situations. Using UAVs for delivering urgent medical requests will be very effective due to their flexible maneuverability and low costs. However, off-the-shelf UAVs suffer from limited payload capacity and battery constraints. In addition, urgent requests may be requested at an uncertain time, and delivering in a short time may be crucial. To address this issue, we proposed a novel framework that considers the limitations of the UAVs and dynamically requested packages. These previously unknown packages have source–destination pairs and delivery time intervals. Furthermore, we utilize deep reinforcement learning (DRL) algorithms, deep Q-network (DQN), proximal policy optimization (PPO), and advantage actor–critic (A2C) to overcome this unknown environment and requests. The comprehensive experimental results demonstrate that the PPO algorithm has a faster and more stable training performance than the other DRL algorithms in two different environmental setups. Also, we implemented an extension version of a Brute-force (BF) algorithm, assuming that all requests and environments are known in advance. The PPO algorithm performs very close to the success rate of the BF algorithm.

Segmenting images is an intricate and exceptionally demanding field within computer vision. Instance Segmentation is one of the subfields of image segmentation that segments objects on a given image or video. It categorizes the class labels according to individual instances, ensuring that distinct instance markers are assigned to each occurrence of the same object class, even if multiple instances exist. With the development of computer systems, segmentation studies have increased very rapidly. One of the state-of-the-art algorithms recently published by Meta AI, which segments everything on a given image, is called the Segment Anything Model (SAM). Its impressive zero-shot performance encourages us to use it for diverse tasks. Therefore, we would like to leverage the SAM for an effective instance segmentation model. Accordingly, in this paper, we propose a hybrid instance segmentation method in which Object Detection algorithms extract bounding boxes of detected objects and load SAM to produce segmentation, called Box Prompted SAM (BP-SAM). Experimental evaluation of the COCO2017 Validation dataset provided us with promising performance.

Stroke is a life threatening medical condition that is caused either by a blood clot or a bleeding inside the brain. It is generally agreed that immediate treatment of stroke patients is crucial for their ability to recover; however, before treatment can be initiated, the stroke patient has to be diagnosed using, for example, a computed tomography scan of the brain. This, in turn, requires that the patient is transported to a hospital for diagnosis, which is a procedure that consumes valuable time and resources. In the current paper, we present an agent-based simulation model for assessment of logistical stroke patient triage policies. Using a population of stroke patients as input, the model enables to simulate the activities and the main decisions involved in the logistical operations of stroke patients. In an experimental study covering the southernmost part of Sweden, we used the simulation model in order to assess two different policies regarding where to send patients for diagnosis; the nearest hospital policy and the nearest hospital towards the stroke center policy. Our simulation results show that the patients in need of special treatment favor from being transported in direction towards the stroke center, whereas the patients who are not in need of specialist treatment favor from being sent to the closest hospital.

Background Medication discrepancies in care transitions and medication non-adherence are problematic. Few interventions consider the entire process, from the hospital to the patient’s medication use at home.

Aim In preparation for randomised controlled trials (RCTs), this study aimed (1) to investigate the feasibility of recruitment and retention of patients and data collection to reduce medication discrepancies at discharge and improve medication adherence and (2) to explore the outcomes of the interventions.

Method Participants were recruited from a hospital and a residential area. Hospital patients participated in a pharmacist-led intervention to establish a correct medication list upon discharge and a follow-up interview two weeks post-discharge. All participants received a person-centred adherence intervention for three to six months. Discrepancies in the medication lists, the Beliefs about Medicines Questionnaire (BMQ-S), and the Medication Adherence Report Scale (MARS-5) were assessed.

Results Of 87 asked to participate, 35 were included, and 12 completed the study. Identifying discrepancies, discussing discrepancies with physicians, and performing follow-up interviews were possible. Conducting the adherence intervention was also possible using individual health plans for medication use. Among the seven hospital patients, 24 discrepancies were found. Discharging physicians agreed that all discrepancies were errors, but only ten were corrected in the discharge information. Ten participants decreased their total BMQ-S concern scores, and seven increased their total MARS-5 scores.

Conclusion Based on this study, conducting the two RCTs separately may increase the inclusion rate. Data collection was feasible. Both interventions were feasible in many aspects but need to be optimised in upcoming RCTs.

The integration between cloud computing and vehicular ad hoc networks, namely, vehicular clouds (VCs), has become a significant research area. This integration was proposed to accelerate the adoption of intelligent transportation systems. The trustworthiness in VCs is expected to carry more computing capabilities that manage large-scale collected data. This trend requires a security evaluation framework that ensures data privacy protection, integrity of information, and availability of resources. To the best of our knowledge, this is the first study that proposes a robust trustworthiness evaluation of vehicular cloud for security criteria evaluation and selection. This article proposes three-level security features in order to develop effectiveness and trustworthiness in VCs. To assess and evaluate these security features, our evaluation framework consists of three main interconnected components: 1) an aggregation of the security evaluation values of the security criteria for each level; 2) a fuzzy multicriteria decision-making algorithm; and 3) a simple additive weight associated with the importance-performance analysis and performance rate to visualize the framework findings. The evaluation results of the security criteria based on the average performance rate and global weight suggest that data residency, data privacy, and data ownership are the most pressing challenges in assessing data protection in a VC environment. Overall, this article paves the way for a secure VC using an evaluation of effective security features and underscores directions and challenges facing the VC community. This article sheds light on the importance of security by design, emphasizing multiple layers of security when implementing industrial VCs.

To consider the climate and strive to reduce greenhouse gas emissions is a current issue in today's society. The outer wall hybrid sandwich wall is a new, more environmentally friendly wall type that is being researched for use in the market. The purpose of this study is to analyze whether the hybrid sandwich wall is a better choice for future construction projects and to compare it to the semi-sandwich wall. The study is limited to examining LCA module A (A1-A5) and module C (C1-C4), as well as how the pile foundation is affected by the use of the hybrid sandwich wall.

To conduct this investigation, literature studies, quantitative, and qualitative methods were used. The quantitative method involved climate calculations performed both manually and using the Bidcon and BM Tools software. With the assistance of the company Sigma Civil, a reference project was provided where the hybrid element could be tested. The qualitative method consisted of an interview study with Håkan Arnebrant, Sales Development Manager at Metsä Wood, who works with Kerto LVL and has background information on the hybrid sandwich wall. The software used to conduct the study was FEM-Design for load calculations, BM and Bidcon for LCA analysis.

The results of the study showed that the LCA analysis of module A indicated a reduction in carbon dioxide emissions by 28 000 kg Co2e when using the hybrid sandwich wall. For module C, emissions decreased by 1 000 kg Co2e. Additionally, during the element exchange, the self-weight of the outer wall decreased by 1,8 MN, which corresponded to the replacement of only six out of the total 27 piles along the facade with RD140. This resulted in a reduction of carbon dioxide emissions by only 1 600 kg Co2e for module A and 20 kg Co2e for module C. The cost savings for piles after the element exchange amounted to 15 600 SEK, and the total cost savings for the entire building during the element exchange were 235 000 SEK. Despite this, the hybrid sandwich wall also contributed to a 9% lower energy consumption. However, in conclusion, the hybrid element is considered a better, more environmentally friendly alternative for future construction projects.

Despite the benefits that BIM has on a project, there are still companies that choose to create their APD plans in the traditional way. The reason why there are still companies that draw up APD plans on the traditional working method is that they do not have sufficient will or knowledge to change working method despite the method being considered uncertain and time consuming. Instead, there has been a new working method for producing plans and drawings that will replace the traditional working method. This working method creates models in 3D where the constituent building components also contain information. This working method is known as BIM as a wound for building information modeling. The model that is established with BIM and which contains information about the available building components is called the BIM model. BIM as a working method can in turn be used to create APD plans with the help of supporting tools such as SketchUp and Revit, which brings many benefits.

This study therefore aims to investigate how APD plans are visualized in the current situation and to inform which factors all construction companies must take into account when choosing tools for visualization of the construction site. Advantages, disadvantages and obstacles will be highlighted in this study with regard to 3D and BIM in order to investigate which dimension is best suited for visualization of the APD plan and which dimension the APD plan is visualized with at present. Another purpose is to investigate where in the construction process the APD Plan should be integrated. The focus will be on demonstrating the benefits of expanding the use of 3D and BIM-related APD visualization tools, respectively. What is addressed in the issues is what are the different advantages and disadvantages as well as obstacles that exist with applying 3D and BIM when visualizing APD plans. In addition, two different visualizations are made with 3D and BIM tools to show how the APD plan is visualized.

The most useful dimension in visualizing the APD plan is 2D where the APD plan is created with Bluebeam. There are some companies that have switched to 3D in visualization but which are combined with 2D drawings or sketches. Visualization with BIM has not been relevant for all the companies interviewed. On the other hand, the pre-designed BIM models are used as part of the 3D visualization in order to create as realistic a visualization as possible. The advantages of visualizing an APD plan with 3D and BIM tools are that it provides a realistic picture of what the construction site will look like and that risks, opportunities and problems that could not be detected with the 2D model become detectable. The disadvantage, however, of visualizing an APD plan with 3D or BIM tools is that the files can become too heavy, which in turn leads to the tool becoming difficult to handle and perceived as choppy. However, what prevents many from implementing 3D and BIM-related tools is the human factor that puts a stop to development, where human conveniences and work routines are crucial for the implementation of the tools. The most important factors that a company should consider when choosing tools when visualizing APD plans are Profitability, user experience, compatibility and support.

The time to treatment plays a major factor in recovery for stroke patients, and simulation techniques can be valuable tools for testing healthcare policies and improving the situation for stroke patients. However, simulation requires individual-level data about stroke patients which cannot be acquired due to patient’s privacy rules. This thesis presents a hybrid simulation model for generating a synthetic population of stroke patients by combining Agent-based and microsimulation modeling. Subsequently, Agent-based simulation is used to estimate the locations where strokes happen. The simulation model is built by conducting the Design Science research method, where the simulation model is built by following a set of steps including data preparation, conceptual model formulation, implementation, and finally running the simulation model. The generated synthetic population size is based on the number of stroke events in a year from a Poisson Point Process and consists of stroke patients along with essential attributes such as age, stroke status, home location, and current location. The simulation output shows that nearly all patients had their stroke while being home, where the traveling factor is insignificant to the stroke locations based on the travel survey data used in this thesis and the assumption that all patients return home at midnight.

For patients suffering from a stroke, the time until the start of the treatment is a crucial factor with respect to the recovery from this condition. In rural regions, transporting the patient to an adequate hospital typically delays the diagnosis and treatment of a stroke, worsening its prognosis. To reduce the time to treatment, different policies can be applied. This includes, for instance, the use of Mobile Stroke Units (MSUs), which are specialized ambulances that can provide adequate care closer to where the stroke occurred. To simulate and assess different stroke logistics policies, such as the use of MSUs, a major challenge is the realistic modeling of the patients. In this article, we present an approach for generating an artificial population of stroke patients to simulate when and where strokes occur. We apply the model to the region of Skåne, where we investigated the relevance of travel behavior on the spatial distribution of stroke patients.

For acute medical conditions, for instance strokes, the time until the start of the treatment is a crucial factor to prevent a fatal outcome and to facilitate the recovery of the patient’s health. Hence, the planning and optimization of patient logistics is of high importance to ensure prompt access to healthcare facilities in case of medical emergencies. Computer simulation can be used to investigate the effects of different stroke logistics policies under realistic conditions without jeopardizing the health of the patients. The success of such policies greatly depends on the behavior of the individuals. Hence, agent-based simulation is particularly well-suited as it imitates human behavior and decision-making by means of artificial intelligence, which allows for investigating the effects of policies under different conditions. Agent-based simulation requires the generation of a realistic synthetic population, that adequately represents the population that shall be investigated such that reliable conclusions can be drawn from the simulation results. In this article, we propose a process for generating an artificial population of potential stroke patients that can be used to investigate the effects of stroke logistics policies using agent-based simulation. To illustrate how this process can be applied, we present the results from a case study in the region of Skåne in southern Sweden, where a synthetic population of stroke patients with realistic mobility behavior is simulated.