Blekinge Institute of Technology
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Utveckling av miljonprogramsområden : – ett gestaltningsförslag för Rosengård
No full textSveriges stadsutveckling står inför stora utmaningar till följd av urbanisering och befolkningstillväxt. Förtätning ses som en central strategi för att möta bostadsbristen och skapa mer hållbara, funktionsblandade stadsmiljöer. Samtidigt finns kritik mot hur förtätning påverkar socioekonomiskt utsatta områden, där det kan leda till gentrifiering och ökad segregation. Miljonprogramsområden, ofta präglade av sociala problem och bristfällig fysisk struktur, har blivit mål för förtätningsinsatser. Tidigare forskning visar att dessa åtgärder både kan bidra till förbättrad livskvalitet och nya sociala utmaningar. Syftet med arbetet är att undersöka lämpliga förtätningsstrategier och ta fram ett gestaltningsförslag för miljonprogramsområden med särskilt fokus på funktionsblandning. För att undersöka detta har en fallstudie i Malmö tagits fram. De tillämpade metoder utgörs av en kombination som möjliggjort en bred och fördjupad förståelse för ämnet. Genom kvalitativ innehållsanalys har insikter kring förtätning och funktionsblandning kunnat utvecklas, medan observationsmetoden gett en konkret förståelse för Rosengård fysiska och sociala kontext. Baserat på kunskapsöversikten och platsanalysen har flera mål och strategier tagits fram och tillämpats i ett planförslag för delområdet Apelgården i Rosengård. Genom utveckling av funktionsblandad bebyggelse och nya stråk som kopplar samman området med angränsande stadsdelar, skapas en mer tillgänglig och levande stadsdel. Slutsatsen visade på att förtätning i miljonprogramsområde är en positiv utveckling som kan hantera sociala utmaningar genom en noggrann tillämpning av strategier som utgår från platsens förutsättningar och människornas behov
Analyzing the Performance Scaling of Radiance Cascades : Exploring a Novel Solution for Dynamic Diffuse Real-Time Global Illumination
No full textRadiance cascades (RC) is a novel deterministic technique for dynamic real-time global illumination, created by Alexander Sannikov. The technique is based on capturing scene radiance using multi-level grids of light probes, where each cascade level employs different probe densities and directional sampling rates to sample emissive objects at varying scales of a scene. Despite its recent adaptation in commercial applications, a comprehensive multi-parameter performance analysis of a 3D RC implementation utilizing hardware-accelerated ray tracing remains unexplored. This thesis aims to assess how 3D RC performance scales with respect to render resolution, probe spacing, cascade level count, and initial ray count per probe in terms of frame time and VRAM usage, establishing a baseline for real-time feasibility of the technique. A 3D RC implementation was developed using DirectX 12 to enable the usage of hardware-accelerated ray tracing on an RTX 3080 10GB GPU. Performance measurements were collected with a total of 48 parameter configurations at 1920x1080 and 2560x1440 resolutions, each configuration tested 30 times in a Sponza evaluation scene consisting of 262k triangles. To make the technique feasible on consumer-grade GPUs, the implementation leveraged pre-averaging optimizations to reduce total VRAM costs by a factor of 4. Frame time measurements yielded tight 95% confidence intervals (within ±0.04 ms of the mean for all configurations), which enabled reliable comparative analysis between parameter configurations. Probe spacing demonstrated the strongest performance impact, suggesting a super-linear scaling, while resolution scaling aligned with the theoretical pixel ratios between target resolutions. Ray count increases produce sub-linear frame time scaling, demonstrating efficiencies that could not solely be attributed to implementation specifics, alluding to hardware-level related speed-ups. The RC Gathering pass (ray tracing pass) consumed 87-96% of frame time across all testing configurations. At 1080p, 79.2% of configurations achieved frame times below 33.33 ms, with 62.5% falling under 16.67 ms when measuring only RC-specific passes. The observed scaling patterns suggest that RC is able to achieve real-time performance assuming appropriate parameter selection, particularly when choosing probe spacing values of 2 or greater. The technique shows promise performance-wise but future work is left for: visual evaluation, analysis of precise hardware counters, and more comprehensive statistical analysis of measurement data, which this thesis did not cover. This thesis contributes identification of fundamental performance scaling characteristics of 3D RC and optimistically encourage further exploration of this novel technique as a real-time global illumination solution
I ständig beredskap – om att aldrig riktigt kunna andas ut : En allmän litteraturöversikt om orsaker till arbetsrelaterad stress hos sjuksköterskor på akutmottagning
No full textBakgrund: Grundutbildade sjuksköterskor har en överrisk för sjukdomsfall som i synnerhet består av stressrelaterad ohälsa. Att arbeta på en akutmottagning som sjuksköterska kan upplevas som stressigt. Arbetet är utmanande och patienternas tillstånd kan ändras snabbt. Antalet besökande på akutmottagningar i Sverige ökar och att besöka akutmottagningar som patient kan väcka känslor, där ibland rädsla. Säker vård är viktigt inom alla sektioner av hälso- och sjukvården, dock visar en tillsyn att patientsäkerhets risker identifierats vid samtliga av Sveriges akutsjukhus. Syfte: Beskriva orsaker till arbetsrelaterad stress hos sjuksköterskors på akutmottagning. Metod: Allmän litteraturöversikt av kvantitativ och kvalitativ forskning, tolv kvalitativa och en kvantitativ studie inkluderades efter genomförd dataanalys. Dataanalysen följde Fribergs (2022) beskrivning. Resultat: Den allmänna litteraturöversiktens analys resulterade i två huvudkategorier med tillhörande underkategorier. Att arbeta i en utmanande vårdmiljö och Att påverkas psykiskt och fysiskt av våld – en orsak till arbetsrelaterad stress. Huvudkategorin Att arbeta i en utmanande vårdmiljö har tre underkategorier, Att arbeta på akutmottagning med bristande resurser, Att arbeta i en stressig arbetsmiljö och Covid-19. Huvudkategorin Att påverkas psykiskt och fysiskt av våld – en orsak till arbetsrelaterad stress har en underkategori, Att möta våld på sin arbetsplats. Slutsats: Syftet med denna allmänna litteraturöversikt var att beskriva orsaker till arbetsrelaterad stress hos sjuksköterskor på akutmottagning. Resultatet visar att arbetsrelaterad stress främst orsakas av hög arbetsbelastning och bristande resurser, där arbetsgivaren ansvarar för att säkerställa adekvat bemanning och resurser. Arbetsrelaterad stress kan leda till utbrändhet, trötthet, sjukfrånvaro och påverkan på patientsäkerheten, vilket understryker vikten av förbättrade organisatoriska förutsättningar. Covid-19 förvärrade befintliga problem och belyste särskilt behovet av skyddsutrustning vid kris. Kollegialt stöd är av vikt för att hantera upplevelse av hot och våld. Sammantaget framhålls en hållbar arbetsmiljö som centralt för sjuksköterskors hälsa samt för att säkerställa trygg och säker vård för patienterna
Comparing Serverless Computing Platforms : A Performance and Cost Analysis
No full textBackground: Serverless computing, primarily Function as a Service (FaaS), is transforming cloud computing by allowing developers to focus on application logic without managing underlying infrastructure. While this model offers potential cost savings and rapid deployment, challenges remain concerning its performance and cost efficiency. Objectives: This thesis aims to analyze the trade-offs between performance and cost across two major serverless platforms: AWS Lambda and Azure Functions. Specifically, it investigates how different configurations (e.g., memory allocation) and workload characteristics affect performance and cost, providing actionable insights into optimizing serverless applications. Methods: A mixed-method approach was used to explore these dynamics. Quantitative experiments were conducted to measure the impact of configurations across the platforms. The configurations tested include memory allocations, and invocation frequencies. In parallel, surveys were administered to gather qualitative insights from cloud architects and developers, offering perspectives on practical optimization strategies and real-world challenges. Results: The findings indicate that optimization of serverless configurations involves a complextrade-off between cost efficiency and performance, influenced by workload types and provider-specific factors. AWS and Azure Cloud exhibited distinct performance and cost patterns depending on the workload. For instance, higher memory allocations generally led to better performance but increased costs, while resource-constrained settings significantly impacted latency-sensitive applications. Conclusions: This study contributes to understanding the performance-cost relationship in serverless computing, highlighting specific optimization strategies suitable for each cloud provider. The results suggest that while each platform has strengths, careful workload specific configurations are essential for achieving an optimal balance between cost and performance.
Hyperspectral retinal imaging to detect Alzheimer’s disease in a memory clinic setting
No full textBackground Previous literature indicate retinal hyperspectral imaging as a non-invasive method with the potential for identifying amyloid-beta (Aβ) protein deposits. Current diagnostic methods, such as cerebrospinal fluid analysis or positron emission tomography, are costly, invasive, and non-scalable. Hyperspectral imaging offers a potentially accessible alternative for early detection of Alzheimer’s disease. The aim of this study is to investigate the potential of retinal hyperspectral imaging in identifying Aβ-positive patients within a clinical cohort from a memory clinic. Methods A prospective cross-sectional cohort study was conducted between January 2023 and May 2024 at a single memory clinic in Sweden. The study recruited 57 patients (35 Aβ-positive and 22 Aβ-negative) who underwent lumbar puncture as part of their diagnostic workup for cognitive complaints. Retinal hyperspectral images were captured from all participants at the time of their lumbar puncture and again 2–4 weeks later. Data was collected from five anatomical regions of the retina (Superior 1, Superior 2, Inferior 1, Inferior 2, and the center of the Fovea).The main outcome was the Aβ status (Aβ-positive or Aβ-negative). Catboost machine learning models were trained on hyperspectral imaging data to predict Aβ status. A nested cross-validation approach was used to train and evaluate classification models. Performance metrics included area under the curve (AUC), accuracy, sensitivity, and specificity. Results The best-performing model used the combination of regions Superior 1, Superior 2, and center of the fovea, achieving a mean AUC of 0.77 (0.05), mean accuracy of 0.66 (0.03), and mean sensitivity of 0.73 (0.13) and mean specificity of 0.55 (0.12). Performance was consistent across outer folds. Models using all five regions or less informative combinations yielded lower and more variable results. Conclusions Retinal hyperspectral imaging combined with the Catboost algorithm demonstrated significant potential as a non-invasive biomarker for detecting Alzheimer’s disease in a consecutive clinical cohort. Further studies should validate these findings in larger, more diverse populations and explore the integration of hyperspectral imaging with other diagnostic modalities. Limited sample size and imaging constraints highlight the need for validation in diverse clinical settings. Trial registration ClinicalTrials.gov, ID: NCT05604183 (registration date: 2022-10-27)
Lokalisering av nya verksamhetsområden : en tvåfallsstudie om hur processen för lokalisering av nya verksamhetsområden ser ut i svensk kommunal fysisk planering
No full textUtbredning av industriområden, logistikcentraler och externhandel bidrar till en pågående stadsutglesning. Denna studie tar sig an att undersöka hur processen för lokalisering av nya verksamhetsområden ser ut i svensk kommunal fysisk planering. Studien har genomförts som en tvåfallsstudie i två skånska kommuner. I studien har tjänstepersoner som primärt arbetar med översiktsplanering intervjuats samt kvalitativa innehållsanalyser på översiktsplaner och relevanta kommunala policydokument har utförts. Som ett komplement har kompletterande empiri inhämtats via en semistrukturerad intervju med en organisation respektive en kvalitativ innehållsanalys av tidningsartiklar. Studien visar att processen för lokalisering av nya verksamhetsområden till största del utgörs av processen för framtagande av översiktsplaner. Det framgår att flera olika kompetenser inom kommunen samverkar vid framtagandet och att detta gemensamma arbete skapar förutsättningar för att lokalisera nya verksamhetsområden till den mark som är mest lämpad för ändamålet. Kontinuiteten i kommunernas arbete brister dock när framtagande av översiktsplan ej pågår. Den bristande kontinuiteten förmildras dock genom arbete med andra kommunala verktyg. Studien konstaterar också att kortare planperioder kan gynna arbetet med lokaliseringar av nya verksamhetsområden genom att kontinuitet upprätthålls samtidigt som prognostiseringar för behovet av nya verksamhetsområden kan bli mer förankrade i närtid. Studien konstaterar att det historiskt har lokaliserats verksamhetsområden utan ett hushållningsperspektiv men att en ökad insikt om detta har utvecklats. Utifrån ett hushållningsperspektiv framgår det också att det finns en ökad insikt i att undanta jordbruksmark från exploatering för nya verksamhetsområden. Att undanta jordbruksmark från exploatering bidrar till att Sverige kan stärka sin livsmedelsförsörjning och beredskap och på så sätt i förlängningen också få konkurrensfördelar vid export av livsmedel. Avslutningsvis konstaterar studien att prissättning av mark är en viktig faktor i hur effektiv markanvändningen faktiskt blir. Prissättningen påverkar hur stadssilhuetten ser ut. Studien konstaterar också att silhuetten, genom volymer och höjder, är problematiskt att hantera vid lokaliseringar i översiktsplaneringen. Men samtidigt är det viktigt att arbeta vidare med volymer och höjder i den efterföljande planeringen och byggandet. Likaså behövs mer uppmärksamhet ägnas åt plangränsens betydelse
Developing a Framework for Semantic Disagreement Interruption Turn-taking Model
No full textBackground: Spoken Dialogue Systems increasingly strive to exhibit natural and context-aware conversational behaviour. While existing turn-taking models have achieved progress in predicting turn-shifts and backchannels using prosodic or lexical cues, the ability to strategically interrupt based on semantic understanding, such as when a user expresses disagreement or factual inconsistency, remains largely unexplored. Objectives: This thesis investigates the development of a real-time interruption framework capable of detecting semantic disagreement between a user’s spoken input and a trusted reference statement. The objective is to enable a conversational agent to make contextually appropriate interruption turn-taking decisions by modelling both the stance relationship and the pragmatic conditions under which interruptions are justified. Methods: A custom dataset was constructed by adapting the Fake News Challenge (FNC-1) corpus into a conversational, speech-like format encompassing eight semantically nuanced classes. The framework recommends suitable components for real-time operation, including an automatic speech recognition (ASR) architecture for transcription, scalable reference retrieval through similarity search, and a pre-trained encoder-only transformer for stance classification. Model performance was evaluated using accuracy, macro F1, and an F1-score on the class of interest. Results: The proposed dataset comprises approximately 1,400 labelled text pairs across eight semantically nuanced classes. The Transformer Transducer architecture was identified as an appropriate ASR model for real-time transcription. The DistilBERT encoder-only transformer was fine-tuned and evaluated under varying training configurations, achieving a best accuracy of 0.66, macro F1 of 0.51, and 0.48 F1 score on the class of interest. Precision–recall analysis further revealed that model responsiveness could be fine-tuned via threshold selection to balance conservative and assertive interruption strategies. The framework also demonstrated scalability through similarity search and responsiveness through parallel ASR-classification processing. Conclusions: The study highlights both the feasibility and challenges of modelling interruption behaviour driven by semantic disagreement. Although current performance remains moderate due to dataset size and class imbalance, the proposed framework establishes a foundation for real-time, semantically grounded interruption modelling. Future directions include integrating spoken language models, reasoning-based decision mechanisms, and empirical identification of temporal cues for interruption timing to develop more socially aware and human-like conversational agents
Industrial Practices of Requirements Engineering for ML-Enabled Systems in Brazil : An Extended Analysis
No full text[Context] In Brazil, 41% of companies use machine learning (ML) to some extent. However, several challenges have been reported when engineering ML-enabled systems, including unrealistic customer expectations and vagueness in ML problem specifications. Literature suggests that Requirements Engineering (RE) practices and tools may help to alleviate these issues, yet there is insufficient understanding of RE’s practical application and its perception among practitioners. [Goal] This study aims to investigate the application of RE in developing ML-enabled systems in Brazil, creating an overview of current practices, perceptions, and problems in the Brazilian industry. [Method] To this end, we extracted and analyzed data from an international survey focused on ML-enabled systems, concentrating specifically on responses from practitioners based in Brazil. We analyzed the cluster of RE-related answers gathered from 72 practitioners involved in data-driven projects. We conducted quantitative statistical analyses on contemporary practices using bootstrapping with confidence intervals and qualitative studies on the reported problems involving open and axial coding procedures. [Results] Our findings highlight distinct RE implementation aspects in Brazil’s ML projects. For instance, (i) RE-related tasks are predominantly conducted by data scientists; (ii) the most common techniques for eliciting requirements are interviews and workshop meetings;(iii) there is a prevalence of interactive notebooks in requirements documentation; (iv) practitioners report problems that include a poor understanding of the problem to solve and the business domain, low customer engagement,and difficulties managing stakeholders expectations. Our analysis suggests that development methodology plays a role in these challenges. Agile methods appear to facilitate the management of customer expectations compared to traditional approaches; however, they also appear to introduce greater difficulties in problem understanding and customer involvement. [Conclusion]These results provide an understanding of RE-related practices and challenges in the Brazilian ML industry, helping to guide research and initiatives toward improving the maturity of RE for ML-enabled system projects
The pioneering role of Stanford DesignX and legacy of Larry Leifer on the field of engineering design
No full textThis retrospective paper explores the profound impact of DesignX at the Stanford Center for Design Research (CDR) on engineering design research and education. Through a historical lens, the authors examine the evolution of the DesignX laboratory and its role in fostering interdisciplinary collaboration, innovative research, and team-based research by highlighting key milestones and influential projects over time. The authors also discuss the pioneering role of Stanford Professor Larry Leifer, whose leadership of CDR for much of its history shaped the practices and methodologies of engineering design from the 1980s up through the 2020s. This paper underscores the significance of Leifer’s contributions to the academic community and the enduring legacy of DesignX in advancing the field of engineering design research and education
Triple-Use Innovation : Embedding Sustainability into Civil-Military Innovation
No full textThis paper introduces and explores triple-use innovation, a novel conceptual framework that extends beyond the established dual-use paradigm by embedding sustainability as a core dimension within innovation processes. Whereas dual-use research traditionally focuses on the civilian–military duality, triple-use innovation integrates civil, military, and sustainability domains from the outset. It argues that conventional innovation approaches create long-term vulnerabilities by relying on finite resources and infrastructures susceptible to disruption, without systematically incorporating resilience. In contrast, triple-use innovation seeks to align technological progress with societal and ecological stability by addressing how innovation can integrate crisis management, adaptation, and foresight while reducing resource intensity and unsustainable practices. Situated within planetary and social boundaries, triple-use innovation emphasises adaptability under uncertainty and offers a structure for co-designing civil, defence, and sustainability domains to maintain technological development within safe and regenerative limits. This research is performed as part of the Marine Technology Center of Sweden initiative, partly funded by the Marine Technology Center of Sweden regional fund (Region Blekinge and Blekinge Institute of Technology) and partly funded by the KK foundation as the PhD student is a Jubilee Doctoral Student. </p