Publikationer från Mälardalens högskola
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Automatic Navigation and Self-Driving Technology in Agricultural Machinery : A State-of-the-Art Systematic Review
No full textThe advent of automatic navigation and self-driving technology in agricultural machinery has transformed modern farming by enhancing efficiency and safety. This systematic review aims to evaluate the development, implementation, and impact of self-driving technology in agriculture. We synthesized recent advancements and research findings on the integration of Global Positioning System (GPS), machine learning algorithms, and sensor technologies in agricultural machinery. Key applications of self-driving machinery in planting, harvesting, and field monitoring were explored, with findings showing improvements in farm productivity, reduced operational costs, and enhanced worker safety. Despite the benefits, challenges such as technological barriers, regulatory issues, and infrastructure limitations remain. This review informs stakeholders about the future potential of self-driving technology in promoting sustainable and precision farming practices
A critical review and meta-analysis of studies investigating the effects of the professional development teachers typically receive
No full textIn this review, we map and summarize studies examining the effects of teachers’ participation in professional development (PD) on teaching practices and student achievement based on nationally representative datasets, reflecting both the teacher population and the PD they typically receive. We also critically assess the statistical approaches used in these studies to evaluate the credibility and robustness of their findings. The reviewed studies demonstrate that large-scale datasets (e.g., TIMSS and NAEP) offer valuable opportunities to study PD in representative settings. However, only a minority of the studies adequately address the methodological challenges associated with these datasets. As a result, while our meta-analysis indicates that PD participation correlates with teaching practices and student achievement, we caution against interpreting these results as causal due to methodological limitations in most of the reviewed studies. Finally, we propose strategies for future research to produce more credible results
A GIS-portal platform from the data perspective to energy hub digitalization solutions- A review and a case study
No full textThe emergence of Geographic Information Systems (GIS) web platforms provides unique opportunities for human societies. GIS web platform technology has a two-way function, utilizing data obtained from physical and virtual environments to create harmony between the two. This review and case study paper examines the recent development and implementation of GIS web technology, focusing on urban areas and city scales. Firstly, this article reviews technology trends in online GIS web platform tools by identifying key features and applications, including their role in decision-making support. Secondly, it describes the GIS-Web platform, data sharing framework, the end-user services integrated, case study and project overview, platform digitalization as next generation. Thirdly, a new energy data portal called “NRGYHUB” is introduced for municipal urban areas in Västerås City, Sweden. This GIS portal platform provides hourly data from thousands of energy meters, collected from electrical and heating energy networks to develop, maintain, and showcase a collection of city-wide GIS tools that assist in creating, implementing, and managing innovative services for urban planning in Västerås City. Additionally, this paper presents a Geospatial Artificial Intelligence (GeoAI) approach for generating wind power projection maps using Machine Learning (ML) models which collectively aim to provide insightful wind power forecasts under the effects of climate change focusing on Västerås. Time series data for each grid cell served as inputs for the Radial Basis Functions (RBF) models, incorporating wind speed projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) along with other influential variables, such as pressure gradient, temperature gradient, humidity, and Digital Elevation Model (DEM) data. The performance of the ML models was rigorously evaluated using multiple statistical metrics, including bias, Mean Absolute Error (MAE), Correlation Coefficient (Corr), Mean Error (ME), and Root Mean Square Error (RMSE). These metrics enabled a thorough assessment of the model's accuracy and bias-correction capabilities, ultimately improving the reliability of wind speed projections for the study area
AI in Qualitative Health Research Appraisal : Comparative Study
No full textBackground: Qualitative research appraisal is crucial for ensuring credible findings but faces challenges due to human variability. Artificial intelligence (AI) models have the potential to enhance the efficiency and consistency of qualitative research assessments. Objective: This study aims to evaluate the performance of 5 AI models (GPT-3.5, Claude 3.5, Sonar Huge, GPT-4, and Claude 3 Opus) in assessing the quality of qualitative research using 3 standardized tools: Critical Appraisal Skills Programme (CASP), Joanna Briggs Institute (JBI) checklist, and Evaluative Tools for Qualitative Studies (ETQS). Methods: AI-generated assessments of 3 peer-reviewed qualitative papers in health and physical activity–related research were analyzed. The study examined systematic affirmation bias, interrater reliability, and tool-dependent disagreements across the AI models. Sensitivity analysis was conducted to evaluate the impact of excluding specific models on agreement levels. Results: Results revealed a systematic affirmation bias across all AI models, with “Yes” rates ranging from 75.9% (145/191; Claude 3 Opus) to 85.4% (164/192; Claude 3.5). GPT-4 diverged significantly, showing lower agreement (“Yes”: 115/192, 59.9%) and higher uncertainty (“Cannot tell”: 69/192, 35.9%). Proprietary models (GPT-3.5 and Claude 3.5) demonstrated near-perfect alignment (Cramer V=0.891; P<.001), while open-source models showed greater variability. Interrater reliability varied by assessment tool, with CASP achieving the highest baseline consensus (Krippendorff α=0.653), followed by JBI (α=0.477), and ETQS scoring lowest (α=0.376). Sensitivity analysis revealed that excluding GPT-4 increased CASP agreement by 20% (α=0.784), while removing Sonar Huge improved JBI agreement by 18% (α=0.561). ETQS showed marginal improvements when excluding GPT-4 or Claude 3 Opus (+9%, α=0.409). Tool-dependent disagreements were evident, particularly in ETQS criteria, highlighting AI’s current limitations in contextual interpretation. Conclusions: The findings demonstrate that AI models exhibit both promise and limitations as evaluators of qualitative research quality. While they enhance efficiency, AI models struggle with reaching consensus in areas requiring nuanced interpretation, particularly for contextual criteria. The study underscores the importance of hybrid frameworks that integrate AI scalability with human oversight, especially for contextual judgment. Future research should prioritize developing AI training protocols that emphasize qualitative epistemology, benchmarking AI performance against expert panels to validate accuracy thresholds, and establishing ethical guidelines for disclosing AI’s role in systematic reviews. As qualitative methodologies evolve alongside AI capabilities, the path forward lies in collaborative human-AI workflows that leverage AI’s efficiency while preserving human expertise for interpretive tasks
An Empirical Investigation of Requirements Engineering and Testing Utilizing EARS Notation in PLC Programs
No full textRegulatory standards for engineering safety-critical systems often demand both traceable requirements and specification-based testing, during development. Requirements are often written in natural language, yet for specification purposes, this may be supplemented by formal or semi-formal descriptions, to increase clarity. However, the choice of notation of the latter is often constrained by the designers’ training, skills, and preferences. The Easy Approach to Requirements Syntax (EARS) addresses the inherent imprecision of natural language requirements concerning potential ambiguity and lack of accuracy. This paper investigates requirements specification using EARS, and specification-based testing of embedded software written in the IEC 61131-3 language, a programming standard for developing programmable logic controllers (PLC). Further, we study, utilizing an experiment, how human participants translate natural language requirements into EARS and how they use the latter to test PLC software. We report our observations during the experiments, including the type of EARS patterns that participants use to structure natural language requirements and challenges during the specification phase, and present the results of testing based on EARS-formalized requirements in real-world industrial settings
Assessing an Outdoor Office Work Intervention : Exploring the Relevance of Measuring Frequency, Perceived Stress, Quality of Life and Connectedness to Nature
No full textBackground/Objectives: Outdoor office work (OOW) has been shown to promote health and well-being and to reduce stress. However, few empirical studies have examined research-based, simple approaches to implementing OOW. In preparation for a larger study, we conducted a feasibility study focusing on limited efficacy testing of potentially relevant outcomes for future OOW research. Methods: The simple Pop Out OOW programme consists of three workshops and access to online tutorials designed to support employees in transitioning relevant everyday office tasks outdoors. Before and after a 12-week intervention, employees from five small- and medium-sized Danish companies (N = 70) reported their weekly number of days including OOW, connectedness to nature (CNS and INS), Perceived Stress Scale (PSS), and well-being (WHO-5) scores. Results: At baseline, higher CNS scores were associated with a greater number of days including OOW per week (r = 0.25, p = 0.020). Following the intervention, participants reported a significant increase in the number of days per week with OOW (p < 0.01, d = 0.65). CNS scores also increased significantly (p = 0.019, d = 0.32). No significant changes were observed in stress or well-being scores across the entire sample. However, participants with PSS scores exceeding a national Danish criterion for high stress (n = 11) exhibited a significant and substantial reduction in perceived stress (p < 0.01, d = 1.00). Conclusions: Days including OOW, along with PSS and CNS scores, may serve as relevant outcome measures in future studies evaluating interventions aimed at promoting OOW. These outcomes should be assessed in larger and more diverse and controlled samples to establish generalisability
SJUKSKÖTERSKANS ERFARENHETER AV VÅRD I SEN PALLIATIV FAS OCH LIVETS SLUTSKEDE : Allmän litteraturöversikt
No full textMULTI-MODAL DOCUMENT CONTEXT SEARCH with LLMs for MANUFACTURING INDUSTRIES
No full textManufacturing industries rely on vast collections of multi-modal documents for product development and maintenance, encompassing hardware specifications, soft- ware documentation, and technical diagrams across diverse formats. Efficiently retrieving relevant information from these complex documents presents significant challenges due to their domain-specific terminology and structural complexity. This thesis investigates the application of Retrieval-Augmented Generation (RAG) sys- tems with Large Language Models (LLMs) for manufacturing document search and question answering. The research compares traditional vector-based RAG approaches with advanced graph-based methods like LightRAG to evaluate their effectiveness for industrial documentation retrieval. A comprehensive preprocessing pipeline was de- veloped to handle multi-modal content, extracting structured information from text, tables, and technical diagrams while preserving document context. Experimental evaluations using documents from the European Union Agency for Railways demon- strate that different RAG architectures excel in different scenarios: vector-based approaches with advanced prompting strategies performed well for specific low-level queries, while graph-based global retrieval strategies showed superior performance for complex questions requiring synthesis across multiple documents. While automated metrics showed advanced prompting strategies achieving higher ROUGE and BLEU scores, manual analysis revealed that graph-based methods often produced more comprehensive and contextually relevant answers for complex queries. This research contributes to the understanding of RAG systems for industrial applications and provides insights for optimizing multi-modal document retrieval in manufacturing contexts
Support for innovation - Balancing the paradox of innovation and democracy in municipalities
No full textThis thesis investigates how innovation tensions surface and are managed when a public organization intends to build support for innovation. Based on paradox theory, the study conceptualizes innovation tensions as persistent, interdependent contradictions that cannot be resolved but must be confronted and worked through. This research is contextually situated as an insider research project, where the author works as an embedded researcher within a Swedish municipality, combining academic and practical responsibilities. Public sector innovation is inherently paradoxical, shaped by the tensions it faces between the need for flexibility, experimentation, relevance, and the principles of democratic governance, which emphasize stability, accountability, and predictability. The thesis introduces three key sources of the paradoxes that influence innovation support in the public sector: (1) the innovation imperative; (2) organizational fragmentation at the local level; and (3) the conflict between risk taking and responsibility. Adopting a multilevel analytical approach, the study examines how innovation tensions surface and how responses to them have both organizational and individual dimensions. It finds that responses to tensions are multidimensional and dynamic, and influenced by a continuous interplay between organizational and individual level factors. Central in shaping how innovation is supported within fragmented organizations is the identified phenomenon of departmental variation. Siloed operations and departmental drift present ongoing challenges for maintaining support for innovation within organizations. Thus, innovation support must be both intentionally built, through strategic ambitions reflected in both policy and routines, and actively balanced and maintained by individual managers, by continuously countering organizational biases toward stability and fragmentation. The thesis concludes that, for systematic innovation to take place, a more nuanced understanding of what a supportive environment means should be developed for public sector organizations. This concept could better capture the evolving interplay between innovation and standard operations within public sector organizations and offer a valuable framework for understanding the tensions associated with the inherent paradox between innovation and democracy in the public sector and to the further development of appropriate forms of support
SJUKSKÖTERSKORS ERFARENHETER AV KOMMUNIKATION INOM PALLIATIV VÅRD I LIVET SLUTSKEDE : En allmän litteraturöversikt
No full textSAMMANFATTNING Bakgrund: Kommunikation är en grundläggande del av sjuksköterskors arbete inom palliativ vård i livets slutskede. En god kommunikation stärker relationen mellan sjuksköterska, patient och anhöriga, och bidrar till trygghet, delaktighet och värdighet. Trots detta visar tidigare forskning att kommunikationen ofta brister på grund av tidsbrist, otydlig ansvarsfördelning, kulturella skillnader och emotionella faktorer Syfte: att skapa en översikt av sjuksköterskors erfarenheter av kommunikation inom palliativ vård i livets slutskede. Metod: En allmän litteraturöversikt genomfördes där elva vetenskapliga artiklar inkluderades, varav åtta kvalitativa och tre kvantitativa. Resultat: fyra teman identifierades:att bygga förtroendefulla relationer, att påverkas av vårdkulturen, att hantera hinder i kommunikationen samt att utveckla kommunikativ kompetens. Sjuksköterskor betonade vikten av empatisk närvaro, tydlig och anpassad information samt att det fanns tydliga ansvarsfördelning för att kunna kommunicera tryggt och professionellt. Slutsats: Kommunikation i livets slutskede är en komplex process som kräver både mänsklig närvaro och professionell kompetens. För att kunna erbjuda god vård i livets slutskede krävs ökad utbildning, handledning, tydligare riktlinjer, tid och teamstöd. Nyckelord: Erfarenheter, Kommunikation, litteraturöversikt, livets slutskede, palliativ vård, sjuksköterska