Blekinge Institute of Technology
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Physical Layer Security and DOA Estimation Under Doppler Shift in Directional Modulation
No full textBackground. In wireless communication, Doppler shift—caused by relative motion between the transmitter and receiver—poses a significant challenge to Direction of Arrival (DOA) estimation. This issue is particularly critical in Directional Modulation (DM) systems, which enhance physical layer security by controlling the directionality of transmitted signals. However, existing DOA estimation methods struggle in dynamic environments where Doppler-induced distortions impact accuracy, leaving a gap in secure beamforming techniques. Objectives. This thesis proposes a novel joint Doppler-DOA estimation framework to address these challenges. The study focuses on analyzing how Doppler shift affects traditional DOA estimation methods, designing an improved algorithm for joint estimation, and evaluating its performance in varying conditions. Methods. The proposed approach is tested using MATLAB-based simulations, incorporating a Uniform Linear Array (ULA) antenna system and modeling real-world wireless scenarios. Key performance metrics are used to assess its effectiveness, including estimation accuracy, bit error rate (BER) and signal-to-interference-plus-noise ratio (SINR). Results. The findings suggest that integrating Doppler shift compensation into DOA estimation significantly improves accuracy and enhances the security of DM systems. By simulation results shows that Kalman filtering integration helps lower BER, reduce DOA estimation errors, and increase secrecy capacity across mobility scenarios. This ensures proposed model provides reliable and secure communication even in high mobility. Conclusions. The results validate the proposed system featuring MIMO processing, Kalman-based Doppler DOA estimation, and artificial noise injection (AN), which offers an improvement over traditional models. Mainly strengthens PLS by signal integration and directionality in mobility scenarios. This research contributes to developing robust and secure wireless networks, particularly for high-mobility applications such as autonomous vehicles, IoT, and next-generation communication systems
The Impact of the CHIPS Act on the Financial Performance of U.S. Semiconductor Companies
No full textBackground: The CHIPS and Science Act was introduced by the U.S. government in 2022 to strengthen domestic semiconductor manufacturing, research, and development. The policy aims to reduce dependence on foreign supply chains and enhance national competitiveness in an increasingly geopolitical industry. Purpose: This study evaluates the financial impact of the CHIPS Act on U.S. semiconductor firms by comparing performance before and after the policy’s introduction and comparing U.S. firms with their international peers. Method: A sample of semiconductor companies from America, Europe, and Asia was selected, covering the period from 2018 to 2024. Financial performance indicators such as stock price performance and revenue were collected from reliable financial databases. The data was analyzed using regression models to evaluate the financial impact of the CHIPS Act. Results and analysis: The results indicate that the CHIPS Act is positively and significantly associated with revenue growth across firms. For stock returns, the CHIPS Act alone showed no significant impact, but U.S. firms showed a positive impact compared to firms in Europe and Asia. Conclusions: The analysis showed that the US based firms experienced higher revenue growth and stock returns after the CHIPS Act compared to firms in Europe and Asia. Employee growth was also investigated, however it was not statistically significant, suggesting that no differential effect for employment in U.S. firms was seen related to non-U.S. firms. Recommendations for future research: Future research could benefit by expanding the present analysis to include a longer time frame, including more firms and other KPIs in the statistical analysis. This will strengthen the conclusion presented in this study and contribute to future research within the field
Den aktiva staden : Ett kombinerat vetenskapligt och konstnärligt arbete om hur fysisk planering kan skapa förutsättningar för rörelse och fysisk aktivitet
No full textMänniskan har genom hela vår historia haft ett grundläggande behov av rörelse och fysisk aktivitet. Att vara fysiskt aktiv medför positiva hälsoeffekter för både den fysiska och psykiska hälsan, och kan vidare bidra till att förebygga sjukdomar och negativa hälsotillstånd. Trots detta så lever många människor i Sverige en inaktiv livsstil, vilket kan skapa problem på individnivå och för samhället i stort. Människors möjligheter till fysisk aktivitet påverkas bland annat av hur städer planeras och utformas. I dagsläget är förtätning en tydlig trend i samhällsplaneringen, till följd av att Sveriges befolkning växer och att det råder brist på bostäder i många kommuner. I takt med att städer förtätas så tenderar däremot ytor som gagnar en aktiv och hälsosam livsstil att nedprioriteras eller helt försvinna. Detta motverkar möjligheten till rörelse och fysisk aktivitet och främjar i stället stillasittande beteenden. Genom att vända utvecklingen och utgå från människans behov av rörelse och fysisk aktivitet i planeringen, gör att hållbara och hälsosamma stadsmiljöer kan skapas för alla. Det här masterarbetet är ett kombinerat vetenskapligt och konstnärligt arbete som syftar till att undersöka vilka faktorer i den fysiska miljön som påverkar människors möjligheter till rörelse och fysisk aktivitet. Studien ämnar vidare att undersöka hur en centrumnära stadsmiljö kan förtätas och gestaltas med fokus på lösningar som uppmuntrar till rörelse och fysisk aktivitet. Arbetet syftar också till att föreslå lösningar i stadsplaneringen på åtgärder som ökar förutsättningarna för rörelse och fysisk aktivitet. För att undersöka arbetets syfte har metoderna dokumentär forskning och platsanalys tillämpats. Dokumentär forskning har legat till grund för arbetets kunskapsöversikt och teoretiska ramverk. Studiens teoretiska ramverk har varit konceptet 15-minuters staden. Platsanalysen har legat till grund för studiens analysdel. Utifrån arbetets vetenskapliga del har ett gestaltningsförslag tagits fram. Planområdet för gestaltningsförslaget har utgjorts av industriområdet på Lövholmen i Stockholm. Gestaltningsförslaget har syftat till att undersöka och ge förslag på åtgärder för hur rörelse och fysisk aktivitet kan främjas i samband med förtätning av Lövholmen i Stockholm. Utifrån studiens slutsatser och resultat framgår det att fyra typer av stödjande miljöer utgör en grund för hur rörelse och fysisk aktivitet kan främjas inom en centrumnära stadsmiljö. De fyra stödjande miljöerna är bebyggelse, mötesplatser, transportsystemet samt grön- och blåstrukturen. Gemensamma faktorer som vidare är betydelsefulla är att skapa förutsättningar för närhet och tillgängliga målpunkter. Samtidigt behöver stadsmiljön vara trygg, säker och anpassad för olika målgrupper och väderförhållanden. I studiens avslutande del presenteras även de målsättningar som legat till grund för gestaltningsförslaget. Målsättningarna har varit att möjliggöra för en blandad och trygg stadsmiljö samt utveckla levande mötesplatser. Målsättningar var även att främja aktiv transport samt skapa en grön och blå stadsmiljö. Studien avslutas med att formulera förslag på framtida forskningsinriktningar
AI-Driven Pattern Recognition and Object Detection : Emphasis on Precision Agriculture
No full textPrecision agriculture utilizes Artificial Intelligence (AI) and remote sensing to address challenges in sustainable food production. A significant obstacle is effective weed management, particularly for species like black-grass (Alopecurus myosuroides), which visually resembles wheat. This thesis introduces AI-driven methods using Unmanned Aerial Vehicle (UAV)-based multispectral image analysis to improve weed detection, addressing key challenges such as limited datasets, sensor misalignment, and the need for robust algorithms. The first part of the thesis addresses data scarcity using synthetic data augmentation. A study using a Mask Region-based Convolutional Neural Network (Mask R-CNN) model for black-grass detection shows that scaling foreground objects is a particularly effective technique for improving performance, providing a basis for adapting models to new field conditions with less data. The second part focuses on multispectral data quality, where sensor misalignment can corrupt Vegetation Indices (VIs) like Normalized Difference Vegetation Index (NDVI). A method for sensor calibration and image registration is presented to correct for these errors. The study then evaluates various VIs, finding that models integrating indices like Triangular Greenness Index (TGI) and Excess Green Index (ExG) show improved detection performance compared to using only the basic spectral bands, particularly between crop rows. Finally, the third part draws parallels to biometrics to explore the robustness of different network architectures. By evaluating triplet-based and Siamese networks for fingerprint recognition, it is demonstrated that clustering-based approaches using contrastive loss offer better performance with incomplete and variable data. This insight highlights broader principles for creating robust recognition systems. Overall, this thesis contributes methods for addressing key obstacles in precision agriculture, spanning data augmentation, sensor calibration, and the optimization of deep learning models. The findings of this work aim to contribute to the ongoing development of more effective agricultural practices.Paper III is excluded from the attached file because of being submitted for publication in a journal.</p
Locus of control and breathlessness : a cross-sectional analysis of 28 730 people
No full textBackground Long-term pathological breathlessness is a life-limiting symptom that risks taking control of the individual’s life. We aimed to evaluate how locus of control (LOC), an individual’s perceived control of present and past life events, relates to breathlessness in a middle-aged general population. Methods A population-based, cross-sectional analysis of people aged 50–64 years was conducted in the Swedish CArdioPulmonary bioImage Study (SCAPIS). Breathlessness was measured using the modified Medical Research Council (mMRC) breathlessness scale. LOC was assessed using five-point scales related to work, life events, perceived future, treated by other people, past changes and life improvements. The LOC factors were dichotomised as having an external or internal LOC. Logistic regression was used to examine the association between external LOC and presence of moderate/severe breathlessness (mMRC ⩾2). Associations between external LOC and higher breathlessness severity score (mMRC 0–4) were analysed using ordinal regression. The models were adjusted for age, sex, education level, pack-years of smoking, body mass index, lung function, depression and cardiorespiratory diseases. Results Of 28 730 participants (52% women), 4% experienced breathlessness. Breathlessness was related to external LOC in relation to life events (odds ratio (OR) 1.47, 95% confidence interval (CI) 1.26–1.71), future (OR 1.89, 95% CI 1.53–2.34), treated unfairly (OR 1.73, 95% CI 1.42–2.09), past changes (OR 1.50, 95% CI 1.30–1.74) and life improvements (OR 2.91, 95% CI 2.35–3.59). External LOC was associated with increased breathlessness severity. Conclusion External LOC is associated with experiencing worse breathlessness, and the identified LOC factors can be considered in future intervention studies aiming to reduce the suffering from breathlessness.
Synthetic Cloud and Shadow Generation for Segmentation of Cloud and Shadow Regions using a U-Net Deep Learning Model
No full textCloud and shadow regions in satellite images pose significant challenges for accurate image interpretation and analysis. This thesis investigates a deep learning approach using the U-Net model for synthetic generation and segmentation of cloud and shadow regions. A synthetic dataset was created to train and validate the model, reducing dependency on limited annotated data. The performance was evaluated using IoU and accuracy metrics, showing that the proposed method achieves reliable segmentation results. The study demonstrates the effectiveness of combining synthetic data generation with U-Net for robust cloud and shadow detection in remote sensing applications
Cybersecurity of remote work migration : A study on the VPN security landscape post Covid-19 outbreak
No full textThe Covid-19 pandemic led to an unprecedented reliance on Virtual Private Networks (VPNs) for remote work, exposing critical vulnerabilities in global cybersecurity infrastructures. As organizations rapidly transitioned to remote operations, many lacked the necessary security measures to protect their VPN systems, making them prime targets for cybercriminals. This study synthesizes findings from 106 studies (2020–2023) to analyze the evolution of VPN-targeted cyberattacks, the tactics employed by threat actors, and effective mitigation strategies. Our analysis reveals that the widespread adoption of remote work triggered a 238% surge in VPN-targeted attacks between 2020 and 2022, as adversaries exploited vulnerabilities, misconfigurations, and inadequate security policies. Both independent cybercriminals and state-sponsored actors leveraged phishing, ransomware, and advanced persistent threats (APTs) to gain unauthorized access to corporate networks. In many cases, organizations struggled with outdated VPN protocols, weak authentication mechanisms, and insufficient network segmentation, allowing attackers to infiltrate systems with minimal resistance. To address these challenges, we propose a VPN Hardening Framework incorporating strong authentication, robust encryption, secure configurations, and continuous monitoring, expected to significantly reduce breach risks and enhance VPN resilience in the post-pandemic era. Additionally, we highlight emerging cybersecurity trends, including the role of zero-trust architectures, quantum-resistant encryption, and AI-driven intrusion detection in fortifying VPN security against evolving threats
Accessibility Adherence in Swedish Municipal Websites : Evolution and continuity of WCAG Guideline adherence on Swedish Municipal Websites
No full textBackground. Web accessibility ensures equitable digital access for users with disabilities, as mandated by WCAG 2.2 and Swedish law (SFS 2018:1937) [13]. Smaller municipalities often struggle with compliance, largely due to limited resources and technical expertise, with prior studies noting lower adherence compared to larger entities [4]. This study addresses a research gap by examining accessibility in Sweden’s ten smallest municipalities by population. Objectives. This study aims to:1. Assess the level of WCAG 2.2 AA compliance among the selected municipalities, 2. Compare these results with each municipality’s published accessibility statement, 3. Evaluate the reliability and overlap of four automated accessibility tools, and 4. Identify contributions of manual evaluation in uncovering issues missed by automated tools. Methods. A multiple-case study design was employed, evaluating each municipal website with four automated tools (WAVE, AChecker, SortSite, Lighthouse) and manual expert testing. Accessibility statements were analyzed against W3C and DIGG guidelines [20]. Results. None of the municipalities fully complied with WCAG 2.2 AA, though many achieved high success rates on individual criteria (e.g., 96.8% A-level, Section 4.3.2). Automated tools showed limited overlap in detecting failures, with SortSite identifying 29 unique issues (Section4.3.2). Accessibility statements were sparse, often failing to reflect evaluation findings (Section4.3.1). Conclusions. Although half the municipalities fail to meet WCAG 2.2 AA requirements under stricter evaluation criteria, they demonstrate significant progress toward accessibility goals. Sparse documentation, infrequent updates, and overreliance on automated tools highlight organizational shortcomings, reinforcing the need for manual evaluation and external audits. (Section 5.1.5)
In the wild light: How to handle encounters with animals in nature.
No full textI dagens digitala samhälle finns ett ökande behov av att sprida viktig säkerhetsinformation på ett engagerande och effektivt sätt. Projektet syftar till att utveckla en interaktiv webbapplikation i Twine för att utbilda användare i hur man bör agera vid möten med vilda djur, med särskilt fokus på varg. Genom att kombinera berättande scenarier, faktatexter och quiz skapas en lärandeupplevelse som bygger på spelifiering och användarinteraktivitet. För att utvärdera applikationens pedagogiska effekt genomfördes ett användartest med 35 deltagare. Resultaten visar att 77,1 % av användarna kände sig mycket säkra på hur de skulle agera efter att ha använt appen, jämfört med endast 2,7 % före. 97,1 % lärde sig vad de skulle göra om en varg följde efter dem, och 94,3 % upplevde quizet som både roligt och lärorikt. Resultatet visar att interaktiva digitala lösningar har stor potential att förmedla praktisk kunskap och öka handlingsberedskap i naturrelaterade risksituationer. Applikationen kan därmed fungera som modell för liknande utbildningsinitiativ inom andra säkerhetsområden.In today’s digital society, there is a growing need to communicate important safety information in engaging and effective ways. This project aims to develop an interactive web application in Twine to educate users on how to act when encountering wild animals, with a specific focus on wolves. By combining storytelling scenarios, factual texts, and quizzes, the application creates a learning experience grounded in gamification and user interactivity. To evaluate the pedagogical effect of the application, a user test was conducted with 35 participants. The results show that 77.1% of users felt very confident about how to respondafter using the app, compared to only 2.7% before. Additionally, 97.1% learned what to do if a wolf follows them, and 94.3% found the quiz both fun and educational. The findings indicate that interactive digital tools have strong potential for conveying practical knowledge and increasing preparedness in nature-related risk situations. The application may serve as a model for similar educational initiatives in other safety contexts
Att forma trygghet : En modell för trygghetsskapande gestaltning i offentliga gångmiljöer
No full textDenna studie undersöker hur den fysiska miljöns utformning påverkar upplevd trygghet i offentliga rum. Utgångspunkten är behovet av att med mindre ingrepp stärka tryggheten i redan befintliga miljöer. I arbetet utvecklas en teoretisk modell som kopplar konkreta designprinciper för belysning och vegetation till rumsliga variabler som överblickbarhet, dolda ytor och visuella flyktvägar. För att besvara forskningsfrågorna och undersöka modellens tillämpbarhet har platsobservationer och rumsliga analyser genomförts på fyra olika platser. Resultatet visar att även mindre justeringar av vegetation och belysning kan ha stor påverkan på hur en plats upplevs ur ett trygghetsperspektiv. Särskilt tydligt är att strategiskt placerad belysning och omstrukturering av vegetationen stärker siktlinjer och känslan av kontroll. En miljö som underlättar orientering och erbjuder visuella flyktvägar minskar upplevelsen av instängdhet och utsatthet. Studien visar att den föreslagna modellen kan fungera som ett stöd vid trygghetsskapande gestaltning i redan befintliga miljöer, och erbjuder en strukturerad metod för att identifiera och åtgärda otrygga platser