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Gemensamma kurser | Studentwebben LTH Hoppa till huvudinnehåll Den här webbplatsen använder cookies för att förbättra användarupplevelsen. Genom att fortsätta använda webbplatsen samtycker du till att cookies används enligt vår cookie-policy (på LTH:s webbplats) . Absolut nödvändiga cookies Dessa cookies är nödvändiga för att webbplatsen ska fungera och kan inte stängas av i våra system. Dessa coo

https://www.student.lth.se/kurs-och-programinformation/gemensamma-kurser/ - 2026-05-28

Urban meteorology, the study of atmospheric phenomena in urban areas, is vital for understanding the dynamic interactions between rapid urbanization and environmental changes. Over the past two decades (2004–2024), urban heat islands (UHIs), extreme rainfall, pollution, and temperature anomalies have intensified, adversely affecting human health, infrastructure, and ecosystems worldwide. The prese

Senior lecturer Contact details Email: per [dot] norberg [at] jur [dot] lu [dot] se Phone: +46 46 222 10 44Organisation Department of Law Room number: 437 Service point: 56 WebpagePer Norbergs profile in Lund University research portalOther affiliations Researcher Norma Research Programme Publications Displaying of publications. Sorted by year, then title. Filter by type AllBookBook chapterConfere

https://www.law.lu.se/norberg - 2026-05-28

Extreme environmental events such as Heat Waves (HWs), cold waves, and droughts intensified by climate change are increasingly associated with adverse health outcomes. In this study, investigation of the extreme temperature across Uttar Pradesh (U. P.), one of India’s largest and densely populate states has been done. Using high-resolution climate data from the Providing REgional Climates for Impa

Centre for Retail Research at Lund University ANNUAL REPORT | 2014 2 CENTRE FOR RETAIL RESEARCH AT LUND UNIVERSITY, ANNUAL REPORT 2014 3CENTRE FOR RETAIL RESEARCH AT LUND UNIVERSITY, ANNUAL REPORT 2014 Introduction Centre for Retail Research at Lund University – the first year It is with great pleasure that we at the Centre for Retail Research at Lund University publish our first annual report, si

https://www.lusem.lu.se/sites/lusem.lu.se/files/2024-01/annualreport-2014.pdf - 2026-05-29

Organizations and individuals maintain and use an ever increasing amount of computer systems, either deployed locally, or in the cloud.These systems often store and handle vast amounts of data, some of which is sensitive and should be kept private.Regardless of where the data is located, there is a need to prevent data from falling into the wrong hands.To this end, this dissertation presents contr

Vehicle traffic management is becoming more complex due to increased traffic density in cities. Novel solutions are necessary for emergency vehicles, which despite growing congestion must be able to quickly reach their destination. Emergency vehicles are usually equipped with transmitters to control the traffic lights on their path and warn other vehicles with sirens. Transmitters are operated man

There exist several datasets for developing self-driving car methodologies. Manually collected datasets impose inherent limitations on the variability of test cases and it is particularly difficult to acquire challenging scenarios, e.g. ones involving collisions with pedestrians. A way to alleviate this is to consider automatic generation of safety-critical scenarios for autonomous vehicle (AV) te

Recently there has been an increase in the number of available autonomous vehicle (AV) models. To evaluate and compare the safety of the various models the AVs need to be tested in several diverse safety-critical scenarios. We propose the Adversarial Test Case Generator (ATCG) that differently from previous test case generators allows for the generation of realistic collision scenarios with varied

We consider a perturbation problem for embedded eigenvalues of a self-adjoint differential operator in L2(R;Rn). In particular, we study the set of all small perturbations in an appropriate Banach space for which the embedded eigenvalue remains embedded in the continuous spectrum. We show that this set of small perturbations forms a smooth manifold and we specify its co-dimension. Our methods invo

It is difficult to perform 3D reconstruction from on-vehicle gathered video due to the large forward motion of the vehicle. Even object detection and human sensing models perform significantly worse on onboard videos when compared to standard benchmarks because objects often appear far away from the camera compared to the standard object detection benchmarks, image quality is often decreased by mo

Realistic modelling of pedestrians in Autonomous Vehicles (AV)s and AV testing is crucial to avoid lethal collisions in deployment. The majority of AV trajectory forecasting literature do not utilize the motion cues present in 3D human pose because it is hard to gather large datasets of articulated 3D pedestrian motion. In this thesis we discuss the difficulties in data gathering and propose a ped

Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel res

Activation functions play a central role in deep learning since they form an essential building stone of neural networks. In the last few years, the focus has been shifting towards investigating new types of activations that outperform the classical Rectified Linear Unit (ReLU) in modern neural architectures. Most recently, rational activation functions (RAFs) have awakened interest because they w

Many hand-held or mixed reality devices are used with a single sensor for 3D reconstruction, although they often comprise multiple sensors. Multi-sensor depth fusion is able to substantially improve the robustness and accuracy of 3D reconstruction methods, but existing techniques are not robust enough to handle sensors which operate with diverse value ranges as well as noise and outlier statistics

Globally, solar projects are being rapidly built or planned, particularly in high solar potential regions with high energy demand. However, their energy generation potential is highly related to the weather condition. Here we use state-of-the-art Earth system model simulations to investigate how large photovoltaic solar farms in the Sahara Desert could impact the global cloud cover and solar gener

A distinctive representation of image patches in form of features is a key component of many computer vision and robotics tasks, such as image matching, image retrieval, and visual localization. State-of-the-art descriptors, from hand-crafted descriptors such as SIFT to learned ones such as HardNet, are usually high-dimensional; 128 dimensions or even more. The higher the dimensionality, the large

We uncover a critical side-channel vulnerability in the Hamming Quasi-Cyclic (HQC) round 4 optimized implementation arising due to the use of the modulo operator. In some cases, compilers optimize uses of the modulo operator with compiletime known divisors into constant-time Barrett reductions. However, this optimization is not guaranteed: for example, when a modulo operation is used in a loop the