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In compressed sensing a sparse vector is approximately retrieved from an underdetermined equation system Ax = b. Exact retrievalwouldmean solving a large combinatorial problem which is well known to be NP-hard. For b of the form Ax0 + ϵ, where x0 is the ground truth and ϵ is noise, the 'oracle solution' is the one you get if you a priori know the support of x0, and is the best solution one could h
During recent years, research on authenticated encryption has been thriving through two highly active and practice-motivated research directions: provably secure leakage-resilience schemes and key- or context-commitment security. However, the intersection of both fields had been overlooked until very recently. In ToSC 1/2024, Struck and Weish\"aupl studied generic compositions of Encryption scheme
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
This paper explores recent trends in Uzbek labor migration, with a focus on the growing role of the European Union as a destination. While Russia remains the largest host country, ongoing diversification has led to a notable increase in migration to EU member states, particularly for employment. Drawing on official statistics and fieldwork, the study highlights rising numbers of Uzbek migrants in
With the help of modern technologies and advances in communication systems, the functionality of Industrial control systems (ICS) has been enhanced leading toward to have more efficient and smarter ICS. However, this makes these systems more and more connected and part of a networked system. This can provide an entry point for attackers to infiltrate the system and cause damage with potentially ca
Given a sensor network, TDOA self-calibration aims at simultaneously estimating the positions of receivers and transmitters, and transmitters time offsets. This can be formulated as a system of polynomial equations. Due to the elevated number of unknowns and the nonlinearity of the problem, obtaining an accurate solution efficiently is nontrivial. Previous work has shown that iterative algorithms
Cloud computing has become a prominent technology for the computing paradigm in various industrial sectors nowadays. For most industrial applications to perform in real-time, the support of periodic computing is required. However, it remains a challenge when the computing is executed in a cloud, since both the network connection and the cloud environment are uncertain. In this paper, we propose a
Monocular depth estimation is a highly challenging problem that is often addressed with deep neural networks. While these use recognition of high level image features to predict reasonably looking depth maps,the result often has poor metric accuracy. Moreover,the standard feed forward architecture does not allow modification of the prediction based on cues other than the image.In this paper we rel
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
Hans Henrik Lidgard & Sverker Jönsson enligt delegation Abstract: Anbudssamverkan, kvoteringsöverenskommelser, priskarteller och marknadsuppdelnings-åtgärder förekommer som separata överträdelser av konkurrensrätten. Dessa konkurrensrättens kärnöverenskommelser förefaller i allt att uppfylla kriterierna för allvarliga förmögenhetsbrott. Förfarandena kan fogas in under strafflagstiftningens bed
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
