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This paper proposes an iterative algorithm to reconstruct missing samples from non-stationary signals. The proposed algorithm is based on the well-known amplitude-modulation frequency-modulation model for non-stationary signals. The method initially estimates the instantaneous frequencies of the observed multi-component signal. The estimated IFs are then used to de-chirp the corresponding componen
Kubernetes (K8s) is one of the best options available to deploy applications in large-scale infrastructures. Security has been a big concern for all practitioners in the K8s eco-system. Almost all cloud vendors have their security solution for K8s cluster, pods, workloads, etc. In recent years, a large number of open-source tools and projects related to K8s security have emerged to meet the increa
The generalized sparse iterative covariance-based estimation ( $q$ -SPICE) algorithm was recently introduced for scanning radar applications, resulting in substantial improvements in the angular resolution and quality of the processed images. Regrettably, the computational complexity and storage cost are high and quickly increase with growing data size, limiting the applicability of the estimator.
The size of the authentication tag represents a significant overhead for applications that are limited by bandwidth or memory. Hence, some authenticated encryption designs have a smaller tag than the required privacy level, which was also suggested by the NIST lightweight cryptography standardization project. In the ToSC 2022, two papers have raised questions about the IND-CCA security of AEAD sch
Objectives Accumulating evidence suggested that the laminin Î 32 (LAMC2) expression level was upregulated in various cancers. However, the potential prognostic value of LAMC2 in cancers remains unclear. We conducted a meta-analysis to clarify the association of LAMC2 expression with prognosis. Design We searched Embase, Web of Science and PubMed (up to 25 November 2021) to collect all eligible stu
Background: The aim of this multicentre prospective observational study was to identify the incidence, patient characteristics, diagnostic pathway, management and outcome of acute mesenteric ischaemia (AMI). Methods: All adult patients with clinical suspicion of AMI admitted or transferred to 32 participating hospitals from 06.06.2022 to 05.04.2023 were included. Participants who were subsequently
Introduction: We have previously adapted a clinical linear accelerator (Elekta Precise, Elekta AB) for ultra-high dose rate (UHDR) electron delivery. To enhance reliability in future clinical FLASH radiotherapy trials, the aim of this study was to introduce and evaluate an upgraded beam control system and beam tuning process for safe and precise UHDR delivery. Materials and Methods: The beam contr
The advancement of mobile technologies and their ability to utilize the Global Positioning System (GPS) to accurately locate their substantial number of users, prompt Location-Based Services (LBS) significantly. Ride-sharing is a popular means of transportation that utilizes LBS. With the rapid development of smart cities and their impact on addressing the critical issues of urban life such as tra
We introduce a multi-region model for simultaneous segmentation of medical images. In contrast to many other models, geometric constraints such as inclusion and exclusion between the regions are enforced, which makes it possible to correctly segment different regions even if the intensity distributions are identical. We efficiently optimize the model using a combination of graph cuts and Lagrangia
Underdrawings and pentimenti-typically revealed through x-ray imaging and infrared reflectography-comprise important evidence about the intermediate states of an artwork and thus the working methods of its creator.(1) To this end, Shahram, Stork and Donoho introduced the De-pict algorithm, which recovers layers of brush strokes in paintings with open brush work where several layers are partially v
Joint time-frequency representations are important tools when estimating the instantaneous frequency. The widely used spectrogram is known to have poor energy localisation, which the reassignment method improves. However, the reassignment method is sensitive to noise. In this paper we present a multitaper reassigned spectrogram (MTRS) that is robust to noise and tailored to short duration transien
A fully automatic system for abdominal organ segmentation is presented. As a first step, an organ localization is obtained via a robust and efficient feature registration method where the center of the organ is estimated together with a region of interest surrounding the center. Then, a convolutional neural network performing voxelwise classification is applied. Two convolutional neural networks o
Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede conv
Distinguishers and nonrandomness detectors are used to distinguish ciphertext from random data. In this paper, we focus on the construction of such devices using the maximum degree monomial test. This requires the selection of certain subsets of key and IV-bits of the cipher, and since this selection to a great extent affects the final outcome, it is important to make a good selection. We present
Although a number of different medium access control (MAC) schemes are adopted for wireless multi-hop networks, time division multiple access (TDMA) approaches based on a periodic frame of time slots are the most common when very high efficiency is needed in terms of use of radio and energy resources. Efficient resource usage is typically based on parallel compatible transmissions from multiple no
Background: Multimorbidity has already become common in primary care and will be a challenge in the future. Primary care in Sweden participates to a great extent in the care of patients with two severe, chronic conditions: chronic obstructive pulmonary disease (COPD) and heart failure. Both conditions are characterized by high mortality and often coexist. Age, sex, heart failure and other comorbid
Purpose: The aim of this study was to develop a deep learning-based method for segmentation of bones in CT scans and test its accuracy compared to manual delineation, as a first step in the creation of an automated PET/CT-based method for quantifying skeletal tumour burden. Methods: Convolutional neural networks (CNNs) were trained to segment 49 bones using manual segmentations from 100 CT scans.
Pairwise comparison of sound and radio signals can be used to estimate the distance between two units that send and receive signals. In a similar way it is possible to estimate differences of distances by correlating two received signals. There are essentially two groups of such methods, namely methods that are robust to noise and reverberation, but give limited precision and sub-sample refinement
Algorithms for secure encryption in a post-quantum world are currently receiving a lot of attention in the research community. One of the most promising such algorithms is the code-based scheme called QC-MDPC, which has excellent performance and a small public key size. In this work we present a very efficient key recovery attack on the QC-MDPC scheme using the fact that decryption uses an iterati
