Stable Throughput and Delay Analysis of a Random Access Network With Queue-Aware Transmission

In this work we consider a two-user and a three-user slotted ALOHA network with multi-packet reception (MPR) capabilities. The nodes can adapt their transmission probabilities and their transmission parameters based on the status of the other nodes. Each user has external bursty arrivals that are stored in their infinite capacity queues. For the two- and the three-user cases we obtain the stability region of the system. For the two-user case we provide the conditions where the stability region is a convex set. We perform a detailed mathematical analysis in order to study the queueing delay by formulating two boundary value problems (a Dirichlet and a Riemann-Hilbert boundary value problem), the solution of which provides the generating function of the joint stationary probability distribution of the queue size at user nodes. Furthermore, for the two-user symmetric case with MPR we obtain a lower and an upper bound for the average delay without explicitly computing the generating function for the stationary joint queue length distribution. The bounds as it is seen in the numerical results appear to be tight. Explicit expressions for the average delay are obtained for the symmetrical model with capture effect which is a subclass of MPR models. We also provide the optimal transmission probability in closed form expression that minimizes the average delay in the symmetric capture case. Finally, we evaluate numerically the presented theoretical results.Comment: Submitted for journal publicatio

Detection and Classification of Multiple Objects using an RGB-D Sensor and Linear Spatial Pyramid Matching

This paper presents a complete system for multiple object detection and classification in a 3D scene using an RGB-D sensor such as the Microsoft Kinect sensor. Successful multiple object detection and classification are crucial features in many 3D computer vision applications. The main goal is making machines see and understand objects like humans do. To this goal, the new RGB-D sensors can be utilized since they provide real-time depth map which can be used along with the RGB images for our tasks. In our system we employ effective depth map processing techniques, along with edge detection, connected components detection and filtering approaches, in order to design a complete image processing algorithm for efficient object detection of multiple individual objects in a single scene, even in complex scenes with many objects. Besides, we apply the Linear Spatial Pyramid Matching (LSPM) [1] method proposed by Jianchao Yang et al for the efficient classification of the detected objects. Experimental results are presented for both detection and classification, showing the efficiency of the proposed design

Развитие гибких навыков при обучении английскому языку: миф или реальность

Статья посвящена вопросу поиска эффективных методик по развитию гибких навыков при обучении студентов английскому языку в техническом вузе. Рассматривается понятие «гибкие навыки» и приводится их классификация. Представлен перечень гибких навыков, актуальный для развития при обучении английскому языку. Раскрывается потенциал дисциплины «Английский язык» для развития гибких навыков

Real-Time Abnormal Event Detection for Enhanced Security in Autonomous Shuttles Mobility Infrastructures

Autonomous vehicles (AVs) are already operating on the streets of many countries around the globe. Contemporary concerns about AVs do not relate to the implementation of fundamental technologies, as they are already in use, but are rather increasingly centered on the way that such technologies will affect emerging transportation systems, our social environment, and the people living inside it. Many concerns also focus on whether such systems should be fully automated or still be partially controlled by humans. This work aims to address the new reality that is formed in autonomous shuttles mobility infrastructures as a result of the absence of the bus driver and the increased threat from terrorism in European cities. Typically, drivers are trained to handle incidents of passengers’ abnormal behavior, incidents of petty crimes, and other abnormal events, according to standard procedures adopted by the transport operator. Surveillance using camera sensors as well as smart software in the bus will maximize the feeling and the actual level of security. In this paper, an online, end-to-end solution is introduced based on deep learning techniques for the timely, accurate, robust, and automatic detection of various petty crime types. The proposed system can identify abnormal passenger behavior such as vandalism and accidents but can also enhance passenger security via petty crimes detection such as aggression, bag-snatching, and vandalism. The solution achieves excellent results across different use cases and environmental conditions. Document type: Articl

Accessibility-based reranking in multimedia search engines

Traditional multimedia search engines retrieve results based mostly on the query submitted by the user, or using a log of previous searches to provide personalized results, while not considering the accessibility of the results for users with vision or other types of impairments. In this paper, a novel approach is presented which incorporates the accessibility of images for users with various vision impairments, such as color blindness, cataract and glaucoma, in order to rerank the results of an image search engine. The accessibility of individual images is measured through the use of vision simulation filters. Multi-objective optimization techniques utilizing the image accessibility scores are used to handle users with multiple vision impairments, while the impairment profile of a specific user is used to select one from the Pareto-optimal solutions. The proposed approach has been tested with two image datasets, using both simulated and real impaired users, and the results verify its applicability. Although the proposed method has been used for vision accessibility-based reranking, it can also be extended for other types of personalization context

Case report: First case of neuromelioidosis in Europe: CNS infection caused by Burkholderia pseudomallei

Neuromelioidosis is a rare CNS infection caused by Burkholderia pseudomallei and is characterized by high morbidity and mortality. Our report presents the diagnostic and therapeutic approach of the first case of neuromelioidosis confirmed in Europe. A 47-year-old man with a medical history of recurrent otitis with otorrhea and fever after tympanoplasty and radical cavity revision operation on the left ear was admitted with headache, decreased level of consciousness, dysarthria, left-sided hemiparesis, and urinary incontinence. After extensive investigations including MRI, microbiological, serological, and CSF analyses, and, ultimately, brain biopsy, a diagnosis of neuromelioidosis was established. Despite antibiotic treatment, the patient showed no clinical improvement and remained in a severely compromised neurological state under mandatory mechanical ventilation. Neuromelioidosis can pose a diagnostic challenge requiring an extensive diagnostic evaluation because of its uncommon clinical and radiological presentations

Evaluating the glucose raising effect of established loci via a genetic risk score.

Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. We tested the hypothesis here whether the cumulative effect of glucose raising SNPs, assessed via a score, is associated with glucose levels. A total of 1,434 participants of Greek descent from the THISEAS study and 1,160 participants form the GOMAP study were included in this analysis. We developed a genetic risk score (GRS), based on the known glucose-raising loci, in order to investigate the cumulative effect of known glucose loci on glucose levels. In the THISEAS study, the GRS score was significantly associated with increased glucose levels (mmol/L) (β ± SE: 0.024 ± 0.004, P = 8.27e-07). The effect of the genetic risk score was also significant in the GOMAP study (β ± SE: 0.011 ± 0.005, P = 0.031). In the meta-analysis of the two studies both scores were significantly associated with higher glucose levels GRS: β ± SE: 0.019 ± 0.003, P = 1.41e-09. Also, variants at the SLC30A8, PROX1, MTNR1B, ADRA2A, G6PC2, LPIN3 loci indicated nominal evidence for association with glucose levels (p < 0.05). We replicate associations of the established glucose raising variants in the Greek population and confirm directional consistency of effects (binomial sign test p = 6.96e-05). We also demonstrate that the cumulative effect of the established glucose loci yielded a significant association with increasing glucose levels

The Connection Between ESG Evaluation and Financial Performance: A Study of European Businesses

Background Customers, members of society, and top executives are all showing a growing interest in sustainable practices. Opportunities for leadership in areas of long-term corporate social responsibility and financial success are becoming more available to businesses as they shift towards a more sustainable company model. Objectives The goal of this dissertation is to analyze/evaluate the connection between a company's ESG assessment/evaluation/scoring, and its bottom line in terms of financial performance. European businesses are the focus of the research. An ancillary goal is to look at other industries to see whether there are any differences in the nature of this connection between firms and their respective sectors. Method To support its claims, the dissertation draws on secondary data collected for multiple companies between 2009 and 2020. The data was designed as panel data so that it could be used to study several entities across this time frame. Panel regressions were used to probe the motivation for the study. Results When companies across all industries are combined into a single dataset, it becomes clear that the Environmental scoring/rate has a substantial influence on earnings. The correlation between ESG and financial success is typically negative, as seen by the industries with the highest ESG ratings. Conclusion This dissertation adds to the body of research concerning environmental, social, and financial performance. Consumers, financiers, and business tycoons can all benefit from current and future research's insights as they consider how they can adopt more ethical practices. The link between all ESG factors and a company's net income/profitability is an intriguing area for further study in Europe.Complete