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CHARACTERIZATION OF THE EXISTENCE OF SEMICONTINUOUS RICHTER-PELEG MULTI-UTILITY REPRESENTATIONS

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arXiv 2020年

作者： Andrikopoulos, Athanasios Dept. of Computer Engineering and Informatics University of Patras Patras26504 Greece

The utility representations of preference relations in symmetric topological spaces have the advantage of fully characterizing these relations. But this is not true in the case of representations of preference relations that are mostly incomplete and use asymmetric topologies. To avoid this unfortunate circumstance, due to lack of symmetry, the notion of semicontinuous Richter-Peleg multiutility representation was first introduced and studied by Minguzzi [29]. Generally, the study of semicontinuous functions reveals that topology and order are two aspects of the same mathematical object and therefore should be studied jointly. The mathematical object that can be used to model and analyze the concepts of asymmetry and duality that arise from the coexistence of topology and order is that of bitopological preordered space. In this paper, we characterize the existence of semicontinuous Richter-Peleg multi-utility representations in bitopological spaces. Based on this characterization, we prove that a preorder ≾ has the set of all Scott and ω-continuous functions as a Richter-Peleg multi-utility representation if and only if ≾ is precontinuous in the sense of Erné [18].MSC Codes 91B16 Copyright © 2020, The Authors. All rights reserved.

关键词： Topology

Smart Irrigation and Intrusions Detection in Agricultural Fields Using I.o.T.

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Procedia computer Science 2020年 167卷 154-162页

作者： Divyansh Thakur Yugal Kumar Singh Vijendra Dept. of Computer Science and Engineering Indian Institute of Information Technology Una 177209 India Dept. of Computer Science and Engineering Jaypee University of Information Technology Solan 173234 India Dept. of Informatics School of Computer Science University of Petroleum and Energy Studies Dehradun India

Agriculture plays an important role in the life span of human being not only for their survival but for the better economic growth of the country too. Precision agriculture is the new trending term in the field of technology whose main motive is to reduce the workload of the farmers and increase the productivity of the farms by using technologies like I.O.T, WSNs, Remote Sensing, Drone surveillance and many more. In this paper, we show the work done by our cost effective and reliable device whose aim is to irrigate fields only when there is a need of water and to provide information about detection of any intrusion in agricultural fields. The information is sent to the farmers by using cloud application. The performance of our system is measured in terms of intrusion detection and moisture of soil for irrigation.

关键词： IoT wireless sensor networks soil moisture sensor PIR sensor smart irrigation cloud application

Bayesian modeling of effective and functional brain connectivity using hierarchical vector autoregressions

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arXiv 2021年

作者： Wegmann, Bertil Lundquist, Anders Eklund, Anders Villani, Mattias Div. of Statistics and Machine Learning Dept. of Computer and Information Science Linköping University Sweden Umeå University Sweden Div. of Medical Informatics Dept. of Biomedical Engineering Linköping University Sweden Dept. of Statistics Stockholm University Sweden

Analysis of brain connectivity is important for understanding how information is processed by the brain. We propose a novel Bayesian vector autoregression (VAR) hierarchical model for analyzing brain connectivity in a resting-state fMRI data set with autism spectrum disorder (ASD) patients and healthy controls. Our approach models functional and effective connectivity simultaneously, which is new in the VAR literature for brain connectivity, and allows for both group- and single-subject inference as well as group comparisons. We combine analytical marginalization with Hamiltonian Monte Carlo (HMC) to obtain highly efficient posterior sampling. The results from more simplified covariance settings are, in general, overly optimistic about functional connectivity between regions compared to our results. In addition, our modeling of heterogeneous subject-specific covariance matrices is shown to give smaller differences in effective connectivity compared to models with a common covariance matrix to all subjects. © 2021, CC BY.

关键词： Covariance matrix

Attention based CNN-LSTM Network for Pulmonary Embolism Prediction on Chest Computed Tomography Pulmonary Angiograms

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arXiv 2021年

作者： Suman, Sudhir Singh, Gagandeep Sakla, Nicole Gattu, Rishabh Green, Jeremy Phatak, Tej Samaras, Dimitris Prasanna, Prateek Dept. of Electrical Engineering Indian Institute of Technology Bombay India Dept. of Radiology Newark Beth Israel Medical Center NJ United States Dept. of Computer Science Stony Brook University NY United States Dept. of Biomedical Informatics Stony Brook University NY United States

With more than 60,000 deaths annually in the United States, Pulmonary Embolism (PE) is among the most fatal cardiovascular diseases. It is caused by an artery blockage in the lung;confirming its presence is time-consuming and is prone to over-diagnosis. The utilization of automated PE detection systems is critical for diagnostic accuracy and efficiency. In this study we propose a two-stage attention-based CNN-LSTM network for predicting PE, its associated type (chronic, acute) and corresponding location (leftsided, rightsided or central) on computed tomography (CT) examinations. We trained our model on the largest available public Computed Tomography Pulmonary Angiogram PE dataset (RSNA-STR Pulmonary Embolism CT (RSPECT) Dataset, N=7279 CT studies) and tested it on an in-house curated dataset of N=106 studies. Our framework mirrors the radiologic diagnostic process via a multi-slice approach so that the accuracy and pathologic sequela of true pulmonary emboli may be meticulously assessed, enabling physicians to better appraise the morbidity of a PE when present. Our proposed method outperformed a baseline CNN classifier and a single-stage CNN-LSTM network, achieving an AUC of 0.95 on the test set for detecting the presence of PE in the study. Copyright © 2021, The Authors. All rights reserved.

关键词： computerized tomography

Non-Linear Age of Information: An Energy Efficient Receiver-Centric Approach

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arXiv 2021年

作者： Miridakis, Nikolaos I. Tsiftsis, Theodoros A. Yang, Guanghua The Institute of Physical Internet School of Intelligent Systems Science & Engineering Jinan University Zhuhai Campus Zhuhai519070 China The Dept. of Informatics and Computer Engineering University of West Attica Aegaleo 12243 Greece

The age of information (AoI) performance metric for point-to-point wireless communication systems is analytically studied under Rician-faded channels and when the receiver is equipped with multiple antennas. The general scenario of a non-linear AoI function is considered, which includes the conventional linear AoI as a special case. The stop-and-wait transmission policy is adopted, where the source node samples and then transmits new data only upon the successful reception of previous data. This approach can serve as a performance benchmark for any queuing system used in practice. New analytical and closed-form expressions are derived with respect to the average AoI and average peak AoI for the considered system configuration. We particularly focus on the energy efficiency of the said mode of operation, whereas some useful engineering insights are provided. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

A Study of Multilayer Omega Networks Operating with Cut-Through Mechanism under Uniform Traffic

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A Study of Multilayer Omega Networks Operating with Cut-Thro...

South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Eleftherios Stergiou John Garofalakis Dimitrios Liarokapis Spiridoula V. Margariti Dept. Informatics & Telecommunications University of Ioannina Arta Greece Dept. of Computer Engineering and Informatics University of Patras and Computer Technology Institute and Press—“DIOPHANTUS” (CTI)) Patras Greece

ISBN: (数字)9781728164458

ISBN: (纸本)9781728164465

There is an enduring interest in developing more efficient multistage interconnection networks (MINs), as they are a key aspect of various switching sectors and the demands for higher data transfer rates. Here, semi-layer Omega type networks operating under the cut-through forwarding policy are selected as a test-bed subject for performance evaluation. This special shuffle-exchange network was modelled, analysed, and simulated. Moreover, this type of fabric is compared with corresponding single-layer Omega networks operating via cut-through or a `store and forward' forwarding technique. The results show, in a quantitative manner, how superior is the under study fabric compared to the corresponding single-layer constructions, in terms of network size, showing the advantages that are provided by both usages: fan-out and cut-through mechanisms. Moreover, the roles of the switch element's size and the reliability metric were investigated. The findings that are derived can be valuable assets for MIN designers, in order to achieve more efficient delivering networks with low overall deployment costs.

关键词： Omega network banyan networks performance evaluation cut-through semi-layer multistage interconnection networks uniform traffic multistage interconnection networks cut-through Performance Evaluation Materials

Organization of Regional Situational Centers of the Intelligent System «cONTROL-TEA» using UAVs 6

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Organization of Regional Situational Centers of the Intellig...

6th IEEE International Conference on Actual Problems of Unmanned Aerial Vehicles Development, APUAVD 2021

作者： Melkumian, Kateryna Pisarenko, Julia Koval, Alexander Faculty of Informatics and Computer Engineering National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute of Ukraine Kyiv Ukraine Lab. 236 of Virtual Environment Systems for Organization of Scientific Research V.M. Glushkov Institute of Cybernetics National Academy of Sciences of Ukraine Kyiv Ukraine V.M. Glushkov Institute of Cybernetics National Academy of Sciences of Ukraine Dept. #265 of Mathematical Problems of Applied Informatics Kyiv Ukraine

ISBN: (纸本)9781665438223

Some questions of creating the intellectual system «CONTROL-TEA» concept was considered. The issues of creating organizational support for the situational center of intellectual system «CONTROL-TEA» are reviewed. The structure of the information storage was developed. There is a need for their certification and registration in city services. In order to combine them into a single system, the smart city will be the task manager, and the DAVs will be their executor, it is proposed to organize regional situational centers that will coordinate the work. The regional situation center provides two-way communication between customers (public, municipal, private) and its contractors (UAVs), monitors traffic, provides a variety of operations and, along with the IOT, serves as a data provider. © 2021 IEEE.

关键词： Intelligent systems

Wital: A COTS WiFi Devices Based Vital Signs Monitoring System Using NLOS Sensing Model

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TechRxiv

TechRxiv 2021年

作者： Zhang, Xiang Gu, Yu Yan, Huan Wang, Yantong Dong, Mianxiong Ota, Kaoru Ren, Fuji Ji, Yusheng The School of Computer and Information Hefei University of Technology China I+ Lab School of Computer Science and Engineering University of Electronic Science and Technology of China China The Dept. of Sciences and Informatics Muroran Institute of Technology Japan The National Institute of Informatics Tokyo101-8430 Japan

Vital sign (breathing and heartbeat) monitoring is essential for patient care and sleep disease prevention. Most current solutions are based on wearable sensors or cameras;however, the former could affect sleep quality, while the latter often present privacy concerns. To address these shortcomings, we propose Wital, a contactless vital sign monitoring system based on low-cost and widespread commercial off-the-shelf (COTS) Wi-Fi devices. There are two challenges that need to be overcome. First, the torso deformations caused by breathing/heartbeats are weak. How can such deformations be effectively captured? Second, movements such as turning over affect the accuracy of vital sign monitoring. How can such detrimental effects be avoided? For the former, we propose a non-line-of-sight (NLOS) sensing model for modeling the relationship between the energy ratio of line-of-sight (LOS) to NLOS signals and the vital sign monitoring capability using Ricean K theory and use this model to guide the system construction to better capture the deformations caused by breathing/heartbeats. For the latter, we propose a motion segmentation method based on motion regularity detection that accurately distinguishes respiration from other motions, and we remove periods that include movements such as turning over to eliminate detrimental effects. We have implemented and validated Wital on low-cost COTS devices. The experimental results demonstrate the effectiveness of Wital in monitoring vital signs. © 2021, CC BY.

关键词： Wireless local area networks (WLAN)

Quality Grading of Beef using Deep Convolutional Neural Network

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Quality Grading of Beef using Deep Convolutional Neural Netw...

HCT Information Technology Trends (ITT)

作者： Aarav Sharma Tanupriya Choudhury Tanmay Sarkar Madhusmita Mohanty Nikunj Bansal Sachi Nandan Mohanty Informatics Cluster School of Computer Science University of Petroleum and Energy Studies (UPES) Dehradun Uttarakhand India CSE Dept. University of Petroleum and Energy Studies (UPES) CSE Dept. Graphic Era Hill University Dehradun Uttarakhand India Department of Food Processing Technology West Bengal State Council of Technical Education Govt. of West Bengal Malda Polytechnic Malda India VIT-AP School of Business (VSB) VIT-AP University Amaravati Andhra Pradesh India School of Computer Science & Engineering VIT-AP University Amaravati Andhra Pradesh India

Beef is one of the most widely consumed meat, being an organic substance it is prone to degradation over time. In our paper we have proposed a Convolutional Neural Network model to grade a given sample of Beef and predict its freshness as good or bad. We have proposed a CNN model architecture along with a data (image) pre-processing pipeline that can be used to classify a given Beef sample. We have done comparative analysis between different pre-processing pipelines as well as other CNN based classification models and after training have achieved 99.63% test accuracy.

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