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International Conference on Wireless and Telematics (ICWT)

作者： Ade Nurhayati Syaiful Ahdan Tutun Juhana Nana Rachmana Syambas School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Faculty of Applied Science Telkom University Jakarta Indonesia Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Indonesia

ISBN: (数字)9798350377057

ISBN: (纸本)9798350377064

Named Data Networking as an alternative network for 5G network traffic is required to be able to provide better performance compared to other networks such as internet protocol networks. In NDN wireless, it is known that there is producer mobility and consumer mobility, so optimal mobility management is needed, including the handover process. In this paper the author proposes a simple RSSI-based 5G handover algorithm with distance as a reference RSSI value. This algorithm is a preparation for the handover algorithm on the NDN wireless network. By using the assumed distance value MS to eNB as the basic value for calculating RSSI, handover determination is determined by comparing the RSSI value to the RSSI threshold value. With the scenario of different numbers of users and cluster sizes, from the handover process involving 8 eNB. It can be calculated how big the handover probability is for each user. From the simulation results, it can be concluded that the more users and the larger the cluster size, the greater the handover probability value. This is linear, with the wider the cluster, the probability of getting an RSSI signal from the original eNB becomes smaller, making it possible to get an RSSI signal from neighboring eNB, so that a handover occurs.

关键词： 5G mobile communication Wireless networks Simulation Clustering algorithms Telecommunication traffic Handover Probability

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Drug Repurposing Targeting COVID-19 3CL Protease using Molecular Docking and Machine Learning Regression Approach

arXiv

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arXiv 2023年

作者： Aqeel, Imra Majid, Abdul Biomedical Informatics Research Lab Department of Computer & Information Sciences Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan

The COVID-19 pandemic has initiated a global health emergency, with an exigent need for effective cure. Progressively, drug repurposing is emerging a promise solution as it saves the time, cost and labor. However, the number of drug candidates that have been identified as being repurposed for the treatment of COVID-19 are still insufficient, so more effective and thorough drug exploring strategies are required. In this study, we joint the molecular docking with machine learning regression approaches to find some prospective therapeutic candidates for COVID-19 treatment. We screened the 5903 approved drugs for their inhibition by targeting the main protease 3CL of SARS-CoV-2, which is responsible to replicate the virus. Molecular docking is used to calculate the binding affinities of these drugs to the main protease 3CL. We employed several machine learning regression approaches for QSAR modeling to find out some potential drugs with high binding affinities. Our outcomes demonstrated that the Decision Tree Regression (DTR) model with best scores of R2 and RMSE, is the most suitable model to explore the potential drugs. We shortlisted six favorable drugs with their respective Zinc IDs ZINC (3873365, 85432544, 203757351, 85536956, 8214470, and 261494640) within the range of -15 kcal/mol to -13 kcal/mol. These drugs have novel repurposing potential, except for one antiviral ZINC203757351 compound that has already been identified in other studies. We further examined the physiochemical and pharmacokinetic properties of these most potent drugs and their best binding interaction to specific target protease 3CLpro. Our study provides an efficient framework to explore the potential drugs against COVID-19, and establishes the impending combination of molecular docking with machine learning regression approaches to accelerate the identification of potential therapeutic candidates. Our verdicts contribute to the larger goal of finding effective cures for COVID-19, which is an a

关键词： COVID-19

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Measurement of Synthetic-Dimension Band Structures in Silicon Coupled Ring Resonators 16

Measurement of Synthetic-Dimension Band Structures in Silico...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Zhang, Ruming Li, Liucun Kamata, Mikiya Baba, Toshihiko Ozawa, Tomoki Ota, Yasutomo Iwamoto, Satoshi Research Center for Advanced Science and Technology The University of Tokyo Tokyo153-8904 Japan Yokohama National University Department of Electrical and Computer Engineering Yokohama240-8501 Japan Advanced Institute for Materials Research Tohoku University Sendai980-8577 Japan Keio University Department of Applied Physics and Physico-Informatics Yokohama223-8533 Japan

We fabricated integrated silicon coupled-ring resonators and measured photonic band structures for synthetic frequency lattices with different configurations. A phase difference between two modulation signals introduc... 详细信息

ISBN: (纸本)9798350372076

关键词： Silicon photonics

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Mqtt Routing Optimizing Based Intrusion Detection for Internet of Things Using Hybrid Machine Learning

Mqtt Routing Optimizing Based Intrusion Detection for Intern...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Hoomod, Haider K. Al-Hamami, Mohammad Alaa Kadhim, Aqeel Kamil Mohammed, Qutaiba Humadi Niaf, Jolan Rokan College of Education Mustansiriyah University Baghdad Iraq Applied Science University Manama Department of Management Information Systems Manam Bahrain Imam Al-Kadhim College Computer Techniques Engineering Department Baghdad Iraq College of Nursing University of Baghdad Baghdad Iraq Informatics Institute for Postgraduate Studies University of Information Technology and Communications Baghdad Iraq

ISBN: (纸本)9798350369106

With the advent of the Internet of Things, a world was born in which everything could be uniquely identified and monitored, tracked, and managed by computer programs. Items can self-configure using a predefined communication protocol. Other software programs can be linked to operate together using Message Queue Telemetry Transport Protocol (MQTT) or MQSeries components. Business integration software and middleware are common terms for this category of applications. With its suggested lightweight, easy-to-implement, and lowbandwidth system for billions of smart items, the MQTT protocol offers a wide range of potential applications, including home automation. In order to enhance the power savings in MQservice routing, we presented an intelligent assistant for optimizing routing model. For Internet of Things (IoT) purposes, it introduces an optimal routing model based on optimized hybrid machine learning-based anomaly detection (OHMLA). In order to extend the reach of a network, the offered approach allows Internet of Things devices to make efficient use of energy. To further enhance Intrusion Detection identification and get optimum network selection routes, the moth Salp Swarm technique (SSA) technique is used for the optimized hyperparameters. The model is capable of accurately detecting attacks that result in network congestion, causing delays in connection response and data transfer in IoT network. © 2024 IEEE.

关键词： Middleware

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The Calibration of Single Beam Distance Sensors based on Machine Learning Methods

The Calibration of Single Beam Distance Sensors based on Mac...

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IEEE International Conference on Big Data

作者： Piotr Biernacki Adam Ziebinski Jia-Hao Syu Jerry Chun-Wei Lin Institute of Theoretical and Applied Informatics Polish Academy of Sciences Institute of Informatics Silesian University of Technology Gliwice Poland Institute of Informatics Silesian University of Technology Gliwice Poland Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Smart cities require the use of many different types of sensors to make the communication, and distance sensors are one of the most commonly used elements in transportation systems and related infrastructures. The introduction of increasingly advanced autonomous systems in many areas of smart cities requires high measurement precision of the sensors used. High precision is essential for proper operation, long-term use, and safety in machine-to-machine or machine-to-human interactions. This paper presents a comparison of the accuracy of distance measurements for two commercially available single-beam LiDARs and two ultrasonic sensors. The aim of the research was to develop a calibration method in order to improve the accuracy of distance sensors. Based on the collected distance measurements, the sensors were calibrated using selected machine learning algorithms. The results of the experiments show the effectiveness of the proposed calibration methods, which yield an average mean absolute error (MAE) of 1.76 E-05 meters (m) and a root mean square error (RMSE) of 1.33 E-04 m for the tested sensors.

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Joint Radar-Communication Systems by Optimizing Radar Performance and Quality of Service for Communication Users

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 778-790页

作者： Tsinos, Christos G. Arora, Aakash Tsiftsis, Theodoros A. National and Kapodistrian University of Athens Department of Digital Industry Technologies Evripus Campus Euboea 34400 Greece University of Twente Radio Systems Group Faculty of Electrical Engineering Mathematics and Computer Science AE Enschede7500 Netherlands Indian Institute of Technology Delhi Centre for Applied Research in Electronics New Delhi110016 India University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece Jinan University Zhuhai Campus School of Intelligent Systems Science and Engineering Zhuhai519070 China

In this article, the problem of linear precoding and radar receive beamforming design for joint radar-communication (JRC) systems is studied. A multiple antenna base station (BS) that serves multiple single-antenna user terminals on the downlink is assumed. Furthermore, the BS employs a simultaneous radar function in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. In this work, we jointly design the JRC linear precoder and the radar receive beamformer, thus aiming to optimize the performance of the radar part while maintaining a desired quality of service (QoS) for the communication one subject to a total transmit power constraint. To that end, we formulate a challenging fractional nonconvex optimization problem via which the optimal precoder and radar receive beamformer are derived. Then, we develop algorithmic solutions based on the majorization-minimization (MM) principle and the semidefinite relaxation (SDR) methodology for the formulated optimization problem. The performance of both the proposed solutions is examined and compared to the one of a system that supports only the radar functionality via numerical results. © 2023 IEEE.

关键词： Signal to noise ratio

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Digital Twin Definition for Detecting Abnormal Perspiration Patterns in High-Stress Professions 23

Digital Twin Definition for Detecting Abnormal Perspiration ...

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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Vizitiu, Cristian Turcin, Ioan Dominey, Kevin Alexander Softic, Selver Dinculescu, Adrian-Catalin Bocanet, Vlad I. Dugan, Cosmin Moraru, Sorin-Aurel The Space Applications and Technologies Laboratory Institute of Space Science-Subsidiary of INFLPR Magurele Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Automatics and Information Technology Brasov Romania CAMPUS 02 University of Applied Sciences Department Automation Technology Graz Austria CAMPUS 02 University of Applied Sciences Department IT and Business Informatics Graz Austria Robotics and Production Management Technical University of Cluj-Napoca Cluj-Napoca Faculty of Industrial Engineering Department of Manufacturing Engineering Romania Bucharest University Emergency Hospital Bucharest Romania

ISBN: (纸本)9798331540388

Perspiration is a physiological response in high-stress situations, that also plays a key role in thermoregulation and stress management. Understanding perspiration patterns is used for assessing physiological responses and optimizing human performance especially in professions such as emergency medical services and military operations, as well as for individuals exposed to Isolated Confined Extreme (ICE) environments such as astronauts and space analog mission participants. This paper defines a Digital Twin (DT) model, that will be integrated with an existing physical sweat simulator module (SSM) prototype. Its goal is to simulate human perspiration under high-stress conditions by integrating environmental, physiological, and psychological data. The system architecture is developed via Model-Based Systems engineering (MBSE). The scope of the designed virtual model is to accurately reflect physical perspiration, detect abnormal perspiration patterns, and generate recommendations regarding stress countermeasures. The goal is to influence the behavioral and/or physiological state of the physical twin, thereby creating a dynamic, responsive system. Machine learning (ML) models will be used to identify patterns in the environmental, physiological, and psychological inputs and predict sweat volume, chemical composition, and regional sweat distributions across the body. ML will also be used to detect abnormal perspiration patterns based on input data. The application of generative AI for creating test data from simulation templates is anticipated to facilitate the comparative analysis of two to three distinct profiles, such as astronauts, soldiers, and paramedics or firefighters, using simulated values. The SSM, with its integrated sensors, will serve the dual purpose of validating the model and providing realistic physical simulation. © 2024 IEEE.

关键词： Physiological models

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Acoustic cavitation bubble under influence of frequency ultrasound: Numerical analysis 3

Acoustic cavitation bubble under influence of frequency ultr...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Abu-Nab, A.K. Abu-Bakr, A.F. Abushaeer, Zain Menoufia University Faculty of Science Department of Mathematics and Computer Science Shebin El-Koom32511 Egypt Moscow Institute of Physics and Technology Phystech School of Applied Mathematics and Informatics Moscow141700 Russia Menoufia University Faculty of Science Department of Mathematics and Computer Science Shebin El-Koom32511 Egypt Higher Institute of Engineering and Technology Department of Basic Science Kafrelsheikh33511 Egypt

ISBN: (纸本)9798350323511

This work presents a numerical investigation of acoustic cavitation in Newtonian fluid based on frequency ultrasound. The model of ultrasonic cavitation dynamics is formulated by a modified Rayleigh-Plesset equation and an acoustic pressure equation. The exponential B-Spline collection method was employed to obtain the numerical solutions of the given cavitation bubble model, considering the effect of acoustic pressure. The behaviour of the cavitation microbubbles' radius and the internal pressure of acoustic cavitation were examined at different values of frequencies. The obtained results reveal the importance of frequencies in ultrasound, which play a vital role in changing the behaviour of cavitation bubbles. © 2023 IEEE.

关键词： Numerical methods

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EEG Analysis of Human Perception based on Video-Audio Stimuli 1

EEG Analysis of Human Perception based on Video-Audio Stimul...

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1st International Conference on Smart Technologies Communication and Robotics, STCR 2021

作者： Manochitra, S. Partheepan, Ravinthiran Kalasalingam Institute of Technology Faculty of Computer Science and Engineering Tamilnadu Virudhunagar India Vytautas Magnus University Faculty of Informatics Master Programme - Applied Informatics Kaunas Lithuania

ISBN: (纸本)9781665418065

Emotions plays a potential role in human computer interaction which are having an obligatory models of cognitive measures. The emotions are dominated by the human physiological communication channels. Those emotions could affect several human activities like learning, decision making, communication, perception, cognitive and so on. Also, some of the emotions are quite difficult to measure and interpret and having difficulty in incorporating them into a technology and design. On the other hand, state of the technologies has enabled us to capture the emotions and integrate them for the use of human computer interaction contexts. This paper delivers an attempt to model the emotions using electroencephalography (EEG). The video stimuli for the two representatives are based on a few negative, positive and neutral contents were shown to volunteers and EEG data was obtained. Further, EEG analysis were experimented and collected about their emotional states with subject's self reports. This study determines that the human emotions could be modelled for affect assessment module or for the usage in human computer interaction and affect based intelligent interactions. © 2021 IEEE.

关键词： Human computer interaction

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Implementing a Robust and Scalable Detect-and-Avoid Algorithm for UAV Navigation in ROS

Implementing a Robust and Scalable Detect-and-Avoid Algorith...

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Dimitrios Meimetis Ioannis Daramouskas Vaios Lappas Isidoros Perikos Vaggelis Kapoulas Michael Paraskevas Department of Aerospace Science & Technology NKUA Athens Greece Computer Technology Institute and Press “Diophantus” Patras Greece Applied Mechanics Lab UoP Patras Greece Computer Engineering and Informatics Department UoP Patras Greece Electrical and Computer Engineering Dept. Computer Technology Institute and Press “Diophantus” University of Peloponnese Patras Greece

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions that drones must execute efficiently is navigation in real-world environments. This paper presents a decentralized approach for enabling unmanned aerial vehicles (UAVs) to navigate safely in unknown environments and avoid obstacles. Leveraging the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, implemented in the Robot Operating System (ROS), our method facilitates conflict detection and resolution in 2D environments. Through simulations using ROS, Gazebo, and Iris drones, we validate the effectiveness of our approach in scenarios with initial trajectory conflicts. Our work addresses the pressing need for UAVs to autonomously plan and execute safe flights, laying the groundwork for enhanced UAV capabilities in various real-world applications. The simulation results demonstrate the efficiency and robustness of our approach.

关键词： Simulation Autonomous aerial vehicles Aircraft navigation Sensor systems Robustness Real-time systems Trajectory Safety Sensors Drones

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