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Deep Learning Based Uplink Power Allocation in Multi-Radio Dual Connectivity Heterogeneous Wireless Networks 35

Deep Learning Based Uplink Power Allocation in Multi-Radio D...

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35th IEEE international symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Rahman, Md. Habibur Chowdhury, Mayukh Roy Sultana, Abida Tripathi, Asheesh Silva, Aloizio Pereira Da Commonwealth Cyber Initiative Virginia Tech United States

ISBN: (纸本)9798350362244

Multi-Radio dual connectivity (MR-DC) has been emerged as a promising 3rd generation Partnership Project (3GPP) feature aiming at improving per-user data throughput enabling traffic aggregation from two base stations (BSs) simultaneously operating the same or different radio access technologies (RATs). In MR-DC uplink (UL) data transmission, UL power assigned to the two interfaces may exceed the maximum transmission power of the user equipment (UE) leading to increased UL effective interference at the network. An optimal power allocation strategy can significantly reduce the effective UL interference which also leads to the enhancement of network throughput. But in the MR-DC scenario, dynamic switching of node assignment and consideration of effective UL transmission in a given sub-frame introduce additional challenges, making existing methods like semi-static or iterative and heuristic optimization algorithms inefficient. In this study, we aim to design a deep convolutional neural network (DCNN) model, more specifically a U-Net based model, for intelligent power allocation in the MR-DC network. A constrained optimization function is formulated considering data rate maximization, UL effective interference reduction, and effective UL transmission towards any node in the MR-DC, as well as an Interior-point method (IPM) algorithm is utilized to generate a labeled dataset. The proposed model is trained to predict the optimal power label more efficiently, especially when dealing with varying numbers of UEs and BSs. Finally, we have depicted that the proposed U-Net based model can achieve up to 10.98% total throughput improvement predicting optimal power label for 88 UEs within 0.07 seconds through simulations. © 2024 IEEE.

关键词： Constrained optimization

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3rd international Conference on Recent Advances in Mechanical Engineering Research and Development, ICRAMErd 2022

3rd International Conference on Recent Advances in Mechanica...

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3rd international Conference on Recent Advances in Mechanical Engineering Research and Development, ICRAMErd 2022

ISBN: (纸本)9789811994920

The proceedings contain 59 papers. The special focus in this conference is on Recent Advances in Mechanical Engineering Research and Development. The topics include: Parametric optimization of LPG Refrigeration System Using Artificial Bee Colony Algorithm;a Generalized Oppositional Differential Evolution Algorithm for Parameter Extraction of Different Photovoltaic Models;analysis of Community Engagement on Social Networking Sites During the Kerala Floods in 2018;application of Evolutionary Technique for Mapping onto Network on Chip;Parametric optimization of Resistance Spot Welded Dissimilar Metals Utilizing Advanced Hybrid Taguchi-MARCOS Method;Prioritizing the Factors Affect in Covid-19 Vaccines, a Fuzzy-AHP Approach;Apriori Versus FP-Growth for Recommendation System;optimization of EDM Process Parameters in Machining of Titanium Alloy Used for Aerospace Applications;Ergonomic Risk Assessment of Rubber Tappers Using Rapid Upper Limb Assessment (RULA);Finite Element Analysis of Cranked Beam with Reinforcement Detailing of SP 34 (1987);free Convection from Isothermally Heated Hollow Tube with Annular Fins;design and Analysis of Coir Fibre Reinforced Polypropylene Based Internal Car Door Panel;pedobarography-Based Prosthetic Foot Design and optimization Methodology;atlas generation of Leg Mechanisms for Walking Platforms Using Creative Synthesis;effect of Curve Angle on Prestressed Box-Girder Bridges;design, Analysis and optimization of Chassis for a Utility Vehicle;design and Development of Semi-automated Manual Transmission;analysis of Interdependence of Structural Irregularity in Connected Buildings;numerical Investigation on the Effect of Inclination Angle of the Wall Fin on the Hydrogen–Air Micro-combustion;Modeling of a Severe Accident in a VVR-Type Research Reactor Using MELCOR Accident Analysis code.

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A Simulation Environment of Solar-Wind Powered Electric Vehicle Car Park for Reinforcement Learning and optimization 3rd

A Simulation Environment of Solar-Wind Powered Electric Vehi...

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3rd international symposium on New Energy and Electrical Technology (ISNEET)

作者： Li, Handong Dai, Xuewu Kotter, Richard Aslam, Nauman Cao, Yue Northumbria Univ Dept Math Phys & Elect Engn Newcastle Upon Tyne NE1 8ST Tyne & Wear England Northumbria Univ RENU Newcastle Upon Tyne NE1 8ST Tyne & Wear England Wuhan Univ Sch Cyber Sci & Engn Wuhan Peoples R China

ISBN: (纸本)9789819905553;9789819905539;9789819905522

In accordance with the United Kingdom's goal to reach net zero by 2050, electric vehicles (EVs) play a crucial role in transportation. However, if the electricity used to charge EVs is derived from fossil fuels, this does not necessarily imply a reduction of overall emissions nationally or globally. To achieve optimal EV charging, a deeper comprehension of the unpredictability of on-site renewable energy sources (ORES) energy output is required. In this paper, the predicted renewable energy generated is used as the actual value for the reinforcement learning algorithm simulation environment. Such a model can represent the relationship between the power generation and the wind speed as well as solar irradiation, which are characterized by significant uncertainties. The uncertainty analysis shows that the wind speed at Newcastle upon Tyne can be modelled as a Weibull distribution with parameters A = 19.98 and B = 1.91. As for energy demand, this paper integrates information from an Oslo (Norway) car parking garage-based set of EV charging stations with EVs' demand statistics. The charging habits of EV users range from 800 min to 1,000 min of parking time, and from 5 kWh to 20 kWh in terms of charging energy. The maximum connection frequency for EV charging is 20 min. In addition, this paper develops methods for stochastic EV charging and parking space occupancy employing actual data. Based on the aforesaid renewable energy generation and the EV charging status, it is possible to develop a decision algorithm to optimal renewable energy efficiency.

关键词： ORES Reinforcement learning Wind power Renewable energy EV

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optimization of Line Justification Algorithm for Single Stuck at Faults Using Memory for Backtracking

Optimization of Line Justification Algorithm for Single Stuc...

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Advancement in Electronics & Communication Engineering (AECE), international Conference on

作者： Kaushik Makwana Yash Panavkar Usha S Mehta Electronics and Communication Institute of Technology Nirma University Ahmedabad India

In this paper, Line justification algorithm is implemented using C++. Line justification is a part of ATPG test vector generation process. ATPG first performs fault collapsing then it is followed by line justification and error propagation in order to get test vectors for a netlist given in ISCAS(international symposium on Circuits and Systems) format. The flow chart of algorithm and outputs of code have been given in the paper with analysis.

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Thermal optimization design of high-power charging station charging module 3

Thermal optimization design of high-power charging station c...

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2024 3rd international symposium on New Energy Technology Innovation and Low Carbon Development, NET-LC 2024

作者： Zhang, Siqian Zhao, Yingjie School of Energy and Power Jiangsu University of Science and Technology Zhenjiang212103 China

When facing significant heat generation from a 30 kW high-power charging station, traditional air-cooling forced convection methods are insufficient to meet the cooling requirements. In this study, based on an in-depth analysis of power modules, we designed a key component of the liquid cooling system, the cold plate, through theoretical calculations. Using simulation techniques, we analyzed the temperature distribution within the cold plate and performed design optimization under conditions of a 4C charging rate and a thermal load of 1598 W. Considering the actual operating environment of the charging equipment, we selected a 50% volume fraction of ethylene glycol-water solution as the coolant and simulated its performance under extreme outdoor conditions of 50°C. Simulation results showed that the optimized liquid-cooled cold plate module achieved a junction temperature of 69.73°C, significantly lower compared to the initial temperature of 109.9°C, resulting in an approximately 36% improvement in heat dissipation efficiency. This significant enhancement not only highlights the advantages of the liquid cooling system in managing the thermal load of high-power charging stations but also addresses the issue of excessive heat load faced by traditional cooling methods. The outcomes of this research provide important theoretical and practical foundations for the thermal design of charging equipment, which is expected to play a critical role in improving the performance and reliability of charging stations. © Published under licence by IOP Publishing Ltd.

关键词： Cooling systems

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3rd international symposium on New Energy and Electrical Technology, ISNEET 2022

3rd International Symposium on New Energy and Electrical Tec...

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3rd international symposium on New Energy and Electrical Technology, ISNEET 2022

ISBN: (纸本)9789819905522

The proceedings contain 102 papers. The special focus in this conference is on New Energy and Electrical Technology. The topics include: Novel Design Technique of Fuzzy Adaptive PI Regulator for Permanent Magnet Synchronous Motor;multi-port Energy Router for Virtual Motor Control;bidirectional Communication Between Parallel Buck Converters;identification of Key State Information of Substation Equipment Based on Text Mining and Semantic Analysis Technology;a Simulation Method for the Supply-Demand Conditions of Credits Under Corporate Average Fuel Consumption and New Energy Vehicles Credit Policy;Price Discovery and Volatility Modelling in the EU ETS: Evidence from Phase III;research on Intelligent Energy Management System for Differential Pressure Power generation;Distributed Cooperative Control for DC Microgrid Clusters Interconnected by Multi-port Converter;Quantitative Analysis and Diagnosis of High Resistance Contact Fault Based on ANN Neural Network;real-Time Electromagnetic Transient Simulation for Regional Power Grid Based on Cloudpss;IP Core Design of Phase-Locked Loop for Grid-Connected Photovoltaic Inverter Based on FPGA;Prediction of Minimum Miscibility Pressure (MMP) of CO2-Crude Oil System Based on GWO-RBF Neural Network;Research on Operation optimization of Crude Oil Pipeline Based on PPSO Algorithm;research on Life Prediction Method of Motor Bearings;research and Application of Power Distribution Monitoring System Based on Edge Computing;research on Transformer Inter-turn Fault Protection Method Based on Innovation Graph;research on Relay Protection of Active Distribution Network Based on Innovation Graph;optimal Configuration of Charging Station Based on Multi-objective Genetic Algorithm;Decoupling Control Strategy for Multi-active Bridge DC/DC Converters Based on Dichotomy;preface.

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Digital Rural Intelligent Tourism Model on Account of Intelligent optimization Algorithm 3

Digital Rural Intelligent Tourism Model on Account of Intell...

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3rd international symposium on Advances in Informatics, Electronics and Education, ISAIEE 2022

作者： Yu, Hong Inner Mongolia Minzu University Academy of Fine Arts Inner Mongolia Tongliao010000 China

ISBN: (纸本)9781665463577

Digital rural intelligent tourism is an important symbol of social modernization. In this paper, the intelligent optimization algorithm is used to conduct data modeling of rural intelligent tourism. By processing multiple targets of tourism, the innovation of digital rural intelligent tourism model is finally completed, so as to promote the rapid development of rural tourism. Smart tourism mode is an important means for the development of the industry. The adoption of advanced algorithms to enhance the innovation of the mode is conducive to the development and income generation of tourism. This paper studies the construction of digital rural intelligent tourism model on account of intelligent optimization algorithm, and explains the development and working principle of digital rural intelligent tourism model. The data analysis proves that the research on the construction of digital rural intelligent tourism model on account of the intelligent optimization algorithm has an efficient performance in the construction of digital rural intelligent tourism model. © 2022 IEEE.

关键词： Tourism

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Integrated Intelligent Technique for Loss Control in Distribution System via Distributed generation Installation Under Load Variations 3rd

Integrated Intelligent Technique for Loss Control in Distrib...

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3rd international Joint Conference on Energy, Electrical and Power Engineering, CoEEPE 2023

作者： Abdullah, Azlina Musirin, Ismail Othman, Muhammad Murtadha Rahim, Siti Rafidah Abdul Mansor, Mohd Helmi Shaaya, Sharifah Azwa Senthil Kumar, A.V. Department of Electrical and Electronics Engineering College of Engineering Universiti Tenaga Nasional Selangor Kajang43000 Malaysia School of Electrical Engineering College of Engineering Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra Perlis Arau02600 Malaysia Hindusthan College of Arts and Science Coimbatore India

ISBN: (纸本)9789819739394

As power consumption rises, it is essential to minimize line loss to maintain uninterrupted service to the end customer. Expansion of existing power plants has numerous environmental and economic hurdles, necessitating a careful analysis of local best options. As a result, several Distributed generation (DG) technologies have been integrated into the power system. This paper introduces Integrated Immune Moth Flame Evolutionary Programming (IIMFEP) as a new hybrid method for planning distributed generation in distribution systems. The IIMFEP determines the optimal sizing and placement of DG Type II that supplies reactive power under load variations to mitigate power loss in a system. Utilizing the IEEE 69-Bus Radial Distribution Systems (rdS), a comparison is made between the IIMFEP method and Moth Flame optimization (MFO), Artificial Immune System (AIS) and Evolutionary Programming (EP). The IIMFEP outperformed the other three techniques, which managed to achieve the lowest total system power loss. As the system’s real and reactive loads increase, so does the system’s overall power loss. Therefore, DGs must inject more reactive power to compensate for the power loss. The research findings indicate that the proposed IIMFEP reduces system power losses more effectively. The proposed IIMFEP is, therefore, a viable alternative solution addressing optimal DG difficulties in rdS. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Distributed power generation

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Proceedings of the 2022 3rd international symposium on Big Data and Artificial Intelligence, ISBDAI 2022

Proceedings of the 2022 3rd International Symposium on Big D...

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3rd international symposium on Big Data and Artificial Intelligence, ISBDAI 2022

ISBN: (纸本)9781450396882

The proceedings contain 29 papers. The topics discussed include: research on citizenization of the new generation of migrant workers from the perspective of employment policy based on grounded theory and DEA model;study of optimal site selection for brand promotion based on simulated annealing and genetic algorithms;the impact of precise poverty alleviation policies on the vulnerability of farm households to poverty: research based on micro big data;research on the construction of e-learning information ecosystem based on explanatory structural model;financial data processing and forecasting model analysis based on neural network;analysis of the integration and development of the tea-tourism industry based on entropy weight method and coupling coordination degree model;research on economic growth target and operating efficiency of listed tourism companies based on multiple regression model and threshold effect model;an effective software vulnerability detection method based on devised deep-learning model to fix the vague separation;and analysis and research on the related modes of collaborative optimization and deep fusion based on grey fuzzy theory.

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Regression Test Case optimization Using Jaccard Similarity Mapping of Control Flow Graph 3rd

Regression Test Case Optimization Using Jaccard Similarity M...

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3rd international Conference on Innovations in Computational Intelligence and Computer Vision, ICICV 2022

作者： Padmanabhan, Mani Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (纸本)9789819926015

The complexities of cyber physical systems development are mapping with controlling software in the modern engineering. Software testing are major key role in the modern engineering. The expected outcome from the test case suite is an important source for testing the software coding. Test results ensure the quality with the correctness of the developed software. The modification of the software source code has led to a change in the expected outcome in the regression testing. Validating a large number of test cases multiple times can be a high execution time and development cost. The methodology has been proposed for the selection of test paths during regression testing. The selected paths are covering new expected outcomes in the modified software program, thereby reducing the testing time. Regression test path selection methodology is based on Jaccard similarity mapping of control flow graph (CFG) and artificial bee colony (ABC) algorithm to find out the new test path which is not tested in the older version of the software programming. Our experiments show that the proposed approach identifies the new test path for test case generation during regression testing. The fault detection capability is high compared with structural novel test path selection methodology. code coverage criteria for the modified software programs show high effectiveness with less test path selection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Software testing

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