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IEEE Signal Processing and Communications Applications (SIU)

作者： Sevgi Nur Bilgin Aktaş Pı nar Uluer Buket Coş kun Elif Toprak Duygun Erol Barkana Hatice Kö se Tatjana Zorcec Ben Robins Agnieszka Landowska Department of AI and Data Engineering Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Department of Computer Engineering Faculty of Technology and Engineering Galatasaray University Istanbul Turkey Department of Electrical and Electronics Engineering Faculty of Engineering Yeditepe University Istanbul Turkey University Children&#x2019 s Hospital Skopje North Macedonia School of Computer Science University of Hertfordshire Hatfield UK Department of Software Engineering Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk Poland

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450935

This paper proposes a physiological signal-based stress detection approach for children with autism spectrum disorder (ASD) to be used in social and assistive robot intervention. Electrodermal activity (EDA) and blood volume pulse (BVP) signals are collected with an E4 smart wristband from children with ASD in different countries. The peak count and signal amplitude features are derived from EDA signal and used in order to detect the stress of children based on the previously provided reference baselines. Furthermore, a comparison has been made with the stress values determined using low frequency (LF) and high frequency (HF) values extracted from BVP signal.

关键词： Pediatrics Autism Social robots Signal processing Feature extraction Assistive robots Physiology

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Numerical solution of the problem of turbulent currents that occur in the case of edge hardening

Numerical solution of the problem of turbulent currents that...

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International Conference on electronics, computers and Artificial Intelligence (ECAI)

作者： Marius Codrean Mihaela Cornelia Novac Mihaela Codrean Cornelia Emilia Gordan Ovidiu Constantin Novac Gyongyi Bujdoso Francisc Slovac Department of Electrical Engineering Electrical Engineering and Information Technology Faculty University of Oradea Oradea Romania National Geothermal Research Center Technology Transfer Center NGRC-TTC University of Oradea Oradea Romania Department of Electronics and Telecommunications Electrical Engineering and Information Technology Faculty University of Oradea Oradea Romania Department of Computers and Information Technology Electrical Engineering and Information Technology Faculty University of Oradea Oradea Romania Department of Computer Science and Library and Information Science Faculty of Informatics University of Debrecen Debrecen Hungary

The aim of this work is to develop numerical procedures for analyzing edge hardening using induction heating by turbulent currents. The section through the steel bar, whose lower edge needs to be hardened, is presented. For the inductor adapted to the piece configuration, the 2D model is assumed. The surface treatment of the piece must be differentiated: in the tip area, the heating must be greater than in the rest of the surface. Only the tip area needs to be subjected to hardening, while the rest of the piece must remain elastic to ensure the desired mechanical strength. The main purpose of this work is to propose inductor models for achieving differentiated heating of the blade.

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Talk to your data: Enhancing Business Intelligence and Inventory Management with LLM-Driven Semantic Parsing and Text-to-SQL for Database Querying

Talk to your data: Enhancing Business Intelligence and Inven...

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Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International Conference on

作者： Jerry Zhu Saad Ahmed Bazaz Srimonti Dutta Bhavaraju Anuraag Imran Haider Srijita Bandopadhyay Faculty of Mathematics University of Waterloo Ontario Canada Dept. of Computer Science National University of Computer and Emerging Sciences Islamabad Pakistan School of Agro and Rural Technology Indian Institute of Technology Guwahati Guwahati India Dept. of Electronics and Communication Engineering Vellore Institute of Technology India Dept. of Industrial and Systems Engineering Indian Institute of Technology Kharagpur Kharagpur India Dept. of Electronics and Communication Engineering University of Engineering and Management Kolkata India

ISBN: (数字)9798350369786

ISBN: (纸本)9798350369793

This paper delves into the potential of Large Language Models (LLMs) in revolutionizing business intelligence and inventory management through semantic parsing and text-to-SQL methodologies. It assesses various LLM models, such as DIN-SQL, DSP, NSQL, GPT, CoPilot, and LLaMa, elucidating their capabilities and contributions. Two critical analyses are presented here. The first compares cutting-edge LLM models using cosine similarity and cost efficiency metrics. The second analysis enhances GPT’s precision through prompt engineerings, like few-shot techniques, and explores frameworks like DIN-SQL, NSQL, and DSP. DIN-SQL substantially boosts accuracy, and NSQL demonstrates potential in specific scenarios. This research underscores the transformative potential of LLM-driven models in business intelligence and inventory management. DIN-SQL, in particular, emerges as a game-changer with the potential to reshape inventory management practices. GPT showcases its versatility through fine-tuning for tasks beyond conventional programming, while CoPilot offers a cost-effective alternative. This study emphasizes the importance of cost-effectiveness in real-world applications, with LLaMa and CoPilot being practical choices. NSQL, with its budget-friendly and semi-accurate solution, holds promise for semantic parsing in growing companies. These insights are a foundation for further innovation, promising unmatched efficiency and competitiveness across industries in the evolving Artificial intelligence landscape.

关键词： Industries Structured Query Language Technological innovation Costs Large language models Semantics Inventory management

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Smart Sampling and Residual Bottleneck Dense Network for Reliable and Energy-Efficient Routing in WSNs

Smart Sampling and Residual Bottleneck Dense Network for Rel...

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Trends in Material Science and Inventive Materials (ICTMIM), International Conference on

作者： Asma Anjum Dattathreya Salman Arafath Mohammed Dhaval Rabadiya K. B. Venkata Brahma Rao Ramya Maranan Department of Computer Science and Engineering HKBK College of Engineering Bengaluru Karnataka Department of Electronics and Communication Engineering Alva’s Institute of Engineering and Technology Moodbidri Karnataka Department of Electrical Engineering Computer Engineering Section College of Engineering King Khalid University Abha Asir Region Saudi Arabia Faculty of Management Studies Parul University Dist. Vadodara Gujarat Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

The fundamental requirement for WSNs made up of power-efficient and inexpensive sensor nodes depends on short-distance multi-hop communication. The potential of WSNs expands through new digital electronics and wireless communications technology despite the ongoing critical challenge related to energy efficiency. The main energy issues in WSNs stem from the excessively high control signal overhead between base stations and sensor nodes together with packet losses that require retransmissions to reduce energy efficiency. The proposed routing technique solves energy inefficiencies by employing RBDN-HMOA as an energy-efficient routing method. The proposed approach lowers system power consumption through its algorithm which picks distance and energy residual-based optimum forwarding nodes and adapts sampling rates automatically. The algorithm adopts Human Memory Optimization Algorithm (HMOA) to optimize network parameters. Research data shows that experimental results demonstrate both power efficiency and enhanced data transfer rate. The network demonstrates scalability because both throughputs reach 1100 kbps and energy usage reduces to 0.08 J when using 10 nodes. The RBDN-HMOA creates a practical method which extends network duration in practical deployments by diminishing WSN energy utilization without compromising data integrity.

关键词： Wireless sensor networks Energy consumption Fluctuations Heuristic algorithms Throughput Routing Energy efficiency Real-time systems Delays Optimization

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Enhancing Video Captioning: A Bayesian Normalized Attention-based Multi-Dimensional Graph Network with Moss Growth Optimization

Enhancing Video Captioning: A Bayesian Normalized Attention-...

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Pervasive Computing and Social Networking (ICPCSN), International Conference on

作者： Khallikkunaisa H. S. Niranjana Murthy Shirish Kulkarni Syed Mohd Uzair Iqbal Umang Pancha Natrayan L Department of Computer Science and Engineering HKBK College of Engineering Bangalore Karnataka India Department of Electronics and Instrumentation Engineering Ramaiah Institute of Technology Bangalore Karnataka India Symbiosis Law School Symbiosis Centre for Advanced Legal Studies and Research Symbiosis International (Deemed University) Pune India Faculty of Law Symbiosis Centre for Advanced Legal Studies and Research Symbiosis Law School Symbiosis International (Deemed University) Pune India Department of Computer Science and Engineering Faculty of Engineering and Technology Parul Institute of Technology Parul University Post Limda Gujarat India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798331535193

ISBN: (纸本)9798331535209

The explosive increase of video data requires the creation of advanced automated video captioning systems that can produce effective textual descriptions. Current methods, such as traditional deep learning (DL) models, are plagued with drawbacks such as high computational expense, overfitting, and inefficacy in contextual modeling, resulting in poor caption generation. For resolution of these difficulties, this contribution introduces the Bayesian Normalized Attention-based Multi-Dimensional Graph Network with Moss Growth Optimization (BN-AMGN-MGO) model, engineered to improve video captioning automatization on the MSVD set. The proposed framework starts off with pre-processing, in which unnecessary frames are removed via template matching to get only the representative frames. The feature encoding process utilizes a Bayesian Normalized Neural Network (BNNN) for dynamically manipulating probabilistic weight distributions to counter overfitting and increase robustness. During the decoder process, a Hierarchical Attention-based Multi-Dimensional Edge Graph Neural Network (HAM-GNN) combines temporal context modeling, graph neural networks, and hierarchical attention mechanisms to create structured textual descriptions. Classification stage employs a temporal attention mechanism to project dialogue act labels into attention-weighted representations, utilizing speaker dependencies for better accuracy. To further optimize performance, MGO is employed to refine HAM-GNN’s hyperparameters through wind direction determination, spore dispersal search, dual propagation search, and cryptobiosis mechanisms, ensuring effective exploration and exploitation of the search space. The proposed BN-AMGN-MGO model achieves the lowest MSE (0.021), highest PSNR (34.89), and SSIM (0.905), ensuring high-quality caption generation. Additionally, it outperforms existing models with an accuracy of 94.5% while maintaining the shortest computational time (5.6 sec), making it a robust and efficient

关键词： Attention mechanisms Accuracy Computational modeling Streaming media Graph neural networks Encoding Bayes methods Computational efficiency Context modeling Overfitting

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Energy Efficient Cluster Based Clinical Decision Support System in IoT Environment

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computers, Materials & Continua 2021年第11期69卷 2013-2029页

作者： C.Rajinikanth P.Selvaraj Mohamed Yacin Sikkandar T.Jayasankar Seifedine Kadry Yunyoung Nam Department of Electronics and Communications Engineering Erode Sengunthar Engineering College(Autonomous)Erode638057India Department of Information Technology SRM Institute of Science and TechnologyKattankulathur603203India Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Electrical Communication Engineering University College of EngineeringBIT CampusAnna UniversityTiruchirappalli620024India Faculty of Applied Computing and Technology(FACT) Noroff University CollegeKristiansand4608Norway Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

Internet of Things(IoT)has become a major technological development which offers smart infrastructure for the cloud-edge services by the interconnection of physical devices and virtual things among mobile applications and embedded *** e-healthcare application solely depends on the IoT and cloud computing environment,has provided several characteristics and *** research works reported that the energy consumption for transmission process is significantly higher compared to sensing and processing,which led to quick exhaustion of *** this view,this paper introduces a new energy efficient cluster enabled clinical decision support system(EEC-CDSS)for embedded IoT *** presented EECCDSS model aims to effectively transmit the medical data from IoT devices and perform accurate diagnostic *** EEC-CDSS model incorporates particle swarm optimization with levy distribution(PSO-L)based clustering technique,which clusters the set of IoT devices and reduces the amount of data *** addition,the IoT devices forward the data to the cloud where the actual classification procedure is *** classification process,variational autoencoder(VAE)is used to determine the existence of disease or *** order to investigate the proficient results analysis of the EEC-CDSS model,a wide range of simulations was carried out on heart disease and diabetes *** obtained simulation values pointed out the supremacy of the EEC-CDSS model interms of energy efficiency and classification accuracy.

关键词： Energy efficiency intelligent models decision support system IoT e-healthcare machine learning

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Twin-Array Quasi FSS Reflector with Dual Band Cross-Dipole for 5G Base Station Antenna Application

Twin-Array Quasi FSS Reflector with Dual Band Cross-Dipole f...

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Conference on Power, Energy and Innovations (ICPEI)

作者： Ian Jerome Q. Santos Maleeya Tangjitjetsada Paitoon Rakluea Norakamon Wongsin Chawalit Rakluea Chatree Mahatthanajatuphat Nonchanutt Chudpooti Tawan Thianthong Department of Electronics and Telecommunication Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Thanyaburi Pathum Thani Thailand Department of Electronics and Telecommunication Engineering Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Wongsawang Bangsue Bangkok Thailand Department of Industrial Physics and Medical Instrumentation Faculty of Applied Science King Mongkut’s University of Technology North Bnagkok Wongsawang Bangsue Bangkok Thailand Siam Airport Ground Service Co. Ltd. Don Mueang Bangkok Thailand

This article provides an explanation of the use of a Twin-Array Quasi Frequency Selective Surface (FSS) Reflector with Dual Band Cross-Dipole for antenna applications in 5G base stations. The base material employed in this study is FR4 sheet, which has a dielectric constant (ε r ) of 4.3. The antenna obtained has dimensions of 100x100 mm 2 and functions throughout the frequency spectrum spanning from 730 to 860 MHz, 1700 to 2130 MHz. The primary benefits of this antenna design are its lightweight structural composition, compatibility with the frequency range of 730–860 MHz, and discernible performance attributes. The CST Studio Suite software was used to conduct a simulation of the antenna’s performance. The antenna has an operating frequency range of 730–860 MHz and 1700–2130 MHz, enabling it to support a unidirectional wave propagation pattern that is suitable for the implementation of a 5G mobile communication base station.

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Exploring Environmentally Friendly Corrosion Inhibitors: Insights from Natural and Biomass Residue-Derived Compounds

SSRN

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SSRN 2024年

作者： Othman, Norinsan Kamil Mohammed, Naba Jasim Yusop, Muhammed Rahimi Al-Gburi, Ahmed Jamal Abdullah Materials Science Program Department of Applied Physics Faculty of Science and Technology University Kebangsaan Malaysia Selangor Bangi43600 Malaysia Faculty of Science and Technology School of Chemical Sciences and Food Technology University Kepangsaan Malaysia Selangor Bangi43600 Malaysia Faculty of Electronics and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Melaka Durian Tunggal76100 Malaysia

In this investigation, we explored the corrosive effects of date palm seed extracted from natural sources and biomass residues on mild steel in a solution of 0.5 M hydrochloric acid (HCl), employing a combination of experimental and theoretical approaches. Our objective was to scrutinize the interaction of the inhibitor with the metal surface, analyze experimental data, and elucidate how the structural characteristics of the inhibitors influence the corrosion process. The experimental results indicated that as the immersion time and temperature increased, the inhibitory effectiveness declined. Notably, the highest level of inhibition occurred when the concentration of date palm seed extract (DPSE) reached 1100 ppm, showcasing peak inhibitory effects of 95.8% and 97.8% through potentiodynamic polarization and electrochemical impedance spectroscopy techniques, respectively. Additionally, an analysis using X-ray diffraction (XRD) was conducted to scrutinize the chemical composition of the mild steel's surface. The adsorption data were evaluated using adsorption isotherms, revealing that DPSE adhered to the Langmuir adsorption isotherm on the mild steel surface. The Langmuir model exhibited the highest linear regression coefficient value and a slope close to unity. The Gibbs free energy () values suggested that the protection afforded by DPSE involved physical and spontaneous absorption. Examination of the results pertaining to the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) indicated that the carboxyl (COOH) group and the C=C bond were the principal regions exhibiting elevated electron acceptance activity. These components were found to be crucial in the adsorption process on the surface of iron (Fe). © 2024, The Authors. All rights reserved.

关键词： Electrochemical impedance spectroscopy

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Wireless Control Modelling for Overhead Crane 7

Wireless Control Modelling for Overhead Crane

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7th International Conference on Man Machine Systems, ICoMMS 2021

作者： Omar, M. Nazri Ismail, Mohd Muzafar Ayob, Mohd Nasir Arith, Faiz Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka 76100 Malaysia Faculty of Engineering Technology Electricals and Electronics Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka 76100 Malaysia Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Malaysia

Radio frequency (RF) remote controllers are widely used in manufacturing, construction, transportation, and many other industrial applications. Cranes, drills, and miners, among others, are commonly equipped with RF remotes. Installation wired communication takes a long time to set up the connection as compared to the wireless connection. The installation becomes very lengthy and complex if we want to get connected with each router. For the same reason, for a system expansion to add more device(s), the re-routing process to connect this new device(s) to the network can be avoided. Instead, with the wireless connection, we don't have to perform all the setup again. The network can be accessed with the authorized passcode. Radio-controlled devices are ubiquitous in all sorts of industries. In fact, many cranes are now being equipped with radio-controlled technology, which is revolutionizing the way crews move materials around a warehouse or job site. In the steel manufacturing industries, the wireless crane control has proven to assure. more advantage compared to the disadvantage. Through the surveillance and monitoring of wireless remote control for crane that done at AJSB, Prai, Malaysia. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Cranes

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Dual-Stage Interleaved On-board Charger for Electric Vehicle using Snow Geese Algorithm

Dual-Stage Interleaved On-board Charger for Electric Vehicle...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： A Chandrashekhar B Mallikarjuna Thiyagesan M L. Umasankar G. Ezhil Rukmani Devi Department of Mechanical Engineering Faculty of Science and Technology ICFAI Foundation for Higher Education Hyderabad Telangana India Department of Electrical and Electronics Engineering RNS Institute of Technology Bengaluru Karnataka India Department of Electrical and Electronics Engineering R.M.K Engineering College Chennai Tamil Nadu India Department of Electrical and Electronics Engineering S. A. Engineering College Chennai Tamil Nadu India Department of English Bannari Amman Institute of technology Sathyamangalam Tamil Nadu India Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Deemed to be University Chennai Tamil Nadu India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The growing demand for electric vehicles (EVs) has highlighted the need for efficient and reliable on-board chargers (OBCs) to reduce charging time and enhance battery life. Nevertheless, there are some issues in classic OBC designs: harmonic distortion may become too large, electromagnetic interference increases, and thermal management is not proper; all of which directly affects other elements of the system. As an optimization approach to enhance the performance of the dual-stage interleaved on-board charger (OBC) for electric vehicles (EVs), this work introduces the Snow Geese Algorithm (SGA). The objective of the proposed method is to enhance charging efficiency and minimize cost. The proposed SGA is used to optimize the dual-stage interleaved converter, focusing on reliable performance and effective operation within EV charging systems. The suggested approach is then put into practice on the MATLAB platform and contrasted with a number of current techniques, including Artificial Bee Colony (ABC), Simulated Annealing (SA), Multi-objective Genetic Algorithm (MOGA), and Particle Swarm Optimization (PSO). The proposed SGO method for dual-stage interleaved EV chargers achieves a cost of $1,050.80 and an efficiency of 97.2 %, demonstrating its effectiveness in reducing expenses while maximizing optimization performance in charging systems.

关键词： Sentiment analysis Costs Heuristic algorithms Snow Electromagnetic interference Simulated annealing Thermal management Harmonic distortion Reliability Vehicle dynamics

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