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检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

共 2957 条记录，以下是611-620 订阅

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Computational fluid dynamics (CFD) analysis of thermoelectric generator for Regenerative Braking of the Hybrid Electric Vehicle 3

Computational fluid dynamics (CFD) analysis of thermoelectri...

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3rd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2023

作者： Saif, Md. Zilan Uddin Ahmed, Md. Rasel Hanif, Md Abu Tasnim, Farhan Hossain, Chowdhury Akram American International Universiy-Bangladesh Dept. of Electrical & Electronics Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346435

Electric automobiles are a vital, dynamic, and quickly growing issue that touches on a range of topics, including increased energy demand and consumption, reduced environmental emissions, ensuring the use of renewable energy sources, and so more. Electric vehicles are also becoming more affordable. With the rising amount of research and development being done on electric cars on a worldwide basis, regenerative braking is becoming more and more significant. Using the vehicle's waste heat energy, it is hoped to extend the range of the battery, so providing an additional source of benefit. The goal of this publication is to propose of a Thermoelectric Generator (TEG) model based on an analysis of gas velocity pressure and turbulence kinetic energy at peak temperature to increase the operating range of hybrid electrical vehicles (HEVs) by storing the electrical power output in the battery. According to the regenerative braking system concept, kinetic energy from automobiles that was released into the environment as waste heat energy is converted into electricity using this method. © 2023 IEEE.

关键词： Hybrid vehicles

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Analytical Comparison of the Impact of Si and GaAs as Materials in Designing 3D Density Gradient Nanowire MOSFET for Low Power Applications 3

Analytical Comparison of the Impact of Si and GaAs as Materi...

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3rd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2023

作者： Nazreen, Syeda Fahima Ali, M. Tanseer American International University-Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350346435

Semiconductor industry has been one of the most promising industries and MOSFET is its main component. Extensive research is going on ever since it started to provide better performance and low-cost effective devices in the market. The study is done on a 3D density gradient nanowire MOSFET for showing the impact of using varied materials on the device performance. A comparison has been made between Silicon (Si) and Gallium Arsenide (GaAs) as semiconductor materials. DC and AC analysis have been done on both models and their results have been compared. The drain current in the Id-Vg and Id-Vd curve for GaAs used model is higher than the Si used model by about 10 times which is useful for analog applications. The threshold voltage for both models is 0.7V. Besides that, the electron concentration forming a potential well of the depth of about 104 for GaAs used material than the model made using Si as material. In the case of AC analysis, the transconductance range for the model using GaAs is almost double of the model designed using Si. © 2023 IEEE.

关键词： Drain current

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AI-based Consumers' Preference Prediction Using a Research-grade BCI and a Commercial-grade BCI for Neuromarketing: A Systematic Comparison 3

AI-based Consumers' Preference Prediction Using a Research-g...

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3rd international conference on Electrical, Computer and Communication Engineering, ECCE 2023

作者： Ishtiaque, Farhan Mashrur, Fazla Rabbi Miya, Mohammad Tohidul Islam Rahman, Khandoker Mahmudur Vaidyanathan, Ravi Anwar, Syed Ferhat Sarker, Farhana Mamun, Khondaker A. Institute of Advanced Research United International University Aims Lab Dhaka Bangladesh Neuroengineering University of Rochester RochesterNY United States School of Business and Economics United International University Dhaka Bangladesh Imperial College London Department of Mechanical Engineering London United Kingdom Institute of Business Administration University of Dhaka Dhaka Bangladesh University of Liberal ArtsBangladesh Department of Computer Science and Engineering Dhaka Bangladesh United International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350345360

In Neuromarketing, BCI technology is used to analyze how a consumer behaves in response to a marketing stimulus, to evaluate the stimuli itself. Traditionally it can be achieved by different marketing research techniques such as questioner-based surveys, interviews, field surveys, etc. But since these procedures are time-consuming and prone to human error, neuromarketing promises a more advanced, automated, and accurate solution. Most of the neuromarketing solutions use research-grade EEG devices to analyze consumer preferences, but their effectiveness using consumer-grade EEG devices is unknown. In this study, we designed an experiment to compare a research-grade EEG device with a consumer-grade EEG device for predicting consumer preference stated as affective attitude (AA) and purchase intention (PI). We determined what type of setup, processing, and algorithm brings out the best result using the two devices. EEG signals were collected while the participants were shown pictures of different products in two different setups After that several signal-processing techniques were applied to remove artifacts and multi-domain features were extracted. 50 features were selected using Recursing Feature Elimination techniques. SMOTE was used to balance out the data. After that SVM classifier was used to classify Positive and Negative consumer preferences. With the first setup, we managed to achieve 82.4 % and 85.23 % accuracy for predicting purchase intention and affective attitude respectively with the research-grade EEG device whereas we achieved 75.43% and 79.5% accuracy with the commercial-grade EEG device. With the second setup, it's 78.75% and 83.75% using the research-grade EEG device whereas it's 75% and 82.97% using the commercial-grade EEG device for purchase intention and affective attitude respectively. © 2023 IEEE.

关键词： Brain computer interface

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Accuracy verification of sulfur dioxide data based on ultraviolet hyperspectral solar radiometer observations 3

Accuracy verification of sulfur dioxide data based on ultrav...

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3rd international conference on Environmental Remote Sensing and Geographic Information Technology, ERSGIT 2024

作者： Zeng, Hao Wang, Shun Xun, Lina The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781510690219

One of the primary air pollutants that has a detrimental effect on both the environment and human health is sulfur dioxide. The ecosystem and climate greatly depend on the high-precision monitoring of sulfur dioxide. In this study, SO2 ground-based data in Xi'an and Hangzhou were calculated using the UV continuous spectral inversion method, and the accuracy was confirmed using OMI satellite data that had undergone bilinear spatial interpolation. Although there are still some discrepancies in the comparative analysis results, the results indicate a good correlation between the ground-based measurement results of the UV hyperspectral solar radiometer and OMI data products;the correlation numbers are 0.938 and 0.941, respectively, and the relative errors are roughly 10%. The ultraviolet hyperspectral solar radiometer can complement this study's findings with accuracy and is a valuable tool for environmental monitoring. © 2025 SPIE.

关键词： Air quality

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On the Issue of Teaching data Analysis and Machine Learning to Students of Medical Specialties 3

On the Issue of Teaching Data Analysis and Machine Learning ...

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3rd international conference on Technology Enhanced Learning in Higher Education, TELE 2023

作者： Dorofeeva, V.I. Stroev, S.P. Dorofeeva, Ek.Yu. Turgenev Oryol State University Department of Informatics Oryol Russia Turgenev Oryol State University Departament of Algebra and Mathematical Methods in Economics Oryol Russia Medical Institute Turgenev Oryol State University Oryol Russia

ISBN: (纸本)9798350326567

Current trends in the transition to the use of new information technologies in all spheres of society make the issue of digital transformation of medicine relevant and significant as the most important means of solving the problem of digital transformation of the economy. Building digital medicine is one of the main strategic directions of the state policy of the Russian Federation. There is a need to teach students of a medical institute disciplines related to modern information technologies, namely data analysis technologies and machine learning as one of the relevant devices for processing and analyzing large volumes of medical information in order to increase the availability of medical care for patients and create auxiliary tools that simplify the work of doctors. The article presents the discipline (module) 'data Analysis and Machine Learning in the Medical Sphere', which can be useful for medical students, as well as medical residents and graduate students. The skills acquired during its study will make it possible to implement applied projects in the field of medicine and natural sciences. Note that this discipline (module) is universal and is aimed at training various professional groups. Among the students there can be both those studying in the direction of 'General Medicine', and students of the directions 'Pediatrics', 'Dentistry' and 'Pharmacy', due to the availability of the proposed material, and the importance of obtaining theoretical knowledge and practical experience in solving problems in the field of data analysis in digital medicine. © 2023 IEEE.

关键词： Machine learning

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Research on Radar Emitter signal Classification Technology based on SqueezeNet Lightweight Network 3

Research on Radar Emitter Signal Classification Technology b...

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3rd international conference on signal Image processing and Communication, ICSIPC 2023

作者： Jiang, Hu Wang, Wei Wu, Juan Chen, Xi Han, Ruoyu Zhang, Zhiyong Shi, Zhan Li, Pengfei State Key Laboratory of Mechatronics Engineering and Control Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781510670945

With the rapid advancement of information technology, the modern battlefield is characterized by a highly complex electromagnetic environment. Radar radiation sources exhibit wide-ranging parameter variations and strong random characteristics, presenting formidable challenges to the signal selection of radar radiation sources in missile-borne countermeasure systems. This paper addresses the issue of reliable identification and selection of radar source signals by on-board countermeasures systems. Through the analysis of source signal characteristics, the Smooth Pseudo Wigner-Ville Distribution (SPWVD) method is employed for time-frequency analysis to extract the time-frequency features of the source signals. Furthermore, a lightweight network based on SqueezeNet is implemented to achieve high-precision source signal selection. The results demonstrate that, when the SNR of the source signals is greater than 0dB, the network model achieves a recognition accuracy above 94.59%. The selection accuracy is comparable to that of the Convolutional Neural Network (CNN), thereby meeting the requirements of on-board countermeasure systems for reliable selection of radar source signals. The analysis confirms that under low signal-to-noise ratio conditions, noise significantly affects the network's selection accuracy by impacting the time-frequency clarity of the modulation signals. © 2023 SPIE.

关键词： Wigner-Ville distribution

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Technical talent training effectiveness: vocal versus visual feedback 3

Technical talent training effectiveness: vocal versus visual...

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3rd international conference on Electronic Information Engineering and data processing, EIEDP 2024

作者： Zhao, Xinbo Sun, Yi Yu, Jun Xu, Baodan Liaoning University of International Business and Economics Dalian116052 China Dalian Polytechnic University Dalian116034 China Segi University 47810 Malaysia

ISBN: (纸本)9781510680531

With the rapid advancement of digital technology, such as big data, artificial intelligence, cloud computing, etc., these technologies provide unprecedented possibilities for enterprises. Enterprises realize that in order to establish themselves in a fiercely competitive market, they must leverage digital technology to enhance the efficiency of cultivating skilled talents. The cultivation of employee presentation ability is an important guarantee for improving work efficiency. In this study, an Enterprise Technical Talent Training System, E3T, was developed to improve technical talents’ body and vocal expressions. Using the real-time feedback functions, E3T can detect undesirable states, provide instructions to presenters, and help them achieve the desired states. Among the basic operational skills, the practice support functions were implemented to improve face direction, body direction, and voice volume. By comparing the vocal feedback function with the visual feedback function, the results show that vocal feedback is more effective than visual feedback in improving face direction and voice volume. © 2024 SPIE.

关键词： Efficiency

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Networked Radar System: A More Advanced Radar Detection Platform 3

Networked Radar System: A More Advanced Radar Detection Plat...

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3rd international conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2023

作者： Zhou, Zhigang Zeng, Cao Wang, Haotian Liao, Guisheng Xidian University National Key Laboratory of Radar Signal Processing Xi'an China

ISBN: (纸本)9798350302356

A review is presented of work on the history of radar development, explaining the current high degree of interest in a more advanced radar detection platform (i.e., a networked radar system). Importantly, the advantages of the proposed networked radar detection system in this paper are also summarized in comparison with the existing multistatic radar system and netted radar system. Moreover, the characteristics of the networked radar detection system with high-speed and high-capacity communication networks are exploited in detail. More specifically, the concept of a radar node as the basic unit of a networked radar system and radar nodes deployment strategies for different detection scenarios are developed for further research. Most importantly, the prior art on the widespread variants in military and civilian fields with respect to the networked radar system are also discussed and investigated in this paper. © 2023 IEEE.

关键词： Tracking radar

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SceneAlert: A Mass Media Brand Listening Tool 3

SceneAlert: A Mass Media Brand Listening Tool

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3rd international Mobile, Intelligent, and Ubiquitous Computing conference, MIUCC 2023

作者： Ghoneim, Lara Helmy, Salma Yasser, Mohammed Wael, Omar Heidar, Mahmoud Ghanim, Taraggy Misr International University Faculty of Computer Science Egypt

ISBN: (纸本)9798350306231

Nowadays, a company's reputation is a main determinant of its success;it is beneficial for companies to be aware of what observers are saying about them in the media so that they may respond correctly. The proposed system is a website application that facilitates staying up to date with the latest mentions of companies. The system allows clients to enter keywords that represent what they want to monitor and select the media platforms they want to search. Our website application supports different media platforms, including social media platforms, blogs and articles, radio stations, podcasts, and television. Various tools and APIs implement data gathering from these platforms. The system accesses Twitter through the Twitter API v2, blogs and articles through the Bing Search API, and accesses podcasts through the iTunes Search API, and YouTube, television and radio using the y_dl tool. Audio preprocessing is implemented on the retrieved audio files, after which the Automated Speech Recognition (ASR) process is achieved using the Google Web Speech API, followed by the text preprocessing phase. The system detects the keyword mentions and alerts clients with the awaited context. It processes the data received to provide clients with data visualization on a web application after the data processing and analysis phase, which essentially includes sentiment analysis using the Mazajak API operating on a Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM) model as well as topic modelling using BERTopic and text summarization using the Latent Dirichlet Allocation (LDA) topic model. © 2023 IEEE.

关键词： Speech recognition

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An Assessment of Big data Analysis Technologies for Improved Information Delivery 3

An Assessment of Big Data Analysis Technologies for Improved...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Chanthati, Sasibhushan Rao Velmurugan, T. Gulati, Neha Kedia, Naresh Akram, Faiz Wegari, Getachew Mamo Harrisburg University of Science and Technology T. Rowe Price United States Srm Institute of Science and Technology Faculty of Management Kattankulathur India Jims Department of It Delhi India Manipal University Jaipur Department of Business Administration Rajasthan Jaipur India Jimma Institute of Technology Jimma University Faculty of Computing and Informatics Oromia Jimma Ethiopia

ISBN: (纸本)9798350319125

Massive information analysis is becoming more and more vital for turning in improved records to the healthcare industry. It has the potential to allow healthcare companies to better apprehend patient information, track affected person results, and improve the general affected person experience. To absolutely comprehend these potentials, healthcare companies have to apprehend the special big statistics evaluation technologies to be had to them and their related strengths and *** this paper, we perform a comprehensive assessment of big data evaluation technologies for improved statistics delivery in the healthcare industry. We check the technology and techniques relevant to the industry and speak their relative strengths and weaknesses. Specially, we consciousness on facts mining, device getting to know, herbal language processing, and fraud detection techniques. We evaluate the blessings and downsides of those technologies in phrases of information accuracy, evaluation speed, and value effectiveness. We conclude that facts mining comprehensive provide the most comprehensive answer for large statistics analysis inside the healthcare industry. © 2023 IEEE.

关键词： comprehensive consciousness techniques technologies weaknesses

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