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5th international conference on Advanced Informatics for Computing Research, ICAICR 2021

5th International Conference on Advanced Informatics for Com...

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5th international conference on Advanced Informatics for Computing Research, ICAICR 2021

ISBN: (纸本)9783031094682

The proceedings contain 23 papers. The special focus in this conference is on Advanced Informatics for Computing Research. The topics include: Efficient Entity Resolution for Bibliographic Data Using MapReduce;securing of Identification System Data Transmission Using Deep Autoencoders and Data Hiding;a Hybrid Filter/Wrapper Machine Learning Model for Classification Cancer Dataset;edge-Assisted IoT Architecture: A Case of Air Pollution Monitoring Frameworks;optimized Analysis Using Feature Selection Techniques for Drug Discovery Detection;crop Identification and Disease Detection by Using Convolutional Neural networks;an Efficient Novel Approach for Detection of Handwritten Numericals Using Machine Learning Paradigms;multiclass Classification in Machine Learning algorithms for Disease Prediction;CREA-Components Reusability Evaluation and Assessment: An Algorithmic Perspective;capsule network Based Speech Emotion Recognition for Efficient Capturing of Spatial Features;a Survey and Analysis on the Distraction Patterns of the Students in E-Learning and M-Learning Environments;relationships Among Human Genome Graph Elements Using Clusters Detection;transfer Learning Architecture Approach for Smart Transportation System;preface;a Blockchain-Based Solution for Electronic Medical Records System in Healthcare;analysing Sentiments of People Over Vaccines in Reddit Posts Using Natural Language Processing;segmentation of Tumor Region from Mammogram Images Using Deep Learning Approach;review on IoT Based Real-Time Healthcare Monitoring System;application of IoT in 5G Wireless Communication: A Detailed Review;enhanced Service Point Approach for Microservices Based Applications Using Machine Learning Techniques;Worldwide Vaccination Report for COVID-19 Analysis and Visualization Using Deep Learning.

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Expression recognition based on convolutional difference contextual feature fusion

Expression recognition based on convolutional difference con...

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2022 international conference on Electronic Information Engineering and computer Science, EIECS 2022

作者： Lu, Shengfu Yang, Chuang Li, Mi Kang, Jiaming Faculty of Information Technology Beijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Department of Automation Faculty of Information Technology Beijing University of Technology Beijing China Department of Automation Faculty of Information Technology Beijing China

ISBN: (纸本)9781510663312

Facial expression recognition has always been a focus of study in emotion computing. With the aim of solving the problem that previous facial expression recognition studies are susceptible to individual differences and background noise, as well as the loss of facial expression features in deep networks of deep convolutional networks, we propose a facial expression method based on convolutional difference contextual feature fusion. The convolutional difference module can carry out difference operation between emotional image and neutral image in the input image, eliminate individual difference and background noise in expression features and improve the accuracy and generalization of the network. Finally, convolutional difference and contextual features are combined to improve the accuracy of the network further. Experiment results of 4 public facial expression datasets illustrate that compared with the existing facial expression recognition methods, this method has higher accuracy, can extract facial expression features more effectively, and has a better generalization ability. © 2023 SPIE.

关键词： Convolutional neural networks

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2nd international conference on Innovation in Electrical Power Engineering, Communication, and Computing technology, IEPCCT 2021

2nd International Conference on Innovation in Electrical Pow...

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2nd international conference on Innovation in Electrical Power Engineering, Communication, and Computing technology, IEPCCT 2021

ISBN: (纸本)9789811670756

The proceedings contain 47 papers. The special focus in this conference is on Innovation in Electrical Power Engineering, Communication, and Computing technology. The topics include: Stability Improvement of Fractional-Order Filters Using Gain Bandwidth and Step Response Approach;tidal Energy Connected with Grid for Coastal Area;design of Switched Capacitor-Based Charge Amplifier in 180 nm technology;optimal Power Trading for a Micro-grid with Demand Response in Competitive Electric Market;A Comparative Study of Deep Learning algorithms for Identification of COVID-19 Disease Using Chest X-Ray Images;electrical and Dielectric Characteristics of Ethylene Vinyl Acetate/Aluminum Nitride Polymer Composite for Usage in Flexible Electronics;advanced Adaptive Filter-Based Control Strategy for Active Switch Inverter Operation;Bypass Diodes Configurations for Mismatch Losses Mitigation in Solar PV Modules;sentiment Analysis of Bengali Facebook Data Using Classical and Deep Learning Approaches;Design and Analysis of RF Optimization in 2G GSM and 4G LTE network;analysis and Recognition of Emotions from Voice Samples Using Ant Colony Optimization Algorithm;Moth Flame Optimized Automatic Generation Control with PIDF Controller for the Integration of Plug-In Electrical Vehicles with Interconnected Power System;Cost and Feasibility Analysis for Designing a PV–Wind Hybrid Renewable Energy System (A Case Study for Campus-3, KIIT University, Bhubaneswar);Design of Optimal Multi-band PSS for Variable Solar-Penetrated Power System;TLBO Designed 2-DOFPIDF Controller for LFC of Multi-area Multi-source Power System;Automatic Generation Control of an Interconnected Power System Using 2-degree of Freedom Fractional Order PID Controller;Performance Assessment of Three-Phase Standalone PV System with Machine Learning-Based Controller;development of Conceptual Framework for Reinforcement Learning Based Optimal Control.

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3D reconstruction in industrial environments based on an improved neural radiation field method research

3D reconstruction in industrial environments based on an imp...

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2024 international conference on computer network Security and Software Engineering, CNSSE 2024

作者： Zhou, Kaichen Huang, Tianlun Wang, Weijun Luo, Haowen Khan, Fawad Du, Ziqian Feng, Wei Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Laboratory of Construction Robotics and Intelligent Construction Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial International Joint Research Center for Robotics and Intelligent Construction Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781510680234

Neural Radiation Field (NeRF) is driving the development of 3D reconstruction technology. Several NeRF variants have been proposed to improve rendering accuracy and reconstruction speed. One of the most significant variants, TensoRF, uses a 4D tensor to model the radiation field, resulting in improved accuracy and speed. However, reconstruction quality remains limited. This study presents an improved TensoRF that addresses the aforementioned issues by reconstructing its multilayer perceptron network. Increasing the number of neurons in the input and network layers improves the render accuracy. To accelerate the reconstruction speed, we utilized the Nadam optimization algorithm and the RELU6 activation function. Our experiments on various classical datasets demonstrate that the PSNR value of the improved TensoRF is higher than that of the original TensoRF. Additionally, the improved TensoRF has a faster reconstruction speed (≤30min). Finally, we applied the improved TensoRF to a self-made industrial dataset. The results showed better global accuracy and local texture in the reconstructed image. © 2024 SPIE.

关键词： network layers

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Blended Teaching System for English Education Based on computer Software

Blended Teaching System for English Education Based on Compu...

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2022 international conference on Education, network and Information technology, ICENIT 2022

作者： Guo, Lin Heilongjiang International University Heilongjiang Harbin China

ISBN: (纸本)9781665463072

In the 21st century, the relationship between computer technology and education is becoming more and more rigid, and its influence is getting bigger and bigger. The traditional single teaching mode in English education will cause problems such as low learning interest and unsatisfying individual needs. In order to make up for the shortcomings brought by the traditional teaching model of single professors, blended teaching (BT), that is, a teaching form that combines classroom face-to-face instruction and online learning, has developed rapidly in the field of English education. Therefore, this article will launch a research on the design of a BT system for English education based on computer software. This article designs the structure of the English education BT system, including the presentation layer, the intermediate business layer, and the database layer, and introduces the technical application and operation mode of each layer of the structure. This article designs the functions of the English education BT system in detail from the perspectives of students, teachers, and administrators, and uses genetic algorithms to develop sub-function modules for intelligent English education arranging courses. Finally, the system test shows that when the concurrent number is 50, 80, 100, 200, 300, the CPU usage of the English education mixed system is 17.4%, 20.1 %, 26.4%, 30.7%, 44.6%;memory usage The rates are 16.3%, 20.9%, 22.4%, 27.9%, 37.2%. This shows that the CPU usage and memory usage increase with the increase in concurrency, but the system can run stably and smoothly. © 2022 IEEE.

关键词： computer software

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A Novel Collision Detection Protocol for Wireless Full-duplex networks 20

A Novel Collision Detection Protocol for Wireless Full-duple...

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20th IEEE international conference on networking, Sensing and Control, ICNSC 2023

作者： Zhao, Qinglin Feng, Li Zhou, MengChu Yu, Haisheng Sun, Yi Macau University of Science and Technology School of Computer Science and Engineering China New Jersey Institute of Technology Department of Electrical and Computer Engineering Newark United States Macau University of Science and Technology International Institute of Next Generation Internet China Chinese Academy of Sciences Institute of Computing Technology Beijing China

ISBN: (纸本)9798350369502

Conventional wireless networks are half-duplex and most of them use contention-based protocols. These protocols usually adopt a principle of contention with collision avoidance and infer a collision occurrence very late from the absence of an acknowledgement after data transmission, thus causing low network performance. Wireless full-duplex enables simultaneous transmission (TX) and reception (RX) on the same channel. By exploiting this functionality, this work proposes a novel design that enables contention with collision detection (CCD) to improve the network performance. With this design, in contention, a node exploits its TX antenna to transmit a signal for channel contention, while exploiting its RX antenna to sense if other nodes are transmitting too. By checking the status of TX and RX antennas, the node can detect the contention collision before data transmission and hence obtains an opportunity to avoid data collision effectively. This work then develops a theoretical model to analyze the collision probability of this design. Extensive simulation results verify the effectiveness of our proposed design in improving wireless network performance. © 2023 IEEE.

关键词： network performance

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16th EAI international conference on Cognitive Radio Oriented Wireless networks, CROWNCOM 2021 and 14th EAI international Wireless Internet conference, WiCON 2021

16th EAI International Conference on Cognitive Radio Oriente...

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16th EAI international conference on Cognitive Radio Oriented Wireless networks, CROWNCOM 2021 and 14th EAI international Wireless Internet conference, WiCON 2021

ISBN: (纸本)9783030980016

The proceedings contain 25 papers. The special focus in this conference is on Cognitive Radio Oriented Wireless networks. The topics include: The Performance Research of LTE-A Cellular network Based on Relay and Pass-Through D2D technology;A Survey Channel Estimation for Intelligent Reflecting Surface (IRS);minimum Class Variance Thresholding Based on Multi-objective Optimization;pedestrian Detection Based on Deep Learning Under the Background of University Epidemic Prevention;Gesture Recognition Controls Image Style Transfer Based on Improved YOLOV5s Algorithm;Detection of Malicious Nodes Using Collaborative Neighbour Monitoring in DSA networks;research on Denoising Method in Pseudo-analog Video Transmission;Confidential Communications for Mobile UAV Relaying network;Implementation and Performance Analysis of Smart Attendance Checking Using BLE-Based Communications;methodology for Characterizing Spectrum Data by Combining Quantitative and Qualitative Information;intra-train Wagon Wireless Channel Connectivity Analysis of Ultra Dense Node Deployments;hardware-Accelerated Blockchain-Based Authentication for the Internet of Things;an Investigation of Vulnerabilities in Internet of Health Things;faking Smart Industry: A Honeypot-Driven Approach for Exploring Cyber Security Threat Landscape;anonymous Key Agreement and Mutual Authentication Protocol for Smart Grids;SAMA: Security-Aware Monitoring Approach for Location Abusing and UAV GPS-Spoofing Attacks on Internet of Vehicles;computationally Efficient Look-up-Tables for Behavioral Modelling and Digital Pre-distortion of Multi-standard Wireless Systems;metaheuristic Optimisation for Radio Interface-Constrained Channel Assignment in a Hybrid Wi-Fi–Dynamic Spectrum Access Wireless Mesh network;performance of Cooperative Spectrum Sensing Based on Random Transition of the Primary User in Laplacian Noise;assessment of Spectrum Management Approaches in Offshore Private Industrial 5G networks;An Eigenvalue Based Cooperative Sp

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A Face Morph Detection Method Based on Convolutional Neural networks and Occlusion Test 7

A Face Morph Detection Method Based on Convolutional Neural ...

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7th international conference on Image, Vision and Computing, ICIVC 2022

作者： Ma, Tian Bamweyana, Arnold Guo, Ming Benon, Kavuma Xi'an University of Science and Technology Department of Computer Science and Technology Xi'an China Kangchiao International School Department of Computer Science Xi'an China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

Face morphing is by far the greatest threat to effective automatic boarder control systems. However, there is a lack of consideration and examination of a morphed face image frame as a blend of two images;hence, one image obstructs the other. To address this, we proposed a combination of an occlusion detection method, FSG-FD and a VGG19 neural network architecture to detect these face morphs. First, we designed our algorithms for each of our proposed systems;one for FSG-FD and the other for the VGG19 architecture. Then, we blended the two methods into a joined model by pre-training the neural network and increasing its convolutional layers by an additional three layers. The experiments showed that our algorithm achieved higher accuracy than other methods at detecting face morphs. © 2022 IEEE.

关键词： Convolution

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K-Pointer-network for Express Delivery Routes Planning 3

K-Pointer-Network for Express Delivery Routes Planning

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Zheng, Xuyi Dalian University of Technology International School of Information Science and Engineering Dalian116620 China

ISBN: (纸本)9781665459112

In this study, the author intends to provide a suitable design for the express distribution path to shorten delivery times. If the route is not well-planned, the delivery time for an express shuttle between cities will be extremely long. The primary purpose of this experimental research is to combine K-means and pointer network optimization to examine the ability of pointer networks in express route planning, improve pointer network performance in the TSP challenge, and obtain a shorter express route planning. The improved K-Pointer-network is compared to the regular pointer network in this study. According to model theory and experimental data, it can be demonstrated that clustering data samples independently improves computational performance and planning results in many cases, and that when the model is confronted with a large number of test inputs, the K-Pointer-network outperforms the traditional pointer network and provides relatively good express route planning. © 2022 IEEE.

关键词： Computation theory

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Analysis on Generative Adversarial networks: Application in Graphics and Image Processing 4

Analysis on Generative Adversarial Networks: Application in ...

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4th IEEE international conference on Civil Aviation Safety and Information technology, ICCASIT 2022

作者： Li, Tianbai Liu, Yeung Miao, Yingpei Zhu, Zihe Nanjing Foreign Language School Fangshan Campus Nanjing China Beijing Keystone Academy Beijing China Shenzhen bao'An Middle School Shenzhen China Hunan Guangyi International Academy Changsha China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

General Adversarial network, or GAN, a novel algorithm that is efficient and not too sophisticated for most computer engineers with often greater precision than other existing algorithms, has exhibited vast amounts of merits and conveniences after dominating the major computer domains. So far, the method has been applied to and made some singular achievements in statistical and medical and other similar domains. In today's and future's fast paced world, this paper has seen greater demands for such a method to provide more reliable data with fewer resources and time, inspiring us to uncover the potential and possible applications of this algorithm in the future. © 2022 IEEE.

关键词： Generative adversarial networks

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