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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 11084 条记录，以下是571-580 订阅

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Latency Minimization in Blockchain-Enabled Fog computing Networks: A Novel Byzantine Fault Tolerance Approach 23

Latency Minimization in Blockchain-Enabled Fog Computing Net...

引用

23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Sajo, Assadig Abdelrhman Huang, Xiaoge Saif, Moatssim Chen, Qianbin School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781665494571

Recently, fog computing networks (FCNs) have shown enormous benefits yet suffer from security and privacy issues. Blockchain technology has been introduced as a solution to these issues. Nevertheless, it brought new challenges. In this paper, we propose Smart Byzantine Fault Tolerance (SBFT) algorithm for blockchain-enabled FCNs. the proposed algorithm is designed to overcome the challenges of deploying BFT algorithms into FCNs. Such as high latency, computational cost, and communication overhead. the problem was formulated to achieve low latency for the system by optimizing task computation resource allocation, task partitioning, transmission power control, and blockchain computation resource allocation while ensuring the system's security. Simulation results were conducted to illustrate the effectiveness of the proposed algorithm, which can achieve low latency, computational cost, and communication overhead. © 2021 IEEE.

关键词： Fault tolerance Simulation Fault tolerant systems Power control Partitioning algorithms Blockchains Resource management

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Multi-class Waste Segregation using EfficientNetb3 Model through Waste Segregation Dataset 7

Multi-class Waste Segregation using EfficientNetb3 Model thr...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Prasher, Shikha Nelson, Leema Chitkara University Insititue of Engineering & Technology Chitkara University Punjab India

ISBN: (纸本)9798350372816

Efficient waste segregation is critical for successful recycling and sustainable waste management methods. In this paper, we investigate the use of EfficientNetB3, a cutting-edge deep learning model, to obtain high accuracy in trash segregation tasks. Using the Adam optimizer and training the model for 30 epochs, achieving 97% accuracy rate in categorising various waste types. the Adam optimizer's adaptive learning rate approach improves model efficiency and convergence, allowing for rapid training and durable performance. Deep learning algorithms, particularly EfficientNetB3, have the potential to automate trash segregation procedures, streamline recycling efforts, and enhance environmental sustainability. this study helps to advance intelligent waste management systems by demonstrating the efficacy of AI-driven approaches in addressing difficult environmental concerns. Future research will concentrate on incorporating AI technology into practical problems waste management infrastructures to improve efficiency and support circular economy concepts. © 2024 IEEE.

关键词： Circular economy

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Detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Swarm Optimization and Comparison with Particle Swarm Optimization Algorithm 7

Detection of Tongue-Based Myeloid Sarcoma Using Novel Cat Sw...

引用

7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Nalini, N. Deva Shahila, D Ferlin Ashwini, A. Vaishnavi, T. Rosi, A. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Electronics and Communication Engineering India

ISBN: (纸本)9798350372816

the exact scope of this research work is to compare novel cat swarm optimisation to particle swarm optimisation for tongue-based Myeloid Sarcoma detection. To perform the detection of tumor and leukemia, ten sample tongue datasets were subjected to novel Cat Swarm Optimisation and Particle Swarm Optimisation (PSO) methods, and the fiducial interval remaining at 95%. According to the simulation's performance metrics, Novel Cat Swarm Optimisation outperforms PSO (79%) in terms of accuracy, with a significant level of p = 0.001 (p0.05) in SPSS statistical analysis. From this study, the accuracy of detection of tumor and leukemia using Novel Cat Swarm Optimization showed better results than the PSO algorithm for the considered sample images. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Multi-band discriminant speech synthesis analysis based on Natural Language Processing 7

Multi-band discriminant speech synthesis analysis based on N...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Liu, Songjia Yao, Yuancheng Liu, Binyu Zhu, Rui Ren, Jing Southwest University of Science and Technology School of Information Engineering Mianyang China

ISBN: (纸本)9781665478571

With the rapid development of neural networks and deep learning, speech synthesis technology has been significantly improved. the end-to-end speech synthesis systems based on deep learning have been able to synthesize speech with naturalness close to the original human pronunciation. However, the existing end-to-end speech synthesis system model is complex, and it is impossible to achieve real-time speech synthesis on devices with low computing power. In this paper, a multi-band discriminative autoregressive speech synthesis model is proposed based on natural language processing. the model uses an encoder-decoder architecture with attention mechanism, which is mainly composed of DSC-GRN modules. Stacking multiple convolutions with different expansion coefficients by gating the residual structure can increase the receptive field so that the encoder and decoder can pay attention to the context information with a longer time span, which can improve the performance of the model. the whole model uses full convolution architecture and can be trained in parallel. Compared with the existing autoregressive model, the number of parameters of the model is greatly reduced. the synthesis speed is improved, and the quality of synthesized speech is ensured. © 2022 IEEE.

关键词： Deep learning

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Automatic Billing Trolley for an Enhanced Supermarket using RFID 7

Automatic Billing Trolley for an Enhanced Supermarket using ...

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7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Perumal, A. Vinoth, A. Navaneetha Krishnan, C. Sriraman, R. Kumar, K. Dept of EEE National Engineering College Tamilnadu Kovilpatti628501 India

ISBN: (纸本)9781665464086

Many customers find it challenging to wait in a lengthy line for the billing of their purchases. this results in financial loss and a subpar bill for the incorrect consumer. In grocery stores or supermarkets, trolleys are utilised to make shopping easier. By automatically identifying the products being added to the cart and providing the relevant information on the user interface, the suggested smart cart can make the shopping experience easier. Shopping malls are still popular, even if it is common to see individuals getting excited about online shopping via e-commerce websites. there are many different types of shopping carts available in malls and shopping centers. this study presents a technologically-assisted intelligent shopping cart that can recognise products. the primary objective of this effort is to reduce wait times in congested supermarkets and other shopping centres using an innovative cart system that makes use of RFID technology to provide an intelligent approach to the billing process. the project's primary focus is the smart cart gadget. It consists of an RFID reader, a GSM module, an Arduino microcontroller, an LCD display, and a keypad. Every item that is put into the cart will be able to have a bill generated by the system. It will be simpler to skip billing lines in shopping malls with the offered method. the suggested design's conventional queuing system for billing generation makes shopping easy and enjoyable. © 2023 IEEE.

关键词： Liquid crystal displays

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A hybrid encryption transmission scheme for industrial control systems 7

A hybrid encryption transmission scheme for industrial contr...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Wang, Lei Wang, Zhi-Hui Guo, Feng Wu, Chuan-Kun Linyi University School of Information Science & Engineering Linyi China

ISBN: (纸本)9781665478571

With the convergence of information technologies such as the Industrial Internet of things (IoT) and cloud computing with industrial control systems (ICS), the security of industrial data is at great risk. To ensure the confidentiality and integrity of industrial data, this paper designs a hybrid encryption, access control and blockchain-assisted logging communication scheme using Advanced Encryption Standard (AES) and Ciphertext-Policy Attribute-Based Encryption (CP-ABE) algorithms. the algorithm is validated by simulation experiments and has the advantage of low decryption overhead. © 2022 IEEE.

关键词： Access control

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Detection of Counterfeit Products with QR Codes using Blockchain technology 7

Detection of Counterfeit Products with QR Codes using Blockc...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Mane, Vijay Patil, Ruturaj Pawar, Shantanu Pujari, Nagesh Vishwakarma Institute of Technology Department of Electronics and Telecommunication Engineering Pune India

ISBN: (纸本)9798350372816

Supply chain management commonly encounters challenges such as duplicate products and a lack of standardization due to insufficient transparency. this creates problem in the supply chain which takes up valuable time and resources. the presence of counterfeit products adds on to these issues, which are very difficult to distinguish visually from the real ones. this paper focuses on providing a solution to this already existing problem by implementing a QR based detection method which uses blockchain technology. the paper provides a thorough analysis of the current scenario of fake products present in the supply chain management system and proposes a novel method for robust detection. this is achieved using blockchain technology, which guarantees the traceability and identification of genuine products all the way through the supply chain. A Blockchain-based system decentralizes information, allowing multiple parties simultaneous access. Novel advantage of the proposed system is the difficulty of altering recorded data without the consensus of all concerned parties, providing a high level of security and protection against vulnerabilities. this system can be readily integrated into the supply chain to identify fake products that are often used for impersonation or fraud. © 2024 IEEE.

关键词： Blockchain

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Satellite-controlled UAV-assisted IoT Information Collection with Deep Reinforcement Learning and Device Matching 7

Satellite-controlled UAV-assisted IoT Information Collection...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Wei, Xin Zhang, Guobin Han, Zhu Dongguan University of Technology School of Computer Science and Technology Dongguan China Dongguan University of Technology School of Electrical Engineering and Intelligentization Dongguan China University of Houston Houston United States

ISBN: (纸本)9781665478571

A space-air-ground integrated network composed of satellite, unmanned aerial vehicles (UAVs) and Internet of things (IoT) devices is constructed to collect the wide-area information in this paper. the IoT devices sense the environment information, and the UAVs fly to collect the data and transmit to the satellite. In order to enhance the collected information freshness, the age of information (AoI) of the system is minimized by the UAV trajectory design with the pairing between the UAVs and IoT devices. the satellite works as the central controller to collect the minimal AoI values between each UAV and IoT device, which are obtained by the UAV training. the deep reinforcement learning is employed during the training to achieve the AoI along with the optimal destined position of the UAV. After then, the satellite builds the prefer lists of the UAVs and IoT devices based on the AoI values and finishes the matching by the Gale-Shapley algorithm. the simulation verifies the superiority of the proposed scheme over the existing approach. © 2022 IEEE.

关键词： Deep learning

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Real-Time Periocular Based Face Recognition System 7

Real-Time Periocular Based Face Recognition System

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Ahalya Rani, G. Harshitha, Anthannagari Reddy, Chada Sadwik Yogendra, Antharvedi Sailaja, Annareddy B V Raju Institute of Technology Computer Science and Engineering Telangana Narsapur502313 India

ISBN: (纸本)9798350372816

this paper presents a stable technique for extracting periocular characteristics from photographs, with an emphasis on critical regions such as eye outlines and their environs. Our technique, which employs edge detection, Gabor filters, and Local Binary Patterns (LBP), accurately captures differentiating periocular properties required for security systems. It properly deals with issues including illumination differences, occlusions, and accessories. In addition, the system has a face identification component optimized for congested situations, which can recognize numerous faces and provide a count of those spotted. Experimental evaluations validate the algorithm's efficacy, highlighting its potential for biometric authentication and monitoring. Detecting and counting faces in crowded environments provides vital information about crowd control, safety, and operational efficiency in a variety of scenarios. © 2024 IEEE.

关键词： Gabor filters

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An Analysis of E-Commerce Identification Using Sentimental Analysis: A Survey 7th

An Analysis of E-Commerce Identification Using Sentimental A...

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7th international conference on computing in engineering and technology, iccet 2022

作者： Pandiaraja, P. Aishwarya, S. Indubala, S.V. Neethiga, S. Sanjana, K. Department of Computer Science and Engineering M. Kumarasamy College of Engineering Karur639113 India

ISBN: (纸本)9789811927188

Sentiment analysis is also known as opinion mining. It is one of the critical and rapidly growing fields in Natural Language Processing. this research is intended to address the most fundamental difficulties relating to sentiment analysis. Sentiment polarity classification. A generic technique for categorizing sentiment polarity, along with detailed processes, is presented. the input data for this project is taken from major e-commerce websites like Amazon’s product ratings. Analyses on sentence-part classification and review-part categorization have shown promising results. At last, insights will be derived from preprocessed data for future execution and how much product structure and features impact execution. Created a significant impact on improving the business by producing a quality product, gadget, or accessory that customers expect and satisfying their expectations. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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