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ReChain-A Blockchain Network for Review and Rating System 3

ReChain-A Blockchain Network for Review and Rating System

引用

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

作者： Ahmed, Rayhan Islam, Md. Sajedul Osmani, Sabbir Shakil, Md. Ahanab Mazid-Ul-Haque, Md. Al-Amin, Md. American International University-Bangladesh Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798350346435

Review and rating is a very important movement for online purchases and also it's an overview of a company's service. The most popular online platform provides a section called reviews and ratings. In this research, a blockchain based technology has been proposed that is fully decentralized but can be implemented inside a centralized system. It has been noticed for a long time that because of the company's image, some people are using it negatively, and fake or paid reviews are very common among them. There are many flaws in conventional systems for review and rating. After finding the flaws, a totally new blockchain network is designed to overcome them. This is a consortium blockchain network that contains hybrid blockchain features. In this proposed model, complexity has been reduced, and it is going to be cost-efficient as well because this decentralized system can be used in any centralized system. © 2023 IEEE.

关键词： Blockchain

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Design of Autonomous Obstacle Avoidance System for Automobiles based on Machine Learning in the Context of Intelligent Transportation 1

Design of Autonomous Obstacle Avoidance System for Automobil...

引用

1st IEEE international conference on Automation, Computing and Renewable systems, ICACRS 2022

作者： Wu, Yangming Nanjing Vocational Institute of Transport Technology jiangsu Nanjing211188 China

ISBN: (纸本)9781665460842

Design of autonomous obstacle avoidance system based on machine learning in the context of intelligent transportation Aiming at the more and more serious traffic congestion and frequent traffic accidents caused by automobiles, an intelligent obstacle avoidance car system is designed. The system takes STC89C52RC as the core controller, combined with the ultrasonic module and LCD1602 display module, for the car obstacles in the image, the color histogram feature and the gradient histogram feature (HOG) of the image are combined in series, and the support vector is used. The high-frequency and low-frequency energy components are separated from their amplitude-frequency characteristics, and the high-frequency and low-frequency energy components are used as signal features to analyze the signal using the Linear SVM algorithm of machine learning. © 2022 IEEE

关键词： Support vector machines

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A Novel Vision Transformer Approach for Driver Fatigue Detection from EEG signal with Correlation-based Channel Selection

A Novel Vision Transformer Approach for Driver Fatigue Detec...

引用

2024 IEEE international conference on Computing, Applications and systems, COMPAS 2024

作者： Khan, Robiul Roy, Dipon Ali, Md. Wajed Refat, Kawsar Ahmed Naziullah, Shekh Pabna University of Science and Technology Department of Electrical and Electronic Engineering Pabna Bangladesh Daffodil International University Department of Computer Science Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Driver fatigue poses a critical threat to road safety, necessitating the development of robust detection methods to minimize traffic accidents and societal burdens. Deep neural networks have recently been effectively applied to Electroencephalography (EEG)-based driving fatigue detection. Nevertheless, most of the existing models, particularly those relying on extensive pooling, often struggle to capture long-range dependencies within images. To address this issue, we propose a Correlation-based Channel Selection (CCS) with a Vision Transformer (ViT) approach for driver fatigue detection using an EEG. Our methodology integrates a pioneering Channel Selection (CS) block to extract discriminative channels via CCS. This mechanism systematically identifies the most informative EEG channels crucial for fatigue detection. Subsequently, we leverage Continuous Wavelet Transform (CWT) to convert the selected EEG channels into a time-frequency spectral image. Finally, the resulting time-frequency spectral images, encompassing both temporal and spectral information, are concatenated and fed into the Vision Transformer (ViT) model to classify them as either normal or fatigued. The proposed model is evaluated on a publicly available EEG dataset containing recordings from twelve subjects. The model achieved superior accuracy: 95.83% for the effective selected combined subject and 99.925% for the average accuracy of each subject, demonstrating its potential for robust driver fatigue detection. © 2024 IEEE.

关键词： Deep neural networks

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Carrier Synchronization Simulation Design based on MATLAB/Simulink 1

引用

2nd international conference on internet of Things, Communication and Intelligent technology, IoTCIT 2023

作者： Ma, Xiaoqing Xi’an Eurasia University Shaanxi Xi’an710000 China

ISBN: (数字)9789819727575

ISBN: (纸本)9789819727568

Carrier synchronization is an important link in wireless communication systems. It ensures frequency and phase synchronization between the receiving end and the transmitting end, thereby achieving reliable data transmission. The accuracy of carrier synchronization is crucial to ensure the performance of communication systems, especially in the case of high-speed data transmission and multi-user access. This article first investigates the current mainstream carrier synchronization algorithm, analyzes its working principle, and analyzes the characteristics of its mathematical model. By comparing the mainstream synchronous carrier implementation methods, two of them were selected, and the simulation models of square ring and COSTAS ring carrier synchronization were built using MATLAB/Simulink simulation software and its code program. Simulink simulation showed that it can be well realized. Simulation design of square ring and COSTAS ring carrier synchronization, and analyzed and compared the impact of square ring and Costas ring carrier synchronization methods on the coherent demodulation effect. The feasibility of the two carrier synchronization technologies has been verified through simulation, and both can better coherently demodulate the signal and have a high degree of signal restoration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： MATLAB

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Method of fruits and vegetables storage shelf life prediction based on multi-source information fusion 2

Method of fruits and vegetables storage shelf life predictio...

引用

2nd international conference on signal image Processing and Communication, ICSIPC 2022

作者： Guo, Meicen Qiao, Jiping Wu, Qiuyuan College of Electrical & Power Engineering Taiyuan University of Technology Taiyuan030024 China

ISBN: (纸本)9781510657694

In the post-harvest supply chain of fruits and vegetables, the spoilage rate during storage is as high as 10% due to improper management measures, which has seriously restricted the development of related industries. In response to this problem, this paper proposes a method for predicting the storage shelf life of fruits and vegetables. In this paper, we develops a micro-environment monitoring system based on the internet of Things (LOT) technology, integrating the sensors of temperature and humidity, oxygen and carbon dioxide, using the LoRa wireless communication module to realize real-time data transmission;With the help of MATLAB platform, we build a multi-sensor data fusion model based on artificial neural network (ANN), and we convert the environmental parameters with multi-source coupling relationship into shelf life by this model. The results show that the model has good prediction performance and meets the requirements of shelf life prediction. The method can effectively reduce the economic losses caused by fruits and vegetables spoilage，when being applied to the post-harvest supply chain management of fruits and vegetables. © 2022 SPIE.

关键词： Digital storage

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Identification Method of Channel Model based on CNN considering AWGN 13

Identification Method of Channel Model based on CNN consider...

引用

13th IEEE Global conference on Consumer Electronic, GCCE 2024

作者： Hirabe, Toshiki Ida, Yuta Ohira, Yasuaki Kuroda, Sho Matsumoto, Takahiro Yamaguchi University Graduate School of Sciences and Tech. for Innovation Ube Japan Kagoshima University Graduate School of Science and Engineering Kagoshima Japan Fx Systems Corporation Osaka Japan

ISBN: (纸本)9798350355079

In wireless communications, the signal is transmitted from the transmitter to the receiver via the channel. In international Telecommunication Union (ITU), the wireless channel model is standardized by the channel profile. However, since multipath environments consist of several waves, channel state information (CSI) is fluctuated at the frequency domain. To estimate the channel model from the CSI, we have proposed the identification method by the convolutional neural networks (CNN). However, it is not evaluated for the imperfect channel with additive White Gaussian noise (AWGN). Therefore, in this paper, we propose the identification method of the channel model based on the CNN considering AWGN. © 2024 IEEE.

关键词： White noise

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Design and Implementation of image Copyright Protection System based on Chinese Cryptographic Algorithms 7

Design and Implementation of Image Copyright Protection Syst...

引用

7th international conference on signal and image Processing, ICSIP 2022

作者： Cai, Zengyu Si, Yajie Zhang, Jianwei Wang, Jingchao Zhengzhou University of Light Industry School of Computer and Communication Engineering Zhengzhou China Zhengzhou University of Light Industry School of Software Engineering Zhengzhou China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

With the sharp increase in the number of netizens, people's online life is becoming richer and richer, the behavior of stealing pictures on the internet is more rampant, and online image infringements continue to occur, so the protection of image copyright is particularly important. This paper first introduces the relevant background knowledge of Chinese cryptographic algorithms, image copyright protection and image steganography technology;secondly, the overall design scheme of the system is proposed, including functional design, hierarchical pattern design and system flow design;then, the key technologies of the system implementation are introduced;finally, test and analyze the system. The test results show that the system can secretly write the image copyright information encrypted by the SM2 algorithm into the image through the LSB algorithm, so as to achieve the purpose of image copyright protection without affecting the beauty of the image. © 2022 IEEE.

关键词： Copyrights

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Transformer-based Chest X-ray Report Generation Model 1

引用

6th international conference on Soft Computing and signal Processing, ICSCSP 2023

作者： Shaikh, Zeeshan Bharti, Jyoti Department of Computer Science and Engineering Maulana Azad National Institute of Technology Bhopal Bhopal India

ISBN: (数字)9789819986286

ISBN: (纸本)9789819986279

In radiological testing for treatment and diagnosis, chest X-rays and medical radiographs are most frequently utilized in clinical practice. A skilled radiologists may require some patience to read and interpret a chest X-ray;less experienced radiologist may find it more challenging;and the common person might find it incredibly difficult. A deep learning-based X-ray report generating system can help doctors with reporting tasks and give radiologists judgment support. In order to generate chest X-ray reports, this paper proposes a deep learning-oriented model that makes use of a transformer method and transfer learning technique. We use a chexnet model that has already been pre-trained and will eventually be trained on X-ray images for visual extraction. Then, an encoder-decoder for a modified transformer is used. We train and evaluate our network using the IU X-ray dataset, one of the most extensive publicly available datasets currently utilized for chest X-ray image captioning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

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Sim-to-Real image Transfer for RL-based Bin Picking 15

Sim-to-Real Image Transfer for RL-Based Bin Picking

引用

15th international conference on Information and Communication technology Convergence, ICTC 2024

作者： Park, In Jun Han, Hyonyoung Digital Convergence Research Laboratory Electornics and Telecommunications Research Institute Daejeon Korea Republic of

ISBN: (纸本)9798350364637

Robotic bin picking has become increasingly important in the field of automated manufacturing and logistics, where precise handling of objects in complex settings is essential. Reinforcement learning (RL) has emerged as a powerful tool for developing policies to manage such tasks. However, a significant challenge persists in transferring these policies from simulation to real-world environments due to visual discrepancies, often resulting in reduced performance when applied to actual robotic systems. To overcome this issue, we introduce an innovative approach that incorporates spatial transformer networks (STN) into the RL framework. This technique specifically addresses the scale variations between simulated and real-world images, enabling the policy to adapt more effectively and enhancing both the robustness and generalizability of the learned behaviors. Our approach has shown a marked improvement in real-world bin picking tasks, with the integration of STN leading to an 11.5% boost in grasping accuracy, achieving a high overall success rate of 95.5%. By effectively narrowing the visual domain gap, our method reduces the reliance on extensive real-world data collection and training, facilitating quicker and more efficient deployment of robotic bin picking solutions in a variety of industrial contexts. © 2024 IEEE.

关键词： Reinforcement learning

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FPGA Interfaced ECG signal Processing based on Machine Learning Classifier

FPGA Interfaced ECG Signal Processing Based on Machine Learn...

引用

2023 international conference on Energy, Materials and Communication Engineering, ICEMCE 2023

作者： Jeya Malar, R. Mary Mettilda, J. Mageshbabu, M. Siva Nagini, R. Grace, Lily Saron Gireesha, B. Kings Engineering College Department of Information Technology Chennai India Ppg Institute of Technology Department of Electronics and Communication Engineering Coimbatore India SIMATS Saveetha School of Engineering Department of Electronics and Communication Engineering Thandalam Chennai India Universal College of Engineering and Technology Department of Electrical and Electronics Engineering Tamilnadu Vallioor India Kings Engineering College Department of Electronics and Communication Engineering Chennai India University College of Science Tumkur University Department of Electronics Karnataka572103 India

ISBN: (纸本)9798350393378

This study aims to propose an FPGA-oriented ECG signal processing system architecture. The method identifies FPGA complexes and classifies beats as either preterm or typical contractions of the ventricular wall. For pulse classification, an element of the Open Source ECG Analysis Software is used, and for FPGA complexity verification, a method based on a phase-space image of an ECG signal is used. Artificial intelligence (AI) is increasingly serving as the basis for autonomous and independent systems. One of the most popular machine learning techniques among many categorization strategies is the Support Vector Machine (SVM) classification. We may further improve the SVM classifier's accuracy and classification process by using convex optimization techniques to identify the best solution. Numerous machine learning techniques, such as SVM classification, need a lot of processing power since they are compute-and data-intensive. Additionally, a number of machine learning algorithms have made it into incorporated and handheld gadgets, which have very particular demands. © 2023 IEEE.

关键词： Electrocardiograms

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