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Vehicle-to-Cloud System New Architecture based on Adaptive AUTOSAR, VSS, and VISS 5

Vehicle-to-Cloud System New Architecture based on Adaptive A...

引用

5th international conference on Computer and Applications, ICCA 2023

作者： Helmy, Mona Mohsen, Amr Siemens EDA Cairo Egypt Ain Shams University Computer and Systems Engineering Cairo Egypt

ISBN: (纸本)9798350303254

In times the automotive industry has undergone a significant transformation due to technological advancements such as the 5G technology. Cloud computing has emerged as a facilitator and the rapid growth of internet-of-things (IoT) devices has showcased the potential synergy between different devices and cloud technology in improving our daily lives. Furthermore, vehicles themselves can also become a part of the IoT infrastructure. This paper explores the importance of integrating cloud solutions into vehicles as well as one possible implementation for a cloud solution based on adaptive Automotive Open System Architecture (AUTOSAR), Vehicle signal Specification (VSS), and The Vehicle Information Service Specification (VISS) standards. © 2023 IEEE.

关键词： Vehicles

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Degraded Data Enhancement based on Regional Similarity Fusion 6

Degraded Data Enhancement Based on Regional Similarity Fusio...

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6th international conference on Information Communication and signal Processing, ICICSP 2023

作者： Ding, Bosheng Zhang, Ruiheng Xu, Lixin Wang, Haichao Liu, Yumeng Zhao, Yijing Su, Yi School of Mechatronical Engineering Beijing Institute of Technology Beijing China Anhui Dongfeng Electromechanical Technology Co. Ltd Research and Development Department Heifei China Institute of Software Chinese Academy of Sciences Beijing China Institute of Software University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350339994

The scattering and absorption effect of dust particles on light leads to low contrast and serious color offset of visible light images obtained in sand-dust weather, which affects the reliability of outdoor visual applications such as traffic safety and monitoring systems. Due to complex scene structure and difficult parameter estimation, the existing sand-dust image enhancement methods can not effectively extract the semantic components of the image, resulting in unreal colors and blurred details of the enhanced image. Therefore, we propose a two-stage sand image enhancement method based on regional similarity fusion. Firstly, the gray distribution of the input dust image is compensated to recover the potential information in the scene, and two sub-images with color balance and high contrast are derived. Then, regional similarity calculation, weight allocation, and image fusion are carried out to generate the final clear image based on the regional similarity fusion strategy. The experimental results show that the proposed method can effectively restore the potential features in the dust scene, and the visible edge number ratio (e-score) and edge gradient ratio (r-score) have increased by 0.24 and 0.47 respectively. © 2023 IEEE.

关键词： degraded data image enhancement regional similarity fusion

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A Physiological signal Emotion Recognition Method based on Domain Adaptation and Incremental Learning 1

A Physiological Signal Emotion Recognition Method Based on D...

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1st international conference on Cyber-Energy systems and Intelligent Energy, ICCSIE 2022

作者： Li, Junnan Wang, Xiaoping Huazhong University of Science and Technology The School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9781665452151

Temporal concept shift (TCS) is an unavoidable problem in physiological signal-based emotion recognition tasks, i.e., the data distribution of physiological signals is constantly changing over time, which gradually degrades the model accuracy. To this end, we propose a method based on a combination of domain adaptation and incremental learning to reduce the impact of temporal concept drift. In this paper, domain adaptation is used to reduce the distribution differences and incremental learning is used to prevent the learned knowledge from being forgotten. Finally, we validate the effectiveness of our approach on two real datasets. © 2023 IEEE.

关键词： Emotion Recognition

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Crack Orientation Recognition Method based on Prototype Learning

Crack Orientation Recognition Method Based on Prototype Lear...

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2023 international conference on image, signal Processing, and Pattern Recognition, ISPP 2023

作者： Liu, Ankang Cheng, Lan Lv, Yingchun Chen, Yan Shi, Weiyan College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan030024 China

ISBN: (纸本)9781510666351

To address the problem that the direction of pipe cracks is difficult to detect, a crack direction recognition method based on prototype learning is proposed with a prototype network as a framework. First, through the convolutional layer of the prototype network, shallow features of crack directions are extracted to improve the generalization ability of the model on the data set of this paper. then, by improving the High-Resolution Network and introducing a location self-attention mechanism, and combined with a migration training method for the data set of this paper, a category that can accurately reflect the crack directions is constructed prototype learning mechanism. Finally, pattern recognition is performed by the metric classification methods, the effective classification of crack direction under small sample condition is achieved. The experimental results show that the recognition accuracy of the crack direction recognition method based on prototype learning can reach 99.2% with the sample parameters unchanged. © 2023 SPIE.

关键词： Learning systems

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4th international conference on Advances in Information Communication technology and Computing, AICTC 2022

4th International Conference on Advances in Information Comm...

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4th international conference on Advances in Information Communication technology and Computing, AICTC 2022

ISBN: (纸本)9789811998874

The proceedings contain 51 papers. The special focus in this conference is on Advances in Information Communication technology and Computing. The topics include: internet of Things and Retail Performance in an Emerging Market: A Qualitative Analysis;the Impact of Social Media on Consumer Purchase Behaviour;the Contribution of the internet of Things to Enhance the Brands of Small and Medium-Sized Enterprises in Iraq;trust Chain for Managing Trust in Blockchain-Associated IoT-Enabled Supply-Chains;supply Chain Management Using Blockchain Security Enhancement;a Novel image Encryption Algorithm Using Logistic and Henon Map;an Analysis of Data Sparsity Resolution Algorithms Used in Recommender systems;recent Trends for Practicing Machine Learning in Brain Tumors: A Survey;voice-based Intelligent Virtual Assistant;The Impact of IT Capabilities on Competitive Advantage;Identification of Autism Spectrum Disorder from Functional MRI Using Deep Learning;conversion of Sign Language to Text and Audio Using Deep Learning Techniques;security Attacks and Key Challenges in Blockchain technology: A Survey;advancing from Manual to Automatic Telecast of News for Deaf;study of Nutrition-based Recommender System for Diabetes and Cardiovascular Patients based on Various Machine Learning Techniques: A Systematic Review;comparing Fish Finding Techniques using Satellite and Indigenous Data based on Different Machine Learning Algorithms;implementation of E-Governance Framework for Rural Areas of India;opinion Summarization from Online Mobile Phone Reviews Using Feature based Association Rule Mining;unconventional to Automated Attendance Marking Using image Processing;synthetic Animations based Dictionary for Indian Sign Language;start of Telemedicine in Uzbekistan. Technological Availability;review of Feature Extraction Techniques for Fake News Detection.

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One-to-many image Super Resolution Algorithm based on Generative Adversarial Networks 2

One-to-many Image Super Resolution Algorithm Based on Genera...

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2nd international conference on Digital Society and Intelligent systems, DSInS 2022

作者： Lin, Liu Yu, Jiang College of Software Engineering Chengdu University of Information Technology Sichuan Chengdu610225 China

ISBN: (纸本)9781510663244

Aiming at the issues that the current Generative Adversarial Network (GAN) used for image super-resolution reconstruction is easy to produce false details and the mapping dependence is not flexible enough, a One-to-many Generative Adversarial Network (OTMGAN) based on Enhanced Super Resolution Generative Adversarial Network (ESRGAN) was proposed. First, the model uses one-to-many constraints to allow the estimated patches to dynamically seek the best supervision during training, instead of the one-to-one constraint from low-resolution (LR) images to high-resolution (HR) images, thus improving the loss function of the model. Then, a new region-aware adversarial learning strategy is used to distinguish between flat regions and textured regions, so that the model can adaptively generate more realistic details for textured regions during training. Finally, the experimental consequences of image super resolution reestablishment on the public datasets BSDS100, Set5, Set14 and DIV2K show that the new model is significantly superior to the classical models such as ESRGAN in terms of Peak signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and Learning Perception image Patch Similarity (LPIPS). © 2023 SPIE.

关键词： Generative adversarial networks

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IoT-based Agriculture Farm Monitoring System and Development of Plant Leaf Disease Detection Using Deep Neural Network

IoT-Based Agriculture Farm Monitoring System and Development...

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2024 international conference on signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Mim, Tanvir Islam Fahim, Ivtiaz Ahkam Islam, Nymul Rahman, Mizanur Rahman, Yasin Rouf, Nirjhor Anowar, Tanbir Ibne Mondal, Shuvra Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798331540685

Throughout history, agriculture or farming has played a vital role in human civilization by providing people's fundamental necessities and significant contributions to a country's economy. Although small-scale smart farming has started in a few nations, it has yet to be adopted scientifically globally. The rapid growth of the world population along with urbanization has rendered modern agriculture increasingly essential day by day. Towards multi-domain modernization, the internet of Things (IoT) technology is a developing paradigm that aims to link many smart physical parameters in smart agriculture. In this paper, an IoT-based smart agricultural farm monitoring system prototype has been proposed which has been designed considering different environmental parameters. Additionally, image processing-based plant disease detection model has been developed in two different methods. The system incorporates various sensors, actuators, and a microcontroller to monitor and control temperature, humidity, soil moisture, and rainfall. It also includes a water pump motor for automated irrigation where a Wi-Fi module allows remote monitoring and controlled by a developed smartphone app. To validate, the proposed hardware model was simulated using Electronic Design Automation (EDA) tools. There have been notable outcomes observed on temperature, humidity, soil moisture, and other monitoring parameters data reading from LCD. Also, deep learning-based image processing algorithm has been proposed using Feature extraction and Convolutional Neural Network (CNN) methods and achieved a high accuracy of about 96%-98% in plant disease detection. The overall proposed system offers improved resource utilization and smart agricultural practices for expanded functionalities and long-term sustainability to ensure food security for the growing population. © 2024 IEEE.

关键词： Soil moisture

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Adaptive blockage detection and prevention for radar chip-based autonomous driving systems 3

Adaptive blockage detection and prevention for radar chip-ba...

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3rd international conference on Advanced Algorithms and signal image Processing, AASIP 2023

作者： Chen, Chao Dai, Mian Liu, Yuying Du, Juan Zhao, Shuai Huacheng Certificate CATARC Dongli Tianjin300399 China CICT CATARC Tianjin Xiqing300393 China ATIRI CATARC Tianjin Dongli300300 China

ISBN: (纸本)9781510668522

This paper presents an radar blockage recognition approach along with blindness prevention measures utilizing intelligent computing methods to address the challenges in radar chip-based autonomous driving systems. A process and algorithm are initially created for detection, enabling real-Time and precise identification. The adaptive blockage performance controller and the automatic diagnosis and recovery strategy are then proposed as part of the adaptive blockage prevention strategy, which enables the system to quickly return to its normal operating state by intelligently adjusting parameters when the sensor blockage occurs. The conventional linear threshold methods are replaced with nonlinear machine learning to deal with complex performance variations, with the aim of lowering false positives and negatives through real-Time optimization. A comparative experiment is conducted to show the effectiveness. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Autonomous vehicles

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3rd international conference on Advanced Computing and Applications, ICACA 2024

3rd International Conference on Advanced Computing and Appli...

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3rd international conference on Advanced Computing and Applications, ICACA 2024

ISBN: (纸本)9789819747986

The proceedings contain 47 papers. The special focus in this conference is on Advanced Computing and Applications. The topics include: Optimizing Task Offloading in internet of Medical Things systems: A Hybrid Fog-Cloud Approach with Actor-Critic Decision Making;solving Delivery Allocation for Logistic Network Using Quantum Annealing;The Combined ECC Scheme with Outer 3-Bit BEC and Inner SEC-DAEC Codes for FSO Communication System;analyzing Multisignature Scheme of Bitcoin based on Threshold Cryptography Guidelines;a Public Key Exchange Protocol Using Tropical Determinant for IoT Environment;Certificateless Verifiable Data Integrity Checking Scheme in Fog-CPSs Architecture;noPass—A Novel Passwordless Multi-authentication-based Approach for Secure Login;an Overview of the Discrete Logarithm Problem in Cryptography;QoS-Aware Decentralized Trustworthy Forensic Evidence Management Framework Using the internet of Vehicle Things (IoVT);implementation of Ethical Hacking—The Importance of Protecting User and System Data;Cryptanalysis of Two Correlation-based Digital Watermarking Schemes in DCT Domain;cryptanalysis of a Histogram-based Watermarking Framework;a Hybrid Deep Learning Framework for Text-Independent Automatic Speaker Recognition System;AMBTC-based High Capacity Data Hiding Scheme Exploiting PVD and BRP;The Impact of UX/UI Usability Constructs on Purchase Decisions for Mobile Food Ordering Applications in India;Breast Cancer Detection and Classification Using MF-FRFCM Segmentation and IGOA-ELM Model;audio Encryption Scheme Applying a 2D Cosine Sine Logistic Map;noisy Electronic Tongue signal Prediction for Tea Quality Estimation Using Autoencoder;a Chain Code-based Methodology for Loop Closure Detection in Digital images;A Hybrid Watermarking Scheme Using DWT and Haar Transform for image Authentication;leveraging Transfer Learning for Screening of Geriatric Depression;emotion-based Song Categorization with Support Vector Machines;filtering-based Movie Recommendati

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An image Scrambling Encryption Algorithm based on Combinatorial Chaos Mapping

An Image Scrambling Encryption Algorithm Based on Combinator...

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2023 international conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Luo, Yuan Zhou, Ying Hou, Yongxu Ye, Jun School of Cyberspace Security Hainan University Key Laboratory of Internet Information Retrieval of Hainan Province Haikou China

ISBN: (纸本)9798350313413

With the development and application of network technology, digital images, as a form of information transmission, are at high risk of being stolen or decrypted. Our scheme utilizes the nature of low dimensional chaos to generate a high dimensional chaotic system with more variables and higher complexity by mixing two different low dimensional chaotic systems to protect digital images and confirms that it outperforms the original system through simulation experiments. In this paper, a new image scrambling encryption algorithm for multi chaotic system is designed by combining improved tent mapping and high-dimensional chaotic system, and compared with the existing encryption scheme in terms of simulation experiments and security performance parameters, which proves that the scheme has better comprehensive ability. © 2023 IEEE.

关键词： Chaotic systems digital images DNA coding encryption algorithms scrambling and diffusion

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