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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68437 条记录，以下是311-320 订阅

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Securing Vehicle-to-Cloud Communication: A Lightweight Approach with SCDSA 2

Securing Vehicle-to-Cloud Communication: A Lightweight Appro...

引用

2nd IEEE international conference on Measurement, Instrumentation, Control and automation, ICMICA 2023

作者： Paramathma, M Krishna Varma, N Likhitha Bhavani, D. Satya Mahatma Gandhi Institute of Technology Computer Science Engineering Hyderabad India

ISBN: (纸本)9798350355048

The Internet of Things (IoT) pertains to a network of interconnected objects and the corresponding technology that enables these objects to communicate with each other, as well as with the cloud. Vehicle-to-Cloud (V2C) is an IoT application that facilitates interaction between automobiles and the cloud. Through this connection, various data regarding the vehicle, such as its position, driving behavior, and diagnostics, can be transmitted. The V2C technology holds great potential for enhancing efficiency, convenience, and safety. However, it is imperative to ensure the authenticity of the transmitted data in order to maintain data integrity across transactions. While existing digital signature techniques address this concern, there is a need for a more lightweight approach that caters to devices with limited resources. To address this challenge, this research proposes the employment of the Shortened Complex Digital Signature Algorithm (SCDSA). By minimizing reliance on large prime numbers, SCDSA optimizes the computational burden associated with signature generation and verification. The aim of this study is to develop a secure communication system between vehicles and the cloud using SCDSA. In this scenario, information supplied from a vehicle will only be synced with the cloud provided the data is intact and uncorrupted during the transmission procedure. SCDSA might be beneficial in other IoT applications, without compromising security. © 2024 IEEE.

关键词： Authentication

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Smart Vision Bot 5th

Smart Vision Bot

引用

5th international conference on Data science, Machine Learning and Applications

作者： Nandeshwar, Vikas J. Borse, Om Buthale, Prateek Borse, Chirayu Borhade, Bharati Borse, Sayali Vishwakarma Inst Technol Dept Engn Sci & Humanities Pune 411037 Maharashtra India

ISBN: (纸本)9789819780334;9789819780310;9789819780303

Smart vision robots have become increasingly essential in various industries and applications due to their ability to perform complex visual tasks with high precision and efficiency. This project focuses on the development of an autonomous surveillance and tracking system. The system aims to utilize computer vision algorithms for object detection and tracking. It has potential applications in security, automation, and remote monitoring. The project aims to enhance safety and efficiency in various environments through autonomous surveillance capabilities.

关键词： automation Autonomous Surveillance Bot Smart Vision Real-time

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Heterogeneous Graph Neural Network Based on Hierarchical Attention Mechanism

Heterogeneous Graph Neural Network Based on Hierarchical Att...

引用

2023 IEEE international conference on Electrical, automation and computer Engineering, ICEACE 2023

作者： Zhang, Zhenghe Shandong University of Science and Technology Qingdao266000 China

ISBN: (纸本)9798350309614

Graph neural networks, as powerful tools for graph representation learning, have been widely applied in graph tasks such as node classification, link prediction, and recommendation. However, most existing graph neural network models focus on homogeneous graphs, overlooking the rich heterogeneity in real-world scenarios. With the increasing attention of researchers on heterogeneous information networks and heterogeneous graphs, designing heterogeneous graph neural network models that can effectively aggregate diverse node types and connection patterns from heterogeneous graphs, and integrate both neighbor node information and semantic information, has become a challenge. Inspired by attention mechanisms, this paper proposes the HAM-HGNN model. This model utilizes hierarchical attention aggregation, where the first layer employs self-attention aggregation to assign weights to neighbor nodes, and the second layer uses semantic-level attention to learn the importance of different meta-paths. Through hierarchical aggregation, the model generates node embeddings based on meta-paths and can be applied to heterogeneous graph data. To validate the effectiveness of this model, experiments were conducted on the real-world heterogeneous graph dataset ACM. The proposed HAM-HGNN model was compared with eight common graph neural network models. The results indicate that the HAM-HGNN model performs well in classification and clustering tasks. © 2023 IEEE.

关键词： attention Graph neural network Heterogeneous graph

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Consensus Control and Disturbance Rejection for Leader-Following Multi-Agent Systems Based on Reduced-Order Observers 13

Consensus Control and Disturbance Rejection for Leader-Follo...

引用

13th IEEE international conference on CYBER technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Pang, Guochen Xiao, Xiong Chen, Xiangyong Lu, Yang Qiu, Jianlong Liu, Yang School of Automation and Electrical Engineering Linyi University Linyi China College of Mathematics and Computer Science Zhejiang Normal University Jinhua China School of Computer Science and Engineering Linyi University Linyi China

ISBN: (纸本)9798350315196

The focus of this paper is on the issue of disturbance rejection in leader-follower multi-agent systems based on a reduced-order observer. By combining with the practical, unknown perturbations are considered to be generated by the external system by designing a reduced-order estimation observer to obtain an estimate of the disturbances in the followers. Second, a control protocol is designed for each follower based on the obtained estimates. The design method of the reduced-order observer used in this paper simplifies the state equations of the reduced-order observer by reducing the order compared to the full-order observer, which is simpler to compute and can also effectively suppress the effects of disturbances. Finally, the feasibility of this scheme is verified by numerical examples. © 2023 IEEE.

关键词： Disturbance rejection

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An Electrical Double-Layer Capacitive-Based Flexible Tactile Sensor Fabricated by Electrospinning Process 13

An Electrical Double-Layer Capacitive-Based Flexible Tactile...

引用

13th IEEE international conference on CYBER technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Liu, Wei Yuan, Huiyu Liu, Na Shanghai University Department in School of Mechatronics Engineering and Automation Shanghai China

ISBN: (纸本)9798350315196

Flexible tactile sensors have wide applications in wearable devices, electronic skins, soft robotics, human-computer interaction technology, and etc. In this paper, a flexible tactile sensor based on the theory of electrical double layer capacitance was fabricated through electrospinning process. The fabricated sensor reveals excellent permeability and sensing performance. Specifically, it demonstrates a high sensitivity of 0.54 kPa-1 and a low detection limit of 12 Pa, alongside superior mechanical stability over 5,000 recurring cycles. © 2023 IEEE.

关键词： Mechanical stability

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Anomaly Detection in the Cloud Environment with Clustering Optimization Model for Attack Detection in IDs

Anomaly Detection in the Cloud Environment with Clustering O...

引用

2023 international conference on IoT, Communication and automation technology, ICICAT 2023

作者： Jain, Ashima Tripathi, Khushboo Jatain, Aman Manju Amity University Department of Computer Science and Engineering Haryana Gurugram India Jaypee Institute of Information Technology Department of Computer Science and Engineering Noida India

ISBN: (纸本)9798350302820

In recent decades the role of the Internet in day-to-day activities are rapidly increased due to the accessibility and completion of tasks with in fraction of a second, as well as the banking and billing process proceeds online. Due to the character of openness in networks, security is the big threat to users. The intruders enter into the network in different manners to get access or change the original contents as well as block the connection, etc. The intrusion detection (IDS) process is a mandate to overcome the issues, the IDS is classified as misuse detection as well as anomaly detection. This paper constructed a framework for anomaly detection in the cloud environment. The constructed framework model uses the Rule-based Bayesian Optimization (RBBO) for the attack and malicious activities detection. The RBBO model uses the weighted rule-based approach with the estimation of mean and standard deviation in the dataset attributed to the attack and anomaly detection. Based on the generated rules the conditions are provided within the Bayesian Network for the dimensionality reduction. Through implementation of the Bayesian Network classification of attacks are performed for the KDD cup and real-time dataset. The comparative analysis expressed that the RBBO model performance is effective for the detection of anomalies and attacks in the cloud with the reduced false positive rate. © 2023 IEEE.

关键词： Bayesian networks

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Vehicular Data Retrieval System

Vehicular Data Retrieval System

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Thajudheen, Shaeif Shanmugarathinum, G. Jesudoss, Angelin Gladys Presidency University Dept. of Computer Science Bengaluru India University of Technology and Applied Sciences Dept. of Computer Science Ibri Oman

ISBN: (纸本)9798350317060

The Vehicular Data Retrieval System is comprehensive research that focuses on collecting real-time data from vehicles and transmitting it to a remote server for storage and later visualization in a web application. The system incorporates advanced technologies such as GPS (Global Positioning System) for precise location tracking and data capturing. The primary aim of this research is to create an efficient and scalable solution that enables the retrieval of essential vehicular parameters including speed, engine temperature, fuel level, and coordinates. By harnessing this data, it becomes possible to visualize and analyze vehicle performance over time, leading to valuable insights for various applications, such as fleet management, transportation optimization, and environmental monitoring. This paper presents a detailed analysis of the research's requirements, an extensive literature review, an evaluation of existing systems, and the proposed system design and implementation. Furthermore, the paper discusses testing methodologies, the achieved outcomes, and recommendations for future enhancements to further enrich the vehicular data retrieval and visualization system. © 2023 IEEE.

关键词： Nonbibliographic retrieval systems

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Play Store App Analysis & Rating Prediction Using Classical ML Models & Artificial Neural Network 7

Play Store App Analysis & Rating Prediction Using Classical ...

引用

2023 7th international conference On Computing, Communication, Control And automation, ICCUBEA 2023

作者： Moharana, Bhimasen Biswal, Bhramara Bar Dey, Snehasis Rath, Manas Kumar Banerjee, Shobhan Lovely Professional University Department of Computer Science and Engineering Punjab India College of Engineering P.G. Department of Computer Science & Applications Bhubaneswar India College of Engineering Electronics & Telecommunication Engineering Bhubaneswar India Maharaja Sriram Chandra Bhanja Deo University Department of Computer Application Baripada India Birla Institute of Technology and Science Department of Engineering Technology Pilani India

ISBN: (纸本)9798350304268

Each app available in the App Store or Play Store has various aspects linked to it such as its version, category, number of installations, genre, etc. which makes it unique, robust & popular. The reviews and ratings given by end users play an important role for both the developers and other users for the performance and survival of the app in the marketplace. Reviews are just a description for justification of the rating given by a user & the rating plays an important role in the first look. In this paper, we have used the Play Store Analysis Dataset to descriptively analyze the various attributes present in it and create models that predict the rating of an app, given its specifications. The models have been compared based on a common accuracy metric based on which their reliability can be judged and used in real-time rating predictions for a new application in the store for which a certain amount of data is available over some period. © 2023 IEEE.

关键词： Descriptive Statistics ML Classification Models Model Comparison Play Store App Analysis Rating Prediction

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Optimal Structure Exploration of Bayesian Network Based on Dealing with the Route Choice Model 6

Optimal Structure Exploration of Bayesian Network Based on D...

引用

6th international conference on computer Information science and Application technology, CISAT 2023

作者： Wang, Ziyi Zeng, Yufei Wang, Rui College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China College of Computer Science and Technology Harbin Institute of Technology Yichun China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China

ISBN: (纸本)9781510668546

Route selection in residents' travel is a key link in travel decision-making in transportation systems. In existing studies, discrete choice models are often used to describe residents' travel path choices. However， with today's highly developed big data, the traditional discrete choice model is too simple to represent residents' travel path choices, ignoring the connection between various factors. Therefore, a big data-driven approach is proposed to solve this problem in this paper. Driven by research data and with the introduction of the Bayesian network model, the paper adopts a hill-climbing search strategy to improve the search efficiency, uses a variety of scoring functions to train data, which optimizes the Bayesian network structure. The experimental results show that the model fully considers the causation between the independent variables, which is more logical and makes the construction of the resident travel route selection model more accurate and efficient. © 2023 SPIE.

关键词： Bayesian networks

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Sensor automation for Industrial Applications and Prediction of Energy Level for Home Appliances Using Machine Learning Algorithm 9

Sensor Automation for Industrial Applications and Prediction...

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9th international conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Duraisamy, Premkumar Natarajan, Yuvaraj Selvakumari Jeya, I Jasmine Niranjani, V. KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Hindusthan College of Engineering and Technology Department of Information Technology Coimbatore India Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397376

In recent years wireless sensor networks have helped with automation in many industry domains. Wireless technology cuts cable costs, deployment time and information to transfer and process from source to destination. To make good intelligent and highly automated systems, sensors are crucial. They make it possible to detect, analyze, measure, and process a variety of alterations that occur in industrial equipment's location, length, height, appearance, displacement, etc. This paper described the industrial standardization of different WSN protocols like Zig-Bee, Wireless HART, UWB, IETF 6LowPAN, ISA100, Bluetooth and Wi-Fi. The work represented a few applications of WSNs in industry and its implementation challenges like safety, security, and availability. The work collected the energy consumption data of different home appliances. We applied the LightGBM machine learning algorithm to find a better energy consumption and prediction result. © 2023 IEEE.

关键词： Energy utilization

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