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检索条件"任意字段=5th International Communication Engineering and Cloud Computing Conference, CECCC 2023"

共 1061 条记录，以下是131-140 订阅

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Homomorphic Encryption Technique in Over the Air (OTA) update in ECUs 5

Homomorphic Encryption Technique in Over the Air (OTA) updat...

引用

5th IEEE international Transportation Electrification conference, ITEC-India 2023

作者： Abichandani, Neetigya Lakshmanan, S.A. Amrita School of Engineering Department of Ece Chennai India

ISBN: (纸本)9798350337808

the paper talks about securing software in electric vehicles (EV). With the advancement in the over the air (OTA) technology, there has been increase in potential threats as well. OTA helps the OEMs to update the software in lesser cost and lesser time. However, as it is wireless communication, it is prone to security attacks. OTA consists of several steps and each step is prone to different security attack. the possible security attack area lines are pointed out and discussed in this paper and validated proposed results. the probable threats that can happen during data transfer from cloud to the vehicle main unit (VMU) and VMU to sub units such as but not limited to traction controller. this paper proposes a new type of cipher. It has several benefits that are not limited to confidentiality. Its nature allows calculations to be performed directly on translated data without the need for decryption as opposed to conventional ways. the proposed system helps in reducing the time to market further and provides extra layer of security. It helps in reducing the bigwig attacks as the data is not visible during the computing. © 2023 IEEE.

关键词： Data transfer

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Establishment and Analysis of New Topology for Power Internet of things 5

Establishment and Analysis of New Topology for Power Interne...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Xue, Honglin Ma, Junwei Zhang, Jianliang Gu, Wei Huo, Meiru Gao, Yinghao Zhong, Yan Information Communication Branch Company. Shanxi Electric Power Company Taiyuan03021 China School of Electrical and Electronic Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798350333442

With the rapid development and wide application of the power Internet of things, its security has received more and more attention. this paper mainly focuses on the topology of power Internet of things, aiming at the problems of poor invulnerability and only applicable to longitudinal data transmission of the existing overall topology of power Internet of things, considering the anti-attack and stability of the topology, based on the traditional topology of power Internet of things, a new topology is established by classifying perception devices, adding intelligent processing nodes and increasing interactive communication links. Simulation results show that the new topology has good anti-attack ability on the basis of ensuring communication efficiency. © 2023 IEEE.

关键词： Topology

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A Bagged Tree Identification Method Combining Higher Order Cumulant and Permutation Entropy for communication Modulated Signal 5

A Bagged Tree Identification Method Combining Higher Order C...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Lv, Haoran Shen, Mingfu Weng, Weijie College of Information and Communication Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of Electronic Information and Automation Civil Aviation University of China Tianjin China School of Information Science and Technology Xiamen University Tan Kah Kee College Fujian Zhangzhou China

ISBN: (纸本)9798350333442

the channel environment of wireless communication is more and more complex, and the modulation modes of communication signals become more diverse, which brings new challenges and problems to the modulation signal recognition technology. In this paper, a bagged tree recognition method combining high order cumulant and permutation entropy is proposed. It's found that compared with other recognition methods, the proposed method has some advantages in prediction speed (40000obs / sec) and accuracy (92.8%). After adding the time-domain and frequency-domain features, the recognition accuracy can be further improved, but it will increase the training time and reduce the classification speed. © 2023 IEEE.

关键词： Time domain analysis

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Exploratory and statistical data analysis of Indian economy 5

Exploratory and statistical data analysis of Indian economy

引用

5th IEEE international conference on Advances in computing, communication Control and Networking, ICAC3N 2023

作者： Singh, Bhawna Vandana Umrao, Sandhya Katiyar, Sanjay Sharma, Vanshika G.L. Bajaj Institute Of Technology And Management Department Of Cse Greater Noida India Noida Institute Of Engineering And Technology Department Of Cse Greater Noida India Greater Noida Institute Of Engineering And Technology Department Of Cse Greater Noida India

ISBN: (纸本)9798350330861

Exploratory Data Analysis provides visual exploration of data and also allows for the identification of trends and relationships between variables. the aim of this research is to study about different factors involved in the economy of India. the dataset has been collected from year 1960 to 2020 and is analyzed by looking at the factors such as GDP, import and export value of goods and services, total reserves(include gold, current US Dollar) and health status of nation's citizens. thus, it suggests that all factors are important for a stable economy and it also provides different ways to improve these factors. © 2023 IEEE.

关键词： Information analysis

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Introducing a novel dataset for product matching: A new challenge for matching systems

Introducing a novel dataset for product matching: A new chal...

引用

communication engineering and cloud computing conference (ceccc), international

作者： Tobias Rettenmeier Alexander Jesser Institute for Intelligent Cyber-Physical Systems Heilbronn University of Applied Sciences Künzelsau Germany

ISBN: (数字)9798350344752

ISBN: (纸本)9798350344769

Finding and matching the same product on different online shops is an essential task in many e-commerce applications such as market analysis. Most often, due to a lack of a global product identifier, this task is non-trivial. this paper describes a novel dataset for product matching that can be used to train and evaluate machine learning models that automate this task. Existing public datasets are either too small to be used for deep learning applications, use data with a present global identifier to artificially create a dataset or are too easy for state-of-the-art models. the novelty of the Markt-Pilot dataset is, that it is substantially larger than existing datasets for product matching while also consisting of real-world data that has been retrieved by querying the search function of online shops through web scraping. the dirtiness of the data and the amount of edge cases present a greater challenge for product matching systems.

关键词： Deep learning cloud computing Training data Data models Electronic commerce Task analysis

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Crowd Density Identification at Cross Section using machine learning and deep learning 5

Crowd Density Identification at Cross Section using machine ...

引用

5th IEEE international conference on Advances in computing, communication Control and Networking, ICAC3N 2023

作者： Dubey, Hemant Singh, Manvendra Raj, Ritesh Nath, Rajiv Kumar Galgotias College Of Engineering And Technology Department Of Computer Science And Engineering Greater Noida India

ISBN: (纸本)9798350330861

the estimation of crowd density at cross sections is a significant problem in the crowd analysis. In this study, we provide a novel technique for determining crowd density using Multi-column Convolutional Neural Networks (M-CNN). the proposed approach uses the M-CNN architecture to predict crowd densities at cross sections and learn hierarchical features from input photographs. Moreover, for this analysis ShanghaiTech dataset is utilized as (80-20)% training and testing datasets. the robustness of the M-CNN model is evaluated on the basis of normal error, Mean average error (MAE), Mean squared error (MSE), and growth truth. the findings demonstrate that the proposed model is highly accurate, and performs well after a few initial iterations. Furthermore, it can be incorporated in public places for crowd estimation and recognition. © 2023 IEEE.

关键词： Mean square error

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A Review on Emotion Detection of Contextual Text 5

A Review on Emotion Detection of Contextual Text

引用

5th IEEE international conference on Advances in computing, communication Control and Networking, ICAC3N 2023

作者： Kumar, Akhilesh Bhartee, Ajeet Kumar Gupta, Hrithik Singh, Puneet Kumar Galgotias College Of Engineering And Technology Department Of Computer Science And Engineering Gautam Buddha Nagar India

ISBN: (纸本)9798350330861

In recent years, emotion detection in text has become increasingly popular due to its potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, and more. Access to vast amounts of textual data, especially unique and self-printing texts, has also played a special role in attracting attention to the field. this article reviews the research that has been done to identify emotional or sentimental expressions in text, and many techniques, methods, and models have been developed to identify sentiment in text. there is a great improvement in the design and architecture of models in past decade. this article covers current developments in emotion identification in texts and offers useful insights for academics and practitioners working in this field. © 2023 IEEE.

关键词： Human computer interaction

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How to Recommend the Best Representation Model for Problem-Solving 5

How to Recommend the Best Representation Model for Problem-S...

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5th IEEE international conference on Advances in computing, communication Control and Networking, ICAC3N 2023

作者： Nakka, Arjun Karthikeya Reddy, A. Brahmananda Akhil, Karnam Lekkala, Jatin Chubb Hyderabad India Vnr Vignana Jyothi Institute Of Engineering & Technology Department Of Cse Hyderabad India

ISBN: (纸本)9798350330861

Knowledge is a representation of truth and facts, enabling the integration of new experiences and information through language comprehension. It is represented using Adaptive Control of thought (ACTR) and the connectionist model. Knowledge organization is a semantic network with labeled relations to conceptual nodes. An Ontology-based framework is built for the Language and Organization of Knowledge in the human brain. this project aims to conduct surveys for graduation levels and analyze factors affecting knowledge skills in problem-solving. A semantic web approach for the Connectivism model is created, and Semantic Web Rule Language (SWRL) is applied to generate inference rules. Knowledge is retrieved using SPARQL, forming an intelligent system based on the inference engine. © 2023 IEEE.

关键词： Adaptive control systems

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A Comprehensive Analysis of Music Genre Classification with Audio Spectrograms using Deep Learning Techniques 5

A Comprehensive Analysis of Music Genre Classification with ...

引用

5th IEEE international conference on Advances in computing, communication Control and Networking, ICAC3N 2023

作者： Abbas, Mohammad Kazim Gupta, Kunal Mudassir, Mohammad Jain, Rishabh Galgotias College Of Engineering And Technology Dept. Of Computer Science And Engineering Greater Noida India Kiet Group Of Institutions Dept. Of Computer Science Delhi-NCR Ghaziabad India

ISBN: (纸本)9798350330861

this review paper investigates the application of audio spectrograms for categorization of musical genres. the use of feature extraction technique in convolutional neural networks (CNNs) for music genre analysis is highlighted in the discussion of these techniques. the relationship between audio spectrograms and musical subgenres is also observed in this paper, as well as how well audio segmentation methods perform in terms of increasing classification precision. the findings of recent research employing various approaches like CNN, PRCNN, LSTM, SVM, etc are used to conduct a comparative analysis of their effectiveness, highlighting the strengths and weaknesses of each approach. the use of spectrogram for feature extraction and multi-layer CNN proved to be ideal for future researches. © 2023 IEEE.

关键词： Feature extraction

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Image Classification Of Material Using CNN 5

Image Classification Of Material Using CNN

引用

5th IEEE international conference on Advances in computing, communication Control and Networking, ICAC3N 2023

作者： Mathur, Mayank Kumar, Divyanshu Narwaria, Mamta Saif, Md Computer Science And Engineering Galgotias College Of Engineering And Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350330861

the classification and detection of a variety of materials that appear to be common in our environment have been the focus of computer vision systems in recent years, which has posed a significant sensory challenge. Application of material categorization is crucial for autonomous visual surveillance systems. Material classification is the process of categorizing a piece of content using its attributes into predetermined and semantically relevant categories. In this study, a brand-new model for material detection and classification is put forth, employing Convolutional Neural Networks (CNN) to categorize the discovered materials based on their attributes. Deep Neural Networks can process enormous amounts of data in higher dimensions with billions of parameters, just like the human brain. the simulation results show that the suggested classifier model generates more accurate feature extraction and classification outcomes using CNN. © 2023 IEEE.

关键词： Image classification

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