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检索条件"任意字段=2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023"

共 3023 条记录，以下是491-500 订阅

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Speech Emotion Recognition from Audio Files Using Feedforward Neural Network 3

Speech Emotion Recognition from Audio Files Using Feedforwar...

引用

3rd international conference on Electrical, computer and Communication Engineering, ECCE 2023

作者： Alam, Khorshed Nigar, Nishargo Erler, Heidy Banerjee, Anonnya United International University Computer Science & Engineering Dhaka Bangladesh Co-Founder Bolo Hamburg Germany Hamburg University of Technology Information & Communication Systems Hamburg Germany

ISBN: (纸本)9798350345360

Speech Emotion Recognition (SER) is an act of recognizing human emotion and affective states from speech. This is because voice often reflects underlying emotion through tone and pitch. Emotion recognition is a component of speech recognition which is gaining more popularity and need for it is increasing exceptionally. Our paper aims to use the Feedforward Neural Network to recognize emotions from unseen data (i.e., audio files) and label them according to the range of different emotions using appropriate variables (such as modality, emotion, intensity, repetition etc.) found in the data. This approach can be particularly useful in the case of identifying the inherent emotion behind human voice. © 2023 ieee.

关键词： Emotion Recognition

来源：评论

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A Cloud Computing Model for Libyan Higher Education Institutions 3

A Cloud Computing Model for Libyan Higher Education Institut...

引用

3rd ieee international Maghreb Meeting of the conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2023

作者： Imragaa, Najwa A. Alfsai, Entesar H. Gargoum, Bothaina F. Maatuk, Abdelsalam M. University of Benghazi Department of Computer Science Benghazi Libya University of Benghazi Department of Software Engineering Benghazi Libya

ISBN: (纸本)9798350319897

Cloud computing is now changing the IT landscape and playing a significant economic role for companies that develop software. Users of educational resources now have more flexibility and access because of cloud computing. Students, faculty members, and support staff all use cloud computing in academic institutions. Internet-based computing, known as "Cloud Computing,"allows users to share IT resources securely and efficiently. The use of cloud computing in universities has many benefits, such as access to files, e-mail, databases, educational resources, and search applications as requested by faculty, administrators, staff, and students at a university alike. Moreover, cloud computing significantly reduces the complexity and cost of IT in universities. This paper discusses cloud computing, its structures, types, and services it provides, and then examines the possibility of implementing cloud services in universities and discovers the various opportunities and benefits of cloud services. The paper presents a proposed model for cloud computing for Libyan universities, which was applied to the University of Benghazi and produced satisfactory results and facilitated a lot of university work. Through the application of the proposed model, effective management of the technological needs of the Libyan university has been achieved, such as connecting programs and providing a platform for development, data storage and computing. © 2023 ieee.

关键词： application programs

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A Boiler Heating Surface Overtemperature Warning Method Based on Multi source data Fusion and Neural Network Model 3

A Boiler Heating Surface Overtemperature Warning Method Base...

引用

3rd international conference on Electronic Information Engineering and computer, EIECT 2023

作者： Gao, Liping Lin, Zhouyong Lian, Dade Li, Yilong Yang, Kaixuan THERMAL POWER CO. LTD. Fujian Quanzhou362804 China Shanghai Power Equipment Research Institute CO. LTD Minhang Shanghai200240 China

ISBN: (纸本)9798350357707

In order to accurately monitor the overheating of boiler heating surfaces and ensure the safety of boiler use, this paper proposes a boiler heating surface overheating warning method based on multi-source data fusion and neural network model. By integrating data from multiple sources such as temperature sensors and pressure sensors, real-time monitoring of the temperature status of the boiler heating surface is achieved. At the same time, a neural network model is used to learn the warning threshold, thereby achieving accurate warning of overheating of the boiler heating surface. The experimental results show that this method can effectively improve the accuracy and timeliness of boiler heating surface overtemperature warning. © 2023 ieee.

关键词： Neural network models

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Research and Implementation of DM1 Based on the J1939 3

Research and Implementation of DM1 Based on the J1939

引用

3rd ieee international conference on computer Systems, ICCS 2023

作者： Wang, Ying Guo, LiWei Tang, Tian Xi'an Aeronautics Computing Technique Research Institute Avic Laboratory of Computer Application Engineering Xi'an China

ISBN: (纸本)9798350313666

The J1939 protocol is a communication protocol widely used in automotive electronic network. It supports real-time closed-loop control and communication among electronic control systems which are distributed in the whole vehicle. This paper focuses on the overall structural characteristics of the J1939 protocol and DM1(the Active Diagnostic Trouble Codes), deeply studies and analyzes the storage mode of the DM1 and the packet transmission, it designs and implements it function, improves the storage structural characteristics and filling mode of DM1. The improved storage structure and filling mode can effectively reduce the high demand for storage space, and not only access efficiently, but also reduce the size of the used space. Through the in-depth research, analysis, implementation and improvement of the paper, DM1 in J1939 protocol has further improved the communication efficiency in the practical applications. © 2023 ieee.

关键词： Filling

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Design of a Tourist Attraction Recommendation Model Integrating Differential Privacy 3

Design of a Tourist Attraction Recommendation Model Integrat...

引用

3rd international conference on Electronic Information Engineering and computer science, EIECS 2023

作者： Feng, Ling Zhang, Su Zhang, Lei Duan, Xiqiang Taishan University College of Information Science and Technology Taian China Taishan University State Owned Assets Management Office Taian China

ISBN: (纸本)9798350316674

A tourist attraction recommendation model that integrates differential privacy is proposed to address the issue of user privacy leakage in current smart tourism recommendation systems. This model utilizes convolutional neural networks to generate feature vectors for users' historical or browsing records of scenic spots. Then, based on the different levels of user interest, different differential privacy noise is added to the feature vectors of each attraction of the user, and the total potential feature vectors of the user are calculated using a weighted sum method. To ensure the security of user data, a unified Laplacian noise is added to the potential feature vector of the user, and similarity calculation is performed with the feature vector of the candidate scenic spot to be recommended. When the similarity exceeds a certain threshold, the scenic spot is recommended to the user. © 2023 ieee.

关键词： Differential privacy Privacy protection Smart tourism Tourism recommendations

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Self-supervised Representation Learning for Time Series via Temporal Contrasting and Transformation 3

Self-supervised Representation Learning for Time Series via ...

引用

3rd ieee international conference on computer Communication and Artificial Intelligence, CCAI 2023

作者： Chen, Qirong Zhao, Menglei Zhang, Zhenguo Yanbian University Department of Computer Science and Technology 977 Gongyuan Road Yanji133002 China

ISBN: (纸本)9798350335262

Learning representations in widely available time series is of great significance, and representations in time series often represent some characteristic of this phase and play an irreplaceable role in fault detection in real industrial tasks, prediction in financial models, and diagnosis in medical data, while learning appropriate representations from unlabeled time series data is a challenging task. Most of the current methods are supervised learning methods, however, the labelling of data is time-consuming and impractical, and how to obtain effective data representations from unlabeled time-series data has great application value, based on this we propose an unsupervised time series representation learning method via Temporal Contrasting and Transformation (TS-TCT) to learn sequence representations from data lacking labelling. First, the time series is transformed into two homology sequences by applying mixed Augmentation and fast Fourier transform. Secondly, we use a cross-prediction based approach to enhance the time representation learning effect. Finally, to further enhance the learning effect, we employ a contextual comparison method based on the temporal comparison. The aim is to maximize the similarity of the same sample contexts while reducing the similarity between different sample contexts. The performance on two time series datasets shows that the unsupervised learning method based on TST-CT has some performance improvement over the existing unsupervised learning methods, and it is worth mentioning that our method has comparable performance with the supervised method and shows excellent results on some datasets. © 2023 ieee.

关键词： Time series

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A Denoising Method Based on Improved VMD-Wavelet Threshold and its application to Rolling Mill Vibration Monitoring 3

A Denoising Method Based on Improved VMD-Wavelet Threshold a...

引用

3rd international conference on computer science, Electronic Information Engineering and Intelligent Control Technology, CEI 2023

作者： Hu, Chenghe Fang, Ting Yang, Chunsheng Xue, Mingyao School of Electrical and Information Engineering Anhui University of Technology Ma'anshan China

ISBN: (纸本)9798350372052

Steel is the lifeblood of the nation, and rolling mill are crucial for steel production. Therefore, it is necessary to monitor rolling mill. The aim of this study is to achieve accurate monitoring of rolling mill vibrations in the presence of noise. This paper utilizes an accelerometer sensor to design a rolling mill vibration signal acquisition device and proposes an improved denoising method that combines variational mode decomposition (VMD) with enhanced wavelet thresholding. The improved coati optimization algorithm is used to optimize the optimal number of decomposition layers and penalty factor for the VMD, enhancing the decomposition performance. Enhanced wavelet threshold function solves the shortcomings of discontinuity and distortion of wavelet denoising methods. The improved joint denoising method is compared with other methods. The experimental results show that the proposed method can effectively reduce the noise of the rolling mill vibration signal and improve the accuracy of the vibration monitoring device, which has good practical application value. © 2023 ieee.

关键词： Variational mode decomposition

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Research on CNN Fusion Processing Technology for GNSS/INS Special Area Navigation application 3

Research on CNN Fusion Processing Technology for GNSS/INS Sp...

引用

3rd international conference on Electronic Information Engineering and computer Communication, EIECC 2023

作者： Li, Jiachang Hou, Jiawei Ning, Yipeng Xing, Jianping School of Integrated Circuits Shandong University Jinan China School of Surveying Mapping and Geographic Information Shandong Jianzhu University Jinan China

ISBN: (纸本)9798350359961

With the rapid development of science and technology, users have put forward high requirements for the positioning accuracy and stability of navigation and positioning systems. In special domain environments such as valleys, viaducts, tunnels, etc., the Global Navigation Satellite System (GNSS) signal is susceptible to external interference, resulting in a decrease in positioning accuracy, and the positioning error of the Inertial Navigation System (INS) will accumulate over time. Therefore, this paper studies the vehicle navigation system of GNSS/INS integrated positioning and proposes a new algorithm model to solve the accuracy problem of the non-integrity constraint model in measuring the lateral and normal velocity of the carrier. The algorithm simulates zero-mean Gaussian white noise by dynamically adjusting the model and uses a convolutional neural network (CNN) to optimize the covariance of pseudomeasurement noise with non-integrity constraints, to achieve the optimal fusion of the Kalman Filter (KF) model. Through the analysis and comparison of positioning accuracy and error, the convolutional neural network-integrated navigation (CNNGNSS/INS) data fusion processing model is finally determined. © 2023 ieee.

关键词： CNN Network Model Integrated navigation Non-integrity constraints Special domain environment

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Role of Blockchain in Higher Education Industries: A Survey 3

Role of Blockchain in Higher Education Industries: A Survey

引用

3rd ieee international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Verma, Ravi Nigam, Shekhar Jain, Ruchi Jain, Nelesh School of Computing Science Engineering Vit Bhopal University Bhopal India School of Computer Science and Engineering Sam Global University Bhopal India Lnct & S Dept. of Computer Science and Engineering Bhopal India Trinity Institute of Technology and Research Dept. of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798350343274

The Blockchain technology are recommended to add an extra security layer with banking, financial and education industries. The basic structure of Blockchain technology serve the security and privacy features using a concept of Block, Blocks has been mined in a way that distribute the transaction to other blocks of the Blockchain network these blocks are managing the data through transaction process in immutable and temper proof mode that makes Blockchain technology very secure throughout the mode of data transmission. In this study, we wish to examine how blockchain technology has impacted colleges in terms of information and technology in order to raise the standard of universities. Reviewing earlier research publications that are relevant to the study is the process utilized. As a result, it is anticipated that this research will make a positive impact by helping to solve issues with blockchain implementation in higher education, in the mean of how Blockchain transforms the education system and its role in near future with various growing industries as banking system, medical and education industries. © 2023 ieee.

关键词： Smart contract

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Research on the application of computer Digital Simulation Technology in the Chaos Model of Analog Circuits 3

Research on the Application of Computer Digital Simulation T...

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3rd ieee international conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Lv, Jing Liu, Yue Liu, Dan Han, Liwei Chen, Biao Shenyang Jianzhu University School of Science Shenyang China

ISBN: (纸本)9798350398410

In this paper, a method of generating wide-interval frequency-hopping sequences for bidirectional coupled mapping grids based on Tent mapping is presented. Multi-bit quantization, bit extraction and improved translation substitution method are adopted. The method is based on FPGA technology with Logistic chaotic mapping circuit as frequency hopping sequence generator. Direct digital frequency synthesizer is used as the basis of frequency hopping signal source. The signal is synthesized on FPGA, and the high performance AD9777 is used to realize the digital to analog conversion. The simulation results show that the wide interval frequency hopping sequence generator has the characteristics of simple structure and low computational complexity. The experimental results captured on a digital oscilloscope demonstrate the physical realizability of the constructed magneto-controlled memristor circuit. © 2023 ieee.

关键词： Mapping

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