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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"

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Driving behavior recognition method based on trajectory data detected by millimeter wave radar 3

Driving behavior recognition method based on trajectory data...

引用

3rd international conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Zhang, Rui Liu, Haiqing College of Transportation Shandong University of Science and Technology Qingdao China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9798350331578

In this paper, a multi-step vehicle driving behavior recognition method based on roadside millimeter-wave radar detecting trajectory data is proposed. The time and vehicle radial speed in trajectory data are selected as characteristic parameters. By analyzing the characteristic parameters of vehicles, different vehicle driving behaviors are classified. The proposed method marks and judges single driving behaviors, continuous driving behaviors, and complete driving behaviors in the state of RA (rapid acceleration), rd (rapid deceleration), GA (general acceleration), GD (general deceleration), and CS (constant speed) by calculating acceleration, interval time, and duration. The identification of vehicle driving behavior is completed finally. Using the vehicle trajectory data of continuous traffic flow scenarios at urban signal intersections as a sample, the established recognition method is applied for recognition and the results are compared with the actual driving behaviors of the sample. The identification results are consistent with the driving behavior reflected by the sample time-speed variation curves. It shows that the identification method proposed in this paper can effectively identify five types of driving behavior, and the accurate identification results of vehicle driving behavior have significance for traffic safety and traffic congestion improvement decision-making. © 2023 ieee.

关键词： Vehicles

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How can Moodle Quiz help teachers and researchers with complex questionnaires? 3

How can Moodle Quiz help teachers and researchers with compl...

引用

3rd international conference on Technology Enhanced Learning in Higher Education, TELE 2023

作者： Parkhomenko, Vladimir Reut, Elizaveta Zyamzina, Anastasiya Komarova, Elena Schukin, Alexander Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350326567

In this paper different tools with extended features for organizing questionnaires are analysed. The existing Moodle tools do not allow to implement questionnaire questions with non-standard functionality: checking of entered text (in short answers), auto-completing data from user profile, s election of cards, post-processing of question execution, for example, saving information in a separate database. To overcome these disadvantages a methodology of creation plugins for new questions and their behaviour using Moodle Quiz is presented. Comparing to another solutions the advantage of the methodology proposed is that it is possible to create a combination of quizzes and surveys (questionnaires). We present the development of a conference support system as another complex application. Also, there is an example of a mixed questionnaire test-like system for collection of a feedback from users about a connected test. In such applications it is necessary not only to collect data, but also to make sure that a person understands how to input it correctly. A system of 8 developed plugins is described. © 2023 ieee.

关键词： User profile

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Cryptocurrency Price Prediction with LSTM and Transformer Models Leveraging Momentum and Volatility Technical Indicators

Cryptocurrency Price Prediction with LSTM and Transformer Mo...

引用

data science and computer application (icdsca), ieee international conference on

作者： Siddharth Penmetsa Maruthi Vemula NCSSM Department of Math and Computer Science North Carolina School of Science and Mathematics Durham USA

Accurate cryptocurrency price prediction is essential to investors and researchers for analyzing trends and advising financial decisions, as price prediction is fundamental to making beneficial investment decisions. Due to the high volatility and unpredictability of the cryptocurrency market, it is difficult to predict these prices based on cryptocurrency time series data accurately. This research paper presents a two-fold analysis of the effectiveness of neural networks and deep learning to predict cryptocurrency prices and proposes a novel approach to cryptocurrency price prediction. This is done by considering Long-Short Term Memory (LSTM) and Transformer neural networks that use historical price features in addition to volatility and momentum technical indicators, along with historical price features, and testing these models on Bitcoin (BTC), Ethereum (ETH) and Litecoin (LTC). Momentum and volatility technical indicators such as Relative Strength Index (RSI), Bollinger Bands %B and Moving Average Convergence/Divergence (MACD) are not commonly used in cryptocurrency machine learning models. Still, the addition of these features can give better insight into the general trend of the price. By adding volatility and momentum features to our LSTM and Transformer models, we see a significant increase in price prediction accuracy, and we also find that Transformers tend to outperform LSTM models in price prediction and trends of cryptocurrency data.

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Design of Multi-Channel data Transmission System Based on PCIe-SRIO 3

Design of Multi-Channel Data Transmission System Based on PC...

引用

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

作者： Wang, Fuge Liu, Jianxin Ling, Yunzhi Zhuo, Qingkun Jiangsu Automation Research Institute Lianyungang China

ISBN: (纸本)9798350359961

In order to meet the long-distance and high-reliable transmission needs of multi- channel data, a multi-channel data transmission system based on PCIE-SRIO is designed. The Xilinx K7 series FPGA chip is designed, and the internal integrated PCIe and SRIO IP cores are used, and then the optical cable is connected to the optical cable to achieve long -range data sending and receiving. The system is based on the PCIe bus to realize the interconnection between the CPU chip and the FPGA chip, and the FPGA actively initiates and terminates the DMA transmission method to realize the high-speed interaction of multiple channels of data between the CPU chip and the FPGA chip. The internal logic of FPGA realizes SRIO interface based on HELLO packet format, and the sender uses Round-Robin arbitration mechanism to design multi-interface, which realizes the com-petition processing when multi-channel interfaces share a SRIO interface to send data at the same time. The results show that the designed system can realize data sending and receiving under 8 channels at most, which has certain reference significance for the application of long-distance transmission of interconnected data between boards. © 2023 ieee.

关键词： component data transmission system multi-channel PCIe SRIO

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A Multi-Objective Hyper-Heuristic Improved Configuration of Svm Based on Particle Swarm Optimization for Big data Cyber Security 3

A Multi-Objective Hyper-Heuristic Improved Configuration of ...

引用

3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Shekhawat, Jyoti Tajpal Vivekananda Global University Department of Computer Science Engineering Jaipur India Chandigarh School of Business Department of Master of Computer Application Jhanjeri India

ISBN: (纸本)9798350399264

Big data Cyber security analytics is a growingly significant field of study and application that uses big data techniques and technology to analyses security event data in order to safeguard networks, computers, and data from illegal access. There have been several reports on Big data Cybersecurity Analytic Systems in the literature, but an exhaustive and systematic analysis of the research from an architectural viewpoint is lacking. When In this paper, the SVM design process is organized as a bi-objective optimization problem with accuracy and model complexity as two competing goals. The system presents a novel, problem-independent hyper-heuristic framework for bi-objective optimization. It is novel to create a hyper heuristic for this situation. The hyper-heuristic structure proposed comprises of low-level heuristics and a significant level system. In light of the pursuit execution, the significant level system figures out which low-level heuristic ought to be utilized to create another SVM arrangement. Every one of the low-level heuristics look through the SVM design search space really utilizing an alternate arrangement of rules. To estimate the Pareto set of SVM arrangements, the suggested design adaptively combines the benefits of degradation with Pareto-based strategies for dealing with bi-objective enhancement. Microsoft's anomalous intrusion detection and big data malware classification have been used to gauge the efficiency of the suggested methodology. © 2023 ieee.

关键词： Cybersecurity

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Blockchain-Based data Verification and Quality Assessment Framework in data Trading Systems 3

Blockchain-Based Data Verification and Quality Assessment Fr...

引用

3rd international conference on computer science and Blockchain, CCSB 2023

作者： Ma, Shansi Zhou, Yu Zhang, Junlang Liang, Chufeng Fang, Jiawen Liu, Wenjun Tang, Hua Luo, Xiang School of Computer Science South China Normal University Guangzhou China School of Artificial Intelligence South China Normal University Guangzhou China Guangdong Tabacco Meizhou Ltd Meizhou China

ISBN: (纸本)9798350359077

In recent years, data trading has become an effective means for obtaining data resources and mitigating the data island phenomenon in fields like big data and artificial intelligence. However, traditional centralized data trading models are hampered by issues such as single-point failures and data leaks. Existing solutions have limitations, like the inability to perform trustworthy data verification and quality assessment before trading. Moreover, trading based on raw data can lead to reselling issues. To tackle these challenges, we introduce a novel framework and protocol that uses Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARKs) for secure and private data verification. Our approach also employs accumulators and other technologies to set new standards for objective data quality assessment. The experimental results indicate that our solution excels in computational efficiency and storage cost, effectively addressing data verification and quality assessment issues in data trading. © 2023 ieee.

关键词： Blockchain

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Real-time Detection of Taikyoku Shodan Karate Kata Poses Using Classical Machine Learning and Deep Learning Models 3

Real-time Detection of Taikyoku Shodan Karate Kata Poses Usi...

引用

3rd international Mobile, Intelligent, and Ubiquitous Computing conference, MIUCC 2023

作者： Walid, Mazen Ameen, Mostafa Atia, Ayman Faculty of Computer Science Cairo Egypt Faculty of Computer Science Giza Egypt Helwan University HCI-LAB Faculty of Computers and Artificial Intelligence Egypt

ISBN: (纸本)9798350306231

The research discusses the necessity for a precise feedback karate training system utilizing machine learning (ML) and deep learning (DL) models to facilitate real-time pose detection by offering instantaneous and accurate feedback. This system has the potential to revolutionize training methodologies, improve performance, and make significant contributions to the field of martial arts *** ML & DL algorithms were explored to achieve optimal results. Among the classical ML methods, the Random Forest, attained an accuracy of 98%. Additionally, DL models were also examined, with the Long-Short term memory model achieving an accuracy of 97%. The research presents an overview of the problem, methods for data collection and preprocessing, model training, and evaluation. The results emphasize the system's potential for real-time pose detection among karate practitioners, ultimately benefiting their training and progress. © 2023 ieee.

关键词： Learning systems

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Research on the Construction of Heterogeneous Resource data Relation Extraction System Based on computer Knowledge Graph 3

Research on the Construction of Heterogeneous Resource Data ...

引用

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

作者： Fan, Zhang Hangyin, Mao Ying, Cao Wei, Li Qing, Nie State Grid Zhejiang Electric Power Co. Ltd Hangzhou China Yingda Media & Investment Group Co. Ltd Beijing China

ISBN: (纸本)9798350398410

In this paper, multi-source heterogeneous online review data is used to construct a knowledge graph framework. The pattern layer constructs the conceptual framework of knowledge map by centering on the information source, content and form of online reviews. word2vec is used to obtain entities, relationships and attributes from heterogeneous texts, and data fusion and knowledge graph analysis are carried out. A two-stage knowledge graph model construction method is proposed to solve the multi-chain knowledge graph model of service value chain. The system realizes the storage of knowledge graph. Finally, the effectiveness of the knowledge map for online review research and mining is verified systematically. The results reveal the characteristics of multi-source heterogeneous online review data. © 2023 ieee.

关键词： Knowledge graph

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Effectiveness of Recurrent Neural Network with Biomimic Components 3

Effectiveness of Recurrent Neural Network with Biomimic Comp...

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

作者： Singh, Paras Nath Sakhare, Anupama Sarada, T. Cmr Institute of Technology Dept. of Computer Science and Engineering Bangalore560037 India Rtm Nagpur University Dept. of Electronics and Computer Science Nagpur440033 India

ISBN: (纸本)9798350343274

In order to improve the energy efficiency and computational capacity of our data processing systems, bioinspired, or neuromorphic, computing draws inspiration from how the brain computes. Emulation of natural systems, patterns, and components is known as biomimetics or biomimicry, and it is done to address challenging challenges in society. The term 'spintronics' refers to the application of a fundamental property of particles (the spin of an electron) known as the spin to information processing. Hopfield was the first to establish a direct connection between physical models and neural networks. To learn any of these models, the neural network must be able to adjust the coupling between each pair of spins. To implement multi-layer perceptron (neural network) structures, current technologies, however, have necessitated the extensive usage of complementary metal-oxide-semiconductor (CMOS) devices, which raises the perceptron's complexity of manufacture, space need, and power consumption. In this paper, it is suggested that the first trainable CMOS-free recurrent neural network with biomimetic components can be built using biomimetic neurons made of domain wall-magnetic tunnel junctions. This analysis shows how well this system performs computationally on benchmark tasks and how much more efficiently it performs computationally than alternative recurrent neural network systems. © 2023 ieee.

关键词： Biomimetics

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Research on Development of Government data Elements Based on Blockchain 3

Research on Development of Government Data Elements Based on...

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3rd international conference on Digital Society and Intelligent Systems, DSInS 2023

作者： Chen, Shenjin Yuan, Junying Zhang, Jianxin School of Electrical and Computer Engineering NanFang College Guangzhou Guangzhou510970 China

ISBN: (纸本)9798350331387

para>Blockchain is distributed, tamper proof, decentralized, and traceable, but it is difficult to implement. The introduction of smart contracts effectively solves this problem. This research uses the combination of privacy computing technology and blockchain technology to create an efficient and compliant solution for the data element market. With the help of smart contract technology based on blockchain, it provides effective technical management tools for all traders of data elements. Privacy computing and blockchain nodes are deployed in each transaction subject. On the premise of protecting the data privacy of each transaction party, the realization of transaction based on data value and the supervision and audit of the whole transaction process is an important security guarantee for the opening and sharing of government data according to the application. It is the most important business innovation application scenario for data elements to use smart contracts and microservices for sharing data authorization through data element development. © 2023 ieee.

关键词： Smart contract

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