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2024 International Conference on Cloud Computing and big data, ICCBD 2024

作者： Xie, Tianxia Liu, Xinning He, Yingjie Software and Big Data Technology Department Dalian Neusoft University of Information China

ISBN: (纸本)9798400710223

In the ever-expanding field of business data analysis applications, historical data serves as the foundation for making better decisions for businesses and management personnel. However, the challenge of fully leveraging the vast historical data to devise smarter strategies is the subject of this paper's research. This paper investigates the historical sales data of a company's sports products, classifies customers using clustering algorithms, and designs more scientific sales strategies through the Apriori algorithm to achieve intelligent recommendations. It has transformed the previous single sales model and assisted businesses in enhancing their sales performance. © 2024 ACM.

关键词： Sales

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Research on Insurance Fraud Identification Based on mRMR Algorithm and SVM Classification 9

Research on Insurance Fraud Identification Based on mRMR Alg...

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9th International Conference on Image, Vision and Computing, ICIVC 2024

作者： Zhou, Limei Fu Hui Department of Software and Big Data Technology Neusoft University of Information Dalian China

ISBN: (纸本)9798350385991

With the development of science and technology and the wide application of big data, the use of raw data for risk identification and early warning has become an effective means. This paper presents a classification method based on mRMR algorithm and SVM, which can be used to identify the risk of fraud and make early warning. First of all, a variety of raw data were collected, including permanent population list information, key offenders, snapshot data, outpatient data, express information and peer relations. Then the mRMR algorithm is used to extract the features of the original data, including key personnel information, entry and exit places, express delivery information and medical information. Then, SVM classification algorithm is used to model and predict the extracted features, and the fraud risk personnel are defined as positive class, and the non-risk personnel are defined as negative class. The experimental results show that the proposed method can effectively identify the risk of fraud and give early warning, and provide a feasible means for relevant institutions to deal with fraud. © 2024 IEEE.

关键词： Crime

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Implementation and Evaluation of Student Microexpression Recognition Method Based on Neural Network Model in Blended Learning 6

Implementation and Evaluation of Student Microexpression Rec...

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6th International Workshop on Artificial Intelligence and Education, WAIE 2024

作者： Peng, Yuying Zhou, Hui Liu, Tong Du, Menghan Dalian Neusoft University of Information Department of Software and Big Data Technology Dalian China

ISBN: (纸本)9798350378894

In the era of artificial intelligence, facial expression recognition is a research hotspot, and student micro expression recognition is a prerequisite for teachers to understand student states and emotions. Facial micro expressions typically contain various difficult to recognize types, and different convolutional neural networks are suitable for different types of facial expression recognition tasks. However, in complex situations, when multiple types of facial micro expressions coexist, the recognition results may be inaccurate. This article proposes a student micro expression recognition method based on neural network models and stacking methods. Experiments have shown that compared with traditional CNN neural network models, this method significantly improves the accuracy of student learning state recognition, can solve the tracking and feedback problems of student learning states in blended learning, adjust instructional design and digital evaluation system in real time, and better assist students in effective learning. © 2024 IEEE.

关键词： Contrastive Learning

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3D Human Pose and Shape Estimation Based on SMPL Model 9

3D Human Pose and Shape Estimation Based on SMPL Model

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9th International Conference on Image, Vision and Computing, ICIVC 2024

作者： Song, Yuanyuan Zhou, Hui Department of Software and Big Data Technology Dalian Neusoft University of Information Dalian China

ISBN: (纸本)9798350385991

3D human pose and body shape estimation is a hot research topic in computer vision, and there are many optimization-based methods that rely only on the input parameters to obtain the optimal solutions for pose and body shape through multiple iterations. However, such methods often ignore the spatial information that may be embedded in the images, and we propose an effective method for reconstructing 3D human body models from a single RGB image. Our method effectively combines a priori information with picture spatial information. The feature information of the image is first obtained by a convolutional neural network. Then, the image features are combined with the joint a priori information to guide the generation of optimal solutions for the parameters, and we propose an improved method based on the optimization method, which enables the parameter updating process to effectively combine the image spatial features, and to obtain the estimation results matching the objectives. The whole process combines the advantages of the CNN method with the optimization-based method to guide the parameter update through the spatial feature information extracted from the CNN. The results of quantitative and qualitative experiments conducted on public datasets mark that our method outperforms previous methods in many aspects. © 2024 IEEE.

关键词： 3D reconstruction

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Research on the Relationship Between New Energy Vehicles and Dual Carbon in Yangtze River Delta Based on GRA-LSTM Model 7

Research on the Relationship Between New Energy Vehicles and...

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7th IEEE Advanced Information technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Zhou, Jinxuan Deng, Liang Tong, Yi Gao, Yan Wuhan Business University Department of Information Engineering Hubei China Data Science and Big Data Technology China Internet of Things Engineering China Software Engineering Big Data Technology

ISBN: (纸本)9798350339161

New energy automobile industry plays an important role in building a green, low-carbon and recycling industrial system. In this paper, the prediction simulation training and prediction accuracy comparison study are carried out with the help of the newly constructed GRA-LSTM model, Biological Neural Network model and the first-order one-variable gray GM (1, 1) model. The LSTM model is created and trained by Learning Rate Decay function. The Learning Rate Decay callback function is set, and the learning rate is gradually reduced during the training process to carry out simulation training, and finally the trained model is used to make predictions, and the time for the Yangtze River Delta region to reach carbon peak is 2028, and the time to reach carbon neutrality is 2060, and at the same time this paper analyzes and finds out that the higher the new energy automobile market ownership is, the shorter the time for carbon peak and carbon neutrality will be.2. © 2024 IEEE.

关键词： Forecasting

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Ultrasonic testing signal image processing based on improved set empirical mode decomposition 7

Ultrasonic testing signal image processing based on improved...

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7th International Conference on Information and Computer Technologies, ICICT 2024

作者： Zhao, Siqi Peng, Yuying Dalian Neusoft University Of Information Department Of Software And Big Data Technology Dalian City China

ISBN: (纸本)9798350385625

In view of the fact that the ensemble empirical modal decomposition (EEMD) method can avoid the modal aliasing phenomenon of the EMD method, it is still lacking in noise removal and retention of effective feature signals, so an ultrasonic nondestructive testing signal processing method combining EEMD and wavelet packets is proposed. In this method, the original signal is first processed by EEMD to ensure that the modal aliasing phenomenon is eliminated. However, this will cause the loss of some characteristic signals, and the lost signals will be retrieved through wavelet packet processing to improve the signal-to-noise ratio. In the process of decomposition signal reconstruction, the correlation coefficient method is used for feature selection, and the effective defect signal with high correlation coefficient is selected for reconstruction, which can not only effectively suppress modal aliasing, but also retain more feature signals. Through the experimental verification of the actual signal, the proposed improved method obtains a better signal-to-noise ratio, a lower root mean square error and a higher correlation coefficient, which is more suitable for processing ultrasonic nondestructive testing signals. © 2024 IEEE.

关键词： Defects

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Research on software Security Based on DVWA 3

Research on Software Security Based on DVWA

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3rd IEEE International Conference on Electronic technology, Communication and Information, ICETCI 2023

作者： Wang, Junmei Liu, Xinning Dalian Neusoft University of Information Department of Software and Big Data Technology Liaoning Dalian116023 China

ISBN: (纸本)9798350398410

[Purpose] With the popularization of software and the Internet, people pay more and more attention to the security of the Web system. software security vulnerabilities have strong concealment. Once the Web system is attacked, it will cause incalculable losses to enterprises and individual users. How to understand the root causes of various software security vulnerabilities, and how to find software security vulnerabilities in order to improve the security of software systems is a very important topic in software development. [Methods] DVWA (Damn Vulnerable Web App) can help people understand various software security vulnerabilities. By using DVWA, people can understand various types of Web system software security vulnerabilities, as well as different levels of vulnerability prevention methods. [Conclusion] The experimental results show that DVWA provides a testing environment for various Web system security vulnerabilities, covers typical types of vulnerabilities, is easy to understand and use, and can effectively help developers improve the security of Web systems. © 2023 IEEE.

关键词： software design

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A survey on cross-user federated recommendation

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Science China(Information Sciences) 2025年第4期68卷 7-32页

作者： Enyue YANG Yudi XIONG Wei YUAN Weike PAN Qiang YANG Zhong MING College of Computer Science and Software Engineering Shenzhen University School of Electrical Engineering and Computer Science The University of Queensland WeBank AI Lab WeBank Department of Computer Science and Engineering Hong Kong University of Science and Technology College of Big Data and Internet Shenzhen Technology University Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.

关键词： cross-user federated recommendation federated recommendation federated learning recommender systems user privacy

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Motion data Collection for Dance Movements based on Inertial Sensors 12

Motion Data Collection for Dance Movements based on Inertial...

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12th International Conference on Orange technology, ICOT 2024

作者： Yang, Keyan Chang, Xingzhi Long, Xiaohan School of Basic Teaching Department Changzhou College of Information Technology Changzhou China School of Software and Big Data Changzhou College of Information Technology Changzhou China

ISBN: (纸本)9798331523602

Dance requires professional instruction during the learning and training process, but high-level guidance at any time and any place can be a challenge. In the context of Orange technology oriented towards human well-being and health care, this paper proposes fixing the data acquisition device terminals on different parts of the body of dancers, motion data during dance performances can be automatically collected. This data is sent to the server side for processing and then stored in the database, and the nine-axis dynamic data collected from various body parts is displayed on the Web page of the user side in time. By reviewing this data, dancers can be guided to improve their pose, helping them enhance their professional skills and experience a sense of satisfaction and happiness during the dance. © 2024 IEEE.

关键词： data acquisition

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A Reduced State-Space Generation Method for Concurrent Systems Based on CPN-PR Model

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年第6期44卷 2328-2342页

作者： Zhong, Wenjie Sun, Tao Zhou, Jian-Tao Wang, Zhuowei Song, Xiaoyu Inner Mongolia University College of Computer Science the Engineering Research Center of Ecological Big Data Ministry of Education the Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software the Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Hohhot010000 China Guangdong University of Technology School of Computer Science and Technology Guangzhou510006 China Portland State University Department of Electrical and Computer Engineering PortlandOR97207 United States

Colored Petri nets (CPNs) provide descriptions of the concurrent behaviors for software and hardware. Model checking based on CPNs is an effective method to simulate and verify the concurrent behavior in system design. However, the model-checking method traverses the full state space, which suffers from the state-space explosion problem. A reduced state-space generation method related to the property of concurrent systems is proposed. Specifically, we extend CPNs to define a property-related model (CPN-PR) and give a property-related analysis method whose results can be used to generate the CPN-PR model. A reduced state-space generation method is developed based on enabled binding element filtering rules. The stutter trace equivalence between the state spaces of CPN and CPN-PR has been proven by showing that the reduced state space may not change the model-checking result. A comparison experiment is conducted to demonstrate the effectiveness of our method. © 1982-2012 IEEE.

关键词： Model checking

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