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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Haibo Ding, Ding Liu, Yuhao Wang, Chi Southeast University School of Computer Science and Engineering Nanjing211189 China Southeast University College of Software Engineering Nanjing211189 China

ISBN: (纸本)9798350331684

Sandplay therapy is a novel psychological consultation and treatment method for people suffering from mental stress and psychological issues. It is popular among the masses owing to its interest and curative effect. However, traditional sandplay games face several problems, such as the requirement of large space, low accessibility, difficulty in keeping treatment records, and lack of engagement. To solve these problems, we put forward a sandplay system based on virtual reality technology. This system provides a virtual scenario of the sandplay room, allowing users to place various sandplay miniatures naturally and smoothly into the sandbox with multiple themes by using motion capture gloves. What is more, users can switch to the first-person perspective to experience the world they have built. Additionally, the system could collect users' eye-tracking data and analyze it by a machine learning algorithm to estimate individuals' emotions which could assist in further treatment. Finally, twelve participants were invited to experience the system. They were asked to evaluate this system as well as their emotional status before and after using it. The experimental results indicate that the participants are satisfied with this system, while their emotions can be improved to a certain extent. © 2023 IEEE.

关键词： Virtual reality

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Design of data processing scheme of 5G terminal protocol conformance test system 4

Design of data processing scheme of 5G terminal protocol con...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Jingyao, Cao Yadav, Amit Khan, Asif Sah, Abhishek Pratap Chengdu Neusoft University School of Computer and Software Chengdu China Charles Darwin University College of Engineering It and Environment NT Australia Integral University Department of Computer Application Lucknow India University of Electronic Science and Technology of China School of Management Science and Engineering Chengdu China

ISBN: (纸本)9798350343670

Considering the fact that the test case runs abnormally and the test case execution fails during the development and debugging of the 5G terminal protocol conformance test system. Here useful approach is implemented by embedding data copy and storage module in the system, which completes the encapsulation, copy and storage of massive data generated during the operation of the system, so that equipment developers can correctly locate the errors in the system according to the data, and repair the system loopholes to ensure the stability and accuracy of the system. © 2024 IEEE.

关键词： 5G Terminal copy and storage module protocol conformance

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A Novel Secure Scan Design Based on Delayed Physical Unclonable Function

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computers, Materials & Continua 2023年第3期74卷 6605-6622页

作者： Weizheng Wang Xingxing Gong Xiangqi Wang Gwang-jun Kim Fayez Alqahtani Amr Tolba School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China College of Information Science and Engineering Hunan Women’s UniversityChangsha410138China College of Mathematics and Computational Science Hunan First Normal UniversityChangsha410138China Department of Computer Engineering Chonnam National UniversityGwangju61186Korea Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia

The advanced integrated circuits have been widely used in various situations including the Internet of Things,wireless communication,*** its manufacturing process exists unreliability,so cryptographic chips must be rigorously *** to scan testing provides high test coverage,it is applied to the testing of cryptographic integrated ***,while providing good controllability and observability,it also provides attackers with a backdoor to steal *** the text,a novel protection scheme is put forward to resist scan-based attacks,in which we first use the responses generated by a strong physical unclonable function circuit to solidify fuseantifuse structures in a non-linear shift register(NLSR),then determine the scan input code according to the configuration of the fuse-antifuse structures and the styles of connection between the NLSR cells and the scan *** the key is right,the chip can be tested normally;otherwise,the data in the scan chain cannot be propagated normally,it is also impossible for illegal users to derive the desired scan *** proposed technique not only enhances the security of cryptographic chips,but also incurs acceptable overhead.

关键词： Cryptographic chips scan testing scan-based attacks hardware security PUF

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Enhancing Sales Forecasting Accuracy in the Presence of Missing Data 17

Enhancing Sales Forecasting Accuracy in the Presence of Miss...

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IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024

作者： Tang, Jun Sun, Jingpeng Guo, Bing Shen, Yan Dai, Shengxin Wang, Peng College of Computer Science Sichuan University Chengdu China College of Computer Science University of Birmingham Dubai United Arab Emirates School of Computer Science Chengdu University of Information Technology Chengdu China College of Software Engineering Sichuan University Chengdu China

ISBN: (纸本)9798350351637

Accurate sales forecasting serves as a critical foundation for informed business decision-making and numerous methodologies have been advanced by scholars predominantly rely on complete datasets, however, in practice, uncontrollable variables often result in the presence of missing data, diminishing the applicability of established techniques, so the sales forecasting research based on missing data is of great significance. Some researchers have resorted to employing deletion or interpolation techniques to pre-process incomplete data before conducting sales forecasts, but such completion methods tend to introduce distributional biases, subsequently leading to forecast inaccuracies. In light of these challenges, this study introduces a novel computational framework combining Convolutional Neural Network (CNN), Self-Attention, and Sequence-to-Sequence (Seq2Seq) models, where global features are first extracted via the synergistic application of CNN and Self-Attention mechanisms, then the extracted features are seamlessly integrated with the original dataset, supplanting conventional interpolation strategies, and finally the amalgamated data are inputted into the Seq2Seq model for sales prediction. The proposed methodology is empirically evaluated using sales data from a real-world company, demonstrating commendable predictive performance and underscoring the efficacy of the proposed approach in enabling accurate sales forecasts within the context of missing data scenarios. © 2024 IEEE.

关键词： Data accuracy

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Research on Map Construction and Location Technology Based on Multi-line LiDAR 5th

Research on Map Construction and Location Technology Based o...

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5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022

作者： Liu, Fang Yang, Yang Su, Weixing School of Software Engineering Tiangong University Tianjin300387 China School of Computer Science and Technology Tiangong University Tianjin300387 China

ISBN: (纸本)9789819910267

Point cloud registration is an important part of 3D point cloud map construction based on multi-line lidar. At present, traditional iterative nearest point algorithm (ICP) is mainly used for point cloud registration. For the traditional iterative nearest point algorithm, point cloud registration is time-consuming and error-prone, which leads to the low accuracy of point cloud registration. Based on the principle of traditional iterative nearest point algorithm, this paper proposes an improved ICP algorithm combining PL-ICP algorithm and PP-ICP algorithm. The map construction is realized by this method, and on the basis of the map construction, NDT algorithm is used to further realize the positioning of unmanned vehicles. The experimental results show that the method can effectively construct the point cloud image, reduce the registration time of point cloud, and has good registration accuracy. Through the validation of the dataset, the positioning experiment can be completed by randomly placing the unmanned vehicle in a certain position on the constructed map. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Optical radar

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A Novel Heuristics for the Strong Generalized Minimum Label Spanning Tree Problem 3

A Novel Heuristics for the Strong Generalized Minimum Label ...

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3rd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2023

作者： Long, Yinyan Li, Xiaoxia Long, Zhuming Wu, Fuying Long, Hao School of Computer Engineering and Science ShangHai University ShangHai200444 China School of Software Jiangxi Normal University Nanchang330022 China

ISBN: (纸本)9781643684444

The strong generalized minimum label spanning tree problem (SGMLSTP) is to search the minimum label spanning tree (MLST) from an Edge-labeled graph (ELG), in which each edge is associated with one or more labels. SGMLSTP is commonly existed in reality and proven NP-hard. In recent years, researchers have proposed some algorithms;however, high computational costs are still severe obstacle, especially for large size graphs. In this paper, we propose a novel heuristics to solve SGMLSTP. We decompose the problem into two sub-problems, one is to search a connected subgraph with minimum labels from the original graph, the other is to search a spanning tree from the subgraph. As the latter sub-problem is solved, we focus on the former sub-problem and propose a community-based zigzag piloting algorithm: Firstly a label graph is derived from the original edge-labeled graph;then the label graph is partitioned and some label community (or community combinations) is chosen to form an initial solution;finally, the zigzag piloting process is applied to refine the initial solution. Label partition finds the initial solution quickly, the zigzag piloting process improves solution refinement. Experimental results on typical benchmark datasets show better effectiveness and performance of our algorithm than that of the state-of-the-art algorithms. © 2023 The Authors.

关键词： Trees (mathematics)

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A novel few-shot learning approach for the classification of histological images of liver tumors

A novel few-shot learning approach for the classification of...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Xu, Bo Wang, Qirui Li, Longjiao Yang, Jinqiao Lin, Hongfei Ding, Feng Dalian University of Technology School of Software Engineering Dalian China Dalian University of Technology School of Computer Science and Technology Dalian China

ISBN: (纸本)9798350337488

The liver is an internal organ that is most commonly affected by cancer metastasis. Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths worldwide. Identifying the histological category of this disease is a crucial step in determining the most appropriate treatment plan. Currently, the classification of HCC primarily relies on the observation of pathologists through a visual microscope, which is undoubtedly subjective. To address this issue, the present study conducted pathological examination of liver tumors based on few-shot learning. In order to achieve automatic identification of the three categories in HCC tissue, we propose a few-shot learning based HCC histological image classification method that combines contrastive learning (CL) using different backbone architectures with several well-known machine learning methods. We evaluate 12 backbone-classifier combinations, and the best performance is achieved by combining CL using DeiT-TinyR as the backbone architecture with support vector machine (SVM), with an accuracy of 74.42% and an F1 score of 74.58% in the 3-way-10-shot setting. Experimental results demonstrate the effectiveness of this method in NB histological image classification. © 2023 IEEE.

关键词： classification contrastive learning few-shot hepatocellular carcinoma hyperspectral image

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ResMHA-Net:Enhancing Glioma Segmentation and Survival Prediction Using a Novel Deep Learning Framework

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computers, Materials & Continua 2024年第10期81卷 885-909页

作者： Novsheena Rasool Javaid Iqbal Bhat Najib Ben Aoun Abdullah Alharthi Niyaz Ahmad Wani Vikram Chopra Muhammad Shahid Anwar Department of Computer Science School of Engineering and TechnologyIslamic University of Science and TechnologyAwantipora192122India Faculty of Computing and Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia Research Groups in Intelligent Machines National School of Engineers of SfaxUniversity of SfaxSfax3038Tunisia Department of Electrical Engineering College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147004Punjab Department of Electrical and Instrumentation Engineering Thapar Institute of Engineering and TechnologyPatiala147004Punjab Department of AI and Software Gachon UniversitySeongnam-si13120Republic of Korea

Gliomas are aggressive brain tumors known for their heterogeneity,unclear borders,and diverse locations on Magnetic Resonance Imaging(MRI)*** factors present significant challenges for MRI-based segmentation,a crucial step for effective treatment planning and monitoring of glioma *** study proposes a novel deep learning framework,ResNet Multi-Head Attention U-Net(ResMHA-Net),to address these challenges and enhance glioma segmentation ***-Net leverages the strengths of both residual blocks from the ResNet architecture and multi-head attention *** powerful combination empowers the network to prioritize informative regions within the 3D MRI data and capture long-range *** doing so,ResMHANet effectively segments intricate glioma sub-regions and reduces the impact of uncertain tumor *** rigorously trained and validated ResMHA-Net on the BraTS 2018,2019,2020 and 2021 ***,ResMHA-Net achieved superior segmentation accuracy on the BraTS 2021 dataset compared to the previous years,demonstrating its remarkable adaptability and robustness across diverse ***,we collected the predicted masks obtained from three datasets to enhance survival prediction,effectively augmenting the dataset *** features were then extracted from these predicted masks and,along with clinical data,were used to train a novel ensemble learning-based machine learning model for survival *** model employs a voting mechanism aggregating predictions from multiple models,leading to significant improvements over existing *** ensemble approach capitalizes on the strengths of various models,resulting in more accurate and reliable predictions for patient ***,we achieved an impressive accuracy of 73%for overall survival(OS)prediction.

关键词： Glioma MRI segmentation multihead attention survival prediction deep learning

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Deep Learning Emotion Recognition Method 10

Deep Learning Emotion Recognition Method

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10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Xiao, Weidong Tan, Wenjin Xiong, Naixue Yang, Ce Chen, Lin Xie, Rui University of Technology Schoole of Software Engineering Xiamen Xiamen361024 China Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798350312461

Emotion recognition refers to the process of actively analyzing human emotions through computer technology, and it has become an important part of modern society. Traditional emotion recognition is mainly based on a single information source, such as text, speech, video, etc., from which emotional features are extracted for classification or regression to recognize human emotions. With the development of artificial intelligence technology, multimodal emotion recognition is gradually becoming widely used. It combines two or more types of information, such as text, speech, and visual information, in different ways to analyze emotions. Multimodal emotion recognition is far superior to a single modality in understanding emotions. This article mainly analyzes the technology of emotion analysis. Firstly, we introduce the basic concepts and research status of emotion recognition. Then, we introduce the main types of emotion recognition and describe various methods used in the process in detail. Finally, we discuss the challenges and future developments of emotion recognition. © 2023 IEEE.

关键词： Emotion Recognition

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STTG-net:a Spatio-temporal network for human motion prediction based on transformer and graph convolution network

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 224-238页

作者： Lujing Chen Rui Liu Xin Yang Dongsheng Zhou Qiang Zhang Xiaopeng Wei tional and Local Joint Engineering Laboratory of Computer Aided Design School of Software EngineeringDalian UniversityDalian 116622China School of Computer Science and Technology Dalian University of TechnologyDalian 116024China

In recent years,human motion prediction has become an active research topic in computer ***,owing to the complexity and stochastic nature of human motion,it remains a challenging *** previous works,human motion prediction has always been treated as a typical inter-sequence problem,and most works have aimed to capture the temporal dependence between successive ***,although these approaches focused on the effects of the temporal dimension,they rarely considered the correlation between different joints in ***,the spatio-temporal coupling of human joints is considered,to propose a novel spatio-temporal network based on a transformer and a gragh convolutional network(GCN)(STTG-Net).The temporal transformer is used to capture the global temporal dependencies,and the spatial GCN module is used to establish local spatial correlations between the joints for each *** overcome the problems of error accumulation and discontinuity in the motion prediction,a revision method based on fusion strategy is also proposed,in which the current prediction frame is fused with the previous *** experimental results show that the proposed prediction method has less prediction error and the prediction motion is smoother than previous prediction *** effectiveness of the proposed method is also demonstrated comparing it with the state-of-the-art method on the Human3.6 M dataset.

关键词： Human motion prediction Transformer Gragh convolutional network

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