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9th International Conference on Computer and Communications, ICCC 2023

作者： Cui, Mingyue Cui, Mingzhang Shandong University School of Software Jinan China Lanzhou University School of Information Science & Engineering Lanzhou China

ISBN: (纸本)9798350317251

This paper aims to explore methods and techniques for achieving verifiability in cloud computing environments. Methodologically, by utilizing game theory as the theoretical foundation and employing blockchain and smart contracts as core technologies, we introduce various cooperative mechanisms, including prisoner's contracts, collusion contracts, and traitor contracts, to construct a trustworthy computational framework. In terms of improvements, we innovatively incorporate local blockchains, state channel technology, zero-knowledge proof technology, multi-signature technology, and dynamic reward and punishment mechanisms to additional optimize existing methods. However, the proposed technologies in this paper still require further research and practical validation to assess their actual applicability. Going forward, it is important to enhance blockchain storage and synchronization mechanisms, as well as promote their implementation in broader domains. © 2023 IEEE.

关键词： Smart contract

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Understanding the Impact of Unexpected Cobot Movements on Human Stress Levels: A Time Series Classification Task

Understanding the Impact of Unexpected Cobot Movements on Hu...

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2024 Workshop on Embracing Human-Aware AI in Industry 5.0, HAII5.0 2024

作者： Shilon, Lior Shevtsov, Vladyslav Schillreff, Nadia Rother, Anne Mark, Shlomo Spiliopoulou, Myra Department of Software Engineering Sami Shamoon College of Engineering Ashdod Israel Faculty of Computer Science Otto-von-Guericke-University Magdeburg Germany

This study investigates the impact of unexpected stimuli on participants’ stress levels during human-robot interactions (HRI). We designed an experiment, where a cobot performs writing tasks, as well as some unexpected actions, intended to surprise the human observer. During this experiment, we are continuously monitoring physiological responses through Electrodermal Activity (EDA) and Electrocardiogram (ECG) sensors. Our goal was to capture the relationship between surprising actions by the cobot and indicators of change in the human stress levels. We employed time series classification techniques, namely ROCKET, Shapelet Transform and WEASEL, along with Support Vector Machine (SVM) analysis on temporal segments. This approach enabled us to develop a binary classification model on stress levels. Our research contributes to the design of AI systems that can detect changes in the stress levels of humans who interact with cobots that perform unexpected actions. Thus, we work towards the improvement of safety protocols in HRI. © 2024 Copyright for this paper by its authors.

关键词： Collaborative robots

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DeCsmith, An automatic generation tool of equivalent program

DeCsmith, An automatic generation tool of equivalent program

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2023 International Conference on Computer Network Security and software Engineering, CNSSE 2023

作者： Chen, Zan Wang, Liyao Liu, Lei Zhang, Peng College of Computer Science and Technology Jilin University Changchun China College of Software Jilin University Changchun China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

Compilers play a very important role in the development of software. More and more researchers are studying how to improve the reliability of compilers. An effective method is to test the compiler with equivalent programs to check whether the running results of equivalent programs are still equivalent after being compiled by the compiler. Generating equivalent program sets is the key to solve this problem. This paper proposes an equivalent program generation tool DeCsmith, which is based on the development of Csmith. Through the equivalence relationship, the program generated by Csmith is equivalently changed, and the equivalent program set is automatically generated. The effectiveness of the method is verified by an example. The work of this paper is beneficial to saving human resources in compiler testing and improving the efficiency of testing compilers. © 2023 SPIE.

关键词： software testing

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Group signature with restrictive linkability: minimizing privacy exposure in ubiquitous environment

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Journal of Ambient Intelligence and Humanized Computing 2024年第2期15卷 1411-1421页

作者： Eom, Sungwook Huh, Jun-Ho Department of Electrical Engineering Pohang University of Science and Technology Gyeongbook Pohang Korea Republic of Department of Software Catholic University of Pusan Geumjeong-gu 57 Oryundae-ro Busan Korea Republic of

As IoT technology evolves, developments of ubiquitous computing accelerates. At the same time, threats of privacy exposure also increase since the IoT systems expose the information such as user’s location or medical status collected from all sorts of things. To handle the data elaborately, the ubiquitous systems need to employ a technology that provides anonymity to prevent exposure of personal information. The group signature scheme is widely used for a cryptographic base for privacy protection which do not reveal user’s identity but prove that he/she is a legitimate user. Recently, a number of researches concerning the basic group signature schemes with a differentiated linkability have been conducted to provide a more flexible service. However, existing researches focused on providing flexible services from the service provider’s position. The systems are exposed to high possibilities of unnecessary breach of privacy. In this paper, we define a restrictive linkability for the anonymous services that require an adequate linkability with a minimum user-designated privacy exposure in anonymous services and propose an efficient group signature scheme providing restrictive linkability. © Springer-Verlag GmbH Germany, part of Springer Nature 2018.

关键词： Ubiquitous computing

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Decision support system of staff member promotion based on cloud computing (Case Study University Of Benghazi) 3

Decision support system of staff member promotion based on c...

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3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and Computer Engineering, MI-STA 2023

作者： Alfsai, Entesar H. Bozed, Kenz A. Hagal, Mohamed A. University of Benghazi Department of Software Engineering Benghazi Libya University of Benghazi Department of Computer Science Benghazi Libya

ISBN: (纸本)9798350319897

The scientific council at Benghazi University suffered from issues related to the scientific promotion process for faculty members. Promotion is still done manually, without a computerized system. Therefore, it faces obstacles in obtaining basic information, issuing promotion decisions, making managerial procedures, lack of flexibility, and the accumulation of papers. There are also unclear biases in decision-making and mechanisms of evaluating promotion criteria. Thus, they need to keep up with the international universities in the promotion process to be successful in administrative business today. Benghazi University needs an information system that can support decision-making, which is a major problem often occurs in the process of promotion of faculty *** use of decision support systems is a solution to reduce subjectivity in decision-making. This work presents an E-Gate that can assist in the promotion of educational staff. It is a system able to provide the best alternative in promotion educational staff. With the decision support system, the promotion process is carried out via the E-Gate using the AHP method according to several criteria. It is stored in the cloud computing because many enterprises are adopting the cloud-computing platform to examine the benefits of self-service, user guide, and high flexibility. The time is right for the educational universities to derive benefits of the cloud, as they are obliged to deliver better ubiquitous services. The study also developed Search Engine to verify the submitted research. © 2023 IEEE.

关键词： Decision support systems

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Optimizing Power Allocation for D2D Communication with URLLC under Rician Fading Channel:A Learning-to-Optimize Approach

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Intelligent Automation & Soft Computing 2023年第9期37卷 3193-3212页

作者： Owais Muhammad Hong Jiang Mushtaq Muhammad Umer Bilal Muhammad Naeem Muhammad Ahtsam School of Information Engineering Southwest University of Science and TechnologyMianyang621010China School of Software Engineering Northeastern UniversityShenyang110167China School of Information and Software Engineering University of Electronic Sciences and TechnologyChengdu610000China

To meet the high-performance requirements of fifth-generation(5G)and sixth-generation(6G)wireless networks,in particular,ultra-reliable and low-latency communication(URLLC)is considered to be one of the most important communication scenarios in a wireless *** this paper,we consider the effects of the Rician fading channel on the performance of cooperative device-to-device(D2D)communication with *** better performance,we maximize and examine the system’s minimal rate of D2D *** to the interference in D2D communication,the problem of maximizing the minimum rate becomes non-convex and difficult to *** solve this problem,a learning-to-optimize-based algorithm is proposed to find the optimal power *** conventional branch and bound(BB)algorithm are used to learn the optimal pruning policy with supervised *** learning is used to train the multiple *** address the imbalanced problem,we used the supervised undersampling *** are made with the conventional BB algorithm and the heuristic *** outcome of the simulation demonstrates a notable performance improvement in power *** proposed algorithm has significantly low computational complexity and runs faster as compared to the conventional BB algorithm and a heuristic algorithm.

关键词： D2D URLLC rician fading supervised learning

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Design and analysis of series and parallel circuits based on plasmonic waveguides for high-performance computing devices

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Journal of Optical Communications 2025年第1期46卷 193-200页

作者： Jain, Satyendra Choudhary, Kuldeep Kumar, Santosh Department of Electrical and Electronics & Communication Engineering DIT University Dehradun248009 India Shandong Key Laboratory of Optical Communication Science and Technology School of Physics Science and Information Technology Liaocheng University Shandong Liaocheng252059 China

Nowadays, mental-insulator-metal (MIM) waveguides are widely used in the design of optical plasmonic waveguides due to their superior ability to confine surface plasmons up to sub wavelength scale. This research proposes the design of series and parallel circuits using cascaded plasmonic Mach-Zehnder interferometers (PMZIs). Each PMZI employs a nonlinear arm to switch light across the output port via the insertion of the nonlinear Kerr material poly(2-methoxy-5-(28-ethylhexyloxy)-PPV). The proposed design is having footprint of 104 μm × 11 μm. The finite-difference time-domain method is used to study, design, and analysis all optical series and parallel circuit proposals. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Metal insulator boundaries

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Image Compression and Stable Reconstruction Based on Multi-Level Hybrid Feature Guidance 2

Image Compression and Stable Reconstruction Based on Multi-L...

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2nd International Conference on Machine Learning, Cloud Computing, and Intelligent Mining, MLCCIM 2023

作者： Zeng, Heng Gong, Nanxu College of Software Engineering Sichuan University Chengdu China School of Computer Science Sichuan University Chengdu China

ISBN: (纸本)9798350328530

Image compression is a technique that reduces storage space and transmission bandwidth requirements by reducing the amount of image data, aiming to improve storage and transmission efficiency while maintaining acceptable image quality. In recent years, learning-based image compression methods have demonstrated superior rate-distortion performance compared to traditional image compression standards. Nevertheless, existing approaches often struggle to simultaneously achieve high compression rates and high-quality reconstruction. To tackle this issue, we present an image compression and stable reconstruction method based on multi-level hybrid feature guidance. Firstly, a hybrid attention module that combines spatial, channel, and shuffle attention is designed to improve the model's ability to capture local features of the image. Secondly, we utilize boundary prediction and frequency domain feature prediction auxiliary branches to guide the network for image compression and reconstruction. Moreover, we propose an image compression and reconstruction algorithm framework based on multi-level feature guidance. Based on experimental results, our method surpasses existing approaches in achieving superior rate-distortion performance. These research results are of great significance to the further development of image compression and reconstruction technology. © 2023 IEEE.

关键词： Image compression

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DUAL ATTENTION-BASED MULTI-SCALE FEATURE FUSION APPROACH FOR DYNAMIC MUSIC EMOTION RECOGNITION 24

DUAL ATTENTION-BASED MULTI-SCALE FEATURE FUSION APPROACH FOR...

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24th International Society for Music Information Retrieval Conference, ISMIR 2023

作者： Zhang, Liyue Yang, Xinyu Zhang, Yichi Luo, Jing The School of Software Xi'An Jiaotong University China The School of Computer Science and Technology Xi'An Jiaotong University China

ISBN: (纸本)9781732729933

Music Emotion Recognition (MER) refers to automatically extracting emotional information from music and predicting its perceived emotions, and it has social and psychological applications. This paper proposes a Dual Attentionbased Multi-scale Feature Fusion (DAMFF) method and a newly developed dataset named MER1101 for Dynamic Music Emotion Recognition (DMER). Specifically, multi-scale features are first extracted from the log Mel-spectrogram by multiple parallel convolutional blocks. Then, a Dual Attention Feature Fusion (DAFF) module is utilized to achieve multi-scale context fusion and capture emotion-critical features in both spatial and channel dimensions. Finally, a BiLSTM-based sequence learning model is employed for dynamic music emotion prediction. To enrich existing music emotion datasets, we developed a high-quality dataset, MER1101, which has a balanced emotional distribution, covering over 10 genres, at least four languages, and more than a thousand song snippets. We demonstrate the effectiveness of our proposed DAMFF approach on both the developed MER1101 dataset, as well as on the established DEAM2015 dataset. Compared with other models, our model achieves a higher Consistency Correlation Coefficient (CCC), and has strong predictive power in arousal with comparable results in valence. © L. Zhang, X. Yang, Y. Zhang, J. Luo.

关键词： Emotion Recognition

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Metadata-P2T-Net: a skin lesion classification network integrating dermoscopic metadata and image data 4

Metadata-P2T-Net: a skin lesion classification network integ...

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4th International Conference on Image Processing and Intelligent Control, IPIC 2024

作者： Liu, Weili Wang, Jingli Wang, Bo Software School Xinjiang University Urumqi830091 China Artificial Intelligence Institute North China University of Science and Technology Tangshan063000 China

ISBN: (纸本)9781510682313

Early detection of skin cancer significantly improves the five-year survival rate for patients. However, early-stage malignant tumors exhibit very subtle lesions in the skin, making their symptoms less noticeable. Professional doctors require multiple biopsies and tissue extraction to diagnose the type of lesion. Existing machine learning methods struggle to focus simultaneously on spatial detail and metadata semantic features, resulting in lower recognition accuracy in skin lesion images. To effectively represent spatial and metadata features and prevent issues such as misclassification of easily distinguishable images due to an overemphasis on detail, a new skin lesion classification network called Metadata-P2T-Net has been proposed. This method uses a P2T-based visual backbone network and incorporates a Multi-Head Attention Feature Fusion Module (MHAFFM), enhancing the model's capability to model global context and dynamically weight visual features with metadata information, highlighting metadata-related visual regions. Additionally, a Multi-Dimensional Fusion Residual Module (MFRM) has been introduced, which effectively integrates visual, fusion, and metadata features to improve the model's classification performance. Experiments conducted on the ISIC2019 dataset show that the Metadata-P2T-Net achieved a Matthews correlation coefficient (MCC) of 0.9086, an accuracy of 93.69%, a precision of 93.89%, a recall of 86.77%, and an F1-Score of 90.18%. Compared with other methods, these metrics significantly improved, demonstrating the effective extraction of detailed and metadata features and providing a new basis for the diagnosis of dermatoscopic images. © 2024 SPIE.

关键词： Deep learning

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