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Efficient Expressive Attribute-Based Encryption with Keyword Search over Prime-Order Groups

Intelligent Automation & Soft Computing 2023年第3期35卷 2737-2754页

作者： Qing Miao Lan Guo Yang Lu Zhongqi Wang School of Computer and Electronic Information Nanjing Normal UniversityNanjing210046China Graduate School of Science and Technology University of Tsukuba TsukubaIbaraki305-8577Japan

Attribute-based encryption with keyword search(ABEKS)is a novel cryptographic paradigm that can be used to implementﬁne-grained access control and retrieve ciphertexts without disclosing the sensitive *** is a perfect combination of attribute-based encryption(ABE)and public key encryption with keyword search(PEKS).Nevertheless,most of the existing ABEKS schemes have limited search capabilities and only support single or simple conjunctive keyword *** to the weak search capability and inaccurate search results,it is difﬁcult to apply these schemes to practical *** this paper,an efﬁ-cient expressive ABEKS(EABEKS)scheme supporting unbounded keyword uni-verse over prime-order groups is designed,which supplies the expressive keyword search function supporting the logical connectives of“AND”and“OR”.The proposed scheme not only leads to low computation and communica-tion costs,but also supports unbounded keyword *** the standard model,the scheme is proven to be secure under the chosen keyword attack and the cho-sen plaintext *** comparison analysis and experimental results show that it has better performance than the existing EABEKS schemes in the storage,com-putation and communication costs.

关键词： Searchable encryption expressive keyword search attribute-based encryption unbounded keyword universe prime-order group

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Posture Prediction in Response to Seat Angle Change with Smart Chair

Posture Prediction in Response to Seat Angle Change with Sma...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Esumi, Tsubasa Takemura, Noriko Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Department of Artificial Intelligence Fukuoka Japan

ISBN: (纸本)9781665410205

Long-term desk work with lousy posture causes physical disabilities. To solve this problem, we have developed a smart chair with a controllable seat angle in our previous research. In order to control the seat angle and guide the user to the correct posture using this smart chair, it is necessary to investigate how the posture changes in response to the seat angle change. In this study, we first constructed a dataset by capturing posture data from 30 subjects while changing the seat angle of the smart chair. This dataset trained a model based on a graph neural network to predict posture in response to seat angle changes. We compared the model's prediction performance in the evaluation experiment depending on the training data and the body part. © 2024 IEEE.

关键词： Graph neural networks

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Right Coprime Factorization for Nonlinear System with Uncertainty Based on Time-Varying Bezout Identity

Right Coprime Factorization for Nonlinear System with Uncert...

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2024 International Conference on Advanced Mechatronic Systems, ICAMechS 2024

作者： An, Zizhen Deng, Mingcong Tokyo University of Agriculture and Technology Graduate School of Engineering Department of Electrical Engineering and Computer Science Tokyo Japan

ISBN: (纸本)9798350366204

In this note, a new structure of Right Coprime Factorization (RCF) for nonlinear systems with uncertainty has been proposed based on a time-varying Bezout identity. This is inspired from the concept of dilation from homogeneous theory. However, this time-varying dilation in right coprime factorized uncertain nonlinear systems is not limited to homogeneous plants but is integrated into Bezout identity so as to ensure the bounded input bounded output (BIBO) stability of uncertain systems. Additionally, simulation results of two numerical examples are exhibited to validate the proposition. © 2024 IEEE.

关键词： Nonlinear simulations

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Multimodal attention-driven visual question answering for Malayalam

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Neural Computing and Applications 2024年第24期36卷 14691-14708页

作者： Kovath, Abhishek Gopinath Nayyar, Anand Sikha, O.K. Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham Coimbatore India Graduate School Faculty of Information Technology Duy Tan University Da Nang550000 Viet Nam

Visual question answering is a challenging task that necessitates for sophisticated reasoning over the visual elements to provide an accurate answer to a question. Majority of the state-of-the-art VQA models are only applicable to English questions. However, applications such as visual assistance and tourism necessitate the incorporation of multilingual VQA systems. This paper presents an effective deep learning framework for Malayalam visual question answering (MVQA), which can answer a specific natural language question about an image in Malayalam. As there is no available dataset in English–Malayalam VQA, a MVQA dataset was created by translating English question–answer pairs from the visual genome dataset. The paper proposes an attention-driven MVQA model on the developed dataset. The proposed MVQA model uses a deep learning-based co-attention mechanism to jointly learn the attention for images and Malayalam questions. A second-order multimodal factorized high-order pooling is used for multi modal feature fusion. Different VQA models using combinations of classical CNNs and RNNs were experimented on the developed MVQA dataset, and the performance was compared against the proposed attention-driven model. Experimental results show that the proposed attention-driven MVQA model achieves state-of-the-art results as compared to other models for MVQA on the custom Malayalam VQA dataset. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Deep learning

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Lightweight Authenticated Key Agreement Protocol for Smart Power Grid Systems Using PUF

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 IEEE.

关键词： Hash functions

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Multi-dimensional ability diagnosis for machine learning algorithms

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science China(Information sciences) 2024年第12期67卷 321-322页

作者： Qi LIU Zheng GONG Zhenya HUANG Chuanren LIU Hengshu ZHU Zhi LI Enhong CHEN Hui XIONG State Key Laboratory of Cognitive Intelligence University of Science and Technology of China Business Analytics and Statistics The University of Tennessee Computer Network Information Center Chinese Academy of Sciences Shenzhen International Graduate School Tsinghua University Hong Kong University of Science and Technology (Guangzhou)

A significant proportion of noticeable improvement in machine learning architectures actually benefits from the consistent inspiration of the way human learning [1]. For instance, curriculum learning [2] is inspired by highly organized human education systems, i.e., training the algorithms with easy samples first and gradually transforming to the hard examples can contribute to faster convergence and lower generalization error.

关键词： Adversarial machine learning

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MESH-POLYPDET: SURFACE MESHES BASED POLYP DETECTION IN VIRTUAL COLONOSCOPY 18

MESH-POLYPDET: SURFACE MESHES BASED POLYP DETECTION IN VIRTU...

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18th International Conference on Interfaces and Human computer Interaction 2024, IHCI 2024, the 17th International Conference on Game and Entertainment Technologies 2024, GET 2024 and the 18th International Conference on computer Graphics, Visualization, computer Vision and Image Processing 2024, CGVCVIP 2024, Part of the 18th Multi Conference on computer science and Information Systems 2024, MCCSIS 2024

作者： Ma, Ming Sun, Chenyang Lei, Na Department of Graduate Computer Science and Engineering Katz School of Science and Health Yeshiva University United States School of Software Technology Dalian University of Technology China International School of Information Science & Engineering Dalian University of Technology China

ISBN: (纸本)9789898704580

Colorectal polyps can evolve into colon cancer over time. Early screening or detection of colon polyps using computer-aided detection (CAD) techniques along with removal of the polyps can lower the risk of colon cancer. As an alternative to optimal colonoscopy (OC), virtual colonoscopy (VC) has the advantage of non-invasiveness in the detection of colon polyps. Recent decades have witnessed rapid advancement in VC based polyp detection and false positive (FP) reduction techniques using machine learning or deep learning methods. However, the majority of existing methods are based on the computation using computed tomography (CT) images of patient data, which are in some cases very computationally expensive, particularly in the scenario of necessity of large dataset for model training. In this paper, we propose a novel automatic polyp detection method termed Mesh-PolypDet using the surface meshes of colorectal data. The initial detection of polyp candidates is performed on 3D colon surface meshes, and the subsequent FP reduction is carried out using the visual transformer and conformal mapping. Experiments are conducted to evaluate the performance of the proposed method in comparison with other existing methods. © 2024 Interfaces and Human computer Interaction. All Rights Reserved.

关键词： Conformal mapping

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Understanding the Definitions of Microcredentials in Higher Education: Systematic Literature Review

Understanding the Definitions of Microcredentials in Higher ...

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2024 International Conference on TVET Excellence and Development, ICTeD 2024

作者： Wihendro Warnars, Harco Leslie Hendric Spits Prabowo, Harjanto Sfenrianto Bina Nusantara University BINUS Graduate Program- Computer Science Information Systems Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program- Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Business School Undergraduate Program Management Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta Indonesia

ISBN: (纸本)9798331516413

The growing focus on microcredentials emphasizes the urgent need for precise and widely accepted definitions, as existing uncertainties hinder their effective implementation. This research aims to investigate the comprehension of microcredentials definitions in the context of higher education by conducting a systematic literature review. The goal is to identify current definitions of microcredentials to facilitate standardization initiatives. Following The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to systematically search in Scopus database within 2019-2024 resulting 940 articles, by removing the duplicates, 280 articles were initially reviewed, with 29 selected for detailed thematic analysis based on specific inclusion and exclusion criteria. By adapting the six phases of thematic analysis, selected articles were identified analyzed, organized, described, and themes found the data set were reported. Key findings reveal that, while a universally accepted definition is lacking, common themes emerge: microcredentials are competency-based, modular, portable, stackable, and often include quality assurance. These attributes highlight microcredentials as valuable for upskilling and reskilling in a flexible manner. The study concludes that establishing standard definitions can increase the recognition and utility of microcredentials across educational and professional sectors and recommends further research to strengthen core elements for consistency. © 2024 IEEE.

关键词： Competency-based Higher Education Microcredentials Modular Reskilling Upskilling

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Design of Household Robotic Arm System to sort Recyclable Resources based on Deep Learning

Design of Household Robotic Arm System to sort Recyclable Re...

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2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber science and technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Guo, Yuning Kameda, Hiroyuki Wu, Bo Graduate School of Bionics Computer and Media Tokyo University of Technology Tokyo Japan School of Computer Science Tokyo University of Technology Tokyo Japan

ISBN: (纸本)9798350304602

As society progresses and living conditions enhance, global domestic waste generation has witnessed a significant surge., and the problem of domestic waste separation has attracted more and more attention from the viewpoint of creating a circular economy (CE) society. Advances in machine learning and robotics offer a promising solution to this problem. Particularly, the intricacies of waste classification at the household level result in high misclassification rates, leading to inefficient waste management and recycling. Our research focuses on utilizing deep learning and robotic technologies to mitigate these issues. In this paper, we aim to design a domestic waste resource classification system built on the YOLOv5 algorithm and a household robotic arm. By integrating computer vision and machine learning with the YOLOv5 target detection algorithm and precise robotic arm operations, the system can automatically identify, classify, and sort different types of waste resources. The critical challenges that the system effectively addresses include reducing manual intervention, minimizing time consumption, and improving the accuracy of household recycling classification, while promoting the development of environmental awareness. To effectively reduce manual intervention, decrease time consumption, and enhance the accuracy of household waste classification, our main contribution is the development of an integrated system for more efficient household waste resource management. © 2023 IEEE.

关键词： Robotic arms

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A Systematic Literature Review: Object Detection in Semi-Autonomous Car 6

A Systematic Literature Review: Object Detection in Semi-Aut...

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6th International Conference on computer and Informatics Engineering, IC2IE 2023

作者： Sunjaya, Eric Kurniadi Daniel, Christian Kurniawan, Afdhal Anggreainy, Maria Susan School of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350345162

Traffic accidents are a serious problem in developing countries. These accidents can be caused by poor infrastructure and the arrogance of drivers. In addition, semi-autonomous systems are automotive technologies that have been developed in recent years and are starting to be implemented in existing vehicles. This literature review paper will mainly discuss how object detection works in semi-autonomous systems, how semi-autonomous systems operate, and whether semi-autonomous cars can reduce the number of traffic accidents. Its main objective is to build driver confidence in semi-autonomous systems by assisting in driving and supporting the development of them. In the process of writing this paper, the method we use follows the guidelines stated in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). © 2023 IEEE.

关键词： neural network object detection semi-autonomous car semi-autonomous system

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