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Provably Secure Authenticated Key-Management Mechanism for e-Healthcare Environment

IEEE Internet of Things Journal 2025年

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Ghaffar, Zahid Xie, Yong Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan Qinghai Institute of Technology School of Computer and Information Science China Qinghai Provincial Laboratory for Intelligent Computing and Application China Key Laboratory of Computing Power Network and Information Security Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security China Shandong Fundamental Research Center for Computer Science Jinan250353 China

The Internet of Things (IoT) is rapidly permeating all aspects of human life, involving a network of devices that share sensitive data. A notable application is the e-healthcare systems, which employ connected sensors, medical servers, and wearable devices. However, the public nature of communication in e-healthcare systems poses challenges such as security, privacy, and authentication of participating entities. Recently, many authentication protocols have been introduced to address these challenges. However, most of these protocols remain vulnerable to various security attacks, including device or medical server impersonation, denial of service, physical or cloning, and de-synchronization attacks. Therefore, we introduce an authenticated key-management protocol utilizing hash functions and Cipher-Block Chaining-Advanced Encryption Standard encryption (CBC-AES) encryption. The proposed protocol also employs the Physical Unclonable Function (PUF), which makes it more robust and efficient in resisting physical or cloning attacks. Additionally, the proposed scheme resists various security threats, including impersonation, session key leakage, ephemeral secret leakage, and de-synchronization attacks. We analyze the scheme’s security and reliability through formal and informal analysis. The informal analysis demonstrates that the scheme encompasses crucial security features, while the formal analysis substantiates. Moreover, performance analysis of the proposed protocol with various competing results indicates that our protocol achieves an average reduction in communication and computation overheads by 36.03.% and 41.79%, respectively. © 2014 IEEE.

关键词： Electronic health record

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Machine Learning Analysis for Temperature Classification using Bioelectric Potential of Plant 6

Machine Learning Analysis for Temperature Classification usi...

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6th International Conference on information Technology, information systems and Electrical engineering, ICITISEE 2022

作者： Tahyudin, Imam Akbar Awal Rozaq, Hasri Nambo, Hidetaka Amikom Purwokerto University Faculty of Computer Science Department of Information System Jl. Letjendpol Soemarto Purwanegara Banyumas53127 Indonesia Graduate School of Informatics Faculty of Computer Science Gazi University Yenimahalle Ankara Turkey Division of Electrical Engineering and Computer Science Graduate School of NST Kanazawa University Kakumamachi Ishikawa Kanazawa920-1192 Japan

ISBN: (纸本)9798350399615

Plants can respond to changes in their surroundings, such as temperature, humidity, and human behavior. This ability is due to photosynthesis and respiration in plants, resulting in low electrical signals. We focus on room temperature change by plant bioelectric potential detection. The temperature topic is interesting for the actual research because it is one of important factor in health aspect. This study aims to analysis of temperature of Bioelectric potential of plant using machine learning. This implementation identifies the plants' bioelectric potential in distinguishing three-room temperature categories: A, B, and C temperature. We conducted the experimental in room control. For the transformation process is using wavelet transform. Furthermore, the analysis process, we used the Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighborhood (K-NN), Naïve Bayes, and linear regression. Then, for the evaluation is using confusion Matrix. The result showed that the best level of transformation using Wavelet is 7thlevel for reducing the noise. Furthermore, the best accuracy of analysis process is using Decision tree which obtained 75%. © 2022 IEEE.

关键词： Bioelectric Electric Potential of Plant Machine Learning Temperature Wavelet Transform

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Major strategies for improving the performance of perovskite solar cells

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iEnergy 2023年第3期2卷 172-199页

作者： Lixiu Zhang Hang Li Kai Zhang Wenzhe Li Chuantian Zuo George Omololu Odunmbaku Jingde Chen Cong Chen Luozheng Zhang Ru Li Yuping Gao Baomin Xu Jiangzhao Chen Yongsheng Liu Yang Wang Yanlin Song Jianxin Tang Feng Gao Qing Zhao Yong Peng Mingzhen Liu Lei Tao Yuelong Li Zhimin Fang Ming Cheng Kuan Sun Dewei Zhao Yixin Zhao Shihe Yang Chenyi Yi Liming Ding Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing 100190China State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Shenzhen Graduate School Peking UniversityShenzhen 518055China School of Environmental Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China College of Materials Science and Engineering&Engineering Research Center of Alternative Energy Materials&Devices Sichuan UniversityChengdu 610065China School of Energy&Power Engineer-ing Chongqing UniversityChongqing 400044China Institute for Energy Research Jiangsu UniversityZhenjiang 212013China Institute of New Energy Technology Department of Electronic EngineeringCollege of Information Science and TechnologyJinan UniversityGuangzhou 510631China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow UniversitySuzhou 215123China Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055China College of Optoelectronic Engineering Chongqing UniversityChongqing 400044China College of Chemistry Nankai UniversityTianjin 300071China Institute of Chemistry Chinese Academy of SciencesBeijing 100190China State Key Lab for Mesoscopic Physics and Frontiers Science Center for Nano-optoelec-tronics School of PhysicsPeking UniversityBeijing 100871China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 611731China Institute of Photoelectronic Thin Film Devices and Technology Nankai UniversityTianjin 300350China School of Materials Science and Engineering Shaanxi Normal UniversityXi’an 710119China

Metal halide perovskite solar cell(PSC)has successfully distinguished itself in optoelectronic field by virtue of the sharp rise in power conversion efficiency over the past *** remarkable efficiency breakthrough at such a fast speed can be mainly attributed to the comprehensive study on film deposition techniques,especially the effective management of surface and interfacial defects in recent ***,we summarized the current trends in performance enhancement for PSCs,with a focus on the generally applicable strategies in high-performance works,involving deposition methods,compositional engineering,additive engineering,crystallization manipulation,charge transport material selection,interfacial passivation,optical coupling effect and constructing tandem solar *** directions and perspectives are also provided.

关键词： Perovskite solar cells efficiency improvement strategies milestones

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XoT (Xducation of Things): Harnessing AI and edge computing to educate all things

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IEEE Access 2024年

作者： Nurtantyana, Rio Hwang, Wu-Yuin Hariyanti, Uun Research Center for Data and Information Sciences Bandung Indonesia Telkom University School of Computing Indonesia Telkom University Center of Excellence Artificial Intelligence for Learning and Optimization Bandung Indonesia National Dong Hwa University College of Science and Engineering Department of Computer Science and Information Engineering Taiwan National Central University Graduate Institute of Network Learning Technology Taiwan Universitas Brawijaya Faculty of Computer Science Department of Information System Indonesia

Most English foreign language (EFL) studies focus solely on human beings. This research explores how edge computing can facilitate learning for all things. The XoT (Xducation of Things) framework was proposed to educate both human and all things. All things encompass two terms: AI-Agent and smartthings (covering physical and digital smart objects). At the core of this framework is Smart Question Answer Forwarding Mechanism (SQA-Forwarding), specifically designed to assist all things in building knowledge. To demonstrate this, the smartXoT environment was developed based on XoT framework, and its impacts on EFL learners was assessed. A quasi-experimental study involving 26 EFL learners, divided into an experimental group (EG) and a control group (CG), examined the differences in learning achievement of smartthings and EFL learners when using the smartXoT environment with/without SQA-Forwarding. Findings, on one hand, indicated that smartthings in the EG developed knowledge bases greater than those in the CG. On the other hand, the interaction between EFL learners and smartthings with SQA-Forwarding significantly improved learners' writing skills, with revisions playing a crucial role in enhancing writing quality. Thus, the XoT framework offers a novel and promising approach to educating both humans and all things. © 2013 IEEE.

关键词： Contrastive Learning

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The effect of extended kit-build concept mapping on students' perceptions 7

The effect of extended kit-build concept mapping on students...

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7th International Conference on Education and Technology, ICET 2021

作者： Prasetya, Didik Dwi Pinandito, Aryo Hayashi, Yusuke Hirashima, Tsukasa Universitas Negeri Malang Dept. of Electrical Engineering Malang Indonesia Universitas Brawijaya Faculty of Computer Science Information System Department Malang Indonesia Graduate School of Engineering Hiroshima University Dept. of Information Engineering Higashihiroshima Japan

ISBN: (纸本)9781665427814

Extension concept mapping is a technique to connect prior existing concept maps with a relevant new knowledge structure. It provides learners with the opportunity to review initial ideas, eliciting missing relationships, adding new components, and improve knowledge structure. While the current study proposed that the Extended Kit-Build design promotes students' achievements, it has yet to evaluate the students' perception. This study investigated the effects of Extended Kit-Build concept mapping design on students' perceptions using the Technology Acceptance Model. The perceived ease-of-use, perceived usefulness, and Behavioral Intention constructs were used to investigate users' intention to use the Extended Kit-Build tool in learning. The results reported that the learners perceived positive effects on Extended Kit-Build as ease of use and a useful learning tool. They also have a high intention to use the tool in the future. © 2021 IEEE.

关键词： Students

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Ubi-Care: An Elderly Life Support Healthcare Framework Based on Ubiquitous Personal Online Data Stores

Ubi-Care: An Elderly Life Support Healthcare Framework Based...

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IEEE International Conference on systems, Man and Cybernetics

作者： Hong Chen Tao Zhou Bo Wu Graduate School of Human Sciences Waseda University Saitama Japan Department of Information and Electronics System Engineering Daiichi Institute of Technology Taito Tokyo Japan School of Computer Science Tokyo University of Technology Hachioji Tokyo Japan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In recent years, the global aging population has intensified, leading to a sharp increase in social security benefits and caregiving costs. The elderly face greater health risks, and their behaviors often indicate signs of crises and illnesses. The rapid development of IoT technology offers new solutions for detecting abnormal signs, thereby promoting healthy aging, independent living, and social participation for the elderly. However, the diversity of IoT devices has led to the phenomenon of personal data silos. When the elderly leave their usual IoT environment, the issue of continuity in healthcare services becomes more pronounced. To address this issue, this study proposes a decentralized Ubi-Care framework. The framework aims to achieve complete separation of data and applications. It is based on the ActivityPub protocol and integrates various data from wearable devices, smart home sensors, and social networks, storing this data in a ubiquitous personal online data store (UPOD) and assigning different roles based on data type. UPOD applications support bidirectional following, allowing users to access data associated with relevant roles, addressing issues related to data categorization, sharing, privacy, and security. Additionally, this study proposes a method for utilizing complete UPOD data to perform anomaly detection based on the hidden Markov model (HMM). By effectively integrating IoT data into UPOD and enhancing data interoperability. The data-sharing model proposed in this study also facilitates elderly individuals and their family members in sharing relevant data as needed, while ensuring privacy protection. The methods proposed in this study will help prevent accidental injuries and enable early diagnosis of diseases, providing strong technical support for elderly healthcare.

关键词： Data privacy Cloud computing Hidden Markov models Prototypes Aging Data models Internet of Things Security Older adults Medical diagnostic imaging

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Computer Vision in Smart City Application: A Mapping Review

Computer Vision in Smart City Application: A Mapping Review

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Applied Computational Intelligence in information systems (ACIIS), International Conference on

作者： Aulia Akhrian Syahidi Kiyoshi Kiyokawa Fumio Okura Department of Electrical Engineering Smart City Information System Politeknik Negeri Banjarmasin Banjarmasin Indonesia Division of Information Science Nara Institute of Science and Technology Ikoma Nara Japan Graduate School of Information Science and Technology Osaka University Suita Osaka Japan

Research interest in the application of Computer Vision (CV) in the context of smart cities has grown significantly in recent years. However, finding relevant studies in databases can be challenging due to the use of non-explicit or varying terms. To address this issue, this research aims to conduct a literature review by collecting papers that discuss the application of CV for smart city needs. The method used is a mapping review, with the following stages: 1) Establishing research questions; 2) Selecting relevant reference sources based on relevant databases; 3) Identifying appropriate keywords; 4) Conducting screening based on criteria; and 5) Extracting and synthesizing relevant data. For this research, we selected a total of 35 papers as the primary review. Our findings show that research trends and interests vary widely, with the most prevalent being in smart mobility components, which on average come from the IEEE Xplore Digital Library database. YOLO and CNN algorithms are also widely used to solve problems. Furthermore, we conclude that there are many benefits to be gained from the application of this technology to support the sustainable development of smart cities, including ensuring the quality of life of their inhabitants.

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RadonPy:automated physical property calculation using all-atom classical molecular dynamics simulations for polymer informatics

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npj Computational Materials 2022年第1期8卷 2155-2169页

作者： Yoshihiro Hayashi Junichiro Shiomi Junko Morikawa Ryo Yoshida The Institute of Statistical Mathematics(ISM) Research Organization of Information and Systems10-3 Midori-choTachikawaTokyo190-8562Japan Department of Mechanical Engineering The University of Tokyo7-3-1 HongoBunkyoTokyo113-8656Japan Institute of Engineering Innovation The University of Tokyo2-11 YayoiBunkyo-kuTokyo113-0032Japan Department of Materials Science and Engineering School of Materials and Chemical TechnologyTokyo Institute of Technology2-12-1 OokayamaMeguro-kuTokyo152-8552Japan Research and Services Division of Materials Data and Integrated System(MaDIS) National Institute for Materials Science(NIMS)1-2-1 SengenTsukubaIbaraki305-0047Japan Department of Statistical Science School of Multidisciplinary ScienceThe Graduate University of Advanced Studies(SOKENDAI)10-3 Midori-choTachikawaTokyo190-8562Japan

The spread of data-driven materials research has increased the need for systematically designed materials property ***,the development of polymer databases has lagged far behind other material *** present RadonPy,an open-source library that can automate the complete process of all-atom classical molecular dynamics(MD)simulations applicable to a wide variety of polymeric ***,15 different properties were calculated for more than 1000 amorphous *** MD-calculated properties were systematically compared with experimental data to validate the calculation conditions;the bias and variance in the MD-calculated properties were successfully calibrated by a machine learning *** the high-throughput data production,we identified eight amorphous polymers with extremely high thermal conductivity(>0.4 W∙m^(–1)∙K^(–1))and their underlying *** to the advancement of materials informatics since the advent of computational property databases for inorganic crystals,database construction using RadonPy will promote the development of polymer informatics.

关键词： property calculation dynamics

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Self-supervised Learning Method for Behavior Prediction during Dialogue Based on Temporal Consistency

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Transactions of the Japanese Society for Artificial Intelligence 2022年第6期37卷

作者： Okadome, Yuya Ata, Kenshiro Ishiguro, Hiroshi Nakamura, Yutaka RIKEN Information R&D and Strategy Headquarters RIKEN Japan Department of System Innovation Graduate School of Engineering Science Osaka University Japan

Developing a communication agent that can mutually interact with a human has been expected. To realize the agent, real-time situation recognition and motion generation are necessary. The human-human interaction data is utilized to develop the recognition and the generation model. However, a cost of giving a certain label to the data is expensive, i.e., the number of labeled data becomes small. To cope with the small dataset problem, one of the approaches is to obtain the pre-trained weight by self-supervised learning. In this research, we propose estimating the amount of time-shift by "lag operation" as a task for self-supervised learning. The observed data is not isolated during the interaction between two people, and using both observed information from two people makes an estimation model reduce the uncertainty of situation detection. By exploiting these properties of interaction data, the time index of data of one person is shifted, i.e., the entrainment of two data is broken. This operation is called a "lag operation", and estimating the amount of time-shift is defined as the pre-training task. We apply this pre-training to the prediction experiment that estimates near-future laughing during a conversation. The result shows the accuracy of the laughing prediction is improved by 1.3 points, and the lag operation is an effect for predicting the change of interaction situation. © 2022, Japanese Society for Artificial Intelligence. All rights reserved.

关键词： Supervised learning

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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Robotics, engineering, science, and Technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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