检索结果-内蒙古大学图书馆

A survey on blockchain-based integrity auditing for cloud data

Digital Communications and Networks 2022年第5期8卷 591-603页

作者： Haoxiang Han Shufan Fei Zheng Yan Xiaokang Zhou The State Key Lab of ISN School of Cyber EngineeringXidian University266 Xinglong Section of Xifeng RoadXi'anShaanxi710126China The Faculty of Data Science Shiga UniversityHikone522-8522Japan The RIKEN Center for Advanced Intelligence Project RIKENTokyo103-0027Japan

With the rapid advancement of cloud computing,cloud storage services have developed *** issue that has attracted particular attention in such remote storage services is that cloud storage servers are not enough to reliably save and maintain data,which greatly affects users’confidence in purchasing and consuming cloud storage *** data integrity auditing techniques for cloud data storage are centralized,which faces huge security risks due to single-point-of-failure and vulnerabilities of central auditing *** technology offers a new approach to this *** researchers have endeavored to employ the blockchain for data integrity *** on the search of relevant papers,we found that existing literature lacks a thorough survey of blockchain-based integrity auditing for cloud *** this paper,we make an in-depth survey on cloud data integrity auditing based on ***,we cover essential basic knowledge of integrity auditing for cloud data and blockchain ***,we propose a series of requirements for evaluating existing Blockchain-based Data Integrity Auditing(BDIA)***,we provide a comprehensive review of existing BDIA schemes and evaluate them based on our proposed ***,according to our completed review and analysis,we explore some open issues and suggest research directions worthy of further efforts in the future.

关键词： Blockchain Cloud storage Integrity auditing Decentralization

来源：评论

学校读者我要写书评

暂无评论

Design of an SSVEP-Based Brain-Controlled Robotic Arm Car System

Design of an SSVEP-Based Brain-Controlled Robotic Arm Car Sy...

引用

Computer Systems (ICCS), IEEE International Conference on

作者： Xin Ma Jinsha Liu Ruixuan Chen Boning Li Jianting Cao Graduate School of Engineering Saitama Institute of Technology Saitama Japan RIKEN Center for Advanced Intelligence Project (AIP) Graduate School of Engineering Saitama Institute of Technology Saitama Japan

ISBN: (数字)9798350366341

ISBN: (纸本)9798350366358

A brain-computer interface (BCI) is a technology that controls external devices through brain signals, helping disabled individuals regain the ability to communicate with the outside world. This technology has significant implications in medical rehabilitation and neuroscience. Our system employs a steady-state visual evoked potential (SSVEP)-based BCI, converting brain signals into control signals to operate a robotic arm car. This study aims to enhance the system's accuracy by changing the type of stimulator, introducing EEG data preprocessing, and using the task-related component analysis (TRCA) algorithm. Experimental results show that using LED visual stimulators, incorporating preprocessing steps, and adopting the TRCA algorithm instead of the traditional canonical correlation analysis (CCA) algorithm positively impact the system's accuracy.

关键词： Visualization Accuracy Neuroscience Correlation Data preprocessing Manipulators Light emitting diodes Electroencephalography Steady-state Automobiles

来源：评论

学校读者我要写书评

暂无评论

Smart industrial IoT empowered crowd sensing for safety monitoring in coal mine

引用

Digital Communications and Networks 2023年第2期9卷 296-305页

作者： Jing Zhang Qichen Yan Xiaogang Zhu Keping Yu Department of Computer Science and Technology Xi'an University of Science and TechnologyXi'an710054China Department of Information Science and Technology Northwest UniversityXi’an 710127China School of Public Policy and Administration Nanchang UniversityNanchangJiangxi330031China Graduate School of Science and Engineering Hosei UniversityTokyo184-8584Japan RIKEN Center for Advanced Intelligence Project RIKENTokyo103-0027Japan

The crowd sensing technology can realize the sensing and computing of people,machines,and environment in smart industrial IoT-based coal mine,which provides a solution for safety monitoring through distributed intelligence ***,due to the difficulty of neural network training to achieve global optimality and the fact that traditional LSTM methods do not consider the relationship between adjacent machines,the accuracy of human body position prediction and pressure value prediction is not *** solve these problems,this paper proposes a smart industrial IoT empowered crowd sensing for safety monitoring in coal ***,we propose a Particle Swarm Optimization-Elman Neural Network(PE)algorithm for the mobile human position ***,we propose an ADI-LSTM neural network prediction algorithm for pressure values of machines supports in underground *** them,our proposed PE algorithm has the lowest average cumulative prediction error,and the trajectory fit rate is improved by 24.1%,13.9%and 8.7%compared with Kalman filtering,Elman and Kalman plus Elman algorithms,***,compared with single-input ARIMA,RNN,LSTM,and GRU,the RMSE values of our proposed ADI-LSTM are reduced by 36.6%,52%,32%,and 13.7%,respectively;and the MAPE values are reduced by 0.0003%,0.9482%,1.1844%,and 0.3620%,respectively.

关键词： Crowd sensing Industrial Internet of things Safety monitoring Coal mine

来源：评论

学校读者我要写书评

暂无评论

Generating Conversation Opportunity for Elderly People Integrating Agent and Conferencing Service 5

Generating Conversation Opportunity for Elderly People Integ...

引用

5th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2023

作者： Okamoto, Hiro Chen, Sinan Nakamura, Masahide Saiki, Sachio Graduate School of Engineering Kobe University Faculty of Engineering 1-1 Rokkodai-cho Kobe Nada657-8501 Japan Riken Center for Advanced Intelligence Project Tokyo103-0027 Japan School of Data and Innovation Kochi University of Technology 185 Miyanokuchi Tosayamada Kami Kochi782-8502 Japan

ISBN: (纸本)9798350304152

The increase in single-person households and the onset of 'COVID-19 frailty' due to COVID-19 have become problems. Our research group focuses on technology support and develops virtual agents using speech recognition technology. In this service, we examined how to promote self-care by having the agent listen to the older person and increase conversation opportunities. However, this service has the problem that it cannot increase opportunities for dialogue with family and friends, which leads to mutual support. In this study, we aim to propose and implement a service called 'Easy Video Chat Service' that increases the opportunities for conversation with others through a virtual agent listening service for the elderly person at home. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Proposal an Automated Management Service for Hybrid Meeting Spaces Using Uni-Messe and IoT 5

Proposal an Automated Management Service for Hybrid Meeting ...

引用

5th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2023

作者： Yoshida, Takeshi Chen, Sinan Nakamura, Masahide Saiki, Sachio Graduate School of Engineering Kobe University Faculty of Engineering 1-1 Rokkodai-cho Kobe Nada657-8501 Japan Riken Center for Advanced Intelligence Project Tokyo103-0027 Japan School of Data and Innovation Kochi University of Technology 185 Miyanokuchi Tosayamada Kami Kochi782-8502 Japan

ISBN: (纸本)9798350304152

In recent years, Japan has been actively promoting the concept of a super-smart society, which aims to leverage various scientific technologies to address societal challenges spanning environmental issues, energy management, and disaster preparedness. Within this context, our focus lies on harnessing the potential of Internet of Things (IoT) devices to playa pivotal role in advancing these objectives. The purpose of this paper is to propose an innovative service that streamlines the automatic management of hybrid conferences. To achieve this, we introduce a service coordination platform that leverages the Unified Rule- Based Message Delivery Service (Uni-messe). Our proposed approach involves the initial implementation of a simplified service version, followed by a case study specifically tailored to the conference setting. Throughout our study, we identified two key areas that require further improvement. Firstly, delays arising from communication between devices during the implementation process need to be addressed. Secondly, there is a limitation in operating devices that do not support infrared functionality. In conclusion, our research contributes to advancing super-smart society initiatives by presenting a novel and promising avenue for automating hybrid conferences using IoT and the Uni-messe service coordination platform. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Long - Term Forecast of Emergency Demand Using EMS Big Data and Population Estimates by Age 5

Long - Term Forecast of Emergency Demand Using EMS Big Data ...

引用

5th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2023

作者： Kaneda, Masaki Chen, Sinan Nakamura, Masahide Saiki, Sachio Graduate School of Engineering Kobe University Faculty of Engineering 1-1 Rokkodai-cho Kobe Nada657-8501 Japan Riken Center for Advanced Intelligence Project Tokyo103-0027 Japan School of Data and Innovation Kochi University of Technology 185 Miyanokuchi Tosayamada Kami Kochi782-8502 Japan

ISBN: (纸本)9798350304152

In recent years, Japan has been facing a super- aging society. The problems of tight emergency medical care and an increase in the number of emergency medical transports have become ¶uite serious. In response to this situation, our research group has been conducting joint research with the Kobe City Fire Department. This study aims to propose and establish a method for medium to long-term prediction of the number of emergency medical transports and to provide an indicator for the strategic deployment of Emergency Medical Services (EMS) and the expansion and contraction of the scale of medical services in the field. This medium to long-term prediction of the number of ambulance transports is achieved by analyzing big data, population data, and future population estimates in each region without machine learning. The proposed method was evaluated in Kobe City, Japan. The results showed that the predicted number of transports is reasonable based on the actual number of transports in the past. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Human–AI collaboration for modeling heat conduction in nanostructures

引用

npj Computational Materials 2025年第1期11卷 1-11页

作者： Ding, Wenyang Guo, Jiang An, Meng Tsuda, Koji Shiomi, Junichiro Department of Mechanical Engineering The University of Tokyo Tokyo Japan Department of Computational Biology and Medical Science The University of Tokyo Tokyo Japan Institute of Engineering Innovation The University of Tokyo Tokyo Japan RIKEN Center for Advanced Intelligence Project Chuo City Japan

Materials informatics, which combines data science and artificial intelligence (AI), has garnered significant attention owing to its ability to accelerate material development. However, human involvement is often limited to the initiation and oversight of machine learning processes and rarely includes roles that capitalize on human intuition or domain expertise. In this study, taking the problem of heat conduction in a two-dimensional nanostructure as a case study, an integrated human-AI collaboration framework is designed and used to construct a model to predict the thermal conductivity. This approach is used to determine the parameters that govern phonon transmission over frequencies and incidence angles. The self-learning entropic population annealing technique, which combines entropic sampling with a surrogate machine learning model, generates a global dataset that can be interpreted by a human. This allows humans to develop parameters with physical interpretations, which can guide nanostructural design for specific properties. © The Author(s) 2025.

关键词： Self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Fluid Actuators Using Surface Acoustic Waves and Their Applications

引用

Journal of Japan Institute of Electronics Packaging 2024年第4期27卷 325-333页

作者： Tsunemasa, Saiki Yuichi, Utsumi Project Management Department Hyogo Prefectural Institute of Technology 3-1-12 Yukihira-cho Suma-ku Hyogo Kobe654-0037 Japan Graduate School of Engineering University of Hyogo 2167 Shosha Hyogo Himeji671-2280 Japan Laboratory of Advanced Science and Technology for Industry University of Hyogo 3-1-2 Koto Kamigori-cho Hyogo Ako-gun678-1205 Japan

来源：评论

学校读者我要写书评

暂无评论

Human-AI collaboration for modeling heat conduction in nanostructures

arXiv

引用

arXiv 2025年

作者： Ding, Wenyang Guo, Jiang An, Meng Tsuda, Koji Shiomi, Junichiro Department of Mechanical Engineering The University of Tokyo Japan Institute of Engineering Innovation The University of Tokyo Japan Department of Computational Biology and Medical Science The University of Tokyo Japan RIKEN Center for Advanced Intelligence Project Japan

In recent years, materials informatics, which combines data science and artificial intelligence (AI), has garnered significant attention owing to its ability to accelerate material development, reduce costs, and enhance product design. However, despite the widespread use of AI, human involvement is often limited to the initiation and oversight of machine learning processes and rarely includes more substantial roles that capitalize on human intuition or domain expertise. Consequently, true human-AI collaborations, where integrated insights can be maximized, are scarce. This study considers the problem of heat conduction in a two-dimensional nanostructure as a case study. An integrated human-AI collaboration framework is designed and used to construct a model to predict the thermal conductivity. This approach is used to determine the parameters that govern phonon transmission over the full range of frequencies and incidence angles. During operation, the self-learning entropic population annealing technique, which combines entropic sampling with a surrogate machine learning model, generates a small dataset that can be interpreted by a human. Therefore, data-efficient and global modeling is achieved, and parameters with physical interpretations are developed, which can guide nanostructural design to produce materials with specific properties. The proposed framework can leverage the complementary strengths of humans and AI, thereby enhancing the understanding and control of materials. Copyright © 2025, The Authors. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Novel Gold Futures Price Prediction Model based on PCA-AGRU 29

A Novel Gold Futures Price Prediction Model based on PCA-AGR...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Wang, Jingyang Lu, Tong Liu, Jindian Sun, Qiuhong Qi, Lianyong Zhou, Xiaokang Hebei University of Science and Technology School of Information Science and Engineering Shijiazhuang China Shiga University Faculty of Data Science Hikone522-8522 Japan Qingdao China RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan

ISBN: (纸本)9798350330717

As an important financial investment commodity, the price fluctuations of gold significantly impact the global economy and the stability of the financial market. Therefore, it is of great significance to accurately predict the price of gold futures. This paper presents a novel gold futures price prediction model, PCA-AGRU, based on Principal Component Analysis (PCA) and Adaptive Gated Recurrent Unit (AGRU). PCA is utilized for the dimensionality reduction of data while extracting essential features. AGRU bases on Gated Recurrent Unit (GRU), embeds Self-Attention (SA), and adds an adaptive adjustment mechanism, making the model more effective in capturing long-term dependencies within time series data. This paper uses the international gold futures market data as the experimental dataset, and uses Maximal Information Coefficient (MIC) to analyze the correlation of the influencing factors. The PCA-AGRU model is compared with five prediction models of GRU, SA-GRU, AGRU, PCA-GRU, and PCA-SA-GRU. The experimental results show that the PCA-AGRU model performs best in forecasting gold futures prices. © 2023 IEEE.

关键词： AGRU deep learning Gold Futures PCA Price Prediction SA

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：