检索结果-内蒙古大学图书馆

2022 9th International Conference on Condition Monitoring and Diagnosis (CMD)

作者： Shekhar Mahmud Faisal. P. Mohamed Md Saiful Islam Saleh Hassan Elkelani Babaa George Chen Systems Engineering Department Military Technological College Sultanate of Oman Civil Engineering Department Military Technological College Sultanate of Oman Electronics and Computer Science University of Southampton UK

ISBN: (数字)9784886864314

ISBN: (纸本)9781665470155

This paper presents requirement of a system to synchronously monitor partial discharge activity with synchronized power quality (PQ) measurements from a substation. Increased use of non-linear loads in power systems leads to higher harmonic content which has an impact on partial discharge activity in high voltage equipment. Hence there is a requirement to synchronously monitor PD activity with PQ measurements, which can inform asset manager to take management decisions affecting the maintenance regimes that will result improved power quality PQ or minimising the cost of insulation repair. Such a system to synchronously monitor PD with PQ is not readily available. This paper presents a system which can monitor PD activity with synchronized PQ measurements using Field Programmable Gate Arrays (FPGA) and Global Positioning System (GPS). The system design, laboratory tests and on-site measurements are discussed.

关键词： Partial discharge measurement Partial discharges Power measurement Substations Power quality Maintenance engineering Synchronization

来源：评论

学校读者我要写书评

暂无评论

Using Natural Language Processing to Predict Costume Core Vocabulary of Historical Artifacts

Using Natural Language Processing to Predict Costume Core Vo...

引用

International Conference on Machine Learning and Applications (ICMLA)

作者： Madhuvanti Muralikrishnan Amr Hilal Chreston Miller Dina Smith-Glaviana Computer Science Dept Virginia Tech Blacksburg VA Informatics Lab Virginia Tech Blacksburg VA Department of Computer and Systems Engineering Alexandria University Egypt Apparel Housing and Resource Management Dept Virginia Tech Blacksburg VA

Historic dress artifacts are a valuable source for human studies. In particular, they can provide important insights into the social aspects of their corresponding era. These insights are commonly drawn from garment pictures as well as the accompanying descriptions and are usually stored in a standardized and controlled vocabulary that accurately describes garments and costume items, called the Costume Core Vocabulary. Building an accurate Costume Core from garment descriptions can be challenging because the historic garment items are often donated, and the accompanying descriptions can be based on untrained individuals and use a language common to the period of the items. In this paper, we present an approach to use Natural Language Processing (NLP) to map the free-form text descriptions of the historic items to that of the controlled vocabulary provided by the Costume Core. Despite the limited dataset, we were able to train an NLP model based on the Universal Sentence Encoder to perform this mapping with more than 90% test accuracy for a subset of the Costume Core vocabulary. We describe our methodology, design choices, and development of our approach, and show the feasibility of predicting the Costume Core for unseen descriptions. With more garment descriptions still being curated to be used for training, we expect to have higher accuracy for better generalizability.

关键词： Training Vocabulary Design methodology Clothing Buildings Machine learning Natural language processing

来源：评论

学校读者我要写书评

暂无评论

Watermarking and Encryption for Electronic Medical Records (EMR) Security Based on mCloud

Watermarking and Encryption for Electronic Medical Records (...

引用

Cyber Resilience (ICCR), International Conference on

作者： Haider Rasheed Abdulshaheed Yaseen Saadi Abbas Jamal F. Tawfeq Karamath Ateeq Saif. E. A. Alnawayseh Taher M. Ghazal Computer Engineering Techniques Department Baghdad College of Economic Sciences University Baghdad Iraq Electronic and Communications Engineering Department College of Engineering Al-Nahrain University Baghdad Iraq Department of Medical Instrumentation Technical Engineering Medical Technical College Al-Farahidi University Baghdad Iraq School of Computing Skyline University College University City Sharjah Sharjah UAE Department of Electrical Engineering College of Engineering Mutah University Al-Karak Jordan Computer Science Department Centre for Cyber Physical Systems Khalifa University Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

Providing quality healthcare services and promoting collaborative clinical research are easier and more efficient with electronic medical record (EMR) systems. All aspects of care are included in electronic health records. Data characterized by volume, variety, and velocity is what IBM defines as big data. Therefore, we evidently have a significant problem managing “big EMR data” from a volume, accuracy, and velocity perspective. Data misuse and patient safety are significant risks associated with poorly implemented EMR-based systems. Storage, access, and retrieval of big data are all aspects of security to consider. Location is another important aspect of secure data use, in addition to strong access control mechanisms. Researchers are investigating secure mobile data usage based on location after recent reports of illegal trade and theft of patient data over mobile devices. To improve work flow dynamics and efficiency, healthcare facilities are increasingly using mobile devices. In spite of this, mobile devices are becoming more and more common. A new technique for preventing EMR infiltration and manipulation by hackers using the cloud is presented in this article.

关键词： Cloud computing Hospitals Watermarking Big Data Mobile handsets Robustness Safety

来源：评论

学校读者我要写书评

暂无评论

Cybersecurity Challenges and Solutions in the Digital Age: An Analysis

Cybersecurity Challenges and Solutions in the Digital Age: A...

引用

Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Sargunavathi S Talluri Upender Sowmiya B Sundar R Rajasekaran E S.Sree Dharinya Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamilnadu India Department of CSE CMR College of Engineering and Technology Hyderabad Telangana Department of Computing Technologies SRM Institute of Science and Technology Department of CSE Sathyabama Institute of Science and Technology Department of Science and Humanities V.S.B Engineering College Karur India School of Computer Science Engineering and Information Systems. VIT University Vellore

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

In the digital age, cybersecurity has become a critical concern for individuals, organizations, and governments worldwide. The rapid advancement of technology and the increasing interconnectedness of systems have introduced numerous vulnerabilities, making cybersecurity a complex and ever-evolving challenge. This paper provides a comprehensive analysis of the current cybersecurity landscape, identifying key challenges such as sophisticated cyber-attacks, data breaches, and the growing threat of ransomware. Additionally, it explores innovative solutions and strategies to mitigate these risks, including the implementation of advanced threat detection systems, and the adoption of robust security protocols. Furthermore, the paper delves into the importance of cyber hygiene, the role of regulatory frameworks, and the necessity of continuous education and awareness programs to foster a culture of cybersecurity. It also examines the impact of emerging technologies like the Internet of Things (IoT) and 5G networks on cybersecurity, highlighting both opportunities and vulnerabilities. Special attention is given to the integration of blockchain technology for secure transactions and identity verification. The paper also addresses the significance of international collaboration and information sharing to combat global cyber threats. By examining both the threats and the potential countermeasures, this paper aims to offer valuable insights into safeguarding digital assets, ensuring the integrity and confidentiality of information, and promoting a proactive and resilient approach to cybersecurity in an increasingly digital world.

关键词： Training Protocols Government Data breach Information age Threat assessment Blockchains Ransomware computer security Cyberattack

来源：评论

学校读者我要写书评

暂无评论

Volatility contagion between cryptocurrencies,gold and stock markets pre-and-during COVID-19:evidence using DCC-GARCH and cascade-correlation network

引用

Financial Innovation 2024年第1期10卷 1847-1874页

作者： Bassam A.Ibrahim Ahmed A.Elamer Thamir H.Alasker Marwa A.Mohamed Hussein A.Abdou Department of Business Administration College of BusinessImam Mohammad Ibn Saud Islamic University11432RiyadhSaudi Arabia Department of Management Faculty of CommerceMansoura UniversityMansouraEgypt Brunel Business School Brunel University LondonKingston LaneUxbridgeLondonUB83PHUK Gulf Financial Center Gulf University for Science and Technology(GUST)Mubarak Al-Abdullah Area/West MishrefKuwait Higher Institute for Computer Science and Information Systems Fifth SettlementNew CairoEgypt Newcastle Business School Northumbria UniversityNorthumberland RoadNewcastle upon TyneNE18STUK

The rapid rise of Bitcoin and its increasing global adoption has raised concerns about its impact on traditional markets,particularly in periods of economic turmoil and uncertainty such as the COVID-19 *** study examines the extent of the volatility contagion from the Bitcoin market to traditional markets,focusing on gold and six major stock markets(Japan,USA,UK,China,Germany,and France)using daily data from January 2,2011,to June 2,2022,with 2958 daily *** employ DCC-GARCH,wavelet coherence,and cascade-correlation network models to analyze the relationship between Bitcoin and those *** results indicate long-term volatility contagion between Bitcoin and gold and short-term contagion during periods of market turmoil and *** also find evidence of long-term contagion between Bitcoin and the six stock markets,with short-term contagion observed in Chinese and Japanese markets during *** results suggest a risk of uncontrollable threats from Bitcoin volatility and highlight the need for measures to prevent infection transmission to local stock *** funds,mutual funds,and individual and institutional investors can benefit from using our findings in their risk management *** research confirms the utility of the cascade-correlation network model as an innovative method to investigate intermarket contagion across diverse *** holds significant implications for stock market investors and policymakers,providing evidence for potentially using cryptocurrencies for hedging,for diversification,or as a safe haven.

关键词： Cryptocurrencies Gold Stock markets COVID-19 Cascade-correlation network

来源：评论

学校读者我要写书评

暂无评论

Tacit knowledge elicitation process for industry 4.0

引用

Discover Artificial Intelligence 2022年第1期2卷 1-15页

作者： Fenoglio, Enzo Kazim, Emre Latapie, Hugo Koshiyama, Adriano Department of Computer Science University College London Glower St LondonWC1E 6BT United Kingdom Holistic AI 18 Soho Square LondonW1D 3QL United Kingdom Emerging Technologies & amp Incubation Cisco Systems Inc 170 West Tasman Dr. San JoseCA95134 United States

Manufacturers migrate their processes to Industry 4.0, which includes new technologies for improving productivity and efficiency of operations. One of the issues is capturing, recreating, and documenting the tacit knowledge of the aging workers. However, there are no systematic procedures to incorporate this knowledge into Enterprise Resource Planning systems and maintain a competitive advantage. This paper describes a solution proposal for a tacit knowledge elicitation process for capturing operational best practices of experienced workers in industrial domains based on a mix of algorithmic techniques and a cooperative game. We use domain ontologies for Industry 4.0 and reasoning techniques to discover and integrate new facts from textual sources into an Operational Knowledge Graph. We describe a concepts formation iterative process in a role game played by human and virtual agents through socialization and externalization for knowledge graph refinement. Ethical and societal concerns are discussed as well. © The Author(s) 2022.

关键词： Industry 4.0

来源：评论

学校读者我要写书评

暂无评论

A Multi-Resolution Deep Forest Framework with Hybrid Feature Fusion for CT Whole Heart Segmentation

A Multi-Resolution Deep Forest Framework with Hybrid Feature...

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Xu, Fei Lin, Lingli Li, DIhan Hong, Qingqi Liu, Kunhong Wu, Qingqiang Li, Qingde Zheng, Yinhuan Tian, Jie Xiamen University School of Informatics China University of Hull Department of Computer Science HullHU6 7RX United Kingdom Xiamen Institute of Technology College of Computer and Artificail Intelligence China Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781665401265

Cardiac medical image segmentation plays an important role in the diagnosis and clinical treatment of cardiovascular diseases. However, due to the variability of cardiac anatomy and the ambiguity between cardiac substructures, it is still difficult to quickly segment the entire heart from medical images. Most of the current researches utilize neural network structure to perform whole heart segmentation. Although good segmentation accuracy has been achieved, it usually requires a long training time. This paper aims to build a new whole heart segmentation model based on Deep Forest, called Multi-Resolution Deep Forest Framework(MRDFF), which performs segmentation through two stages. In the first stage, the heart region is located by rough binary classification, and similarity screening is used to reduce redundancy. The second stage subdivides the heart substructures based on the results of the first stage and uses multi-scale fusion to achieve high segmentation accuracy. The experimental results conducted on the public data set MM-WHS show that under the same training data and configuration, our model can be trained in only 4.5 hours, which is about 1/2 of the training time of neural network models, and can reach the accuracy not lower than neural network models, which shows the feasibility and efficiency of our model. The code will be made publicly available at https://***/xufeixf/MRDFF. © 2021 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach for Mitigating Security Threats in IoT Environment

Machine Learning Approach for Mitigating Security Threats in...

引用

International Conference on Inventive Research in Computing Applications (ICIRCA)

作者： Harnit Saini Saroj Bala S.Jhansi Ida K. Suresh Kumar Shankerpally Swetha Divyabarathi P Department of CSE Ajay Kumar Garg Engineering College Ghaziabad Department of MCA Ajay Kumar Garg Engineering College Ghaziabad Department of Computer Science and Business Systems R.M.K Engineering College Kavaraipettai Department of CSE Kongu Engineering College Erode Department of Information Technology CVR College of Engineering Telangana Department of Artificial Intelligence and Data Science Bannari Amman Institute of Technology Erode

In today's world, a huge amount of data and information is transferred through wireless networks. The Internet of Things (IoT) is a complex network that consists of diverse sensors, devices, and things, which often have limited resources and are susceptible to various security threats, including Distributed Denial of Service (DDoS) attacks. These networks are vulnerable to a variety of cyber threats and privacy issues. Intrusions are harmful activities that can damage a network. IoT networks are particularly vulnerable to security threats. The Bi-Layer Intrusion Detection Model (BIDM) identifies intrusions based on the optimal features selected in the Optimal Feature Vector Selection (OFVS) phase. This scheme not only prevents attacks, but also serves as a defense against legitimate threats. The proposed technique was evaluated using the KDD CUP 99 dataset, a well-known Intrusion Detection System (IDS) benchmark. The performance of the proposed scheme was further analyzed using the NSL-KDD and CICIDS-2017 datasets. The performance of OFVS was also investigated using the relatively new IoT Network Intrusion dataset. The implementation was carried out in Jupyter Notebook using the Python programming language. Matplotlib, Scikit-learn, pandas, and NumPy were some of the packages used in the implementation. The proposed framework achieved high accuracy rates, with NB at 97.4%, SVM at 96.1%, and DT at 98.1%. By utilizing this approach, the security of IoT networks can be significantly enhanced, and the risks associated with DDoS attacks can be mitigated.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of glycemic excursions using morphological and time-domain ECG features

Detection of glycemic excursions using morphological and tim...

引用

International Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Kathan Vyas Carolina Villegas Elizabeth Kubota-Mishra Darpit Dave Madhav Erraguntla Gerard Coté Daniel J. DeSalvo Siripoom McKay Ricardo Gutierrez-Osuna Department of Computer Science and Engineering Texas A&M University Pediatrics Diabetes and Endocrinology Baylor College of Medicine Department of Industrial and Systems Engineering Texas A&M University Department of Biomedical Engineering Texas A&M University

Managing diabetes often involves monitoring blood glucose in real time to detect excursions (e.g., hypoglycemia and hyperglycemia). Continuous glucose monitors (CGMs) are generally used for this purpose, but CGMs are both expensive and invasive (they require inserting a flexible needle under the skin). To address this issue, we examine whether non-invasive devices, such as electrocardiograms (ECG), can be used to predict glucose excursions. In particular, we consider two types of cardiac information: (1) heartbeat morphology, which generally requires ECG recordings, and (2) heartbeat timing, which can be obtained from inexpensive wrist-worn devices, such as fitness trackers. We use convolutional networks to analyze beat morphology, and recurrent networks and feature engineering to analyze the inter-beat interval (IBI) time series. Then, we validate individual models and their combinations on an experimental dataset containing ECG and CGM recordings for then young adults with type 1 diabetes. We find that beat morphology outperforms beat timing in hypoglycemia prediction, but the reverse happens for hyperglycemia prediction. In both prediction problems, combining morphology and time-domain information outperforms using each source of information independently.

关键词：

来源：评论

学校读者我要写书评

暂无评论

State Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

引用

IEEE Transactions on Power systems 2024年第4期40卷 3057-3073页

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-State Estimation (IES-SE) and more established Electric Power System-State Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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：