检索结果-内蒙古大学图书馆

IEEE Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)

作者： Ira Nath Pratnadeep Biswas Kankana Ganguly Dharmpal Singh Sardar M.N. Islam Ton Quang Cuong Souvik Pal Computer Science & Engineering JIS College of Engineering Kalyani India ISILC and Decision Sciences and Modeling Program Victoria University Australia Vietnam National University Hanoi Vietnam Computer Science & Engineering Global Institute of Management and Technology Krisnanagar India

ISBN: (纸本)9781665417853

India is a highly densely populated country. India is facing a very serious challenge due to the novel COVID-I9 outbreak. In this situation, the economic state of the people is very unstable. Blockchain technology proves helpful to subdue the situation. A voting system with ballot papers is quite tuff now. It is very costly for the government. The pandemic may also spread very quickly. The system of developing ledger serves the idea of developments of a new e-voting system that is economical, easy to use, and highly secure. This paper proposes ways and solutions to design an e-voting system using blockchain technology. The paper's primary goal is to develop a highly secure e-voting technique using which people can cast their valuable votes from their home, working place - anywhere from the world. This e-voting technique is least costly, highly secure, and able to prevent further spreading of any infectious disease in the near future. In this paper, an e-voting system using blockchain has been designed to overcome all these difficulties mentioned above during traditional voting using ballot. The significance of the proposed work is to design of a highly safe and least costly e- voting system using blockchain. Using this system the people can cast their vote easily, securely and without wasting any time. Casting vote will be now just from few clicks away and from any place with a stable internet connection.

关键词： COVID-19 Economics Casting Pandemics Infectious diseases Blockchains Electronic voting

来源：评论

学校读者我要写书评

暂无评论

A Transdisciplinary Socio-Technical Systems Approach: Wireless Solutions for the Digital Divide

A Transdisciplinary Socio-Technical Systems Approach: Wirele...

引用

Annual IEEE Systems Conference

作者： Shamsnaz Virani Bhada Casey Canfield Alexander Wyglinski Systems Engineering Program Worcester Polytechnic Institute Worcester MA Engineering Management & Systems Engineering Missouri University of Science & Technology Rolla MO USA Worcester Polytechnic Institue Worcester MA USA

The digital divide limits access to education, employment, and healthcare - particularly in rural areas. Unfortunately, most wireless solutions have been developed for urban and suburban environments. However, by using transdisciplinary systems approaches, we can highlight gaps and opportunities to resolve this divide by addressing technology, policy, and community challenges. By creating a digital entity to represent the problem space, we can tailor solutions to specific scenarios.

关键词： Wireless communication Sociotechnical systems Navigation Employment Medical services Tools Digital divide

来源：评论

学校读者我要写书评

暂无评论

A novel strong duality-based reformulation for trilevel infrastructure models in energy systems development

arXiv

引用

arXiv 2023年

作者： Herrala, Olli Gabriel, Steven A. Oliveira, Fabricio Ekholm, Tommi Aalto University Department of Mathematics and Systems Analysis Espoo Finland University of Maryland Department of Mechanical Engineering/Applied Mathematics Statistics & Scientific Computing Program College ParkMD United States Norwegian University of Science and Technology Department of Industrial Economics and Technology Management Trondheim Norway Finnish Meteorological Institute Helsinki Finland

We explore the class of trilevel equilibrium problems with a focus on energy-environmental applications and present a novel single-level reformulation for such problems, based on strong duality. To the best of our knowledge, only one alternative single-level reformulation for trilevel problems exists. This reformulation uses a representation of the bottom-level solution set, whereas we propose a reformulation based on strong duality. Our novel reformulation is compared to this existing formulation, discussing both model sizes and computational performance. In particular, we apply this trilevel framework to a power market model, exploring the possibilities of an international policymaker in reducing emissions of the system. Using the proposed methods, we are able to obtain globally optimal solutions for a five-node case study representing the Nordic countries and assess the impact of a carbon tax on the electricity production portfolio. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy resources

来源：评论

学校读者我要写书评

暂无评论

Application of online science practicum by using Microsoft Teams and Learning management System (LMS) during the Covid 19 pandemic 10

Application of online science practicum by using Microsoft T...

引用

10th National Physics Seminar, SNF 2021

作者： Pertiwi, W.A. Sanjaya, L.A. Nadiyah Hasirah Haramen, M. Budi, A.S. Zarvianti, E. Puspa, R.W.D. Sianipar, L.K. Qoiriyah, W. Sitompul, H. Islamic Education Management Study Program Faculty Islamic of Education and Teacher Training Muhammad Azim Institute Jambi Indonesia Department of Physics Faculty of Mathematics and Natural Science Universitas Negeri Jakarta Indonesia Sharia Economics Study Program Faculty of Sharia and Law Muhammad Azim Islamic Institute Jambi Indonesia Physics Education Study Program STKIP Muhammadiyah Sungai Penuh Indonesia Kartika VIII-1 Senior High School Jakarta Indonesia Department of Physics Education Universitas Pelita Harapan Tangerang15811 Indonesia Informatics Engineering Study Program Faculty of Engineering Sheikh Yusuf Islamic University Tangerang Indonesia

The research objective of this is to see how to apply science practicum online using Microsoft Teams and Learning management System (LMS). The form of this research is classroom action research which aims to apply the online science practicum during the Covid 19 pandemic. Therefore, it is carried out using two cycles in the application of online science practicum. The subjects of this study were students of the seventh semester in the Natural science practicum course. Through observation and evaluation, it is shown that in the cycle I the percentage of practicum implementation which includes aspects of preparation, process and data and practicum results is 87.5%, in cycle II it has increased to 92.5%. In the assessment aspect of the practicum report, the average practicum assessment obtained in the first cycle was 3.09 from the highest score of 4 and in the second cycle was 3.7, while the aspect of student knowledge about the use of the Microsoft team which was taken using google form was 93%. In the aspect of student knowledge about the use of Learning management System (LMS) by 75% and aspects of student understanding in the implementation of online science practicum using Microsoft Teams by 75%. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Comparative analysis of various oxygen production techniques using multi-criteria decision-making methods

引用

International Journal of Thermofluids 2023年 17卷

作者： Aljaghoub, Haya Alasad, Shamma Alashkar, Adnan AlMallahi, Maryam Hasan, Ranem Obaideen, Khaled Alami, Abdul Hai Department of Industrial Engineering and Engineering Management University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah Sharjah United Arab Emirates Department of Mechanical and Aerospace Engineering United Arab Emirates University Al Ain City United Arab Emirates Department of Sustainable and Renewable Energy Engineering University of Sharjah Sharjah United Arab Emirates Sustainable Energy and Power Systems Research Center RISE University of Sharjah Sharjah United Arab Emirates Center for Advanced Materials Research University of Sharjah Sharjah United Arab Emirates

The current pandemic has adversely affected oxygen production and supply chain, where oxygen treatment is essential for the emergency treatment protocol of patients infected by the virus. This work reports on various techniques of oxygen generation methods, as well as the challenges facing its production, storage, and transportation. Moreover, this study offers a comparative analysis of various oxygen production techniques using Multi-Criteria Decision-Making Methods (MCDM). Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), in addition to the weighting methodologies, Multiplicative Exponential Weighting (MEW) and Simple Additive Weighting (SAW) are chosen as tools to carry out the statistical analysis and rank the oxygen production methods. The ranking criteria includes cost, performance, environmental impact and safety. Moreover, this paper utilizes the Entropy Weight Method (EWM), Criteria Importance Through Inter-criteria Correlation (CRITIC) method, and the Stochastic Dominance (SD) method to distribute the criteria weights. The results show thar oxygen production using membrane technologies is the optimal technique based on all the provided tools and criteria. as it attained the maximum Entropy and Sd values of 0.548 through the TOPSIS method, and the highest CRITIC value through SAW and MEW methods which were 0.260 and 0.236, respectively. © 2022 The Author(s)

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Ant Colony Optimization based Medical Image Preservation and Segmentation

Ant Colony Optimization based Medical Image Preservation and...

引用

Advanced Technologies in Intelligent Control, Environment, Computing & Communication engineering (ICATIECE), International Conference on

作者： Priya Nandihal Piyush Kumar Pareek Victor Hugo Costa De Albuquerque Madhumala R B Ashish Khanna V Sunil Kumar Dept of Computer Science and Design Dayananda Sagar Academy of Technology and Management Bangalore Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceara Fortaleza Brazil Department of Teleinformatics Engineering Federal University of Ceara Brazil Department of ISE Dayananda Sagar Academy of Technology and Management Bangalore CSE Dept Maharaja Agrasen Institute of Technology GGSIPU Department of Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru

ISBN: (纸本)9781665493970

Image segmentation is an essential component in many different types of computer vision systems. Image segmentation is used in order to identify objects and boundaries within pictures. It is important to note that the success of recognition algorithms is heavily dependent on the quality of the picture segmentation, and there is yet no technique that can universally segment images. Boundary detection has a long history of being recognised as one of the most difficult challenges in the fields of image processing and pattern analysis, in particular, when it comes to applications in medical imaging. The clarity of the picture is being muddled by more information, which is the source of the problem's complexity. The creation of segmentation algorithms for medical pictures is an active field of study, and segmentation algorithms are meant to account for a variety of factors, including noise, intensity inhomogeneity, poor contrast between the lesion and the surrounding skin, and so on. There is currently no active contour model that combines the locally statistical property of being more noise-resistant, in which the intensities in the transformed domain have less overlapping in the statistics, and the locally image fitting property of extracting the local image information in order to be able to segment images with intensity inhomogeneity. This is because there is no such model. So the proposed work includes Ant colony optimization based double threshold segmentation in medical images. Performance of the proposed algorithm is more efficient, reliable and accurate than the existing algorithm. Performance parameters such as segmentation accuracy, error rate, and Dice co-efficient are used in order to conduct the evaluation of the proposed work.

关键词： Integrated optics Image segmentation Ant colony optimization Biomedical optical imaging Optical design Image edge detection Metaheuristics

来源：评论

学校读者我要写书评

暂无评论

Towards RehabCoach: Design and Preliminary Evaluation of a Conversational Agent Supporting Unsupervised Therapy After Stroke

Towards RehabCoach: Design and Preliminary Evaluation of a C...

引用

IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Giada Devittori Mehdi Akeddar Alexandra Retevoi Fabian Schneider Viktoria Cvetkova Daria Dinacci Antonella Califfi Paolo Rossi Claudio Petrillo Tobias Kowatsch Olivier Lambercy Rehabilitation Engineering Laboratory ETH Zurich Switzerland Department of Technology Management and Economics ETH Zurich Switzerland Clinica Hildebrand Centro di riabilitazione Brissago Switzerland Institute for Implementation Science in Health Care University of Zurich Switzerland School of Medicine University of St. Gallen Switzerland Future Health Technologies program Singapore-ETH Centre Campus for Research Excellence and Technological Enterprise (CREATE) Singapore

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Unsupervised therapy after stroke is a promising way to boost therapy dose without significantly increasing the workload on healthcare professionals. However, it raises important challenges, such as lower adherence to therapy in the absence of social interaction with therapists. We present the initial prototype of RehabCoach, a novel smartphone-based app with conversational agent to support unsupervised therapy. RehabCoach is designed to increase patients' engagement and adherence to therapy and to provide information (e.g., about stroke, health) in an interactive and user-friendly manner. We report on the design and usability evaluation of the first prototype of RehabCoach, assessed by four stroke patients and five healthcare professionals, who interacted with the app in a single testing session. Task completion time and success rates were measured for 15 representative tasks, and participants assessed usability via questionnaires and a semi-structured interview. Results show that it was feasible for stroke patients to successfully interact with RehabCoach (task success ≥93%) without requiring extensive training. Participants positively rated the usability of RehabCoach (mean mHealth App Usability Questionnaire score: 1.3 for primary users, 1.4 for healthcare professionals, on a scale from 1 (positive evaluation) to 7). The feedback collected in this work opens the door to further enhance RehabCoach as an interactive digital tool to support unsupervised rehabilitation.

关键词： Training Medical treatment Prototypes Stroke (medical condition) Particle measurements Time measurement Usability Interviews Robots Testing

来源：评论

学校读者我要写书评

暂无评论

Ultrasound-Guided Deep Learning for Regional Nerve Block Anesthesia in Scapular Fracture

Ultrasound-Guided Deep Learning for Regional Nerve Block Ane...

引用

Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Upasna Joshi Mohan Raparthi Ramswaroop Reddy Pramod Kumar Praveen Thuniki Mohammad Shabaz Delhi Technical Campus Greater Noida India Software Engineer Alphabet Life Science Dallas Texas USA Yellu Independent Research Richmond VA 23233 University of Texas Austin US Ganga Institute of Technology and Management Haryana India Independent Research Sr Program Analyst Georgia Cumming GA USA Model Institute of Engineering and Technology Jammu J&K India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

This study introduces a novel approach to regional nerve block anesthesia in scapular fractures by integrating ultrasound guidance with deep learning techniques. The proposed method leverages advanced imaging modalities and state-of-the-art deep learning models to achieve precise nerve localization amidst complex fracture patterns. Through extensive experimentation and evaluation, we demonstrate the effectiveness of the proposed method in enhancing surgical planning, intraoperative decision-making, and patient safety. This study represents a significant advancement in the field of orthopedic surgery, offering a promising solution for improving outcomes and quality of life for patients with scapular fractures. The method this study suggests for locating nerves in shoulder fractures advances orthopaedic surgery. We can improve, expedite, and streamline procedures with the use of AI and medical imaging. This will improve the quality of life and outcomes for scapular fractures.

关键词： Deep learning Location awareness Ultrasonic imaging Orthopedic surgery Decision making Shoulder Anesthesia

来源：评论

学校读者我要写书评

暂无评论

IoT Attack Detection and Prevention Through Machine Learning System

IoT Attack Detection and Prevention Through Machine Learning...

引用

Communication, Security and Artificial Intelligence (ICCSAI), International Conference on

作者： Kanishk Agrawal Pavan Kumar Reddy Poli Yash Gupta Garv Juneja Adhip Kishen Bopaiah Dinesh Ashok Arani Department of IET CSE Manglayatan University Aligarh Uttar Pradesh India Managing Information Technology Implementations Program management for fortune 6 Healthcare Company USA Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani India Department of Computer Science and Engineering Maharaja Surajmal Institute of Technology Guru Gobind Singh Indraprastha University Delhi India ICT Trainer Trinity College Bangalore India Manglayatan University Aligarh Uttar Pradesh India

Attacks on web applications are constantly growing in both frequency and severity. Abundant data on the internet stimulates hackers to attempt different types of cyberattacks. Attack detection using conventional approaches and outdated data processing techniques has become outmoded as a result of this development. The purpose of this study is to investigate IoT attacks and discuss the efficient ML technique implementation strategies for restricting security risks. Among different security techniques, Machine learning (ML) systems demonstrated commendable feasibility in improving network and device security for the Internet of Things. The study with contextual research recognises and comprehends that modified “Support Vector Machine (SVM)” as well as “Random Forest (RF)” ML techniques showed optimal performance in IoT attack detection and prevention.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Study on Medicinal Plant Leaf Recognition Using Artificial Intelligence

A Study on Medicinal Plant Leaf Recognition Using Artificial...

引用

International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Vina Ayumi Ermatita Ermatita Abdiansah Abdiansah Handrie Noprisson Mariana Purba Marissa Utami Doctoral Program in Engineering Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Mercu Buana Jakarta Indonesia Program of Informatics Management Politeknik Anika Palembang Indonesia Faculty of Engineering Muhammadiyah University of Bengkulu Bengkulu Indonesia

ISBN: (纸本)9781665427340

Medicinal plant recognition manually takes a lot of time and money. Moreover, to reduce these resources, some researchers propose to implement artificial intelligence technology. This paper aims are to conduct a systematic literature review of medicinal plant leaf recognition published in the last two years (2019–2020) from IEEE, Springer and science Direct. We obtained 15 studies in the field of medicinal plant leaf recognition using artificial intelligence. The dataset used for medicinal plant leaf recognition is mostly used private dataset, however, there are public dataset named Leaf, Flavia, Swedish dataset. We also found robust method that can be used for medicinal plant leaf recognition is Multichannel Modified Local Gradient Pattern (MCMLGP) and Gray Level Co-Occurrence Matrix (GLCM) as feature extraction; and Convolutional Neural Network (CNN), Multi-Layer Perceptron trained with Backpropagation algorithm (MLP-BP), Support Vector Machine (SVM), and Transfer Learning (VGG19) as classifier.

关键词： Support vector machines Systematics Bibliographies Multimedia systems Transfer learning Backpropagation algorithms Feature extraction

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：