检索结果-内蒙古大学图书馆

1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Arun, V. Shenbagavalli, P. Sridhar, T. Manivannan, B. Mahesh, T.R. Anitha, K. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur India Karunya Institute of Technology and Sciences Division of Digital Sciences India Alliance University Alliance College of Engineering and Design Bangalore India Computer Science and Engineering Namakkal India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India Csi College of Engineering Department of Information Technology Tamilnadu Ooty India

ISBN: (纸本)9798350359756

IoT (Internet of Things) technology enables the connectivity and communication of healthcare-related equipment, medical devices, and sensors. This connectivity enables better monitoring, data collecting, and analysis, which leads to better patient outcomes and more effective healthcare delivery. However, with the rising use of linked devices, it is critical to detect and prevent Cyberattacks in order to secure sensitive patient information. In order to tackle this problem, the article delves into the application of machine learning methods like Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest (RF), and Naive Bayes (NB), These algorithms were evaluated using the WUSTL EHMS2020 dataset and demonstrated the highest level of accuracy. © 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

Enhancing IoT Data Security: Integrating Elliptic Galois Cryptography with Matrix XOR Steganography and Adaptive Firefly Optimization 8

Enhancing IoT Data Security: Integrating Elliptic Galois Cry...

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Chinnasamy, P. Ayyasamy, Ramesh Kumar Anuradha, K. Alam, Irfan Nair, Deveendra Menon Narayanan Kiran, Ajmeera Kalasalingam Academy of Research and Education School of Computing Department of Computer Science and Engineering Tamilnadu India Faculty of Information and Communication Technology Kampar Malaysia Telangana India Scai Vit Bhopal University Cyber Security and Digital Forensics Division Kothari Kalan Sehore India Mlr Institute of Technology Department of Computer Science and Engineering Hdyerabad India

ISBN: (纸本)9798350376425

Securing the uninterrupted data flow is crucial in the fast-advancing Internet of Things (IoT) market. This work investigates the incorporation of elliptic Galois cryptography and matrix XOR coding steganography to improve data security. The suggested solution employs the elliptic Galois cryptography protocol to encrypt sensitive data from diverse medical records. The private information is embedded within images through the matrix XOR encoding steganography algorithm. The Adaptive Firefly optimization approach is used to improve the efficiency of utilizing cover blocks for steganography. The effectiveness of the proposed technique is evaluated using various modern approaches. We analyze the efficiency and security of the proposed approach by comparing it with a previous hybrid method employing the New York State Department of Health dataset. The results unequivocally validate that our approach offers enhanced safety in Internet of Things (IoT) applications. © 2024 IEEE.

关键词： Steganography

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence-Based Mobile Application for Sensing Children Emotion Through Drawings

Artificial Intelligence-Based Mobile Application for Sensing...

引用

作者： Ali, Nashva Abd-Alrazaq, Alaa Shah, Zubair Alajlani, Mohannad Alam, Tanvir Househ, Mowafa Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar AI Center for Precision Health Weill Cornell Medicine-Qatar Doha Qatar Institute of Digital Healthcare University of Warwick Warwick United Kingdom

ISBN: (纸本)9781643682907

Children go through varied emotions such as happiness, sadness, and fear. At times, it may be difficult for children to express their emotions. Detecting and understanding the unexpressed emotions of children is very important to address their needs and prevent mental health issues. In this paper, we develop an artificial intelligence (AI) based Emotion Sensing Recognition App (ESRA) to help parents and teachers understand the emotions of children by analyzing their drawings. We collected 102 drawings from a local school in Doha and 521 drawings from Google and Instagram. Four different experiments were conducted using a combination of the two datasets. The deep learning model was trained using the Fastai library in Python. The model classifies the drawings into positive or negative emotions. The model accuracy ranged from 55% to 79% in the four experiments. This study showed that ESRA has the potential in identifying the emotions of children. However, the underlying algorithm needs to be trained and evaluated using more drawings to improve its current accuracy and to be able to identify more specific emotions. © 2022 The authors and IOS Press.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Large Language Models, Computational Chemistry, and digital Reticular Chemistry: A Perspective and Proposed Workflow

引用

Molecular Frontiers Journal 2024年第01N02期08卷 3-6页

作者： Abdullah A. AlGhamdi Department of Chemistry and Kavli Energy Nanoscience Institute and Bakar Institute of Digital Materials for the Planet Division of Computing Data Science and Society University of California Berkeley CA USA UC Berkeley-KACST Joint Center of Excellence for Nanomaterials for Clean Energy Applications King Abdulaziz City for Science and Technology Riyadh 11442 Saudi Arabia

In this article, I explore the synergy between Large Language Models (LLMs) and computational chemistry in the context of digital reticular chemistry and propose a workflow leveraging these technologies to advance research and discovery in the field. I argue that understanding the intricacies of new tools is imperative before integrating them into applications, and that the proposed workflow, though robust, merely offers a glimpse into the expansive potential and applications of this field.

关键词： Reticular Chemistry digital Chemistry Computational Chemistry Large Language Models Generative Pretrained Transformer Artificial Intelligence Machine Learning Data science

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of an IoT-based Emergency Alert and GPS Tracking System using MQTT and GSM/GPS Module

Design and Implementation of an IoT-based Emergency Alert an...

引用

Trends in Material science and Inventive Materials (ICTMIM), International Conference on

作者： P. Chinnasamy Pranavdev P. S Chintha Sivakrishnaiah T. Sathiya Irfan Alam Divya Priya Degala Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamilnadu India Department of MCA Annamacharya University Rajampet India Department of CSE Sona College of Technology Salem Tamilnadu India Cyber Security and Digital Forensics Division SCAI VIT Bhopal University Sehore India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

An optimally optimized emergency response system can prove to be lifesaving by reducing response time during the state of emergency. This paper proposes an IoT-based emergency alert and GPS tracking system implemented on an ESP32 microcontroller and an A9G GSM/GPS module. The system has a continuous log of user position and device battery level and pushes data in intervals through MQTT to the Adafruit IO platform for remote monitoring. To achieve best battery life, the A9G module goes into low power mode in idle mode but keeps GPS monitoring running. One more feature highlighted is the SOS button, which makes an emergency call by sending the user's location as an SMS and calling a pre-configured contact number. The system also maintains data integrity with automatic reconnect of MQTT broker when it loses connection. Low power and battery portable, the system is applicable in personal protection, home health care for elderly, outdoor adventure, and remote area surveillance. The article explains hardware design, software process, MQTT-based data communication, and testing of the performance of the system based on precision, network, and response to emergencies. The results verify reliability and cost saving of the system in real-time monitoring and reporting of emergencies. With its energy-saving and usability design, it helps in the development of IoT-backed safety solutions for real-time tracking and emergency response in case of a need.

关键词： Safety devices Protocols Emergency services Real-time systems Batteries Time factors Older adults Usability Global Positioning System Testing

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Algorithms for the Detection of Threats in IoT Healthcare

Machine Learning Algorithms for the Detection of Threats in ...

引用

Emerging Research in Computational science (ICERCS), International Conference on

作者： Arun V P. Shenbagavalli Sridhar T Manivannan B Mahesh T R K Anitha Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Division of Digital Sciences Karunya Institute of Technology and Sciences India Alliance College of Engineering and Design Alliance University Bangalore India Computer Science and Engineering Vivekanandha College of Engineering For Women(Anna University) Namakkal India Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore India Department of Information Technology CSI College of Engineering Ooty Tamilnadu

关键词：

来源：评论

学校读者我要写书评

暂无评论

RSMA-assisted SHAPTINs: secrecy performance under imperfect hardware and channel estimation errors

引用

Neural computing and Applications 2024年 1-18页

作者： Feng, Zhou Kefeng, Guo Jian, Cheng Sunder Ali, Khowaja Kapal, Dev Reddy, Gadekallu Thippa Hussam Al, Hamadi School of Information Technology Yancheng Institute of Technology Yancheng224051 China School of Space Information Space Engineering University Beijing101407 China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Faculty of Computing Digital and Data Technological University Dublin DublinD07EWV4 Ireland ADAPT Centre and Department of Computer Science Munster Technological University Cork BishopstownT12 P928 Ireland Department of institute of intelligent systems University of Johannesburg Auckland Park Johannesburg2006 South Africa Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Division of Research and Development Lovely Professional University Phagwara144001 India College of Engineering and IT College of Engineering and IT University of Dubai PO Box 14143 Dubai United Arab Emirates

Satellite high aerial platform terrestrial integrated networks have become the hot topic these years, which have been regarded as the major part of the intelligence of things for future networks. During this work, we investigate the secrecy performance for rate-splitting multiple access-assisted satellite high aerial platform terrestrial integrated networks. Besides, imperfect hardware and channel estimation errors are considered in the secrecy networks. Moreover, to enhance the energy utilization efficiency, rate-splitting multiple access scheme is utilized into the considered network, which is prior to that of the non-orthogonal multiple access scheme. What's more, to enhance the satellite transmission, multiple high aerial platforms are used to forward the transmission along with multiple eavesdroppers. In addition, the direct transmission link is not considered in the secrecy networks due to the heavy fading and obstacles. Relied on the former considerations, the exact and asymptotic analysis for the secrecy performance is further obtained to confirm the rightness of the analysis. Finally, some representative Monte Carlo simulations are carried out to validate the obtained results. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Asymptotic analysis

来源：评论

学校读者我要写书评

暂无评论

Efficient Batch Verification and Privacy-Preserving Data Aggregation Scheme in V2G Networks

引用

IEEE Transactions on Vehicular technology 2025年

作者： Wang, Congcong Wang, Chen Shen, Jian Vasilakos, Athanasios V. Wang, Bin Wang, Weizheng Department of Software Engineering Nanjing University of Information Science and Technology Nanjing210044 China the Zhejiang Key Laboratory of Digital Fashion and Data Governance the Zhejiang Provincial International Cooperation Base for Science and Technology on Cloud Computing Security and Data Aggregation Zhejiang Sci-Tech University Hangzhou310018 China Zhejiang Provincial Innovation Center of Advanced Textile Technology Shaoxing312000 China College of Computer Science and Information Technology IAU Saudi Arabia Grimstad4879 Norway Network and Data Security Hangzhou310053 China Computer Science Department City University of Hong Kong Hong Kong the Division of Computer Science University of Aizu Fukushima965–8580 Japan

In recent years, against the backdrop of smart grids, vehicle-to-grid (V2G) interaction has become a hot topic. With the increasing number of new energy vehicles, handling massive amounts of electricity transaction data has become an urgent problem in need of resolution. Ensuring the security of the vast quantities of electricity transaction data has emerged as a significant challenge. Therefore, two data aggregation schemes are proposed in this paper, both supporting batch verification and privacy protection in centralized and distributed scenarios, respectively. Firstly, an improved Paillier cryptosystem is utilized to achieve lightweight encryption in the proposed schemes. In addition, a novel distributed data aggregation structure that combines a large number of geographically distributed fog nodes with centralized cloud servers is introduced. This structure not only meets the requirements of lightweight encryption and resistance against single point failures but also reduces the communication complexity of distributed data aggregation to O(n). According to the security proofs and experimental analysis, it can be demonstrated that both proposed schemes are effective and secure, meeting the lightweight requirements of modern smart grid systems. © 2025 IEEE. All rights reserved,

关键词： Data aggregation

来源：评论

学校读者我要写书评

暂无评论

Enhancing IoT Data Security: Integrating Elliptic Galois Cryptography with Matrix XOR Steganography and Adaptive Firefly Optimization

Enhancing IoT Data Security: Integrating Elliptic Galois Cry...

引用

International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： P. Chinnasamy Ramesh Kumar Ayyasamy K. Anuradha Irfan Alam Deveendra Menon Narayanan Nair Ajmeera Kiran Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamilnadu India Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman (UTAR) Kampar Malaysia Department of CSE (AI &ML) CVR College of Engineering Telangana India Cyber Security and Digital Forensics Division SCAI VIT Bhopal University Kothari Kalan Sehore India Department of Computer Science and Engineering MLR Institute of Technology Hdyerabad India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

关键词： Steganography Protocols Image coding Elliptic curve cryptography Data transfer Encoding Safety Internet of Things Galois fields Optimization

来源：评论

学校读者我要写书评

暂无评论

Touchstone benchmark: are we on the right way for evaluating AI algorithms for medical segmentation? 24

Touchstone benchmark: are we on the right way for evaluating...

引用

Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Pedro R. A. S. Bassi Wenxuan Li Yucheng Tang Fabian Isensee Zifu Wang Jieneng Chen Yu-Cheng Chou Saikat Roy Yannick Kirchhoff Maximilian Rokuss Ziyan Huang Jin Ye Junjun He Tassilo Wald Constantin Ulrich Michael Baumgartner Klaus H. Maier-Hein Paul Jaeger Yiwen Ye Yutong Xie Jianpeng Zhang Ziyang Chen Yong Xia Zhaohu Xing Lei Zhu Yousef Sadegheih Afshin Bozorgpour Pratibha Kumari Reza Azad Dorit Merhof Pengcheng Shi Ting Ma Yuxin Du Fan Bai Tiejun Huang Bo Zhao Haonan Wang Xiaomeng Li Hanxue Gu Haoyu Dong Jichen Yang Maciej A. Mazurowski Saumya Gupta Linshan Wu Jiaxin Zhuang Hao Chen Holger Roth Daguang Xu Matthew B. Blaschko Sergio Decherchi Andrea Cavalli Alan L. Yuille Zongwei Zhou Department of Computer Science Johns Hopkins University and Department of Pharmacy and Biotechnology University of Bologna and Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Department of Computer Science Johns Hopkins University NVIDIA Division of Medical Image Computing German Cancer Research Center (DKFZ) and Helmholtz Imaging German Cancer Research Center (DKFZ) ESAT-PSI KU Leuven Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University and HIDSS4Health - Helmholtz Information and Data Science School for Health Shanghai Jiao Tong University Shanghai Artificial Intelligence Laboratory Division of Medical Image Computing German Cancer Research Center (DKFZ) Division of Medical Image Computing German Cancer Research Center (DKFZ) and Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Helmholtz Imaging German Cancer Research Center (DKFZ) and Interactive Machine Learning Group (IML) DKFZ School of Computer Science and Engineering Northwestern Polytechnical University Australian Institute for Machine Learning The University of Adelaide College of Computer Science and Technology Zhejiang University Hong Kong University of Science and Technology (Guangzhou) Hong Kong University of Science and Technology (Guangzhou) and Hong Kong University of Science and Technology Faculty of Informatics and Data Science University of Regensburg Faculty of Electrical Engineering and Information Technology RWTH Aachen University Faculty of Informatics and Data Science University of Regensburg and Fraunhofer Institute for Digital Medicine MEVIS Electronic & Information Engineering School Harbin Institute of Technology (Shenzhen) Shanghai Jiao Tong University and Beijing Academy of Artificial Intelligence (BAAI) S

ISBN: (纸本)9798331314385

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and short-term outcome pressure. As a consequence, good performance on standard benchmarks does not guarantee success in real-world scenarios. To address these problems, we present Touchstone, a large-scale collaborative segmentation benchmark of 9 types of abdominal organs. This benchmark is based on 5,195 training CT scans from 76 hospitals around the world and 5,903 testing CT scans from 11 additional hospitals. This diverse test set enhances the statistical significance of benchmark results and rigorously evaluates AI algorithms across out-of-distribution scenarios. We invited 14 inventors of 19 AI algorithms to train their algorithms, while our team, as a third party, independently evaluated these algorithms. In addition, we also evaluated pre-existing AI frameworks—which, differing from algorithms, are more flexible and can support different algorithms—including MONAI from NVIDIA, nnU-Net from DKFZ, and numerous other open-source frameworks. We are committed to expanding this benchmark to encourage more innovation of AI algorithms for the medical domain.

关键词：

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：