检索结果-内蒙古大学图书馆

International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Elias Dritsas Maria Trigka Phivos Mylonas Industrial Systems Institute Athena Research and Innovation Center Patras Greece Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9798331504502

ISBN: (纸本)9798331504519

The Diffie-Hellman Key Exchange Protocol (DHKE) is a fundamental element of modern cryptographic systems, enabling secure key exchange over unsecured channels. The present research work aims to provide a comprehensive analysis of DHKE, with a dual focus on performance and security. We examine the protocol’s robustness against classical and emerging threats, particularly in the context of the Discrete Logarithm Problem (DLP) and the advent of quantum computing. Performance is evaluated by measuring execution times for key lengths of 512 and 1024 bits, each recorded over 100 iterations. The results are analyzed to provide insights into both computational efficiency and variability, with graphical representations to illustrate the findings. The study underscores the balance between security and performance in DHKE and offers recommendations for future enhancements to maintain cryptographic resilience in the face of advancing computational capabilities.

关键词： Performance evaluation Protocols Quantum computing Parallel processing Length measurement Software Robustness Computational efficiency Cryptography Resilience

来源：评论

学校读者我要写书评

暂无评论

AI-based Object Detection for Assisting the Visually Impaired People 5

AI-based Object Detection for Assisting the Visually Impaire...

引用

5th International Conference on Mobile Computing and Sustainable informatics, ICMCSI 2024

作者： Sameer, Syed Madan, Parul Kannan, Sathish Upadhye, Vijay Jagdish Patil, Harshal Rajkumar, S. Campus Department of Science and Technology Karnataka Bengaluru560012 India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha Institute of Medical and Technical Sciences Department of VLSI Microelectronics Saveetha School of Engineering Tamil Nadu Chennai602105 India Parul Institute of Applied Sciences Parul University Research and Development Cell Department of Microbiology Gujarat Waghodia India Symbiosis Institute of Technology Maharashtra Pune412 115 India Hawassa University Faculty of Manufacturing Institute of Technology Department of Mechanical Engineering Ethiopia

ISBN: (纸本)9798350395235

In recent decades, vision problems have become more common. One significant barrier is that people who are visually impaired generally require assistance performing their daily tasks. As a result, developing a technological solution to this challenge is critical. Implementing an automatic object identification system can enable visually impaired people to roam independently. The study employs two Artificial Intelligence (AI) models, a Region-based Fully Convolutional Network (RFCN) and a Mask Region-based Convolutional Neural Network (Mask RCNN), to detect objects and assess their performance. The evaluation demonstrates RFCN's outstanding performance with an impressive Mean Average Precision (mAP) score of 0.825. The Raspberry Pi processor is used as a vital component in the process of hardware development. The RFCN model is integrated into the processor to aid in the identification of objects collected by the system's picamera. The detected objects are communicated to users via auditory feedback. The hardware system also includes an ultrasonic sensor, which provides distance information for the detected objects. This full hardware solution is specifically developed to help visually impaired people overcome mobility issues in both indoor and outdoor settings. The suggested system seeks to improve the autonomy and safety of visually impaired individuals in their day-to-day activities by seamlessly mixing advanced technologies such as AI and embedded systems. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Design and implementation of obstacle detection system for powered wheelchairs 7

Design and implementation of obstacle detection system for p...

引用

7th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2022

作者： Tatsis, Giorgos Koritsoglou, Kyriakos Fudos, Ioannis Karvounis, Evaggelos Votis, Konstantinos Tzovaras, Dimitrios Information Technologies Institute Centre for Research and Technology Hellas Ioannina Greece Information Technologies Institute Centre for Research and Technology Hellas Thermi57001 Greece University of Ioannina Dept of Computer Science and Engineering Ioannina Greece University of Ioannina Campus of Arta Department of Informatics and Telecommunications Arta Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

In this paper a detailed description of the design and implementation of a system capable of detecting various obstacles for wheelchairs is provided. This system is part of a larger project that its goal is to create intelligent applications for patients using powered wheelchairs. The system is implemented on an electric wheelchair using low-cost ultrasonic and infrared sensors. All tests took place in indoor environment inside our laboratories, and the performance of the system is found to be adequate for the purposes of our project. © 2022 IEEE.

关键词： Ultrasonic applications

来源：评论

学校读者我要写书评

暂无评论

Managing re-identification risks while providing access to the All of Us research program (feb, 10.1093/jamia/ocad021, 2023)

引用

JOURNAL OF THE AMERICAN MEDICAL informatics ASSOCIATION 2023年第5期30卷 1007-1007页

作者： Xia, Weiyi Basford, Melissa Carroll, Robert Clayton, Ellen Wright Harris, Paul Kantacioglu, Murat Liu, Yongtai Nyemba, Steve Vorobeychik, Yevgeniy Wan, Zhiyu Malin, Bradley A. Department of Biomedical Informatics Vanderbilt University Medical Center Nashville Tennessee USA Vanderbilt Institute for Clinical and Translational Research Vanderbilt University Medical Center Nashville Tennessee USA Law School Vanderbilt University Nashville Tennessee USA Department of Pediatrics Vanderbilt University Medical Center Nashville Tennessee USA Department of Health Policy Vanderbilt University Medical Center Nashville Tennessee USA Department of Biomedical Engineering Vanderbilt University Nashville Tennessee USA Department of Computer Science University of Texas at Dallas Dallas Texas USA Department of Computer Science Vanderbilt University Nashville Tennessee USA Department of Computer Science and Engineering Washington University in St. Louis St. Louis Missouri USA Department of Biostatistics Vanderbilt University Medical Center Nashville Tennessee USA

Objective The All of Us research Program makes individual-level data available to researchers while protecting the participants’ privacy. This article describes the protections embedded in the multistep access process, with a particular focus on how the data was transformed to meet generally accepted re-identification risk *** At the time of the study, the resource consisted of 329 084 participants. Systematic amendments were applied to the data to mitigate re-identification risk (eg, generalization of geographic regions, suppression of public events, and randomization of dates). We computed the re-identification risk for each participant using a state-of-the-art adversarial model specifically assuming that it is known that someone is a participant in the program. We confirmed the expected risk is no greater than 0.09, a threshold that is consistent with guidelines from various US state and federal agencies. We further investigated how risk varied as a function of participant *** The results indicated that 95th percentile of the re-identification risk of all the participants is below current thresholds. At the same time, we observed that risk levels were higher for certain race, ethnic, and *** While the re-identification risk was sufficiently low, this does not imply that the system is devoid of risk. Rather, All of Us uses a multipronged data protection strategy that includes strong authentication practices, active monitoring of data misuse, and penalization mechanisms for users who violate terms of service.

关键词： data privacy data sharing electronic health records All of Us research Program

来源：评论

学校读者我要写书评

暂无评论

Enhancing the clinical relevance of haemorrhage prediction models in trauma

引用

Military Medical research 2024年第3期11卷 467-468页

作者： Sankalp Tandle Jared M.Wohlgemut Max E.R.Marsden Erhan Pisirir Evangelia Kyrimi Rebecca S.Stoner William Marsh Zane B.Perkins Nigel R.M.Tai Centre for Trauma Sciences Blizard InstituteQueen Mary University of LondonLondon E12ATUK The Royal London Hospital Barts Health NHS TrustLondon E11FRUK Academic Department of Military Surgery and Trauma Research and Clinical InnovationThe Royal Centre for Defence MedicineBirmingham B152WBUK Department of Electronic Engineering and Computer Science Queen Mary University of LondonLondon E14NSUK

We read with interest the recent systematic reviewaArtificial intelligence and machine learning for hemorrhagic trauma careoby Peng et al.[1],which evaluated literature on machine learning(ML)in the management of trau... 详细信息

关键词： Trauma Injury Blood transfusion Massive transfusion Prediction Artificial intelligence Machine learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Secure Cross-Border Collaboration among Law Enforcement Agencies for Facial Biometric Search

Enhancing Secure Cross-Border Collaboration among Law Enforc...

引用

Electronic engineering, Information technology & Education (EEITE), International Conference in

作者： Kyriaki Miniadou Asterios Leonidis Georgios Th. Papadopoulos Constantine Stephanidis Institute of Computer Science (ICS) Foundation for Research and Technology - Hellas (FORTH) Heraklion Greece Department of Informatics and Telematics Harokopio University of Athens Athens Greece Department of Computer Science University of Crete Heraklion Greece

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

Addressing the growing challenge of combating international crime involves the development of secure and efficient methodologies that allow Law Enforcement Agencies to exchange information seamlessly, without being hindered by time-consuming bureaucratic processes. In this context, we present a solution centered on facial biometric search methodologies. Our approach underscores the importance of employing accurate and reliable methods to assess image data similarity, particularly in the domain of facial images, which pose unique challenges due to subtle variations. We propose a comprehensive solution that harnesses hashing techniques and homomorphic encryption. By doing so, our approach ensures secure data exchange while safeguarding confidentiality and integrity. We firmly believe that our approach will substantially improve collaboration in law enforcement efforts and make significant contributions to global security.

关键词： Data privacy Law enforcement Scalability Education Collaboration Fingerprint recognition Regulation

来源：评论

学校读者我要写书评

暂无评论

ICSGD-Momentum: SGD Momentum based on Inter-gradient Collision 22

ICSGD-Momentum: SGD Momentum based on Inter-gradient Collisi...

引用

22nd IEEE International Conference on Industrial informatics, INDIN 2024

作者： Zou, Weidong Cao, Weipeng Xia, Yuanqing Zhong, Bineng Li, Dachuan School of Automation Beijing Institute of Technology Beijing China Shenzhen China Guangxi Key Lab of Multi-source Information Mining & Security Guangxi Normal University Guilin China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9798331527471

Deep neural networks (DNNs) are widely used in fields like computer vision and natural language processing. A key component of DNN training is the optimizer. SGD-Momentum is popular in many DNN methodologies, such as ResNet and DenseNet, due to its simplicity and effectiveness. However, its slow convergence rate limits its use. To overcome this, we introduce inter-gradient collision into SGD-Momentum, inspired by the elastic collision model in physics. This new method, called ICSGD-Momentum, aims to improve convergence. We provide theoretical proof of convergence and establish a regret bound for ICSGD-Momentum. Experiments on benchmarks including function optimization, CIFAR-100, ImageNet, Penn Treebank, COCO, and YCB-Video show that ICSGD-Momentum accelerates training and enhances the generalization performance of DNNs compared to optimizers like SGD-Momentum, Adam, RAdam, Adabound, and AdaBelief. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Generative AI-Enabled Quantum Encryption Algorithm for Securing IoT-Based Healthcare Application Using Blockchain

引用

IEEE Internet of Things Journal 2025年

作者： Prajapat, Sunil Kumar, Pankaj Das, Ashok Kumar Muhammad, Ghulam Central University of Himachal Pradesh Srinivasa Ramanujan Department of Mathematics Dharamshala176215 India International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11543 Saudi Arabia

The integration of Artificial Intelligence (AI) with the Internet of Things (IoT) has transformed numerous domains through the AI of Things (AIoT). Nonetheless, AIoT encounters issues related to energy usage and carbon emissions as mobile technology continues to progress. Generative AI (GAI) possesses significant potential to mitigate carbon emissions associated with AIoT, owing to its higher reasoning and generative powers. Conventional security protocols frequently encounter issues with computational efficiency, latency, and overall security comprehensiveness. Blockchain technology, characterized by its decentralized and immutable properties, is a viable approach for improving electronic healthcare data transmission and node authentication in IoT networks. This research examines secure data transmission and node encryption in IoT systems, with a particular emphasis on data management. Conventional approaches encounter constraints in computational efficiency, latency, and comprehensive security. This study presents a novel protocol that combines GAI and blockchain technology with quantum encryption to enhance authentication and ensure secure data transmission. The algorithm comprises multiple consecutive processes, including the encoding and transmission of node requests, followed by the authentication process utilizing hash functions and digital signatures. The authentication approach utilizes a challenge-response technique, guaranteeing that only nodes with authentic credentials can advance. Thereafter, a dynamic key exchange protocol and quantum encryption method provide secure data delivery. The results indicate the procedure’s effectiveness in ensuring secure and regulated access to patient data, underscoring its significance in medical facilities. The system’s functionalities are augmented by a thorough evaluation employing machine learning. The findings indicate that the system exhibits an accuracy of 99.4%, precision of 99.10%, recall of 98.66%, F1-score of

关键词： Quantum computers

来源：评论

学校读者我要写书评

暂无评论

Impact of Expert academic Teaching Quality and its Performance Based on BiLSTM-Deep CNN Network 7

Impact of Expert Academic Teaching Quality and its Performan...

引用

7th International Conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Shukla, Tushar Dhar Acharjee, Purnendu Bikash Chethan, C. Thulasimani, T. Sindhu, M. Sharma, Sanjiv University Institute of Teachers Training & Research Chandigarh University Mohali India CHRIST University Pune India Sri Venkateshwara College of Engineering Department of Information Science and Engineering Bengaluru India Bannari Amman Institute of Technology Department of Mathematics Tamilnadu Sathyamangalam India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India Madhav Institute of Technology and Science Department of IT Madhya Pradesh Gwalior India

ISBN: (纸本)9798350340600

Undergraduate and postgraduate students from eight different departments at a UK institution participated in organized conversations about the impact of teachers' research activities on their education. In both samples, positive responses greatly outnumbered negative ones. There was an increase in positive feedback on professors' research when the overall quantity and quality of research in a specific field (as measured by research Assessment Exercise [RAE] ratings) improved. Undergraduate samples with higher RAE scores were more likely to have negative feedback on research than graduate student samples. Both graduate and undergraduate students agreed that lecturers' research increased the instructor's credibility, relevance, and knowledge, as well as piqued and maintained their own interest, engagement, and drive. Data processing, feature selection, and model training are the first steps in the proposed approach. The data are changed from their raw form into a form suitable for academic use during the data pre-processing phase. They are employing Information Gain and Symmetric Uncertainty for feature selection. Following the feature selection process, the models are trained using BiLSTM-CNN. Both the BiLSTM and the CNN methods are inferior to the proposed method. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Multi-objective VNF Placement Optimization with NSGA-III 1st

Multi-objective VNF Placement Optimization with NSGA-III

引用

1st International Conference on Advances in Computing research, ACR’23

作者： Bekhit, Mahmoud Fathalla, Ahmed Eldesouky, Esraa Salah, Ahmad Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Kent Institute Australia Melbourne Australia Department of Mathematics Faculty of Science Suez Canal University Ismailia Egypt Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia College of Computers and Informatics Zagazig University Zagazig Egypt College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (纸本)9783031337420

With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within constrained resources. This research investigates the challenge of mapping and scheduling VNFs as a multi-objective optimization problem. The state-of-the-art methods have focused on optimizing the mapping or scheduling of VNFs while considering one or two objectives continuously. In this study, we aim to optimize two objectives: minimizing the link capacity cost and maximizing the average resource utilization of each virtual machine. To address this problem, an adaptation of the NSGA-III optimization algorithm is proposed and thoroughly evaluated through a set of experiments. In terms of objective values, the results outlined that the proposed method outperformed the other methods of comparison by a significant margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mapping

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：