检索结果-内蒙古大学图书馆

2023 IEEE INFOCOM Conference on computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Hamdan, Mosab Eldhai, Arwa M. Abdelsalam, Samah Ullah, Kifayat Bashir, Ali Kashif Marsono, M.N. Kon, Fabio Batista, Daniel Macêdo Department of Computer Science Brazil University of Science and Technology Faculty of Engineering Sudan Khartoum University Faculty of Mathematical Sciences and Informatics Sudan Manchester Metropolitan University Department of Computing and Mathematics United Kingdom Universiti Teknologi Malaysia Faculty of Electrical Engineering Malaysia

ISBN: (纸本)9781665494274

The Internet of Things (IoT), like other network infrastructures, requires Intrusion Detection Systems (IDSs) to be protected against attacks. When deploying an IDS in IoT-based smart city environments, the balance between latency and node capacity must be considered, which justifies a distributed IDS with specific classifiers based on the location of the system processing nodes. This paper proposes a two-level classification technique for collaborative anomaly-based IDSs deployed on fog and edge nodes. A Gradient Boosting Classifier (GBC) is used in the lower layer classifier at the edge, while a Convolutional Neural Network (CNN) is used in the upper layer classifier at the fog. Experimentation has demonstrated that the suggested IDS architecture outperforms previous solutions. For instance, in some scenarios, when comparing our proposal with Random Forest, the former obtained an accuracy equal to 99.1%, while the latter obtained 95.3%. Furthermore, our proposal can better select the most important network traffic features, reducing 76% of the data to be analyzed and improving privacy. © 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

Deep learning at the service of metaheuristics for solving numerical optimization problems

引用

Neural computing and Applications 2025年 1-36页

作者： Oyelade, Olaide N. Ezugwu, Absalom E. Saha, Apu K. Thieu, Nguyen V. Gandomi, Amir H. School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Bangladesh Unit for Data Science and Computing North-West University 11 Hoffman Street Potchefstroom2520 United States Department of Mathematics National Institute of Technology Agartala Tripura Agartala799046 India Faculty of Computer Science Phenikaa University Yen Nghia Hanoi Ha Dong12116 Viet Nam Department of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

Integrating deep learning methods into metaheuristic algorithms has gained attention for addressing design-related issues and enhancing performance. The primary objective is to improve solution quality and convergence speed within solution search spaces. This study investigates the use of deep learning methods as a generative model to learn historical content, including global best and worst solutions, solution sequences, function evaluation patterns, solution space characteristics, population modification trajectories, and movement between local and global search processes. An LSTM-based architecture is trained on dynamic optimization data collected during the metaheuristic optimization process. The trained model generates an initial solution space and is integrated into the optimization algorithms to intelligently monitor the search process during exploration and exploitation phases. The proposed deep learning-based methods are evaluated on 55 benchmark functions of varying complexities, including CEC 2017 and compared with 13 biology-based, evolution-based, and swarm-based metaheuristic algorithms. Experimental results demonstrate that all the deep learning-based optimization algorithms achieve high-quality solutions, faster convergence rates, and significant performance improvements. These findings highlight the critical role of deep learning in addressing design issues, enhancing solution quality, trajectory, and performance speed in metaheuristic algorithms. © The Author(s) 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Studying the Fundamentals of Internet of Things (IoT) in the Healthcare Applications 1

Studying the Fundamentals of Internet of Things (IoT) in the...

引用

1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Kadam Rangrao, Shrikant Patil Abhijit, Seema Sharma, Lakshay Rani, D Shobha Ukirade, Chaitali Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Computer Science Engineering Karad India Jaywant College of Management Karad India Indraprastha Institute of Information Technology Delhi India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Obstetrics and Gynecology Karad India

ISBN: (纸本)9798350360707

The Internet of Things (IoT) has brought smart healthcare systems to the medical industry. These systems are typically made up of a network, a remote server, and sensors with smart capabilities. The primary goals of this system are to offer multidimensional feature monitoring and fundamental therapy recommendations. The primary goals of Internet of Things (IoT)-based healthcare services are to enhance quality of life and offer a great user experience at an affordable price. The primary purpose of IoT is to give elderly patients with chronic illnesses access to trustworthy, efficient, and intelligent healthcare services as well as connectivity to the medical resources that are readily available. Thus, many studies are developed on the different applications which worked on the IoT for the healthcare which includes wearable as well as non-wearable devices or machines. Thus, it makes the users to obtain the data from anywhere and wherever required for the study or analysis of the patients. In the meantime, the Internet of Things is expanding to include even the tiniest sensors and the fundamentals of automation and machine-to-machine communication. © 2024 IEEE.

关键词： healthcare internet of things (IoT) network service

来源：评论

学校读者我要写书评

暂无评论

Hybrid Machine Learning Approach for Enhanced Vulnerability Detection in Cloud Environments Using NIST and MITRE Frameworks 5

Hybrid Machine Learning Approach for Enhanced Vulnerability ...

引用

5th International Conference on Advanced Research in computing, ICARC 2025

作者： Lasantha, N W Chanaka Maduranga, M.W.P. Abeysekara, Ruvan Tilwari, Valmik Chakraborty, Nilotpal Sharma, Debashree Iic University of Technology Faculty of Graduate Studies Phnom Penh Cambodia University of Sri Jayewardenepura Department of Electrical and Electronic Engineering Nugegoda Sri Lanka Bcas Campus Faculty of Computing Colombo Sri Lanka Indian Institute of Information Technology Department of Computer Science Engineering Guwahati India Indian Institute of Information Technology Department of Electronics & Communication Engineering Guwahati India

ISBN: (纸本)9798331530983

Cloud security is challenged by constant adaptive cyber threats and traditional detection methods lack real time adaptability. In this paper, we propose a new hybrid ML approach stitching data from National Institute of Standards and Technology (NIST) and MITRE Adversarial Tactics, Techniques and Common Knowledge (ATT&CK) databases together. In contrast to existing methods, this framework combines, in unique and unprecedented fashion, ensemble ML models and Realtime data processing for increased detection accuracy and reduced false positives. This approach addresses specific challenges in the cloud environments and by leveraging standardised frameworks, it offers actionable audiences for efficient and effective vulnerability management process. The framework is validated by the experimental results which prove its robustness to evolution of the cybersecurity demands. © 2025 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

EOG acquisition system based on ATmega AVR microcontroller

引用

Journal of Ambient Intelligence and Humanized computing 2023年第12期14卷 16589-16605页

作者： Abdel-Samei, Abdel-Gawad A. Shaaban, Abdel-Salam Brisha, Ayman M. El-Samie, Fathi E. Abd Ali, Ahmed S. Department of Electronics Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Department of Process of Control Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Department of Mechanical Engineering Mechatronics Division Faculty of Engineering Assiut University Assiut Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

This paper presents a hardware and software of an electrooculogram (EOG) acquisition system based on ATmega AVR microcontroller for the acquisition of vertical and horizontal eye movements. The presented system is used to acquire a dataset of eye movements for volunteers. This system gives two channels representing vertical and horizontal EOG signals. The frequency range of the EOG signal is known to be 0.1 to 10 Hz, and hence this frequency range is isolated with a High-Pass Filter (HPF) with a cutoff frequency of 0.1 Hz followed by a Low-Pass Filter (LPF) with a cutoff frequency of 10 Hz. The EOG acquisition system is interfaced with an ATmega AVR microcontroller to acquire a dataset that can be used for controlling hardware such as Light Emitting Diodes (LEDs), wheelchair, and robot arm. The presented system is composed of EOG signal acquisition, Ag/AgCl electrodes, analog-to-digital converter through Arduino Mega 2560 board microcontroller unit, trainer board, laptop, keypad, and Liquid Crystal Display (LCD). The eye movement is detected by measuring the potential difference between cornea and retina using five Ag–Agcl disposable electrodes. Different volunteers of different ages at different times have been treated with the presented system to obtain data. Classified vertical and horizontal EOG signals and the basic eye movements e.g., open eye, left, right, up, and down can be used to control robots and wheelchairs for rehabilitation purposes. © 2023, The Author(s).

关键词： Electrodes

来源：评论

学校读者我要写书评

暂无评论

Evaluating importance of AI in Robotics and Automation in Healthcare for Different age Groups 1

Evaluating importance of AI in Robotics and Automation in He...

引用

1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Abu Eid, Aws Ismail Pethkar, Rajendra Huda, Bintul Patil, Jaykar Bhaskar Gatla, Ranjith Kumar Kumbhar, Ramchandra Arab Open University Faculty of Computing Studies Amman Jordan Jaywant College of Engineering and Polytechnic Department of Mechanical Engineering Karad India Sharda University Department of Computer Science & Technology Srinagar India Jaywant Institute of Management Karad India Institute of Aeronautical Engineering Department of Electrical and Electronics Engineering Hyderabad India Department of Radio-Diagnosis Karad India

ISBN: (纸本)9798350360707

Nowadays robotics is mostly used in the world. There are many industries which used robots for reducing time and to have high precision of work. The use of artificial intelligence is now increasing which helps in automations and processing of machines. Thus, the focus of study is to find the different applications of automation of robotics (i.e. robotic process automation) in the field of healthcare and its impact on the employment of medical field. Four major categories can be used to group AI applications in healthcare: expressive, analytical, prognostic, and prescriptive. The only way to close the skills gap in the healthcare industry is to increase the application of artificial intelligence. Hospitals are developing mental commit robots to treat their patients. Through physical contact, these robots can have an impact on humans' psyche, physiology, and social interactions. Thus, in coming time most of the healthcare industry will be with the robots which will reduces the human interventions with the patients through one of the host servers. © 2024 IEEE.

关键词： Medical robotics

来源：评论

学校读者我要写书评

暂无评论

Influence of donor age on liver transplantation outcomes: A multivariate analysis and comparative study

引用

World Journal of Gastrointestinal Surgery 2024年第2期16卷 331-344页

作者： Miran Bezjak Ivan Stresec Branislav Kocman Stipislav Jadrijević Tajana Filipec Kanizaj Miro Antonijević Bojana Dalbelo Bašić Danko Mikulić Department of Surgery University Hospital MerkurZagreb 10000Croatia Department of Electronics MicroelectronicsComputer and Intelligent SystemsFaculty of Electrical Engineering and ComputingZagreb 10000Croatia Department of Gastroenterology University Hospital MerkurZagreb 10000Croatia Development of Software Nanobit Ltd.Zagreb 10000Croatia

BACKGROUND The growing disparity between the rising demand for liver transplantation(LT)and the limited availability of donor organs has prompted a greater reliance on older liver ***,utilizing livers from elderly donors has been associated with outcomes inferior to those achieved with grafts from younger *** accounting for additional risk factors,we hypothesize that the utili-zation of older liver grafts has a relatively minor impact on both patient survival and graft *** To evaluate the impact of donor age on LT outcomes using multivariate analysis and comparing young and elderly donor *** In the period from April 2013 to December 2018,656 adult liver transplants were performed at the University Hospital *** multivariate Cox propor-tional hazards models were developed to independently assess the significance of donor *** age was treated as a continuous *** approach involved univariate and multivariate analysis,including variable selection and assessment of interactions and ***,to exemplify the similarity of using young and old donor liver grafts,the group of 87 recipients of elderly donor liver grafts(≥75 years)was compared to a group of 124 recipients of young liver grafts(≤45 years)from the *** rates of the two groups were estimated using the Kaplan-Meier method and the log-rank test was used to test the differences between *** Using multivariate Cox analysis,we found no statistical significance in the role of donor age within the constructed *** when retained during the entire model development,the donor age's impact on survival remained insignificant and transformations and interactions yielded no substantial effects on *** insigni-ficance and low coefficient values suggest that donor age does not impact patient survival in our ***,there was no statistical evidence that the five developed models did not adhe

关键词： Liver transplantation Elderly donors Survival analysis Postoperative complications Cox proportional hazard models

来源：评论

学校读者我要写书评

暂无评论

Task Offloading and Resource Allocation in IoT Based Mobile Edge computing Using Deep Learning

引用

computers, Materials & Continua 2023年第8期76卷 1463-1477页

作者： Ily s Abdullaev Natalia Prodanova KAruna Bhaskar ELaxmi Lydia Seifedine Kadry Jungeun Kim Dean of the Faculty of Economics Department of Management and MarketingFaculty of EconomicsUrgench State UniversityUrganch220100Uzbekistan Basic Department Financial Control Analysis and Audit of Moscow Main Control DepartmentPlekhanov Russian University of EconomicsMoscow117997Russia Department of Computer Science and Engineering KL Deemed to UniversityVaddeswaramGunturAndhra PradeshIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajamIndia Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Recently,computation offloading has become an effective method for overcoming the constraint of a mobile device(MD)using computationintensivemobile and offloading delay-sensitive application tasks to the remote cloud-based data *** city benefitted from offloading to edge *** a mobile edge computing(MEC)network in multiple *** comprise N MDs and many access points,in which everyMDhasM independent real-time *** study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization(TORA-DLSGO)*** proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,which enables an optimum offloading decision to minimize the system *** addition,an objective function is derived based on minimizing energy consumption subject to the latency requirements and restricted *** TORA-DLSGO technique uses the deep belief network(DBN)model for optimum offloading ***,the SGO algorithm is used for the parameter tuning of the DBN *** simulation results exemplify that the TORA-DLSGO technique outperformed the existing model in reducing client overhead in the MEC systems with a maximum reward of 0.8967.

关键词： Mobile edge computing seagull optimization deep belief network resource management parameter tuning

来源：评论

学校读者我要写书评

暂无评论

Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

引用

computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

来源：评论

学校读者我要写书评

暂无评论

Two-Operation Buffering based on Dynamic Optical RAM 17

Two-Operation Buffering based on Dynamic Optical RAM

引用

17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Semenov, Andriy Tsyrulnyk, Serhii Baraban, Serhii Semenova, Olena Rudyk, Andrii Khloba, Anton Vinnytsia National Technical University Faculty of Information Electronic Systems Vinnytsia Ukraine Vinnytsia National Agrarian University Department of Computer Sciences and Digital Economy Vinnytsia Ukraine Poznan University of Technology Faculty of Computing and Telecommunications Poznan Poland National University of Water and Environmental Engineering Department of Automation Electrical Engineering and Computer-Integrated Technologies Rivne Ukraine

ISBN: (纸本)9798331520564

The authors of this paper propose a block diagram for a dual-operating buffer on a dynamic optical RAM. The buffer consists of two dynamic optical RAMs, each controlled separately to allow for simultaneous writing and reading of data, thereby improving performance. This setup enables data to be read from the buffer while new data is being written to it. Implementing a dual-operating buffer on a dynamic optical RAM has the potential to enhance the performance of high-speed data transmission in telecommunications networks. The authors conducted numerical calculations to compare failure probabilities between single-operation and dual-operation buffers on dynamic optical RAM. The results indicated that using a dual-operating buffer significantly reduces the probability of failure with the same buffer memory capacity compared to a single-operating buffer. Additionally, the authors analyzed the effectiveness of the proposed dual-operating buffer. The analysis confirmed that exploiting dynamic optical memory for buffering enhances data transfer speed and efficiency due to the inherent properties of optical data transfer, such as high bandwidth and low latency. © 2024 IEEE.

关键词： Dynamic random access storage

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：