检索结果-内蒙古大学图书馆

13th International Conference on Dependable systems, Services and Technologies, DESSERT 2023

作者： Lysenko, Sergii Vorobiov, Volodymyr Bokhonko, Oleksandr Gaj, Piotr Savenko, Oleg Woloszyn, Jacek Khmelnitsky National University Department of Computer Engineering and Information Systems Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Khmelnitsky National University Department of Computer Engineering and System Programming Khmelnitsky Ukraine Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics and Teleinformatics Radom Poland

ISBN: (纸本)9798350396119

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy. © 2023 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Sensing Metric-Based Hybrid Underlay/Overlay Transmission Framework for CR-IoT Networks for Smart City Applications 7

Sensing Metric-Based Hybrid Underlay/Overlay Transmission Fr...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Bala, Indu Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results. © The Institution of engineering & Technology 2023.

关键词： Smart city

来源：评论

学校读者我要写书评

暂无评论

Ontological Approach to the Formal Specification of the Standard Life Cycle

Ontological Approach to the Formal Specification of the Stan...

引用

Science and Information Conference

作者： Ekaterina Lavrishcheva Software Engineering Department Institute for System Programming of the RAS Prof. MIPT Moscow Russia

ISBN: (纸本)9781479985487

Approach is offered to the formal specification of Standard Life Cycle (LC) of the program systems (PS) by the ontology facilities with purpose automation and generation of the variants LC for making the appropriate kinds process for development different PS. Ontological approach to presentation LC model of the standard ISO/IEC 12207-2007 is included the specification of general, organizational and support processes. These processes are presented in the subject-oriented DSL, which than transformed to XML for realization. One of the processes, the testing process is given in terms of Protégé systems. An eventual result of this system Protégé got generally at accepted to the XML, suitable for implementation tasks testing PS on computer.

关键词： ontology the life cycle standard model of life cycle processes actions task testing DSL description Protégé XML

来源：评论

学校读者我要写书评

暂无评论

Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of engineering & Technology 2023.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Advanced IOT Traffic Light Control system 5

Advanced IOT Traffic Light Control System

引用

5th International Conference on Advances in Computational Tools for engineering Applications, ACTEA 2023

作者： Hamad, Martin Abou El Hajj, Antonio Daou, Roy Abi Zeid Hayek, Ali Haidar, Gaby Abou Lebanese German University Faculty of Public Health Biomedical Technologies Department Lebanon MART Learning Education and Research Center Lebanon University of Kassel Department of Computer Architecture and System Programming Kassel Germany American University of Science and Technology Engineering Faculty Zahle Lebanon

ISBN: (纸本)9798350309959

For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more and more critical, and if not treated smartly this issue will negatively affect drivers by wasting time and fuel gas while waiting for hours in lanes. This paper presents a new and smart way to mitigate this issue in an affordable cost, minimum processing power, and low power consumption. This concept takes into consideration the majority of the cases that may cause congestion and presents a smart and accurate outputs to ease traffic flow leading to the prediction of the peak hours of traffic congestion for smarter control. A model is designed to study the case of a four lanes crossroad with two traffic lights and two LCD monitors. The strategy in reading data is divided into two parts: real data from sensors and pre collected data from google maps to create a kind of a predicted pattern over a certain time interval. The responsiveness of the system is analyzed thoroughly, and the accuracy of all possible cases is carefully considered and evaluated. Each part of the system was tested alone, and the overall system is still in an ongoing testing phase. The results have shown minimum faulty errors and accepted outputs that can lead to safe traffic control decisions. Finally, integrating more IoT devices and sensors between V2V, V2P, V2I with the help of artificial intelligence will definitely optimize this system with higher accuracy. © 2023 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Automatic classification Infectious disease X-ray images based on Deep learning Algorithms 8

Automatic classification Infectious disease X-ray images bas...

引用

8th International Conference on Information Technology and Nanotechnology, ITNT 2022

作者： Makarovskikh, Tatiana Salah, Amir Badr, Amr Kadi, Ammar Alkattan, Hussein Abotaleb, Mostafa South Ural State University System of Programming Department Chelyabinsk Russia Ain Shams University Computers and Systems Engineering Cairo Egypt New England University School of Science and Technology ArmidaleNSW Australia South Ural State University Department of Food and Biotechnology Chelyabinsk Russia

ISBN: (数字)9781665485715

ISBN: (纸本)9781665485715

Recent technological advancements allow deep learning to be employed in practically every aspect of life. Because deep learning techniques are so precise, they can be used in medicine to classify and detect various diseases. The coronavirus (SARSCoV2) epidemic has recently affected global health systems. One of the ways to diagnose SARSCoV2 is with a chest X-ray. This paper proposes a deep learning technique to distinguish SARSCoV2 positive and normal cases. In this study, we fine-Tuned the deep learning models and hyperparameters, and the fine-Tuned deep learning models performed significantly better. To classify X-ray images, we developed a system based on deep learning algorithms that includes five models: Xception, VGG19, ResNet50, DenseNet121, and Inception. We offer deep learning models and algorithms that have been trained and evaluated to support medical efforts and reduce medical staff workload when dealing with SARSCoV2. In addition, the classification model that was proposed yields positive results because it makes use of accurate classification of the SARSCoV2 disease based on medical images. Additionally, the performance of our proposed CNN classification method for medical imaging was evaluated using various edge-based neural networks. The accuracy of tertiary classification with CNN will decrease as the number of classes in the training network grows. In tertiary classification, which includes normal and SARSCoV2 positive images, the proposed model achieved a 0.9897 accuracy. The proposed algorithm achieves a high level of classification accuracy when using the DenseNet121 model for binary classification. © 2022 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

引用

Computer systems Science & engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

来源：评论

学校读者我要写书评

暂无评论

IoT-Based system for Crop Forecasting: Design and Implementation 3

IoT-Based System for Crop Forecasting: Design and Implementa...

引用

3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Sameh, Basant Atef, Menna Makarovskikh, Tatiana Abotaleb, Mostafa Maksimova, Valentina Dernova, Olga El-Kenawy, El-Sayed M. Delta Higher Institute Department of Communications Mansoura Egypt Delta Higher Institute Department of Civil Engineering Mansoura Egypt South Ural State University Dep. of System Programming Chelyabinsk Russia South Ural State University Dep. of Information and Analytical Support Chelyabinsk Russia

ISBN: (纸本)9798350323511

In this paper, we discuss the design of a system for crop forecasting. Despite the presence of a fairly large number of software products for precision farming on the market, many of the existing developments, on the one hand, are not intended to provide data for further analysis by specialists who are not employees of the developer company, and on the other hand, do not ensure food security of the Russian Federation. We have designed a system for the acquisition and subsequent analysis of aerial photographic data. The paper describes the method of presenting data, the process of calculating vegetation indices for a certain date, and provides approaches to modeling the vegetation process using high-quality determinate mathematical models and predicting the yield of a field in the next season, and the cost of this crop. We discuss the opportunities of our system and show the ways of further increasing its quality. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

IoT Cyberattack Detection Approach Based on Energy Consumption Analysis

IoT Cyberattack Detection Approach Based on Energy Consumpti...

引用

IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Kira Bobrovnikova Oleg Savenko Sergii Lysenko Ivan Hurman Department of Computer Engineering and Information Systems Khmelnitsky National University Khmelnitsky Ukraine Department of Computer Engineering and System Programming Khmelnitsky National University Khmelnitsky Ukraine

ISBN: (纸本)9798350333053

Today, the Internet of Things has been widely used and is becoming an increasingly vital part in various areas of human activity, which helps to effectively solve various real-life tasks and problems. The infrastructure of the Internet of Things includes a lot of heterogeneous devices with limited capacities, which makes it difficult to control them in order to detect cyberattacks. The increase in the number of attacks on the infrastructure of the Internet of Things indicates the relevance of developing new solutions for detecting attacks on the networks of the Internet of Things. One of the possible approaches to identify attacks is to analyze the physical parameters associated with IoT devices that describe the behavior of devices on the network, such as power consumption. Power analysis allows you to detect power-hungry attacks such as crypto mining and denial-of-service attacks. The paper proposes a new method for cyberattack detection in the infrastructure of the Internet of Things that is based on the analysis of energy consumption. In order to improve the accuracy of detecting cyberattacks, the approach also uses the analysis of the actions of the IoT software. The proposed approach makes it possible to detect attacks such as DoS/DDoS with high efficiency with a level of detection up to 99.95%.

关键词： Energy consumption Power demand Software Behavioral sciences Internet of Things Object recognition Data mining

来源：评论

学校读者我要写书评

暂无评论

Intelligent system for Classifying of Acoustic Endoscopic Images of the Pancreas Based the Analysis of Walsh Spectra of Local Windows 25

Intelligent System for Classifying of Acoustic Endoscopic Im...

引用

25th International Arab Conference on Information Technology, ACIT 2024

作者： Al-Kasasbeh, Riad Taha Filist, Sergey Shatalova, Olga Kondrashov, Dmitry Sergeevich Shaqadan, Ashraf Korenevskiy, Nikolay A. Al-Habahbeh, Osama M. Tarawneh, Emad Saleh Starkov, Evgeny The University of Jordan Mechatronics Engineering Department Amman Jordan Moscow Polytechnic University Department of Smart Technologies Moscow Russia Southwest State University Department of Biomedical Engineering Kursk Russia Zarqa University Civil Engineering Department Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia South-West State University Russia The University of Jordan Jordan Institute of System Programming The Russian Academy of Sciences Russia

ISBN: (纸本)9798331540012

The purpose of the work is to develop and study methods and algorithms for intelligent classification systems for digital medical images. A method for automatic classification of medical images was developed using neural networks and transparency masks obtained by preliminary image segmentation. This allows you to generate descriptors only for those pixels that are selected by the transparency mask. Also algorithmic and software for classifying medical images has been developed. Experimental testing was carried out on ultrasound images of the pancreas. Differential diagnostics was carried out on control samples. The classes "oncology"and "pancreatitis"were divided. The diagnostic sensitivity by class turned out to be at least 0.8, while the diagnostic specificity is at least 0.85. © 2024 IEEE.

关键词： Ultrasonic imaging

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：