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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

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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...

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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

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq 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 Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of Engineering & Technology 2023.

关键词： Machine learning

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Towards safe data flow processing by integration of design by contract in deterministic UML activities

Towards safe data flow processing by integration of design b...

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XXII International Symposium on Information, Communication and Automation Technologies, ICAT

作者： Zamira Daw Marcus Vetter Josef Boercsoek Institute of Embedded Systems Hochschule Mannheim-University of Applied Sciences Mannheim Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

Data flow processing is a common task of embedded systems which is usually modeled as a pipeline. Errors in a block of this pipeline can be propagated through it thus leading to unexpected and erroneous behaviors. For safety related applications, this pipeline has to be able to identify and react to failures. The DMOSES model-driven development method uses deterministic UML activities to describe and implement data flow processing. This method ensures deterministic behavior of concurrent processing. Design by Contract defines formal, precise and verifiable interfaces for software components. We propose a development method for safe data flow processing based on the integration of this concept in deterministic UML activities. This integration allows the identification of errors by detection of contracts violation. This paper presents an extension of the DMOSES tool for contracts verification at the model level and their monitoring at runtime.

关键词： Unified modeling language Contracts Monitoring Embedded systems Object oriented modeling Safety Pins

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Supporting mobility in content-based publish/subscribe middleware

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2672卷 103-122页

作者： Fiege, Ludger Gärtner, Felix C. Kasten, Oliver Zeidler, Andreas Department of Computer Science Databases Distributed System Group D-64283 Darmstadt Germany School of Computer and Communication Sciences Distributed Programming Laboratory CH-1015 Lausanne Switzerland Department of Computer Science Distributed Systems Group CH-8092 Zurich Switzerland

Publish/subscribe (pub/sub) is considered a valuable middleware architecture that proliferates loose coupling and leverages reconfigurability and evolution. Up to now, existing pub/sub middleware was optimized for static systems where users as well as the underlying system structure were rather fixed. We study the question whether existing pub/sub middleware can be extended to support mobile and location-dependent applications. We first analyze the requirements of such applications and distinguish two orthogonal forms of mobility the system-centric physical mobility and an application-centric logical mobility (where users are aware that they are changing location). We introduce location-dependent subscriptions as a suitable means to exploit the power of the event-based paradigm in mobile applications. Briefly spoken, location-dependency refines a subscription to accept only events related to a mobile user's current location. Implementations for both forms of mobility are presented within the content-based pub/sub middleware REBECA, drawing from its refined routing capabilities (namely, covering and merging). © IFIP International Federation for Information Processing 2003.

关键词： Location

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Ensuring Information Security in the Intelligent Scientific and Technical Information systems 15

Ensuring Information Security in the Intelligent Scientific ...

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15th International Scientific and Practical Conference on Environment. Technology. Resources, ETR 2024

作者： Kerimov, Komil Azizova, Zarina Bekkamov, Fayzi Rakhimov, Mekhriddin Ochilov, Mannon Department of System and Applied Programming Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Information Security Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Library Information Systems Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi Tashkent Uzbekistan Department of Computer Systems Tashkent University of Information Technologies Named after Muhammad al-Khwarizmi Tashkent Uzbekistan

ISBN: (纸本)9781713899570

Scientific and scientific-technical information is a valuable tool for the development of education, technology and society as a whole. The increase in the volume of information and the development of information networks of data exchange requires special means to ensure information protection of data. Methods, means and systems for information security of scientific, technical and scientific-educational resources in intellectual information systems are of particular importance. The purpose of the research is to develop methods and software tools to ensure information security of valuable scientific and technical information resources in intelligent information systems. The proposed solution for intrusion detection in intelligent system is a web application firewall, which is used for enhanced security, detecting and preventing attacks before they reach the web application. It will protect the system from a whole range of attacks while allowing HTTP traffic monitoring and analyzing small changes or persistent state online. The Web Application Firewall (WAF) has the following features: logging of all HTTP protocol transactions, including request termination permissions and logging of the response;HTTP traffic can be examined in real time to detect attacks;preventing attacks before they reach the web application. This work is performed within the framework of the project on creation of an integrated intelligent system "SMART TUIT", which includes several subsystems (Information Retrieval, Voice Recognition, Pattern Recognition, Scientific Information Assessment, Geoinformation system). © 2024 Komil Kerimov, Zarina Azizova, Fayzi Bekkamov, Mekhriddin Rakhimov, Mannon Ochilov.

关键词： Intelligent systems

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Social Engineering Attacks Detection Approach

Social Engineering Attacks Detection Approach

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

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

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.

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Structure and Functioning of Information systems of Background Monitoring of Landscape Elements of Gorgany Nature Reserve

Structure and Functioning of Information Systems of Backgrou...

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International Conference on Advanced computer Information Technologies (ACIT)

作者： Yaroslav Nykolaychuk Yaroslav Petrashchuk Olena Slobodian Ihor Pitukh Taras Grynchyshyn Lyubov Nykolaychuk Volodymyr Hryha Department of Specialized Computer Systems Ternopil National Economic University Ternopil Ukraine Gorgany nature reserve Nadvirna Ukraine Department of Programming and Information Technologies Nadvirna College by National Transport University Nadvirna Ukraine Department of Social Communication and Law Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk Ukraine Department of Computer Engineering and Electronics Vasyl Stefanyk Precarpathian National University Ivano-Frankivsk Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

This paper discusses the structural organization of the background monitoring system (BMS) of the transboundary UNESCO World Heritage Site “Beech forests of the Carpathians and ancient beech forests of Germany” using actual data and information from Gorgany Nature Reserve in Ivano-Frankivsk, Ukraine. The features of the structure and functions of background monitoring of the protected natural resources, forests and wildlife of Gorgany Nature Reserve is based on modern methods of collecting and processing of digital data, implementation of the principles of Internet of Things and cloud technologies, combined with GPS-systems, sensor networks with the use of optical and fiber-optic telecommunication channels. The information technology of the background monitoring system is based on figurative cluster models of monitoring objects according to theoretical principles of statistical, correlatory, spectral, cluster, logic-statistical and entropy analysis.

关键词： Monitoring Forestry Correlation Optical fiber sensors Optical fibers Biological system modeling

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Research of Neural Network Methods of Visual Defectoscopy of Metal Structures

Research of Neural Network Methods of Visual Defectoscopy of...

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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Alexander Chernikov Elena Smirnova Oleg Zhavoronkov Higher School of Automation and Robotics Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia Department of System Programming Saint Petersburg State University St. Petersburg Russia Computer Vision Systems LLC St. Petersburg Russia

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation – 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526.

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