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Ultimately Bounded Output Feedback Control for Networked Nonlinear Systems With Unreliable Communication Channel: A Buffer-Aided Strategy

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1566-1578页

作者： Yuhan Zhang Zidong Wang Lei Zou Yun Chen Guoping Lu the College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China IEEE the Department of Computer Science Brunel UniversityUB83PHUnited Kingdom the College of Information Science and Technology Donghua UniversityShanghai 201620 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the School of Automation Hangzhou Dianzi UniversityHangzhou 310018China the School of Electrical Engineering Nantong UniversityNantong 226019China

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication *** transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear *** the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

关键词： Buffer-aided strategy neural networks nonlinear control output-feedback control unreliable communication channel

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A Network Optimized 3D Intercom Approach For UAV Communication Using 6G Network 1

A Network Optimized 3D Intercom Approach For UAV Communicati...

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1st International Conference on Intelligent Technologies for Sustainable Electric and Communications Systems, iTech SECOM 2023

作者： Premalatha, N. Gayathri, P. Sangavi, N. Ramesh, K. Nandhakumar, R. Samraj, Andrews Pg and Research Department of Computer Science and Applications Namakkal India Mahendra College of Engineering Department of Computer Science and Engineering Namakkal India

ISBN: (纸本)9798350371185

With such motivation, the routing optimization in 3D intercom facility is required when an UAV communication is focused. The ground stations control the autonomous UAVs such that it maintains a high-speed communication in remote areas. A swarm or a group of UAVs, on other hand entails a major issue when there exists an internetworking between them. Hence, the routing between the UAVs in the context of 3D intercom poses a design challenge. The Mobility of Unmanned Ariel Vehicle (UAV) enables the internetworking among them to form a cooperative cluster or swarm behavior. A three-dimensional (3D) intercommunication (intercom) is enabled as a preliminary feature in 6G network that supports high-speed communication. The combination of UAV at a greater altitude of various sizes and 3D intercom facility in 6G supports remote connections but at the cost of energy efficiency and high latency. In this paper, we develop a novel network-optimized 3D intercom (NO3DI) model to increase the connectivity between the UAVs with higher energy efficiency. This novel network-optimized model uses an intelligent Q-learning module to establish routing between the UAVs such that a reliable high-speed communication is maintained between the UAVs, which forms a strong intercommunication between the UAVs. Thus, a high-speed non-latent communication is established between the UAVs and the adoption of 6G networking maintains high data rate even in adhoc environments. The simulation is conducted in matlab to test the ability of internetwork among the UAVs under various UAV sizes and the Q-learning routing is tested in terms of packet delivery rate, latency and energy efficiency. The results of simulation shows that the proposed NO3DI achieves reduced energy consumption and maintains a reliable data rate with a high-speed packet delivery rate. Also, the latency is highly reduced as the Q-learning effectively routes the data packets by maintaining a high-speed communication between the UAVs. © 2023

关键词： Queueing networks

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A Barrier-Based Machine Learning Approach for Intrusion Detection in Wireless Sensor Networks

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computers, Materials & Continua 2025年第3期82卷 4181-4218页

作者： Haydar Abdulameer Marhoon Rafid Sagban Atheer Y.Oudah Saadaldeen Rashid Ahmed Information and Communication Technology Research Group Scientific Research CenterAl-Ayen UniversityThi-Qar64011Iraq College of Computer Sciences and Information Technology University of KerbalaKarbala56001Iraq Enginerring Technical College Al-Ayen UniversityThi-Qar64011Iraq Information Technology College University of BabylonHilla51002Iraq Department of Computer Science College of Education for Pure ScienceUniversity ofThi-QarNasiriyah64001Iraq Artificial Intelligence Engineering Department College of EngineeringAl-Ayen UniversityThi-Qar64001Iraq Department of Computer Science Bayan UniversityErbilKurdistan44001Iraq

In order to address the critical security challenges inherent to Wireless Sensor Networks(WSNs),this paper presents a groundbreaking barrier-based machine learning *** applications like military operations,healthcare monitoring,and environmental surveillance increasingly deploy WSNs,recognizing the critical importance of effective intrusion detection in protecting sensitive data and maintaining operational *** proposed method innovatively partitions the network into logical segments or virtual barriers,allowing for targeted monitoring and data collection that aligns with specific traffic *** approach not only improves the *** are more types of data in the training set,and this method uses more advanced machine learning models,like Convolutional Neural Networks(CNNs)and Long Short-Term Memory(LSTM)networks together,to see coIn our work,we used five different types of machine learning *** are the forward artificial neural network(ANN),the CNN-LSTM hybrid models,the LR meta-model for linear regression,the Extreme Gradient Boosting(XGB)regression,and the ensemble *** implemented Random Forest(RF),Gradient Boosting,and XGBoost as baseline *** train and evaluate the five models,we used four possible features:the size of the circular area,the sensing range,the communication range,and the number of sensors for both Gaussian and uniform sensor *** used Monte Carlo simulations to extract these *** on the comparison,the CNN-LSTM model with Gaussian distribution performs best,with an R-squared value of 99%and Root mean square error(RMSE)of 6.36%,outperforming all the other models.

关键词： Intrusion detection system(IDS) hybrid models of CNN-LSTM WSN extreme gradient boosting(XGBoost)regressor ensemble model

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Social Media Networking Analytics and Growth Perspectives 8th

Social Media Networking Analytics and Growth Perspectives

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8th International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Sabla, Yaashie Gour, Sanjay Mukesh Patel School of Technology Management and Engineering Mumbai India Department of Computer Science and Engineering Jaipur Engineering College and Research Centre Jaipur India

ISBN: (纸本)9789819994854

In the digital age, the significance of social media networking cannot be overstated. Individuals, businesses, and organizations have embraced these platforms as essential tools for communication, brand promotion, and community building. Social media analytics involve the systematic collection and analysis of data to measure the performance of one’s presence on platforms like Facebook, Instagram, Twitter, and LinkedIn. Key performance indicators (KPIs) such as engagement, reach, impressions, and conversion rates are pivotal in assessing the effectiveness of social media strategies. Additionally, understanding audience demographics, content performance, and competitor analysis informs data-driven decision-making. Growth perspectives in social media networking encompass strategies to expand reach, engage audiences, and foster sustainable growth. Consistency in posting, delivering high-quality content, and engaging with users are fundamental principles. Paid advertising, collaborations, and community building are strategies that extend one’s social media reach. Furthermore, data-driven optimization, trend monitoring, and user experience enhancements are indispensable for staying relevant in a dynamic digital landscape. This article is an attempt to provide a concise overview of the critical components related to social media networking along with analytics and growth perspectives. The article encapsulates the essence of social media networking analytics and growth perspectives, offering a foundation for individuals, businesses, and organizations to harness the full potential of these platforms, connect with their target audiences, and achieve enduring growth in the ever-evolving realm of social media. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Decision making

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Adaptive finite-time command-filtered backstepping sliding mode control for stabilization of a disturbed rotary-inverted-pendulum with experimental validation

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JVC/Journal of Vibration and Control 2023年第5-6期29卷 1431-1446页

作者： Mofid, Omid Alattas, Khalid A Mobayen, Saleh Vu, Mai The Bouteraa, Yassine Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Computer Science and Artificial Intelligence College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia School of Intelligent Mechatronics Engineering Sejong University Seoul Korea Republic of Department of Computer Engineering College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Al-Kharj Saudi Arabia University of Sfax Sfax3038 Tunisia

In this paper, the finite-time stabilization of the disturbed and uncertain rotary-inverted-pendulum system is studied based on the adaptive backstepping sliding mode control procedure. For this purpose, first of all, the dynamical equation of the rotary-inverted-pendulum system is obtained in the state-space form in the existence of external disturbances and model uncertainties with unknown bound. Afterward, a novel command filter is defined to enhance the control strategy by consideration of a virtual control input. Therefore, the differential signal is replaced by the output of the command filter to reduce the complicated computing in the control process. Hence, the finite-time convergence of the sliding surface to the origin is attested by using the backstepping sliding mode control scheme according to the Lyapunov theory. Besides, the unknown upper bound of the exterior perturbation and uncertainty is approximated providing the adaptive control technique. Finally, simulations and experimental results are done to demonstrate the impression and proficiency of the suggested method. © The Author(s) 2022.

关键词： Inverted pendulum

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A Deep Study on Encroachment Recognition Model through W-S-N and I-O-T 4

A Deep Study on Encroachment Recognition Model through W-S-N...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Dixit, Krishna Kant Singh, Satyendra Kiran, P. Ravi Al-Attabi, Kassem Sinha, Aashna Angadi, Sanjeev Kumar Gla University Department of Electrical Engineering Mathura India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India Cmr College of Engineering & Technology Department of Ece India The Islamic University Najaf Iraq Uttaranchal University Divison of Research and Innovation School of Applied and Life Sciences Uttarakhand Dehradun India Nutan College of Engineering and Research Computer Science and Engineering Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

The burgeoning challenge of Internet of Things (IoT) technology heralds' transformative capability for agriculture, mainly in enhancing the safety and operational performance of huge-scale farmlands. This paper introduces an revolutionary IoT-based framework that synergizes Global System for Mobile Communication (GSM) and Global Positioning System (GPS) modules to forge a whole, actual-time tracking and intrusion detection answer tailored for agricultural domain names. Our proposed framework is designed to address the dual demanding situations of optimizing farm management practices while ensuring robust safety in competition to capacity intrusions. By deploying a network of brand-new sensors across farmlands, our system enables the seamless collection, evaluation, and transmission of essential environmental statistics, thereby enabling farmers to make knowledgeable alternatives all of sudden. Furthermore, the combination of GSM and GPS technology enhances the tool's functionality to without delay alert farmers about unusual sports activities, making sure immediate reaction to protection breaches. The pilot deployment of our framework demonstrates its effectiveness in no longer best substantially improving tracking accuracy however moreover in bolstering the safety of agricultural lands towards unauthorized get right of entry to. © 2024 IEEE.

关键词： Farms

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Achieving high strength-ductility synergy in a Mg_(97)Y_(1)Zn_(1)Ho_(1) alloy via a nano-spaced long-period stacking-ordered phase

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Journal of Magnesium and Alloys 2023年第4期11卷 1321-1331页

作者： Mingyu Fan Ye Cui Yang Zhang Xinghao Wei Xue Cao Peter K.Liaw Yuansheng Yang Zhongwu Zhang Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001PR China College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001PR China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996-2100USA Institute of Metal Research Chinese Academy of SciencesShenyang 110016PR China

Achieving high strength in Mg alloys is usually accompanied by ductility ***,a novel Mg97Y1Zn1Ho1 at.%alloy with a yield strength of 403 MPa and an elongation of 10%is *** strength-ductility synergy is obtained by a comprehensive strategy,including a lamella bimodal microstructure design and the introduction of nano-spaced solute-segregated 14H long-period stacking-ordered phase(14H LPSO phase)through rare-earth Ho *** lamella bimodal microstructure consists of elongated un-recrystallized(un-DRXed)coarse grains and fine dynamically-recrystallized grains(DRXed regions).The nano-spaced solute-segregated 14H LPSO phase is distributed in DRXed *** outstanding yield strength is mainly contributed by grain-boundary strengthening,18R LPSO strengthening,and fiberlike reinforcement strengthening from the nano-spaced 14H LPSO *** high elongation is due primarily to the combined effects of the bimodal and lamellar microstructures through enhancing the work-hardening capability.

关键词： Mg wrought alloy Mechanical properties Long-period stacking-ordered(LPSO)phase Age-strengthening behavior Strengthening mechanism

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ECDSA-based tamper detection in medical data using a watermarking technique

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 78-87页

作者： Ch, Rupa Vivek K, Naga Srivastava, Gautam Reddy Gadekallu Department CSE VR Siddhartha Engineering College Andhra Pradesh Vijayawada520 007 India Dept of Math and Computer Science Brandon University MB Canada Dept. of Computer Science and Math Lebanese American University Beirut1102 Lebanon Centre of Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara Punjab Rajpura140401 India Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon Lovely Professional University Division of Research and development Phagwara India Jiaxing University College of Information Science and Engineering Jiaxing China

Telemedicine is a form of healthcare delivery that employs communication technology to provide medical care to patients remotely. The use of telemedicine has seen a significant increase in recent years, presenting challenges such as patient privacy, data security, the need for reliable communication technology, and the potential for misdiagnosis without a physical examination. Digital Watermarking can assist in addressing such issues by incorporating a unique identifier into an image that can be used to authenticate its validity. To tackle these issues, this study proposes a robust digital watermarking approach tailored to brain medical images, combining hashing, the Elliptic Curve Digital Signature Algorithm (ECDSA), and the Integer Wavelet Transform-Discrete Cosine Transform (IWT-DCT). This method utilizes the Secure Hash Algorithm (SHA-256) to first segment the brain's Region of Interest (RoI). Subsequently, the hashed RoI, along with an ECDSA signature, is embedded into the high-frequency sub-bands of the medical image using IWT-DCT. The embedding process strategically alters the coefficients of the high-frequency sub-bands to accommodate the signature while minimizing perceptual distortion. The technique leverages the robustness of transformed-domain image watermarking techniques against various attacks and combines it with SHA-256 for integrity and ECDSA for authentication purposes. The results demonstrate that the suggested approach is robust to a variety of image processing techniques, including noise addition, filtering, and compression while maintaining high levels of imperceptibility. Key metrics such as the Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM) were used to evaluate performance. The suggested strategy exhibited a substantial improvement over existing methods. The PSNR increased to 68.67, indicating higher image quality, while the MSE reduced to 0.96, demonstrating closer pixel values to the or

关键词： Mean square error

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Youtube Comment Spam Detection

Youtube Comment Spam Detection

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Nagaraj, P. Sudar, K. Muthamil Thrived, P. Reddy, P Girish Kumar Baji Babu, S.K. Krishna, P Siva Rama Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Virudhnagar India Mepco Schlenk Engineering College Department of Computer Science and Engineering Virudhnagar India

ISBN: (纸本)9798350348217

YouTube is the most commonly used application these days. There are both good users and bad users who use youtube. Spammers have realized that these types of social media are easier to lure the users into malicious activities. In the current project, spam detection was performed on selected youtube comments and we predict the entered comment as 'SPAM' or 'NOT SPAM'. Google Safe Search and Youtube Bookmaker are two tools that can be used to block harmful links;however, they cannot immediately safeguard real-time users. Four Artificial Intelligence approaches have been employed by victimization to run the survey for the spam comment detection methodology: Call tree, Ada Boost, logistic regression, and Random Forest. We shall achieve a 91.65 percent associate degree of accuracy by using neural networks and also to beat the current action course by around 18%. The difficulty of spam and the efficiency of the most well-known AI approaches (SVMs, Bayesian representation, ANNs, k-NN). © 2023 IEEE.

关键词： Social networking (online)

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An Intensive Review on Propagative Antagonistic N/W which is used in Health Care System 4

An Intensive Review on Propagative Antagonistic N/W which is...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Badhoutiya, Arti Sivaiah, Borra Almusawi, Muntather Verma, Rajan Singh, Rajesh Angadi, Sanjeevkumar Gla University Department of Electrical Engineering Mathura India Cmr College of Engineering & Technology Department of Cse India The Islamic University Najaf Iraq Chitkara University Chitkara Center for Research and Development Himachal Pradesh 174103 India Uttaranchal University Uttaranchal Institute of Technology Department of Electronics & Communication Engineering Dehradun248007 India Nutan College of Engineering and Research Computer Science and Engineering Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

This article introduces a Generative Adversarial Network tailored for medical imaging, in particular designed to synthesize retinal images alongside side their segmented mask. This innovation addresses the challenge of obtaining big datasets for deep getting to know, in particular in scientific fields wherein expert annotations are high priced and time-ingesting. It not satisfactory generates fantastic synthetic scientific pics for supervised analysis but moreover achieves cutting-edge day overall performance with dice coefficients of 0.837 on the STARE dataset and 0.832 on the dataset, surpassing present techniques. This development highlights the capability of GANs in scientific imaging, deep gaining knowledge of, and style transfer applications. © 2024 IEEE.

关键词： Gallium nitride

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