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External blast flow field evolution and response mechanism of single-layer reticulated dome structure

Defence technology（防务技术） 2023年第6期24卷 241-253页

作者： Shao-bo Qi Guang-yan Huang Xu-dong Zhi Feng Fan State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing100081PR China Key Lab of Structure Dynamic Behaviour and Control of the Ministry of Education Harbin Institute of TechnologyHarbin150090China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbin150090China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120China

Single-layer reticulated dome structure are commonly high-profile building in the public and can be attractive targets for terrorist bombings,so the public can benefit from enhanced safety with a stronger understanding of the behavior of single-layer reticulated dome structure under *** paper investigates the fluid-structure interaction process and the dynamic response performance of the singlelayer reticulated dome under external blast *** experimental and numerical results shown that structural deformation is remarkably delayed compared with the velocity of blast wave,which advises the dynamic response of large-span reticulated dome structure has a negligible effect on the blast wave propagation under *** failure modes are identified by comparing the plastic development of each ring and the residual spatial geometric of the structure,i.e.,minor vibration,local depression,severe damage,and overall *** plastic deformation energy and the displacement potential energy of the structure are the main consumers of the blast *** addition,the stress performance of the vertex member and the deep plastic ratio of the whole structure can serve as qualitative indicators to distinguish different failure modes.

关键词： External blast loading Reticulated dome structure Fluid-structure interaction Dynamic response mode Response mechanism

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Status Assessment Method of Armored Vehicle Engine Oil and Fluid System Based on ARO-SVM

Status Assessment Method of Armored Vehicle Engine Oil and F...

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Li, Yingshun Yu, Ang Liu, Shiming Yi, Xiaojian School of Information Engineering Beijing Institute of Petrochemical Technology Beijng China The School of Mechatronical Engineering Beijing Institute of Technology China North Vehicle Research Institute Academy of Mathematics and Systems Science Chinese Academy of Sciences Department of Overall Technology Beijing China

ISBN: (纸本)9798350360585

The engine is an important component of armored vehicles, and effective detection of the engine status is an important guarantee for the vehicle and the personnel on board. The lubricating oil information can effectively respond to the health status of the armored vehicle engine, so it is very important to assess the status of the armored vehicle engine. This paper proposes an engine state assessment model based on Artificial Rabbit Optimization Algorithm optimizing Support Vector Machine. The model is simulated and the results show that the algorithm model can effectively assess the engine state and provide a reliable basis for engine maintenance. © 2024 IEEE.

关键词： Armored vehicles

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Public Social Distance Monitoring System Using Object Detection YOLO Deep Learning Algorithm

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SN Computer science 2023年第6期4卷 718页

作者： Vijayan, R. Mareeswari, V. Pople, Vedant School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore 632014 India Fulton Schools of Engineering Arizona State University Tempe AZ United States

Computer vision and deep learning are emerging technologies as the backbone system to maintain the public healthcare sector to detect the object and surrounding, especially during the COVID-19 pandemic. Generally, in a single stage, you only look once version 3 (YOLOv3) algorithms promising the best results to detect the object in images, live feeds, or videos by learning features at a faster rate than two-stage algorithms such as R-CNN, fast CNN, and faster CNN. Deep sort methods were employed to track identified people by supporting bounding boxes and calculating the Euclidian distances between the people to maintain social distance. Moreover, the YOLOV3 model requires more computational cost to detect the object at best with a lower detection time. Hence, it motivates us to practice a single graphics processing unit (GPU) with the multithreaded approach to increase the frames per second at detection. The proposed model uses a background modeling method grounded on frame variance accumulation which is used to define the number of frames and weight updating. This approach uses two steps, localization of the object and then the classification of localized objects. Distances between people are calculated and compared with threshold values to facilitate comparison. The threshold limit triggers the alert system which is accessible to people, monitoring many video streams at a time. The model is tested based on processors, threads consumed, and various types of inputs ranging from static images to moving videos. Tiny-YOLOv3 performs with the best frames per second and the least processing time, followed by SPP-YOLOv3 and YOLOv3. The model proves its evidence on various parameters and metrics to work robustly. As well as the reason to adopt YOLOv3 over other YOLOv4 and YOLOV5 is tabulated. This model initiates the curiosity to develop a mobile application with security systems based on IoT and CCTV to monitor crowded places. Graphical Abstract: [Figure not available: see

关键词： Computer vision Deep learning Object classification Object detection Social monitoring YOLO

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Robust Practical Stabilization for Complex Dynamical Networks With DoS Attacks and Actuator Saturation

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3108-3118页

作者： Shi, Xueya Peng, Zhinan Yu, Junzhi Li, Hongfei Southwest University College of Electronic and Information Engineering Chongqing400715 China Sichuan Artificial Intelligence Research Institute Yibin644000 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China

This article addresses the problem of designing an attack-resilient adaptive event-triggered (AET) controller for complex dynamical networks (CDNs) under DoS attacks and actuator saturation, with a focus on robust practical stability (RPS). First, considering the impact of DoS attacks on closed-loop systems, an AET controller against DoS attacks is designed. Unlike other event-triggered controllers, the complete timeline is divided, and the AET controller is built with two switching modes based on the intervals of dormant and active periods of DoS attacks in which the system is located. Second, to reconcile AET controller with actuator saturation, a switched system modeling approach is established that explicitly incorporates saturation constraints into the coupled network dynamics. Third, a switched Lyapunov-Krasovskii functional (LKF) is proposed, with which sufficient conditions are provided to ensured the RPS, and a joint design strategy is developed for the desired triggered matrix and feedback gain using linear matrix inequalities (LMIs). Moreover, the results are generalized to the case of actuator faults, indicating that the system is able to achieve RPS with actuator faults. Finally, the proposed method is verified through an example. © 2013 IEEE.

关键词： Lyapunov functions

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Recent Advances in Modeling ΔE-Effect Magnetic Field Sensors

Recent Advances in Modeling ΔE-Effect Magnetic Field Sensor...

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2024 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2024

作者： Ilgaz, Fatih Spetzler, Elizaveta Wiegand, Patrick Faupe, Franz Rieger, Robert McCord, Jeffrey Spetzler, Benjamin Kiel University Multicomponent Materials Department Of Materials Science Kiel24143 Germany Institute Of Electrical Engineering And Information Technology Kiel University Networked Electronic Systems Kiel24143 Germany Kiel University Nanoscale Magnetic Materials - Magnetic Domains Department Of Materials Science Kiel24143 Germany Kiel24118 Germany Ilmenau University Of Technology Micro- And Nanoelectronic Systems Department Of Electrical Engineering And Information Technology Ilmenau98693 Germany

ISBN: (纸本)9798350362213

In recent years, magnetoelectric ΔE-effect sensors have been investigated to detect small amplitude and low-frequency magnetic fields. Much progress has been made in understanding the complex interplay of magnetic, mechanical, and electrical properties and their influence on the signal and noise of the sensor system. This holds for different designs of magnetoelectric resonators but also for surface acoustic wave devices. Experimental and theoretical advancements will be reviewed and presented, including the first steps toward applications and arrays with many miniaturized sensor elements. Limitations and prospects will be discussed critically, such as performance variations and strategies to improve signal and noise. A novel origin of magnetic noise owing to the nonlinearity of magnetostriction will be revealed, which applies to all sensor devices incorporating magnetic materials. The results contribute significantly to understanding the limitations of magnetic sensors and provide essential guidelines for optimizing future ΔE-effect sensors. © 2024 IEEE.

关键词： Magnetostrictive devices

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Sensitivity analysis and probability modelling of the structural response of a single-layer reticulated dome subjected to an external blast loading

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Defence technology（防务技术） 2023年第5期23卷 152-163页

The structural response of a single-layer reticulated dome to external explosions is shaped by many variables,and the associated uncertainties imply non-deterministic *** deterministic methods for predicting the consequences of specific explosions do not account for these ***,the impact of the uncertainties associated with these input variables on the structures’response needs to be studied and *** this study,a parametric uncertainty analysis was conducted ***,local and global sensitivity analyses were carried out to identify the drivers of the structural dynamic response.A probabilistic structural response model was established based on sensitive variables and a reasonable sample ***,some deterministic empirical methods for explosion-resistance design,including the plane blast load model of CONWEP,the curved blast load model under the 50%assurance level,and the 20%mass-increased method,were used for evaluating their *** results of the analyses revealed that the structural response of a single-layer reticulated dome to an external blast loading is lognormally ***,the MB0.5 method based on the curved reflector load model yielded results with a relatively stable assurance rate and reliability,but CONWEP did not;thus,the 1.2MB0.5 method can be used for making high-confidence simple *** addition,the results indicated that the structural response is very sensitive to the explosion *** on these results,it is suggested that for explosion proofing,setting up a defensive barrier is more effective than structural strengthening.

关键词： Dome structure Blast load uncertainty Sensitivity analysis Probabilistic investigation Reliability evaluation

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Development of an RFID-Based Record Management Web Portal for Goats Towards Precision Livestock Farming

Development of an RFID-Based Record Management Web Portal fo...

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2024 IEEE International Conference on Computing, ICOCO 2024

作者： Gabato, Aaron Jay Vendivil, Joshua Sison, Bea Alessandra Botangen, Khavee Agustus Rosario, Neal Del Santiago, Kier Department of Information Technology Central Luzon State University Science City of Muñoz Philippines Cyber-physical Systems and IoT Lab Department of Information Technology Central Luzon State University Science City of Munoz Philippines Small Ruminant Center Central Luzon State University Science City of Munoz Philippines

ISBN: (纸本)9798331530303

For sustainable and profitable livestock production, precision livestock farming necessitates the formulation of optimal husbandry and management practices across various aspects, including tracking individual animal pedigrees, monitoring milk production performance, assessing health status, managing feeding and nutrition, making culling decisions, and implementing selective breeding. Data-driven decision-making is essential in these practices, and comprehensive and efficient record keeping is fundamental to producing the reliable data needed for them. This paper presents the design and development of an RFID-based record management system tailored for small to medium-sized goat farms, specifically implemented at the Small Ruminant Center of Central Luzon State University. The system integrates RFID technology to streamline data capturing and management processes, enhancing the efficiency of routine herd operations such as milking, weighing, and health treatments. The system comprises four primary components: animal identification and data capturing, task management, financial management, and real-time reporting and data analysis. Upon deployment, practical enhancements were made based on real-world usage, including improved security measures, streamlined data input processes, and enhanced user notifications. The system was evaluated by IT experts using ISO/IEC 25010 criteria, receiving high ratings across functionality, performance, and compatibility. This system will contribute to the advancement of record management practices for goat farming, leading to increased production and improved livelihoods for small ruminant farmers in the Philippines. ©2024 IEEE.

关键词： Decision making

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Bluetooth Vulnerabilities and Security

Bluetooth Vulnerabilities and Security

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Mareeswari V Vijayan R Ashish Shukla Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Department of Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Master of Computer Applications School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Bluetooth technology, which facilitates wireless communication between Billions of devices including smartphones, tablets, laptops, and Internet of Thing (IoT) devices, is a cornerstone of modern connectivity. Its importance lies in its ability to enable seamless data exchange and interaction across a wide range of applications, from personal gadgets to complex industrial systems. Despite its widespread adoption, Bluetooth is not immune to critical security vulnerabilities. Issues like Bluetooth Low Energy (BLE) vulnerabilities and denial-of-service (DoS) attacks can overwhelm devices with excessive traffic, while BLE Forced Connection can lead to unauthorized access, and eavesdropping exposes sensitive data being exchanged. We have discussed these vulnerabilities in detail, examining their mechanisms, potential impacts, and various implementation aspects. Additionally, we have added demonstrations to illustrate how these attacks can be executed and the potential consequences. To prevent these threats, we explored essential measures, including regular firmware updates, secure pairing protocols, and careful management of Bluetooth settings. Adopting best practices like disabling Bluetooth when not in use and monitoring connected devices can further enhance security, ensuring the reliable and safe operation of the vast and growing ecosystem of Bluetooth-enabled devices.

关键词： Wireless communication Ethics Protocols Ecosystems Denial-of-service attack Security Internet of Things Bluetooth Low Energy Microprogramming Guidelines

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Image Enhancement Using Adaptive Fractional Order Filter

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Computer systems science & engineering 2023年第5期45卷 1409-1422页

作者： Ayesha Heena Nagashettappa Biradar Najmuddin M.Maroof Surbhi Bhatia Arwa Mashat Shakila Basheer Department of Electronics and Communication Engineering Bheemanna Khandre Institute of TechnologyBhalkiVisveswaraya Technological UniversityBelagaviIndia Department of Electronics and Communication Engineering Khaja Banda Nawaz College of EngineeringVisveswaraya Technological UniversityBelagaviIndia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl-HofufAl-AhsaSaudi Arabia Faculty of Computing&Information Technology King Abdulaziz UniversityP.O.Box 344Rabigh21911Saudi Arabia Department of Information Systems College of Computer and Information Science Princess Nourah bint Abdulrahman UniversityP.O.BOX 84428Riyadh11671Saudi Arabia

Image enhancement is an important preprocessing task as the contrast is low in most of the medical images,Therefore,enhancement becomes the mandatory process before actual image processing should *** research article proposes an enhancement of the model-based differential operator for the images in general and Echocardiographic images,the proposed operators are based on Grunwald-Letnikov(G-L),Riemann-Liouville(R-L)and Caputo(Li&Xie),which are the definitions of fractional order *** this fractional-order,differentiation is well focused on the enhancement of echocardiographic *** provoked for developing a non-linear filter mask for image *** designed filter is simple and effective in terms of improving the contrast of the input low contrast images and preserving the textural features,particularly in smooth *** novelty of the proposed method involves a procedure of partitioning the image into homogenous regions,details,and ***,a fractional differential mask is appropriately chosen adaptively for enhancing the partitioned pixels present in the *** is also incorporated into the Hessian matrix with is a second-order derivative for every pixel and the parameters such as average gradient and entropy are used for qualitative *** wide range of existing state-of-the-art techniques such as fixed order fractional differential filter for enhancement,histogram equalization,integer-order differential methods have been *** proposed algorithm resulted in the enhancement of the input images with an increased value of average gradient as well as entropy in comparison to the previous *** values obtained are very close(almost equal to 99.9%)to the original values of the average gradient and entropy of the *** results of the simulation validate the effectiveness of the proposed algorithm.

关键词： Adaptive filter differential filter enhancement mask fractional differential mask fractional-order calculus hessian matrix

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Rolling Bearing Fault Diagnosis Method Based on Wavelet Time–Frequency Map and Improved ConvNext 1

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Qin, Feifan Zhang, Chao Wang, Jianguo Zhao, Wentao Li, Jianjun Liu, Tongtong College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014010 China Inner Mongolia Key Laboratory for Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China College of Information Engineering Inner Mongolia University of Science and Technology Baotou014010 China

ISBN: (数字)9783031494215

ISBN: (纸本)9783031494208

The purpose of this article is to address the issue of traditional fault diagnosis methods for rolling bearings, which are unable to accurately diagnose the fault signals of non-linear and non-stationary rolling bearings. To achieve this goal, this article proposes a rolling bearing fault diagnosis method based on wavelet time–frequency maps and an improved ConvNext model. This method first leverages the advantages of wavelet time–frequency analysis to transform the original signal into a two-dimensional wavelet time–frequency map. Subsequently, a new generation of convolutional neural networks, ConvNext, is utilized as the foundational network for rolling bearing fault diagnosis models. The network is enhanced by introducing lightweight attention modules, such as the Convolutional Block Attention Module (CBAM) and the Efficient Channel Attention Network (ECA), to improve the Block modules in the basic network. The wavelet time–frequency map is then used as a feature map input to the improved ConvNext network for training, aiming to achieve rolling bearing fault diagnosis recognition. Finally, experimental results demonstrate that the proposed method exhibits a high level of fault recognition accuracy and stability in laboratory data. It also demonstrates a certain degree of robustness, offering a new solution for rolling bearing fault diagnosis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Failure analysis

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