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WOA based Optimal TIDF Controller for time Delayed System

WOA based Optimal TIDF Controller for Time Delayed System

引用

IEEE Power India conference

作者： Vineet Kumar Renu Sharma Department of Electrical and Electronics Engineering MITS Madanapalle Department of Electrical Engineering SOA University Odissa

ISBN: (数字)9798350367065

ISBN: (纸本)9798350367072

this manuscript presents a novel methodology to effectively control time-delayed systems. In this work, authors have proposed a Whale Optimization Algorithm (WOA) tuned Tilt Integral Derivative Controller with Derivative Filter (TIDF) specifically designed for regulating time-delayed systems characterized by 4th order dynamics. the efficacy of the proposed method has been thoroughly verified by comparing its transient response specifications with those of existing approaches documented in the literature. this comparative analysis demonstrates that the WOA-tuned TIDF controller offers superior performance in terms of transient response, highlighting its suitability for the intended application. Additionally, the robustness of the proposed algorithm has been rigorously tested under conditions involving variable time delays, which are a common and challenging aspect of real-world systems. the results of these tests indicate that the WOA-tuned TIDF controller not only achieves a better transient response but also maintains stability and robustness across different scenarios. Consequently, the proposed methodology provides a reliable and effective solution for controlling time-delayed systems, ensuring both enhanced performance and resilience in various industrial and technological applications.

关键词： Transient response Heuristic algorithms Delay effects Filtering algorithms Control systems Whale optimization algorithms Robustness Stability analysis Transient analysis Testing

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YOLOv8s-D2: A Novel Object Defect Detection Algorithm Based on Improved YOLOv8s

YOLOv8s-D2: A Novel Object Defect Detection Algorithm Based ...

引用

international conference on Dependable systems and their applications (DSA)

作者： Xinsheng Zhang Jing Hu Junlong Xiao School of Computer Science and Information Engineering Hubei University Wuhan China

ISBN: (数字)9798331532390

ISBN: (纸本)9798331532406

Addressing the issues of low efficiency and poor accuracy in current surface defect detection systems, as well as the challenges posed by existing defect detection models, such as large parameter counts, low generalization capabilities, and poor real-time performance, this paper proposes a novel real-time target defect detection method named YOLOv8s-D2, based on the YOLOv8s deep learning object detection algorithm. this approach optimizes and enhances the YOLOv8s object detection neural network in several key ways. Firstly, the YOLOv8s-D2 model incorporates a lightweight Convolutional Block Attention Module (CBAM) into the output feature maps of the backbone network, enhancing the network's focus on defect-related features. Secondly, it employs depthwise separable convolutions and a Squeeze-and-Excitation (SE) network to reconstruct the feature interaction module. this effectively preserves spatial and channel features while suppressing redundant information. Lastly, the three decoupled heads of YOLOv8s are optimized into four lightweight object detection heads, thereby increasing sensitivity to defective targets. the experimental results show that compared with the YOLOv8s algorithm model, the improved model has a corresponding reduction of 3.3M in parameters and 7.2G in computational complexity, while the mean average precision (mAP) value increases by 7.4%. this verifies the superiority of the improved algorithm presented in this paper.

关键词： Deep learning Accuracy Attention mechanisms Sensitivity Computational modeling Object detection Feature extraction real-time systems Computational complexity Defect detection

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Self-Identification of Reluctance Synchronous Machines with Analytical Flux Linkage Prototype Functions

Self-Identification of Reluctance Synchronous Machines with ...

引用

international conference on Power Electronics (ICPE)

作者： Shih-Wei Su Niklas Monzen Ralph Kennel Christoph M. Hackl Chair of High-Power Converter Systems Technical University of Munich Germany Laboratory for Mechatronic and Renewable Energy Systems (LMRES) HM Munich University of Applied Sciences Germany

this paper presents a self-identification approach for reluctance synchronous machines (RSMs) in combination with analytical flux linkage prototype functions. Due to the severe magnetic saturation, good machine knowledge is required for high-performance electrical drive systems. the proposed self-identification method injects bipolar voltage pulses to an inverter-fed machine at standstill, without additional test equipment and requirements. Within an extremely short time, nonlinear flux linkages, including the magnetic saturation and cross-coupling effects, can be obtained. Instead of saving the samples as lookup tables (LUTs), they are approximated by analytical flux linkage prototype functions, which are parametrized by few parameters, and continuously differentiable throughout the whole operation range. the effectiveness of the developed self-identification method is experimentally validated for a nonlinear 4.0kW RSM. the results prove (i) the simple and time-saving procedure of the self-identification method, (ii) the high approximation accuracy and (iii) the benefits of the flux linkage prototype functions for real-time applications.

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IoT Based Two Way Safety Enabled Intelligent Stove with Age Verification Using Machine Learning

IoT Based Two Way Safety Enabled Intelligent Stove with Age ...

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11th international conference of Computer Communication and Informatics (ICCCI)

作者： Afroz, Mariha Hasan, Nazia Hossain, Md Ishan Arefin Southeast Univ Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9781728158754

Smart embedded systems have become a core component in the latest technologies, and IoT based smart embedded system is the trendiest field in the research area. In our research, we are proposing an IoT based smart stove. Any accident might occur at any time from a stove. So we are designing a two-way safety enabled stove with a child lock system and gas leakage detection feature. the intelligent stove will try to ensure safety and will detect age from real-time video streaming. Our main focus is a child would not be able to turn the stove on. As well as, the stove can entitle safety via gas detection alarm. We are using a Raspberry Pi and Gas Detection Module with a buzzer for the hardware implementation. Also, we are applying a Machine Learning object detection algorithm (Haar Cascade) and a deep learning architecture (CNN) for the system execution. Since our stove is IoT-based, the stove is ensuring safety remotely as well as manually which will try to prevent accidental occurrences.

关键词： IoT embedded System Smart embedded System Child Lock System Age Detection Raspberry Pi Buzzer Machine Learning

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A Robust Network for embedded Traffic Sign Recognition 11

A Robust Network for Embedded Traffic Sign Recognition

引用

11th international conference on Computer Engineering and Knowledge, ICCKE 2021

作者： Manzari, Omid Nejati Baradaran Shokouhi, Shahriar Iran University of Science and Technology School of Electrical Engineering Tehran16846-13144 Iran

ISBN: (纸本)9781665402088

Traffic sign recognition systems are vital in real-world applications such as auto-driving and safety and driver assistance. While deep neural networks have achieved high accuracy in classifying traffic signs in recent years, there is always the discussion of the high computations of these networks and their many teachable parameters. A significant challenge is to design a compact deep neural network for the application of traffic sign recognition. this paper proposes a network that uses residual blocks in the network to obtain a top-1 accuracy of 99.51 for the German traffic sign recognition benchmark. the number of parameters is ~430, 000, which is ~32x fewer than the state-of-the-art. Experiments have been performed to show the network's resistance to destructive factors and its comprehensiveness in the application of traffic sign recognition. these tests show that it is a comprehensive and robust network for the recognition of traffic signs. © 2021 IEEE.

关键词： Traffic signs

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A Two-Step Hybrid Approach for Verifying real-time Robotic systems 26

A Two-Step Hybrid Approach for Verifying Real-Time Robotic S...

引用

IEEE 26th international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Foughali, Mohammed Univ Grenoble Alpes CNRS VERIMAG Grenoble France

ISBN: (数字)9781728144030

ISBN: (纸本)9781728144030

Due to the severe consequences of their possible failure, robotic systems must be rigorously verified against (i) behavioral properties, such as safety and (ii) real-time properties, such as schedulability, while taking into account the real hardware (e.g. number of cores) and operating system (e.g. scheduling policy) specificities. Formal verification and schedulability analysis are popular approaches that may help with such verification, but suffer from limitations such as scalability issues (for the former) and difficulty to generalize to complex robotic tasks (for the latter), when used independently. In this paper, we propose a two-step, efficient solution that combines both approaches. the first step provides a sufficient condition for the schedulability of hard-real-time tasks in a robotic application. then, the second step automatically generates a formal model of the application, on which other important properties may be verified formally using statistical model checking. the solution is applied to an autonomous drone case study.

关键词： Task analysis Robots Drones Genomics Bioinformatics real-time systems Model checking

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A Design of Fault-Tolerant System for Safety-Critical systems

A Design of Fault-Tolerant System for Safety-Critical System...

引用

international conference on Autonomous Robots and Agents, ICARA

作者： Kai Yoshizawa Nobuyuki Yamasaki Graduate School of Science and Technology Keio University Yokohama Japan

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

In safety-critical systems where failures or faults can lead to accidents, especially in special and harsh environments like those encountered in spacecraft, it is well known that multiple levels of errors can significantly increase the likelihood of system failure. For instance, system-level errors may occur due to cable breaks caused by severe vibrations, while gate-level errors can arise from radiation effects on System-on-Chip (SoC) semiconductors. Furthermore, in such specialized environments, human repair is often not feasible, necessitating that the system continue to operate even when a fault occurs in a part of it. therefore, this research discusses the design, implementation, and evaluation of a redundant system that combines multi-level redundancy mechanisms to tolerate multiple errors and maintain operation. the implementation was carried out on the Space I/O Core (SIOC), a System-on-Chip equipped with processors and I/O for distributed real-time systems. Additionally, bitstreams were created from the implemented logic, and the performance of the fault-tolerant system was evaluated using an actual FPGA.

关键词： Vibrations Space vehicles Redundancy Fault tolerant systems Termination of employment Switches Logic gates System-on-chip Field programmable gate arrays Robots

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real-time Arm Motion Tracking and Hand Gesture Recognition Based on a Single Inertial Measurement Unit

Real-time Arm Motion Tracking and Hand Gesture Recognition B...

引用

international conference on Internet of things: systems, Management and Security

作者： Tien-Chiao Chang Yu-Chi Wu Chin-Chuan Han Chao-Shu Chang Dept. of Electrical Engineering National United University Miao-Li Taiwan Dept. of Computer Science and Information Engineering National United University Miao-Li Taiwan Dept. of Information Management National United University Miao-Li Taiwan

ISBN: (数字)9798350366501

ISBN: (纸本)9798350366518

With the development of virtual reality (VR) and augmented reality (AR) devices, handheld controllers and camera-based hand tracking are the most common methods for interacting with the virtual world. this paper proposes arm motion tracking and hand gesture recognition methods based on a single IMU (Inertial Measurement Unit) sensor embedded in a wristband. this approach is more convenient than handheld controllers and more energy-efficient than camera-based tracking. We utilize two deep learning models: one for arm motion tracking and the other for hand gesture recognition. When training the arm motion tracking model, we use two IMU sensors-one placed on the wrist to provide forearm pose data and the other placed above the elbow to provide upper arm pose data. We use the elbow’s IMU data as the reference for training the model and calculate the real-time upper arm pose vector based on the wrist’s pose data. We train the hand gesture recognition model using only the wrist-mounted IMU sensor. this model captures different vibrations in the IMU during various gestures (such as grab, release, snap, and tap) for training. We achieve real-time arm motion tracking and hand gesture recognition using only a single IMU sensor. the angle error for arm motion tracking is only 15 degrees, and the hand gesture recognition accuracy reaches 95%.

关键词： Training Wrist Solid modeling Measurement units Accuracy Tracking Gesture recognition Inertial navigation real-time systems Data models

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WVRF_CGT: WVRF Automatic Filter Based Cascading Graph Transformer for Information Diffusion in Stock Q&A Platform

WVRF_CGT: WVRF Automatic Filter Based Cascading Graph Transf...

引用

international conference on Dependable systems and their applications (DSA)

作者： Xiaobing Feng Ling Feng Pengfei Jiao Zhiliang Zheng Qing Bao School of Financial Management Institute of Artificial Intelligence and Change Management Shanghai University of International Business and Economics Shanghai China School of Robotics Engineering Shanghai Ocean University China School of Cyberspace Hangzhou Dianzi University Hangzhou China School of Computer Science Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9798331532390

ISBN: (纸本)9798331532406

this article takes the interactive platforms of the Shenzhen Stock Exchange and the Shanghai Stock Exchange as a vertical domain-specific dialogue platform. Firstly, it proposes an automated method for quality rating of Q&A pairs based on WordVectorRandForest (WVRF). By constructing a standard StockQ&APair Q&A pair database, extracting text features using Word2Vec and TF-IDF that the combination of Word2Vec and TF-IDF enhances the precision of Q&A filtering in financial platforms by effectively handling semantic relationships in text data, and combining statistical information such as response time and text length, a random forest model is trained to rate the quality of Q&A pairs. Subsequently, based on the foundation of building and validating a high-quality securities interactive platform Q&A automatic filtering system (AutoStockQ &AFilter), the study further introduces a Cascaded Graph Transformer (CGT) for automatic filtering of stock Q&A platform information diffusion. By evaluating the heat index of stocks using high-quality Q&A pairs in the platform, it provides real-time decision analysis tools for investment. Experimental results show that the average accuracy of this method exceeds 95%, and the precision in information dissemination meets the validation threshold.

关键词： Semantics Transformers Feature extraction real-time systems Information diffusion time factors Security Stock markets Standards Random forests

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Proceedings - 17th Annual international conference on Distributed computing in Sensor systems, DCOS 2021

Proceedings - 17th Annual International Conference on Distri...

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17th Annual international conference on Distributed computing in Sensor systems, DCOS 2021

ISBN: (纸本)9781665439299

the proceedings contain 74 papers. the topics discussed include: leveraging cross-technology broadcast communication to build gateway-free smart homes;semi-supervised contrastive learning for human activity recognition;Batterfly: battery-free daily living activity recognition system through distributed execution over energy harvesting analog pir sensors;towards context aware adaptive deployment in ML applications using state machines;resource-constrained target classification on distant aerial targets;an IoT-based system for autonomous, continuous, real-time patient monitoring and its application to pressure injury management;and segregating keys from noncense: timely exfil of ephemeral keys from embedded systems.

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