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Suggestions for Application of intelligent Operation and Maintenance of Urban Rail Transit Traction Power Supply systems

Suggestions for Application of Intelligent Operation and Mai...

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2022 ieee international conference on Power systems and Electrical technology, PSET 2022

作者： Hou, Feng Li, Kunpeng Shang, Cong Feng, Ding Guangzhou Metro Design & Research Institute Co. Ltd. Guangzhou China Southwest Jiaotong University School of Electrical Engineering Chengdu China

ISBN: (纸本)9781665489157

There is an increasing demand for the automation, intelligence and information in the operation and maintenance of urban rail transit traction power supply systems, and hence the construction of the intelligent operation and maintenance system has been raised in the forefront of the industry development. In this paper, firstly the existing problems in the traditional maintenance modes have been analyzed, and the functional requirements in the intelligent operation and maintenance of power supply systems have been summarized. Meanwhile, the key technologies that can be applied are analyzed. Finally, suggestions are put forward for intelligent operation and maintenance of urban rail transit traction power supply systems, which can provide scientific basis for transforming and upgrading the operation and maintenance of urban rail transit traction power supply system. © 2022 ieee.

关键词： Maintenance

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Dynamic Event-Triggered Load Frequency control for Multi-Area Power systems Under Switching cyber-Attacks 8th

Dynamic Event-Triggered Load Frequency Control for Multi-Are...

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Yan Jia, Xinchun Lv, Teng Wang, Zhongbao School of Automation and Software Engineering Shanxi University Taiyuan030006 China School of Mathematical Sciences Shanxi University Taiyuan030006 China

ISBN: (纸本)9789819602247

In this paper, the decentralized dynamic event-triggered load frequency control problem for multi-area power systems under switching cyber-attacks is investigated. A new switching cyber-attack model including Denial of Service (DoS) attacks and deception attacks occurring in the sensor-to-controller channel is considered, which is characterized by being composite in both the spatial and temporal domains. The attack model is characterized by compositing in the spatial and temporal domains. To reduce the network communication burden and mitigate the impact of switching cyber-attacks on the closed-loop system, we design a decentralized dynamic event-triggering mechanism (DETM) that dynamically adjusts threshold parameters using hyperbolic tangent functions related to output measurement deviations. Further, a decentralized secure LFC scheme is developed based on periodic sampling, which can reduce the consumption of communication resources under switching network attacks and protect the security and frequency stability of the power system. Finally, the effectiveness of the proposed method is verified by a simulation case of the ieee 39 BUS test system containing 10 generating units. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Frequency stability

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Exploring Efficient systems for Street Light Management: A Comprehensive Survey 7

Exploring Efficient Systems for Street Light Management: A C...

引用

7th international conference on intelligent Computing and control systems, ICICCS 2023

作者： Arunkumar, P. Prasanna, B. Kabilesh, U. Sundareswari, K. Karpagam Academy of Higher Education Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

The street light management system, which integrates new technologies primarily used for intelligent and adaptive-weather street lighting, is a new intelligent system that runs automatically. The traditional street lighting system is being employed using sodium vapour, bright, and mercury standard lamps. These lamps all require expensive maintenance and use a lot of energy. It is necessary to manually turn the light on before dusk and off when it is light enough in the morning. These street lights are occasionally left on throughout the day without a need, completely wasting power and money. A significant additional problem is time. This technology automatically turns on and off the street lights based on the local weather and the movement of items. This type of system can be used economically where the movement of objects is low, considering other places. The entire set up will be monitored by a PC in a controlled environment, so that if there is any evidence of damage to the light it can be indicated using a sensor. This paper focuses on the importance of saving energy, reducing carbon impact and global warming, by comparison of different systems. © 2023 ieee.

关键词： Internet of things

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Optimizing Hyperspectral Anomaly Detection with a Scalable Quantum Snow Geese Non-Local Neural Network Algorithm 4

Optimizing Hyperspectral Anomaly Detection with a Scalable Q...

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4th international conference on Ubiquitous Computing and intelligent Information systems, ICUIS 2024

作者： Ramkumar, M.Siva Emayavaramban, G. Latha, G.Charlyn Pushpa Giri, Jayant Al-Qawasmi, Khaled Sns College of Technology Department of Ece India Jct College of Engineering and Technology Department of Ece India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Dept of Information Technology Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Saveetha University Department of Vlsi Microelectronics TN Chennai602105 India Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331529635

Hyperspectral Anomaly Detection (HAD) focuses on identifying unusual objects or patterns in hyperspectral imagery (HSI) that differ from the normal background or surrounding pixels. In the past two decades, anomaly detection (AD) has become essential in hyperspectral image analysis, offering a novel approach to differentiate targets from the background without requiring prior information. Current methods face multiple drawbacks, either by neglecting the problem of low resolution or by depending on super-resolution models that aim to reconstruct the entire image, which can result in ineffective detection of abnormal pixels. To address these challenges, a Scalable Quantum Snow Geese Non-local Neural Network Algorithm (ASQSGNon-LNNet) is introduced for hyperspectral anomaly detection, aimed at achieving high accuracy. In this approach, input images are sourced from the ABU-urban dataset. First, the features of these input images are extracted using the Memory Efficient Vision Transformer (ME-ViT) method. Subsequently, the extracted features undergo Hyperspectral Super Resolution using the Deform-Mamba Network. After that, anomaly detection is conducted using a Scalable Quantum Non-local Neural Network (SQNonL-NNet), optimized by the Snow Geese Algorithm (SGA), leading to automated hyperspectral anomaly detection with improved efficiency and accuracy. The performance of the proposed ASQSGNon-LNNet is assessed using the ABU-urban dataset, achieving an accuracy of 99.8% and surpassing existing methods. The results of this technique reveal unusual patterns or objects in hyperspectral images by analyzing their spectral signatures and enhancing accuracy in detecting hidden or subtle anomalies in remote sensing, environmental monitoring, and military applications. This technology provides greater accuracy than traditional methods. © 2024 ieee.

关键词： Snow

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Accurate Stability Analysis of Modular Multilevel Converters Modeled as Delayed Periodic systems 2

Accurate Stability Analysis of Modular Multilevel Converters...

引用

ieee 2nd international conference on Power Science and technology (ICPST)

作者： Jia, Xiaofan Ye, Hua Gao, Lei Hou, Kaiyuan Wang, Kefei Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Peoples R China China Elect Power Res Inst Power Syst Dept Beijing Peoples R China State Grid Cooperat China Dispatch & Commun Ctr Northeast Branch Shenyang Peoples R China

ISBN: (纸本)9798350349047;9798350349030

The increasing use of modular multilevel converters (MMCs) raises system stability concerns, such as instability in a wide frequency range. Accurate stability analysis of such systems thus is urgently demanded. In this regard, the small signal modeling of the system can be described by a set of linear time-periodic (LTP) differential equations involving time delays, which requires much more effort. A generalization of the ordinary differential equation (ODE)-based harmonic state space (HSS) framework to delayed differential equations (DDEs), HSS-DDE for short, has been proposed to tackle time delays and periodicity within a unified framework. However, the authors found in practical application that this model produces erroneous results when the time delay involved is not an integer multiple of the period. Therefore, this paper first intensively analyzes the limitations of the HSS-DDE model, and then introduces the time-periodic infinitesimal generator and partial discretization idea to reconstruct an improved model that is not affect by the relationship between time delays and period. Thus, the stability of delayed periodic systems can be readily studied. The results of a numerical example and the grid-connected MMC system verify the accuracy and validity of the proposed model.

关键词： harmonic state-space linear time-periodic system time delays modular multilevel converter small signal stability analysis

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A Fatigue Driving Recognition Method Based on WOA-Attention-GRU 2

A Fatigue Driving Recognition Method Based on WOA-Attention-...

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2nd international conference on Robotics, Artificial Intelligence and intelligent control, RAIIC 2023

作者： Li, Minghong Li, Zuojin Shi, Lanyang Li, Dongyang Chongqing University of Science and Technology School of Electrical Engineering Chongqing China

ISBN: (纸本)9798350328004

This academic paper addresses the challenges related to the limited accuracy and practicality of laboratory simulation data in driving tests. The main goal is to investigate driving behavior under real-world vehicle conditions. To achieve this, the paper proposes a dual time window approach that effectively captures time series lengths. Moreover, it extracts the intersection of operational behaviors and employs the verification recursive feature elimination method to identify the optimal fatigue feature indices. These indices are then combined with whale optimization and gate-cycle control neural network techniques to detect fatigued driving more effectively. To enhance recognition accuracy, an attention mechanism is introduced. Experimental results using vehicle data demonstrate that the proposed method achieves an 89.84% accuracy rate in detecting three-level fatigued driving, with a false negative rate of 10.99%. © 2023 ieee.

关键词： intelligent vehicle highway systems

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Implementation of Scrum Method on Mobile-Based Billing Information System Design (Case Study: ABC Company) 4

Implementation of Scrum Method on Mobile-Based Billing Infor...

引用

4th international conference on intelligent cybernetics technology and Applications, ICICyTA 2024

作者： Esa, Dhiwani Maharani Aulia Nur Putri, Salsabila Amara Murmanto, Imanuel Revelino Binus Online Learning Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

ABC Company, a prominent leather shoe manufacturer, has been facing a series of internal problems that have significantly impact its overall business performance. These issues are diverse, including an ineffective billing system that lacks automation and accuracy, customers displaying passive behavior when it comes to timely payments, and collectors failing to carry proper billing cards during transactions. Moreover, there is an evident lack of integrated records or reports regarding billing and payment statuses, which leads to confusion and delays in processing. To address these pressing concerns, the author has meticulously designed a mobile-based billing information system using the Scrum approach, which was selected for its inherent flexibility and emphasis on iterative development. Scrum allows for constant feedback and adjustments, ensuring that the system evolves to meet the company's needs as the project progresses. The result is an innovative, mobile-based billing system that has been thoroughly evaluated for its potential to enhance operational efficiency and improve the quality of service offered to both customers and internal staff. This evaluation demonstrated marked improvements, including timely customer payments, streamlined billing processes, and significantly better tracking and reporting of all billing activities. The successful implementation of this system is projected to have broader impacts beyond the company itself, contributing to local economic development by enhancing productivity, increasing operational efficiency, creating new job opportunities, and fostering avenues for further business development. As ABC Company strengthens its financial management systems, the potential for scaling and contributing to a more vibrant local economy becomes increasingly feasible. © 2024 ieee.

关键词： Efficiency

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Recognition of Pick Wear State Based on Deep LSTM Neural Network

Recognition of Pick Wear State Based on Deep LSTM Neural Net...

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2023 international conference on cyber-Physical Social Intelligence, ICCSI 2023

作者： Song, Dong Taiyuan Institute of China Coal Technology and Engineering Group Taiyuan China Shanxi Tiandi Coal Mining Machinery Co. Ltd Taiyuan China

ISBN: (纸本)9798350312492

Picks are the vital components used in mining machinery for cutting coal-rock mass, and their wear state significantly influence cutting efficiency during the cutting process. Currently, manual experience serves as the primary basis for replacing worn-out picks in most coal mines. However, to improve efficiency, picks are often replaced collectively, resulting in premature replacement of a considerable number of picks that have not reached their expected lifespan, which leads to substantial economic wastage. In this study, real pick replacement data from H coal mine in China is leveraged that classify the wear state of picks into four categories: new picks, slight wear, moderate wear, and severe wear. Due to the purpose of identify picks wear state, a method based on wavelet packet decomposition of the vibration signals generated by cutting drums when cutting coal-rock is proposed. The method utilizes feature vectors composed of the standard deviation of decomposed wavelet packet coefficients and establishes a identification model based on deep Long Short-Term Memory (LSTM) neural networks using the MATLAB platform. The analysis reveals that the deep LSTM network outperforms the single-layer LSTM neural network in capturing the nonlinear variation characteristics of the data. Moreover, the deep learning model achieves more accurate recognition results compared to the basic Back-Propagation (BP) network. This method presents a novel approach to realize intelligent recognition of the pick wear state and to implement an optimal pick replacement strategy. © 2023 ieee.

关键词： Wear of materials

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Low Power Low Leakage Domino Circuit for Wide Fan-in Gate: A Review 3

Low Power Low Leakage Domino Circuit for Wide Fan-in Gate: A...

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3rd international conference on intelligent systems, Advanced Computing, and Communication, ISACC 2025

作者： Talukdar, Dalvi Richa, Akho John Dutta, Pranab Kishore North Eastern Regional Institute of Science and Technology Department of ECE Itanagar India

ISBN: (纸本)9798331523893

Leakage current is one of the major concerns in Very Large Scale Integration mainly for designing a low power computational device in nanometer technology. Preferably, any device should consume zero or nearly zero power when it is in non-active mode. When the internal circuitry has a low leakage current, then only the device will be very efficient in power consumption. It happens when the transistors are having a very high threshold voltage. On the contrary to the technology scaling, a device should have high performance with a very less amount of supply voltage that is a low threshold voltage. Hence, different types of techniques have been initiated to control the leakage for appeasing the challenging requirements so that the performance becomes high throughout the active period and have a very less amount of leakage current throughout standby period. This paper presents a review on recent advanced techniques for domino circuits to reduce leakage current and hence increasing its efficiency. © 2025 ieee.

关键词： Leakage currents

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Smart Energy Management in Classroom using IoT

Smart Energy Management in Classroom using IoT

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2023 international conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Challa, Manoj Shreya Reddy, Kumbham Jacob, Merin Varna, Nikita S Cmr Institute of Technology Department of Cse Bangalore India

ISBN: (纸本)9781665474511

Responsible energy consumption is one of the most crucial features in the development of a country. However, due to various factors like design of the current conventional systems, lack of awareness and human negligence, a large amount of energy is wasted every year. With recent technological advances in fields like IoT (Internet of Things), it is entirely possible to optimize the consumption of energy by automating the electrical appliances in a room. The scope of IoT is vast and limitless in innumerable areas. This article proposed a system to accomplish automation in classrooms by controlling and managing electrical appliances such as fans, lights, projector etc. based on human presence and analyzing their exact location in the room by making use of a camera. This has been achieved by dividing the classroom into segments where only the appliances in a particular segment where human presence is detected are turned ON. Through the energy saving technology, students or lecturers do not purposely need to turn OFF the electrical equipment each time they leave the class. The main objective of this article is to develop a smart classroom system, where the electrical appliances are automated with a focus towards energy conservation. © 2023 ieee.

关键词： Energy conservation

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