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Unified control Algorithm for Multi-Mode Operation of Bidirectional DC/DC Converters in Renewable Energy systems

Unified Control Algorithm for Multi-Mode Operation of Bidire...

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2023 international conference on Power Energy, Environment and intelligent control, PEEIC 2023

作者： Ramesh, B. Manjunatha, B. Jain, Alok Khan, Irfan Pahwa, Shilpa Alkhafaji, Mohammed Ayad Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Mechanical Engineering Karnataka Bangalore India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India Lloyd Institute of Management and Technology Plot No.-11 Knowledge Park-II Uttar Pradesh Greater Noida201306 India College of Engineering Technology National University of Science and Technology Dhi Qar Iraq

ISBN: (纸本)9798350357769

In the evolving landscape of renewable energy systems, bidirectional DC/DC converters have emerged as pivotal components, facilitated energy storage integration and ensured optimal power flow between different energy sources and loads. This paper introduces a novel unified control algorithm adept at seamlessly transitioning between multiple operational modes of these converters, thus enhancing the reliability and flexibility of energy systems. The proposed control methodology integrates innovative modulation techniques and control strategies, ensuring maximum power point tracking (MPPT), battery charge/discharge control, and grid-tied operations without necessitating mode-switching controls. Performance evaluation, carried out using both simulation tools and experimental setups, reveals significant improvements in transient response, reduced switching losses, and consistent voltage regulation across all operational modes. With its adaptive capabilities, this algorithm holds promise for future renewable energy systems, simplifying converter controls and ensuring resilient power management in diverse scenarios. © 2023 ieee.

关键词： Adaptive Power Management.Top of Form Bidirectional DC/DC Converters Maximum Power Point Tracking Renewable Energy systems Unified control Algorithm

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Digital Twin-Enhanced Methodology for Training Edge-Based Models for cyber Security Applications 20

Digital Twin-Enhanced Methodology for Training Edge-Based Mo...

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20th ieee international conference on Industrial Informatics (INDIN)

作者： Allison, David Smith, Paul McLaughlin, Kieran Queens Univ Belfast Belfast Antrim North Ireland AIT Austrian Inst Technol Vienna Austria AIT Austrian Inst Technol Ctr Digital Safety & Secur Vienna Austria Queens Univ Belfast Ctr Secure Informat Technol Belfast Antrim North Ireland

ISBN: (数字)9781728175683

ISBN: (纸本)9781728175683

Digital twins can address the problem of data scarcity during the training machine learning models, as they can be used to simulate and explore a range of process conditions and system states that are too difficult or dangerous to explore in real-world cyber-Physical systems (CPSs). Meanwhile, advances in industrial control systems technology have enabled increasingly complex functionality to be deployed on or near so-called edge devices, such as Programmable Logic controllers (PLCs). In this paper, we propose a methodology for training a machine learning model offline using data extracted from a digital twin, before converting the model for deployment on an edge device to perform anomaly detection. To examine the model's suitability for anomaly detection, we execute several simulations of fault conditions. Results show that the model can successfully predict normal operations as well as identify faults and cyber-attacks. There is a negligible drop in performance on the edge device, when compared to executing the model on a personal computer, but it remains suitable for the application.

关键词： Digital Twins Edge Computing Machine Learning cyber Security

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Eigenvalue Extraction of Automated Pothole Road Image Based on AlexNet Model

Eigenvalue Extraction of Automated Pothole Road Image Based ...

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2024 international conference on Interactive intelligent systems and Techniques, IIST 2024

作者： Yan, Xiaochen Yang, Huichao Meng, Xinmeng Yang, Huixiang Harbin Institute of Technology China Qingdao City University China Sichuan University China

ISBN: (纸本)9798350374421

In the rapid progress of urbanisation, the safety and smoothness of road traffic has become a problem that needs to be solved by urban management. The pothole problem on the road surface, as one of the main influencing factors of traffic safety and driving comfort, is difficult to guarantee the accuracy and efficiency of the traditional manual visual inspection method. Therefore, this study is dedicated to the automated pothole road detection and recognition technology based on AlexNet model to solve the problems in practical traffic management. We processed two versions of image files, high pixel and low pixel, and built a classification model for pothole situation recognition. Firstly, 301 images were preprocessed into two pixel versions of 256*256 and 512*512 using de-mean, normalisation and batch cropping. Subsequently, we extracted the feature values of the images using the AlexNet model. In the initial feature value extraction, we obtained a feature table of 301*4096 through the convolutional layer part. Then, a feature downscaling step was performed, where features were first extracted from the pooling layer of AlexNet with an output size of 6*6*256. for this, a global average pooling was performed to downsize the 6*6*256 feature map to 11*256. in order to find a more accurate classification model, we performed feature extraction and visualisation on both low and high pixel versions of the data. This process aims to further optimise the performance and accuracy of the model. Therefore, this study not only technically improves the automation of pothole road detection, but also provides a strong support for solving practical problems in urban traffic management through in-depth data processing and model optimisation. © 2024 ieee.

关键词： Highway administration

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Out-of-Order Architecture for Real-Time Data-Driven Resilient Planning and Scheduling of cyber-Physical Manufacturing systems

Out-of-Order Architecture for Real-Time Data-Driven Resilien...

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ieee international conference on automation Science and Engineering (CASE)

作者： Mingxing Li Ting Qu Mian Yan Ming Li Zhen He George Q. Huang School of Intelligent Systems Science and Engineering the Institute of Physical Internet and the Guangdong International Cooperation Base of Science and Technology for GBA Smart Logistics Jinan University Zhuhai China Department of Industrial and Systems Engineering and the Research Institute for Advanced Manufacturing The Hong Kong Polytechnic University China College of Management and Economics Tianjin University Tianjin China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

The intrinsic stochasticity of manufacturing is one of the main factors that hinder system resilience. Planning and scheduling problems are typical examples plagued by various manufacturing uncertainties such as stochastic processing time, arrivals of new orders, and uncertain breakdowns of stations. Frequent uncertainties regarding operations and resources disturb the workflow, and their cascading effects create chaos in the whole system. The transparency and traceability in cyber-physical manufacturing systems (CPMS) bring new hope to tackle uncertainties. Inspired by the core spirit of Out-of-Order (OoO) Execution in CPU, this paper proposes a novel OoO architecture, under which production and logistics operations are performed according to real-time executability, for resilient planning and scheduling of CPMS. Computational results have confirmed the effectiveness and resilience of the proposed solution under various uncertainties.

关键词： Out of order Uncertainty Job shop scheduling Processor scheduling Computer architecture Production Real-time systems Planning Manufacturing systems Resilience

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Retinal Vessel Segmentation Based on UNet and Edge Detection 12

Retinal Vessel Segmentation Based on UNet and Edge Detection

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12th international conference on Information technology in Medicine and Education, ITME 2022

作者： Yan, Peixin Li, Zuoyong Hu, Rong Cao, Xinrong Fujian University of Technology College of Computer Science and Mathematics Fuzhou350118 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Colloge of Computer and Control Engineering Fuzhou350121 China

ISBN: (纸本)9798350310153

Retinal vessel segmentation is important for the diagnosis of many diseases. The segmentation of microscopic vessels is one of the challenges because of the complex structure of retinal vessels, which makes it challenging to tell the vessels apart from the background. In order to improve the segmentation performance of retinal vessels, we use the edge detection method of HED to optimize the segmentation effect of UNet. Using Hybrid Dilated Convolution not only increases the perceptual field, but also avoids the loss of information continuity caused by the continuous use of dilated convolution. The Pyramid Pooling Module is used at the end of the encoder to compensate for the information loss caused by downsampling. Finally, the output of edge detection and image segmentation is combined as the final result. The model is evaluated in two mainstream datasets DRIVE and CHASE-DB1, and the experimental results show that the proposed model can improve the performance of retinal vessel segmentation. © 2022 ieee.

关键词： Convolution

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Low Energy Consumption and Time Deterministic Energy-saving Workflow Task Scheduling Algorithm based on DVFS 9

Low Energy Consumption and Time Deterministic Energy-saving ...

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9th ieee international conference on cyber Security and Cloud Computing and 8th ieee international conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2022

作者： Liu, Xun Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan China

ISBN: (数字)9781665480666

ISBN: (纸本)9781665480666

With the development of streaming media, soft real-time system in today's life could participate in the use of more extensive areas. The use frequency was also increasing. Consequently, modern processors were equipped with software control mechanisms such as DVFS (Dynamic Voltage Frequency Scaling) to allow operating systems to meet required performance while reducing power consumption. Therefore, we propose a task scheduling algorithm combined DVFS technology and time deterministic cyclic scheduling to achieve energy saving effect. First, the algorithm needed to minimize the preemption between tasks to reduce latency, so we created a buffer to save periodic tasks to avoid preemption. Second, to reduce the computational cost of the scheduling scheme, a scheduling template were designed to perform tasks. In this paper, the scheduling of periodic tasks, task scheduling would be designed when the task scheduling template would be fixed length. Besides, this algorithm supported that task could adopt appropriate voltage and frequency through DVFS technology in idle time under the condition of satisfying task dependence. Experimental analysis showed that the proposed algorithm could effectively reduce the system energy consumption while ensuring the completion of the task. © 2022 ieee.

关键词： Scheduling

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Air Quality Prediction using Deep Learning models

Air Quality Prediction using Deep Learning models

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2024 international conference on Advancements in Power, Communication and intelligent systems, APCI 2024

作者： Fathima, M. Dhilsath Donavalli, Sashank Kambham, Harshitha School of Computing Srm Institute of Science and Technology Department of Computational Intelligence Chennai Kattankulathur India

ISBN: (纸本)9798350363289

In today's world, air pollution is an important concern for both the general public and the environment. Monitoring and forecasting pollutant concentrations in the environment is critical to effective pollution control and management. Using advanced deep-learning techniques, this study focuses on the development of a time series air quality prediction (AQP) model for numerous pollutants in the air, including small particles of PM2.5, PM10, ground-level ozone (O3), carbon monoxide (CO), sulphur dioxide (SO2), and nitrogen dioxide (NO2). Time series data are used in the study to capture temporal relationships and seasonal trends inherent in air quality measurements. This proposed AQP model evaluates many deep learning architectures, such as Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional LSTM (Bi- LSTM). This study demonstrates how effective these models are at capturing temporal dependencies and seasonal patterns in air quality datasets, pointing towards novel approaches for precise and timely air quality monitoring. The results of this research provide a substantial contribution to the advancement of air quality prediction systems, allowing for better decision- making for public health and environmental protection. © 2024 ieee.

关键词： Sulfur dioxide

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A Concept for Semi-Automatic Configuration of Sufficiently Valid Simulation Setups for Automated Driving systems 27

A Concept for Semi-Automatic Configuration of Sufficiently V...

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27th ieee international conference on intelligent Transportation systems, ITSC 2024

作者： Braun, Niklas Steimle, Markus Torngren, Martin Maurer, Markus Institute of Control Engineering Technische Universitat Braunschweig Braunschweig38106 Germany Kth Royal Institute of Technology Department of Engineering Design Stockholm10044 Sweden

ISBN: (纸本)9798331505929

As simulation is increasingly used in scenario-based approaches to test Automated Driving systems, the credibility of simulation results is a major concern. Arguably, credibility depends on the validity of the simulation setup and simulation models. When selecting appropriate simulation models, a trade-off must be made between validity, often connected to the model's fidelity, and cost of computation. However, due to the large number of test cases, expert-based methods to create sufficiently valid simulation setups seem infeasible. We propose using design contracts in order to semi-automatically compose simulation setups for given test cases from simulation models and to derive requirements for the simulation models, supporting separation of concerns between simulation model developers and users. Simulation model contracts represent their validity domains by capturing a validity guarantee and the associated operating conditions in an assumption. We then require the composition of the simulation model contracts to refine a test case contract. The latter contract captures the operating conditions of the test case in its assumption and validity requirements in its guarantee. Based on this idea, we present a framework that supports the compositional configuration of simulation setups based on the contracts and a method to derive runtime monitors for these simulation setups. © 2024 ieee.

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Importance of cybersecurity Education to Reduce Risks in Academic Institutions 1

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8th international conference on Information and Communication technology for intelligent systems, ICTIS 2024

作者： Guaña-Moya, Javier Salgado-Reyes, Nelson Arteaga-Alcívar, Yamileth Espinosa-Cevallos, Alejandra Pontificia Universidad Católica del Ecuador Quito Ecuador Instituto Tecnológico Universitario Internacional Quito Ecuador Instituto Tecnológico Universitario Cordillera Quito Ecuador

ISBN: (数字)9789819757992

ISBN: (纸本)9789819757985

technology has become a fundamental part of current educational processes, which is why many academic institutions have adopted technological tools in order to improve teaching and learning practices. However, as digital dependence increases in the educational field, it becomes increasingly necessary to guarantee that the systems adopted are secure and protected against cyber threats, considering that academic institutions store a high amount of confidential information, from personal data of students to cutting-edge research, especially at higher levels. For this reason, it is vital that these institutions promote continuous education and training in cybersecurity, both for staff, students, and other members of the educational community. That is why this bibliographic review was developed with the objective of establishing the importance of cybersecurity education for the reduction and control of risks associated with computer attacks within academic institutions, considering the main risks they face, as well as the possible strategies that can be applied to avoid them. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： cyber attacks

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IT Security for Collaborative Machines and Human-Machine Interaction 26

IT Security for Collaborative Machines and Human-Machine Int...

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26th ieee international conference on Emerging Technologies and Factory automation (ETFA)

作者： Yu, Tianzhe Persico, Giuliano Tekkalmaz, Metin Meisberger, Karsten Raddatz, Hannes Riedl, Matthias Ifak eV ICT & Automat Magdeburg Germany DEMAG Cranes & Components GmbH Embedded Elect Dev Wetter Germany ERSTE Dev Dept Ankara Turkey NXP Semicond Germany GmbH Cooperat Innovat Hamburg Germany Univ Rostock Inst Appl Microelect & CE Rostock Germany

ISBN: (纸本)9781728129891

Improved human integration, machine connectivity and decentralized collaborative control systems play an important role in making production systems more flexible. cyber-Physical systems for machine control, mobile HMI or SCADA systems are increasingly connected via Internet-based technologies and must also be protected by this open communication technology. Based on a STRIDE analysis, the paper presents proposals on how to secure data exchange between CPS as well as between CPS and mobile HMI using IoT communication, whereby the practicability plays an important role. First results show that the concepts are feasible and are currently undergoing prototypical testing. Future work will focus on the detailed evaluation with respect to communication performance and the determination of the code overhead of the presented solutions.

关键词： cyber-Physical systems Industrial Communication systems STRIDE Security Industrial Internet of Things CPS IIoT

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