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Optimized Model Based Controller with Model Plant Mismatch for NMP Mitigation in Boost Converter

Computer systems Science & engineering 2023年第8期46卷 1961-1979页

作者： R.Prasanna Uma Govindarajan NSBhuvaneswari Department of Electrical and Electronics Engineering Power System DivisionCollege of Engineering GuindyAnna UniversityChennai600025India Department of Electrical and Electronics Engineering GKM College of Engineering and TechnologyChennai600063India

In this paper,an optimized Genetic Algorithm(GA)based internal model controller-proportional integral derivative(IMC-PID)controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase(NMP)behavior due to the presence of a right-half plane zero(RHPZ).This RHPZ limits the dynamic performance of the converter and leads to internal *** IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameterλ.Also,this paper addresses the influences of the model-based controller with model plant mismatch on the closed-loop *** conventional IMC PID design is realized as an optimization problem with a resilient controller being determined through a genetic *** results suggested that GA–IMC PID coheres to the optimum designs with a fast convergence rate and outperforms conventional IMC PID controllers.

关键词： Boost converter non-minimum phase internal model control dynamic controller

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Changes in lake surface temperature on the Tibetan Plateau from 2000 to 2022 and their driving factors

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Science China Earth Sciences 2025年第05期68卷 1641-1655页

作者： Yuanlin QIU Jie CHEN Deliang CHEN State Key Laboratory of Water Resources Engineering and Management Wuhan University Department of Earth System Sciences Tsinghua University Regional Climate Group Department of Earth Sciences University of Gothenburg

Lake surface temperature（LST） is a key parameter in regulating regional water-carbon cycles and biological processes, playing a critical role in the energy and mass balance of lakes. The Tibetan Plateau（TP） is home to thousands of lakes and is highly sensitive to climate change. Therefore, the response of these lakes to a warming climate is crucial for the water security and ecological stability of the “Asian Water Tower”. However, the long-term trend of LST and its driving factors on the TP over the past two decades remain unclear. Here, we employ an all-weather land surface temperature dataset and a representative lake method to investigate the interannual trend of LST on the TP from 2000 to 2022. The analysis uses temperature data from 519 to 581 lakes with interannual dynamic changes in surface area. The results show that lakes on the TP exhibit an overall warming trend, with an average rate of 0.10±0.27°C（10 a）-1. Among the representative lakes, 61% show a warming trend. The most significant warming occurs in autumn, with 91% of the representative lakes showing an increase in LST(0.47±0.30°C（10 a）-1). The warming rate in spring is about half of that in autumn. In winter, the LST trend exhibits a polarized pattern: although some lakes experience significant warming, more than half show intense cooling. In summer, the trend of LST change is more moderate than that in other seasons. The positive feedback from the reduction in lake ice duration drives the LST trend on the TP. The lake ice duration reduces every 10-day, the annual LST increases 0.4°***, altitude and lake expansion can also influence LST changes. Lakes at lower altitudes generally experience higher warming trends. Lake expansion can exacerbate lake warming in autumn by enhancing thermal inertia and delaying lake freeze-up.

关键词： Tibetan Plateau Lake surface temperature Climate change Random forest Attribution analysis

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Controlling Mobile Robot Navigation Equipped with Computer Vision Perception for Text using OCR Technique 21

Controlling Mobile Robot Navigation Equipped with Computer V...

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21st International Multi-Conference on systems, Signals and Devices, SSD 2024

作者： Ismael, Khansaa Dheyaa Saeed, Elaf A. Collage of Information Engineering AL-Nahrain University Department of System Engineering Baghdad Iraq

ISBN: (纸本)9798350374131

Recently, computer vision technology has been widely used to understand the visual world by extracting information depending on the digital images, which is done by using a conventional camera with the designed system. This work proposed a system that will employ computer vision for text detection by using the Optical Character Recognition (OCR) technique, where the camera is supported on the four-wheel derived mobile robot. The proposed system integrates the mobile robot navigation and the functionality of OCR to detect the signs text by scanning the street signs, the function of perception text system consists of two steps first one building four-wheel mobile robot using Arduino UNO microcontroller which represent an opensource software and hardware Italian company, UNO meaning one in Italian language, then navigate this mobile robot by using HG-05 Bluetooth wireless communication module, the second step represents the process of detecting text inside images captured by web camera install on the mobile robot and converting the text into an electronic form, the two steps realized by OpenCV(Open Source Computer Vision Library) python by importing cv2 method, using tesseract library, and ImageGrab module in python to detect and recognition text, the proposed system can be employed the digitization to reduce the effort of humans in battle zoon and storing these information in dedicated documents, the proposed system can be employed for military applications, detect path in battle zoon by detection and recognition the text plate in that zoon. The perception text method is presented by using the OCR technique and an android phone with a web camera, where all this equipment is connected to the mobile robot, the result will demonstrate the text extracts match 100% with the snapped image from real-time video, by transforming each road text plate to save as a text file containing a stream of information represent the corresponding character from the real-time video to the r

关键词： Computer vision

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Chemical surface tuning of zinc metal anode toward stable,dendrite-less aqueous zinc-ion batteries

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Journal of Energy Chemistry 2023年第11期86卷 1-8,I0001页

作者： Pranav Kulkarni Sun-Sik Kim Hyun Young Jung Department of Energy Engineering Gyeongsang National UniversityJinju-siGyeongnam 52725South Korea Department of Energy System Engineering Gyeongsang National UniversityJinju-siGyeongnam 52725South Korea

The commercialization of Zn batteries is confronted with urgent challenges in the metal anode,such as dendrite formation,capacity loss,and cracking or ***,surface interfacial engineering of the Zn anode is introduced for achieving safety and dendritic-free cycling for high-performance aqueous Zn batteries through a simple but highly effective chemical etching-substitution *** chemical modification induces a rough peak-valley surface with a thin fluorine-rich interfacial layer on the Zn anode surface,which regulates the growth orientation via guiding uniform Zn plating/stripping,significantly enhances accessibility to aqueous electrolytes and improves wettability by reducing surface *** a result,such a synergetic surface effect enables uniform Zn plating/stripping with low polarization of 29 m V at a current density of 0.5 m A cm^(-2) with stable cyclic performance up to 1000 ***,a full cell composed of a fluorine-substituted Zn anode coupled with aβ-MnO_(2)or Ba-V_(6)O_(13)cathode demonstrates improved capacity retention to 1000 cycles compared to the pristine-Zn *** proposed valley deposition model provides the practical direction of surface-modified interfacial chemistries for improving the electrochemical properties of multivalent metal anodes via surface tuning.

关键词： Dendrite free Peak-Valley surface Zinc-ion batteries Surface modification Fluorinated interface

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Ontology-grounded Automatic Knowledge Graph Construction by LLM under Wikidata schema

Ontology-grounded Automatic Knowledge Graph Construction by ...

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KDD Workshop on Human-Interpretable AI 2024, HI-AI 2024

作者： Feng, Xiaohan Wu, Xixin Meng, Helen Department of System Engineering and Engineering Management Chinese University of Hong Kong Hong Kong

We propose an ontology-grounded approach to Knowledge Graph (KG) construction using Large Language Models (LLMs) on a knowledge base. An ontology is authored by generating Competency Questions (CQ) on knowledge base to discover knowledge scope, extracting relations from CQs, and attempt to replace equivalent relations by their counterpart in Wikidata. To ensure consistency and interpretability in the resulting KG, we ground generation of KG with the authored ontology based on extracted relations. Evaluation on benchmark datasets demonstrates competitive performance in knowledge graph construction task. Our work presents a promising direction for scalable KG construction pipeline with minimal human intervention, that yields high quality and human-interpretable KGs, which are interoperable with Wikidata semantics for potential knowledge base expansion. © 2024 Copyright for this paper by its authors.

关键词： Knowledge graph

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Robust CNN for facial emotion recognition and real-time GUI

AIMS Electronics and Electrical Engineering

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AIMS Electronics and Electrical engineering 2024年第2期8卷 217-236页

作者： Ali, Imad Ghaffar, Faisal Department of Computer Science University of Swat KP Swat Pakistan System Design Engineering Department University of Waterloo Waterloo Canada

Computer vision is witnessing a surge of interest in machines accurately recognizing and interpreting human emotions through facial expression analysis. However, variations in image properties such as brightness, contrast, and resolution make it harder for models to predict the underlying emotion accurately. Utilizing a robust architecture of a convolutional neural network (CNN), we designed an efficacious framework for facial emotion recognition that predicts emotions and assigns corresponding probabilities to each fundamental human emotion. Each image is processed with various pre-processing steps before inputting it to the CNN to enhance the visibility and clarity of facial features, enabling the CNN to learn more effectively from the data. As CNNs entail a large amount of data for training, we used a data augmentation technique that helps to enhance the model's generalization capabilities, enabling it to effectively handle previously unseen data. To train the model, we joined the datasets, namely JAFFE and KDEF. We allocated 90% of the data for training, reserving the remaining 10% for testing purposes. The results of the CCN framework demonstrated a peak accuracy of 78.1%, which was achieved with the joint dataset. This accuracy indicated the model's capability to recognize facial emotions with a promising level of performance. Additionally, we developed an application with a graphical user interface for real-time facial emotion classification. This application allows users to classify emotions from still images and live video feeds, making it practical and user-friendly. The real-time application further demonstrates the system's practicality and potential for various real-world applications involving facial emotion analysis. © 2024 the Author(s).

关键词： Graphical user interfaces

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Achieving tractable and reliable agriculture supply chain operations through Industry 4.0 tools to support Lean Six Sigma application

International Journal of Industrial Engineering and Operatio...

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International Journal of Industrial engineering and Operations Management 2025年第2期7卷 117-149页

作者： Yeni, Fatma Betül Gürsoy Yılmaz, Beren Kayhan, Behice Meltem Özçelik, Gökhan Yılmaz, Ömer Faruk Department of Industrial Engineering Karadeniz Technical University Trabzon Turkey Department of Industrial and System Engineering University of Florida Gainesville FL United States

Purpose: This study aims to address challenges related to long lead time within a hazelnut company, primarily attributed to product quality issues. The purpose is to propose an integrated lean-based methodology incorporating a continuous improvement cycle, drawing on Lean Six Sigma (LSS) and Industry 4.0 applications. Design/methodology/approach: The research adopts a systematic approach, commencing with a current state analysis using VSM and fishbone analysis to identify underlying problems causing long lead time. A Pareto analysis categorizes these problems, distinguishing between supplier-related issues and deficiencies in lean applications. Lean tools are initially implemented, followed by a future state VSM. Supplier-related issues are then addressed, employing root cause analyses and Industry 4.0-based countermeasures, including a proposed supplier selection model. Findings: The study reveals that, despite initial lean implementations, lead times remain high. Addressing supplier-related issues, particularly through the proposed supplier selection model, significantly reduces the number of suppliers and contributes to lead time reduction. Industry 4.0-based countermeasures ensure traceability and strengthen supplier relationships. Originality/value: This research introduces a comprehensive LSS methodology, practically demonstrating the application of various tools and providing managerial insights for practitioners and policymakers. The study contributes theoretically by addressing challenges comprehensively, practically by showcasing tool applications and managerially by offering guidance for system performance enhancement. © 2024, Fatma Betül Yeni, Beren Gürsoy Yılmaz, Behice Meltem Kayhan, Gökhan Özçelik and Ömer Faruk Yılmaz.

关键词： Axiomatic design Food industry Industry 4.0 Lean Six Sigma Supplier selection

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Green Networking: Challenges, Opportunities, and Future Trends for Sustainable Development 23

Green Networking: Challenges, Opportunities, and Future Tren...

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11th International Conference on Computer and Communications Management, ICCCM 2023

作者： Safitra, Muhammad Fakhrul Lubis, Muharman Kurniawan, Mochamad Teguh Alhari, Muhammad Ilham Nuraliza, Hilda Azzahra, Shafira Fatimah Putri, Deyana Prastika Information System Department School of Industrial and System Engineering Telkom University Indonesia Industrial Engineering Department School of Industrial and System Engineering Telkom University Indonesia

ISBN: (纸本)9798400707735

This research discusses Green Networking, an important concept in reducing the environmental impact of information and communication technology in the digital era. In this study, the author conducted secondary data analysis and reviewed published papers related to the implementation of green networking. The analysis results indicate that green networking has great potential to have a positive impact on the environment and reduce carbon emissions, but its implementation still faces several challenges such as higher costs and technological complexity. This research also discusses opportunities that can be taken in the implementation of green networking, such as improving energy efficiency in network infrastructure, developing renewable energy technologies, and increasing public awareness of the importance of preserving the environment through utilization of environmentally friendly technologies. Furthermore, future research and development of green networking are expected to be a primary focus in supporting sustainable development. In conclusion, this paper asserts that green networking has great potential to contribute to sustainable development and environmental preservation. However, the implementation of green networking requires collaboration among various parties, including industry, government, and society. With new innovations and increasing awareness of the importance of preserving the environment, it is expected that green networking can become an effective solution to reduce the environmental impact of information and communication technology in the future. © 2023 ACM.

关键词： Sustainable development

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Leveraging Digital Intelligence for Network Economy and Knowledge Management in Tecnology-Focused Firms 23

Leveraging Digital Intelligence for Network Economy and Know...

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9th International Conference on Industrial and Business engineering, ICIBE 2023

作者： Safitra, Muhammad Fakhrul Putri, Deyana Prastika Lubis, Fahdi Saidi Lubis, Muharman Fakhrurroja, Hanif Saedudin, Rd Rohmat Information System Department School of Industrial and System Engineering Telkom University Indonesia Industrial Engineering Department School of Industrial and System Engineering Telkom University Indonesia

ISBN: (纸本)9798400708824

This paper examines the role of digital intelligence in leveraging the network economy and enhancing knowledge management in technology-focused firms. It explores the key elements of knowledge management, such as knowledge creation and sharing, and their importance in driving innovation and regional development. The relationship between digital intelligence and the resource-based view is explored, highlighting the strategic utilization of digital intelligence to optimize knowledge management strategies and gain a competitive advantage. The paper also investigates the significance of social capital, social network theory, and their connection to knowledge management, emphasizing the role of digital intelligence in strengthening social capital, facilitating collaboration, and enabling seamless knowledge sharing. Additionally, the implications of risk and real options theory in knowledge management are discussed, emphasizing how digital intelligence aids in identifying, assessing, and managing risks and real options, thereby enhancing decision-making processes. Furthermore, the paper explores the integration of digital intelligence in the network economy, highlighting its impact on connectivity, collaboration, and knowledge exchange among stakeholders. The findings underscore the transformative potential of digital intelligence in driving innovation and enhancing firm performance. In conclusion, this paper emphasizes the significance of digital intelligence in leveraging the network economy and optimizing knowledge management in technology-focused firms, providing valuable insights for practitioners and researchers, and calling for further exploration of innovative strategies and technologies in knowledge management and the network economy. © 2023 ACM.

关键词： Knowledge management

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Highly dense and ultrathin gadolinia-doped ceria interlayer for enhanced performance of large-area anode-supported solid oxide fuel cell

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Progress in Natural Science:Materials International 2023年第5期33卷 733-741页

作者： Sang Woo Shin Amjad Hussain Muhammad Zubair Khan Dong Woo Joh Tak-Hyung Lim Seung-Bok Lee Jong-Eun Hong Joon Hyung Shim Rak-Hyun Song Hydrogen Energy Research Division Korea Institute of Energy Research Department of Mechanical Engineering Korea University Department of Advanced Energy and System Engineering Korea University of Science and Technology(UST) Department of Materials Science & Engineering Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology

The fabrication of a highly dense and ultrathin Gd doped ceria(GDC) interlayer on a large-area, porous electrolyte-coated planar anode support using vacuum slurry coating is studied for application in solid oxide fuel cells(SOFCs). The electrolyte-coated planar anode support body is fabricated by tape casting and pre-sintering is performed at 1100, 1150, and 1200°C. The GDC interlayer is coated onto the pre-sintered electrolyte-coated anode support using a vacuum slurry coating process with different immersion times(30–60 s). A highly dense and ultrathin GDC interlayer with a thickness of 1.48 μm is produced after co-sintering at 1400°C. The 1200°C pre-sintered electrolyte-coated anode support showed a thin and highly dense GDC interlayer which is attributed to a lower shrinkage difference between the coated GDC interlayer and pre-sintered body. The electrochemical performance of a vacuum slurry-coated GDC interlayer cell is 38 % higher compared to that of the screen-printed GDC-coated cell at 700°C due to the greatly reduced Ohmic and electrode polarization resistances. The considerable improvement in the performance is attributed to the ultrahigh GDC density which has prevented the secondary phase formation between the cathode and electrolyte. This study presents the economical, scalable, and reproducible process for the fabrication of highly robust GDC interlayer for the large-area planar anode-supported SOFCs.

关键词： Solid oxide fuel cell Vacuum slurry coating GDC interlayer Sintering Performance

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