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The Challenges and Opportunities of Smart Cities Infrastructure

SN Computer Science 2024年第6期5卷 713页

作者： Abuali, Amer Alharthi, Wejdan Althbyani, Mariam Ghabban, Fahad Ameerbakhsh, Omair Alfadli, Ibrahim Al-Shehri, Ashwaq Hasen Fallatah, Najmah Adel College of Computer Science and Engineering Information System Department Taibah University

Information communications technology (ICT) refers to the technology used for communication and managing information must be utilized to enhance the environment, economics, mobility, and governance, among other facets of urban life, in order to create smart cities. However this progress is frequently accompanied by a number of challenges and unfavorable outcomes. This study aims to uncover ICT difficulties related to smart city infrastructure through an extensive literature review. In addition, a survey was carried out among Saudi nationals to find out what they thought about, anticipated, and worried about in terms of smart city concepts and features. The study also looked at a literature checklist of ICT problems, which included dangers to information security, incompatibilities across systems, privacy concerns, and deficiencies in digital capabilities. Based on the findings it appears that privacy breaches and information security concerns are the most important issues. This is explained by heightened susceptibility and potential, cyberattacks and a pervasive ignorance of the protection of personal data. Because of the anticipated high costs and difficulties with adaption and utilization, the public is concerned about incompatibility between systems and services. Furthermore, older individuals and those with lesser educational achievement have different digital skills. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Compatibility ICT challenges Information insecurity Privacy Smart city Technology skills

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Soft-switching predictive Type-3 fuzzy control for microgrid energy management

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Energy Informatics 2025年第1期8卷 1-33页

作者： Ayadi, Walid Tavoosi, Jafar Sarvenoee, Amirhossein Khosravi Mohammadzadeh, Ardashir Mechatronics and Intelligent System Abu Dhabi Polytechnic Abu Dhabi United Arab Emirates Department of Electrical Engineering Ilam University Ilam*** Iran Department of Electrical Engineering University of Bonab Bonab Iran

Because each mode has distinct optimization requirements, optimizing the economic performance of microgrids (MGs) in grid-connected and islanded modes presents unique issues. This research offers a novel methodology to overcome this difficulty and better use renewable resources while satisfying the growing needs of the energy market. To maximize the MG’s performance, this approach combines fuzzy control, machine learning, and artificial intelligence with soft switching technologies. Two predictive rules are used in the design of the control system to handle the particular requirements of either the grid-connected or islanded mode depending on the MG’s operational condition. The study’s findings demonstrate that, in addition to lowering energy expenses in large commercial buildings, the suggested strategy optimizes the use of renewable energy sources and storage capacity in a range of network scenarios. This method offers more flexibility in response to network changes and greatly improves energy efficiency. © The Author(s) 2025.

关键词： Fuzzy control

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An attention-based approach for Koopman modeling and predictive control of nonlinear systems

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ISA Transactions 2025年 162卷 47-63页

作者： Wang, Meixi Lou, Xuyang Cui, Baotong Suykens, Johan Institute of System Engineering Jiangnan University Wuxi214122 China Department of Electrical Engineering ESAT-STADIUS KU Leuven Kasteelpark Arenberg 10 LeuvenB-3001 Belgium

We develop an innovative attention-based deep learning method for constructing Koopman eigenfunctions, addressing the challenge of accurately modeling nonlinear systems for predictive control. This method is motivated by the need to identify a diffeomorphism that precisely delineates the topological conjugacy between nonlinear dynamics and their linearized counterparts. Leveraging the capabilities and suitability of invertible neural networks, we deploy an architecture equipped with conditional affine coupling layers to approximate this diffeomorphism. A pivotal feature is the integration of an attention mechanism within these layers, enhancing the capture of complex interactions across various layers. Additionally, we propose an alternative strategy, which employs an invertible decoding neural network in conjunction with a frozen decoder, to refine the diffeomorphism approximation further. Utilizing Koopman eigenfunctions and eigenvalues obtained from the learned diffeomorphism, we construct a lifted linear system with an optimized input matrix via multi-step error minimization, which facilitates the predictive control of nonlinear systems through an extended robust linear model predictive control framework. Numerical examples and a physical experiment validate the efficacy of our framework, demonstrating superior prediction performance compared to existing dynamic mode decomposition-based methods. © 2025 International Society of Automation

关键词： Eigenvalues and eigenfunctions

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Brain inspired iontronic fluidic memristive and memcapacitive device for self-powered electronics

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Microsystems & Nanoengineering 2025年第1期11卷 465-476页

作者： Muhammad Umair Khan Bilal Hassan Anas Alazzam Shimaa Eissa Baker Mohammad Center for Cyber-Physical Systems-System on Chip Lab Khalifa UniversityAbu Dhabi 127788UAE Department of Computer and Information Engineering Khalifa UniversityAbu Dhabi 127788UAE Department of Electrical Engineering Khalifa UniversityAbu Dhabi 127788UAE Division of Engineering New York UniversityAbu Dhabi 129188UAE Department of Mechanical and Nuclear Engineering Khalifa UniversityAbu Dhabi 127788UAE Department of Chemistry Khalifa UniversityAbu Dhabi 127788UAE

Ionic fluidic devices are gaining interest due to their role in enabling self-powered neuromorphic computing *** this study,we present an approach that integrates an iontronic fluidic memristive(IFM)device with low input impedance and a triboelectric nanogenerator(TENG)based on ferrofluid(FF),which has high input *** incorporating contact separation electromagnetic(EMG)signals with low input impedance into our FF TENG device,we enhance the FF TENG’s performance by increasing energy harvesting,thereby enabling the autonomous powering of IFM devices for self-powered ***,replicating neuronal activities using artificial iontronic fluidic systems is key to advancing neuromorphic *** fluidic devices,composed of soft-matter materials,dynamically adjust their conductance by altering the solution *** developed voltage-controlled memristor and memcapacitor memory in polydimethylsiloxane(PDMS)structures,utilising a fluidic interface of FF and polyacrylic acid partial sodium salt(PAA Na^(+)).The confined ion interactions in this system induce hysteresis in ion transport across various frequencies,resulting in significant ion memory *** IFM successfully replicates diverse electric pulse patterns,making it highly suitable for neuromorphic ***,our system demonstrates synapse-like learning functions,storing and retrieving short-term(STM)and long-term memory(LTM).The fluidic memristor exhibits dynamic synapse-like features,making it a promising candidate for the hardware implementation of neural *** TENG/EMG device adaptability and seamless integration with biological systems enable the development of advanced neuromorphic devices using iontronic fluidic materials,further enhanced by intricate chemical designs for self-powered electronics.

关键词： iontronic memristive ionic fluidic devices memcapacitive ff teng s ff teng fluidic triboelectric nanogenerator teng based

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

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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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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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