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5th International Conference on Advances in Distributed Computing and Machine Learning, ICADCML 2024

作者： Priakanth, P. Jothimani, K. Gopikrishnan, S. Linga Reddy, C. Department of Computer Science and Design Kongu Engineering College Erode India School of Computer Science and Engineering VIT-AP University Amaravati India Department of Information and Communication Technology University of Agder Kristiansand Norway

ISBN: (纸本)9789819735228

Urban-city administrators are proceeding on smart applications with the fully integrated IoT-artificial intelligence analytics explication assists intelligent-safer workstation, immediate happenstance response, disaster control management including smart electricity, trash, air and water allowing them to produce more prominent levels of flexibility, yielding, sustainability and profitability. Though smart city notion is gradually developing and yet not established all over the world owing to economical, technological, and administrating blockades. This perspective paper aims to accomplish a review of IoT-enabled artificial intelligence regarding the usage of machine learning and deep learning for the development of smarter cities in addition to different computing tools to employ methods, platforms, architectures, and its real-world enactment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Internet of things

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A Study on Wall Climbing of a Four-wheel Drive Ship Painting Robot Using RBF-NN and I-PID Control

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Journal of Institute of Control, Robotics and systems 2024年第7期30卷 740-749页

作者： Kim, Dong-Ju Kim, Sung-Jae Lee, Mun-Haeng Sung, Tae-Kyong Suh, Jin-Ho Department of Intelligent Robot Engineering Pukyong National University Korea Republic of The Industrial Science Technology Research Center Pukyong National University Korea Republic of SI-WARE Co. Ltd Korea Republic of Department of Mechanical System Engineering Pukyong National University Korea Republic of

Painting operations on ships present significant challenges and risks, highlighting the requirement for developing robotic systems that enhance the safety and precision of these operations. This study introduces an adaptive robust control scheme for wall-climbing robots designed for ship painting applications;this design integrates an intelligent proportional-integral-derivative (PID) controller with a radial basis function neural network. The proposed system overcomes the limitations of traditional PID controllers by effectively estimating complex nonlinear dynamics and uncertainties using time-delay information. Furthermore, the accuracy of path-tracking tasks is improved by compensating for errors in time-delay estimation using a neural network. Additionally, the stability of the control system is proven using a Lyapunov-based analytical method. The simulation is highly reliable because it used models that closely resemble actual ship-painting robots. The proposed controller achieves higher tracking performance than traditional PID controllers. The implications of this study extend beyond ship-painting automation, offering insights into other industrial domains in which the use of high-precision robotic systems is paramount. © 2024, Institute of Control, Robotics and systems. All rights reserved.

关键词： Three term control systems

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Electricity Market-Clearing With Extreme Events

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2025年第2期3卷 194-208页

作者： Tapia, Tomas Liang, Zhirui Konstantinou, Charalambos Dvorkin, Yury Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218 United States King Abdullah University of Science and Technology Department of Computer Electrical and Mathematical Sciences and Engineering Thuwal Makkah23955 Saudi Arabia Johns Hopkins University Department of Electrical and Computer Engineering Department of Civil and System Engineering BaltimoreMD21218 United States

Extreme events jeopardize power network operations, causing beyond-design failures and massive supply interruptions. Existing market designs fail to internalize and systematically assess the risk of extreme and rare events. Efficiently maintaining the reliability of renewable-dominant power systems during extreme weather events requires co-optimizing system resources, while differentiating between large/rare and small/frequent deviations from forecast conditions. To address this gap in both research and practice, we propose managing the uncertainties associated with extreme weather events through an additional reserve service, termed extreme reserve. The procurement of extreme reserve is co-optimized with energy and regular reserve using a large deviation theory chance-constrained (LDT-CC) model, where LDT offers a mathematical framework to quantify the increased uncertainty during extreme events. To mitigate the high additional costs associated with reserve scheduling under the LDT-CC model, we also propose an LDT model based on weighted chance constraints (LDT-WCC). This model prepares the power system for extreme events at a lower cost, making it a less conservative alternative to the LDT-CC model. The proposed market design leads to a competitive equilibrium while ensuring cost recovery. Numerical experiments on an illustrative system and a modified 8-zone ISO New England system highlight the advantages of the proposed market design. © 2024 IEEE.

关键词： Weather forecasting

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Enhancing Road Safety: An Intelligent Drowsiness Detection system Based on Deep Neural Networks 7

Enhancing Road Safety: An Intelligent Drowsiness Detection S...

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7th IEEE Pune Section International Conference, PuneCon 2024

作者： Nalavade, Jagannath E. Sachdeo, Rajneeshkaur Kale, Dattatray R. Buchade, Amar Subhedar, Mansi Shinde, Swapnil K. Mit Art Design and Technology University Computer Science and Engineering Pune India BRACT's Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Pune India Pillai Hoc College of Engineering and Technology Electronics and Computer Science Rasayani India

ISBN: (纸本)9798331527822

The aim of this research is to create an intelligent vehicle system that can effectively mitigate the risks associated with drowsy driving, thereby preventing road accidents. Various factors like driver exhaustion, challenging road conditions, and adverse weather contribute to motor vehicle crashes, leading to over 1.35 million deaths annually, as estimated by entities such as the World Health Organization (WHO). To achieve this, the development of a robust warning system is crucial. In this study, we proposed an alert system to detect drowsy drivers. It utilizes a video stream process (VSP) to analyze the gaze's eye-aspect ratio (EAR) and geometric distance through an innate reflex model. Additionally, a facial landmark-based algorithm is employed for accurate eye recognition. When driver drowsiness is detected, the system issues a warning message, along with crash impact and location information, and activates the voice surveillance system. The suggested technique establishes a non-invasive approach for evaluating driver weariness in connection with accident severity. The camera, the fundamental element of this system, continuously acquires facial landmarks recognized by designated locations and analyzes them. Drivers who are distracted and have poor lighting may show signs of sleepiness. © 2024 IEEE.

关键词： Deep neural networks

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STARTUP ANALYSES OF A HELIUM-XENON GAS-COOLED REACTOR 30

STARTUP ANALYSES OF A HELIUM-XENON GAS-COOLED REACTOR

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30th International Conference on Nuclear engineering, ICONE 2023

作者： Ma, Yugao Bao, Hui Lu, Jiahao Ding, Shuhua Zhang, Meng Yang, Xiaolong Deng, Jian Zhang, Muhao Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China

ISBN: (纸本)9784888982566

The Helium-Xenon (He-Xe) gas-cooled reactor uses a He-Xe gas mixture to remove the heat from the reactor core. It has the characteristics of a long life-cycle, simple operation, and high power-mass ratio, which has an excellent application prospect in the field of Space Reactors Power systems. The high operation temperature distinguishes the He-Xe gas-cooled reactor from the traditional reactor in reactivity feedback characteristics. Except for the Doppler effect of the fuel and monolith, the thermal expansion also introduces reactivity feedback during reactor operation. In this work, reactivity feedback characteristics, steady-state characteristics, and transient characteristics of a hundred-kilowatt-level He-Xe gas-cooled reactor (Submersion-Subcritical Safe Space reactor, S4) were analyzed. The Doppler feedback characteristics and thermal expansion feedback coefficients of fuel, matrix, and reflector from the cold to the hot state of the S4 reactor core were calculated based on the reactor Monte Carlo code (RMC). The results show that the S4 reactor core is mainly affected by the fuel Doppler effect and the matrix thermal expansion effect. Furthermore, the temperature distributions of fuel and He-Xe gas of the S4 reactor were calculated using the He-Xe reactor transient analysis code (HXRTRAN). The transient characteristics of the S4 reactor core when different reactivity was introduced were analyzed. This study may provide a reference for the operation state of the He-Xe gas-cooled reactor. © 2023 by JSME.

关键词： Helium

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Entangled chip removal utilizing mass-spring model with mobile manipulator

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CIRP Annals 2025年

作者： Takahashi, Ryuki Kimura, Hayato Kakinuma, Yasuhiro Department of System Design Engineering Faculty of Science & Technology Keio University 3-14-1 Hiyoshi Yokohama Kohoku-ku Japan

This study aims to automate the removal of entangled chips in manufacturing environments using a mobile manipulator. Despite advancements in factory automation technology, this task often necessitates manual intervention. Accordingly, this study proposes a deformable chip model (based on a reconfigurable mass-spring system per frame), incorporating visual chip tracking data and force reactions. Consequently, to evaluate the removal state, an efficient removal strategy is derived by defining the instantaneous stiffness and energy absorption rate. Validation of system performance through two removal tests demonstrates the feasibility of automating entangled chip removal, contributing to enhanced operational efficiency in fully automated production lines. © 2025 The Author(s)

关键词： Factory automation

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Predicting Financial Success: Regression Modeling of Sustainable Business Practices in Start-up Ecosystem 18

Predicting Financial Success: Regression Modeling of Sustain...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Sharma, Riya Christa, Sharon Mani, Ambica Prakash Sarishma Graphic Era Deemed to Be University Department of Commerce Dehradun India Mit Art Design and Technology University Department of Computer Science and Engineering Pune India

ISBN: (纸本)9789380544519

This research investigates the intricate relationship between sustainability adoption and the financial performance of startups in the Indian business landscape. Utilizing data from a survey conducted among 152 startups, the study employs robust statistical analyses, including regression to discern the impact of sustainable practices on financial outcomes. Positioned at the nexus of global imperatives for sustainable development and the pragmatic challenges faced by startups, the research addresses the unique context of India's entrepreneurial ecosystem. By combining empirical insights with statistical rigor, the study illuminates the mechanisms by which sustainability affects financial health. This study provides actionable information for startup decision-makers, informs policy discussions, and broadens scholarly discourse on the symbiotic relationship between sustainability and financial performance. Its findings are relevant to a wide range of stakeholders, providing a nuanced knowledge of how entrepreneurs might navigate the convergence of sustainability and economic resilience within the unique contours of the entrepreneurial scene. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： circular economy startup sustainable business model sustainable business practices triple bottom line

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Fabrication and Properties of Tungsten-doped Indium Oxide Ultraviolet Photodetector

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Sensors and Materials 2024年第5期36卷 1835-1848页

作者： Lam, Artde Donald Kin-Tak Chang, Sheng-Po Kuan, Chieh-Yu Chang, Shoou-Jinn School of Design Straits College of Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Fujian Province Fuzhou City China Department of Microelectronics Engineering National Kaohsiung University of Science and Technology Kaohsiung City811 Taiwan Institute of Microelectronics Department of Electrical Engineering National Cheng Kung University Tainan City70101 Taiwan

In this study, we deposit tungsten-doped indium oxide (InWO) thin films as an active layer for ultraviolet (UV) photodetectors (PDs) by radio-frequency (RF) magnetron cosputtering and discuss the optical and electrical properties of the thin film under different process conditions. The introduction of oxygen gas during the thermal annealing of oxide thin films leads to further rearrangement of the lattice and fulfills the oxygen deficiency region. When InWO thin films are thermally annealed in oxygen ambient, its photo-dark current ratio can be greatly improved. Thus, InWO UV PDs with active layers fabricated by cosputtering with sputtering powers of 80 W for the In2O3 target and 5 W for the WO3 target followed by thermal annealing for 1 h in oxygen ambient have the highest performance with an ON/OFF current ratio greater than 106, a responsivity of 160 A W−1, and a UV-to-visible rejection ratio of 4.71 × 104. Also, time-dependent switching properties have been demonstrated. © 2024 M Y U Scientific Publishing Division. All rights reserved.

关键词： Annealing

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Identification of Key Signaling Pathways and Novel Computational Drug Target for Depression and Coronary Artery Disease

Identification of Key Signaling Pathways and Novel Computati...

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2024 IEEE International Conference on Computing, Applications and systems, COMPAS 2024

作者： Hosen, Md. Faruk Basar, Md. Abul Yasmin, Mst. Farjana Morshed, Monir Uddin, Muhammad Shahin Daffodil International University Department of Computing and Information System Dhaka1216 Bangladesh Department of Computer Science and Engineering Dhaka1230 Bangladesh Mawlana Bhashani Science and Technology University Department of Information and Communication Technology Tangail1902 Bangladesh

ISBN: (纸本)9798331529765

Psychological disorders, such as anxiety, bipolar disorder, panic disorder, stress, depression, and schizophrenia, are increasingly prevalent worldwide. Among these conditions, depression is particularly notable as one of the most common and debilitating neuropsychiatric disorders. Individuals with depression may be at a higher risk of developing oronary Artery Disease (CAD). Depression can contribute to poor lifestyle choices, such as unhealthy eating, lack of exercise, and smoking, which are risk factors for CAD. The emotional stress and anxiety associated with depression can strain the heart and exacerbate CAD symptoms. The relationship is not one-sided. CAD itself can be a significant source of emotional distress, leading to symptoms of depression and anxiety in affected individuals. Managing both conditions in tandem can be complicated. Treating CAD may involve medications, lifestyle modifications, and potentially surgical interventions. Meanwhile, depression often requires therapy, counseling, and medication. Coordinating care and addressing both conditions simultaneously is crucial. In our study, we investigated the molecular connections between CAD and Depression using GSE98793 and GSE20681 microarray datasets. After preprocessing, we identified key hub genes, including CCT2, SVIL, REPS2, ASPH, and UBC, in the shared ProteinProtein Interaction network. KEGG pathways linked these DEGs to colorectal and cancer pathways. Our next steps involve exploring microRNAs, TFs, and GO analysis. These findings offer promising leads for potential therapies, uniting CAD and Depression under a common molecular framework, advancing our understanding of these conditions. © 2024 IEEE.

关键词： Blood vessels

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Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction 3

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

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3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. Lathif, Syed Ismail Abdul Leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 IEEE.

关键词： Smart contract

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