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作者： Feng, Hao Deng, Yuhui Yu, Liang Department of Computer Science Jinan University Guangzhou China Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

With the explosive growth of data, hundreds of thousands of servers may be contained in a single data center. Hence, node failures are unavoidable and generally negatively effects the performance of the whole data center. Additionally, data centers with a large number of nodes will cause plenty of energy consumption. Many existing task scheduling techniques can effectively reduce the power consumption in data centers by considering heat recirculation. However, the traditional techniques do not take the situation of node failures into account. This paper proposes an airflow-based failure model for data centers by leveraging heat recirculation. In this model, the spatial distribution and time distribution of failures are considered. Furthermore, a genetic algorithm (GA) and a simulated annealing algorithm (SA) are implemented to evaluate the proposed failure model. Because the positions of node failures have a significant impact on the heat recirculation and the energy consumption of data centers, failures with different positions are analyzed and evaluated. The experimental results demonstrate that the energy consumption of data centers can be significantly reduced by using the GA and SA algorithms for task scheduling based on the proposed failure model. © 2019 John Wiley & Sons, Ltd.

关键词： Energy efficiency

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Achieving concurrency in cloud-orchestrated Internet of Things for resource sharing through multiple concurrent access

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Computational Intelligence 2024年第1期40卷 e12630-e12630页

作者： Xu, Xuedong Sun, Wei Vivekananda, G.N. Shankar, Achyut Department of Mechanical Engineering School of Mechanical and Electrical Engineering Changchun Institute of Technology Changchun China School of Architecture and Design Changchun Institute of Technology Changchun China Department of CSE Madanapalle Institute of Technology & Science India Department of computer science and Engineering ASET Amity University Noida India

Cloud-orchestrated Internet of Things (IoT) facilitates proper utilization of network resources and placating user demands in smart communications. Multiple concurrent access (MCA) techniques designed for cloud-assisted communication helps to achieve better resource sharing features with fault tolerance ability. A multi-objective resource allocation and sharing (RAS) for balancing MCA in cloud-orchestrated IoT is presented in this article. The RAS constraints are modeled through linear programming (LP) as an optimization approach. The constraints are resolved using genetic representations (GR) for reducing the unserviced requests and failed resource allocations. Conventional genetic stages are inherited by the LP model to solve resource allocation and access issues reducing latency. The combined LP and GR jointly resolve resource allocation and MCA stagnation in cloud network. A fair outcome of LP-GR is estimation using the metrics response latency, resource utilization, request handled, and average latency. © 2020 Wiley Periodicals LLC.

关键词： Linear programming

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Evaluation of Critical Factors in Urban Matrix Environment from the Perspective of Ecological Design

Evaluation of Critical Factors in Urban Matrix Environment f...

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2022 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2022

作者： Hou, Yi-You Liu, Kuang-Sheng Lin, Jiun-Hung Lin, Ming-Hung Tin, Lou-Yang National Kaohsiung University of Science and Technology Department of Intelligent Commerce Kaohsiung City Taiwan Cheng Shiu University Department of Architecture and Interior Design Kaohsiung City Taiwan College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Cheng Shiu University Department of Electrical Engineering Kaohsiung City Taiwan

ISBN: (数字)9781665495875

ISBN: (纸本)9781665495875

The ecological environment of human-centered habitats, cities, is gradually emphasized that the idea of sustainable development is proposed to stress on the integration of development and conservation. Besides, under current resource-applied environment, long-term management of resources is planned and used for preventing resources from shortage. Current development of urban central areas is about saturated, and the rapid expansion of urban fringe is about out of control. Effective recovery of urban landscape ecological structure and function as well as retention, restoration, and regeneration of urban natural environment to balance urban ecosystem and natural ecosystem are primary issues to improve urban environmental quality. Aiming at residents in Kaohsiung City, as the questionnaire objects, 360 copies of questionnaire are distributed as the research samples, and 294 valid copies are retrieved, with the retrieval rate 82%. The research results show *** ecology as the most emphasized dimension in the evaluation of urban matrix environment from the perspective of ecological design, and *** five mostly emphasized indicators, among 20, are green coverage ratio, provision of learning opportunities, diversity of plant species, recoverable materials, and participation ways. According to the results to propose the conclusion. It is expected to dig out specific opportunities for the sustainable use and development of urban matrix and to develop a complete and systematic landscape ecological network, with the combination with other landscape elements, to promote urban ecological quality. © 2022 IEEE.

关键词： Ecosystems

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Spline Global MPPT with PID Controller Based on Levy Invasive Weed Technique for Renewable Energy Resources of Smart Homes

Spline Global MPPT with PID Controller Based on Levy Invasiv...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Aziza I. Hussein Mady Mohammad Passent Elkafrawy Rabab Hamed M. Aly College of Engineering Energy and Technology Research Center Effat University Jeddah Saudi Arabia College of Architecture Effat University Jeddah Saudi Arabia The Higher Institute for Management and Information Technology Minya Egypt Computer Science Department Faculty of Computer Science Nahda University Beni Suef Egypt

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

Renewable energy systems, particularly photovoltaic (PV) systems, have been played important role in the reducing carbon emissions. A primary concern in the field of photovoltaics (PV) based on the design of the maximum power point tracking (MPPT) is the capacity to accurately monitor power across many parameters in addition to ascertain the power production of solar cells or wind turbines and adjust the load to maximise power efficiency under varying weather conditions. On another hands, the hybrid smart system uses a wind catcher to reduce the amount of energy consumed by buildings from the grid, which is a historically significant architectural component for cross ventilation and passive cooling. This paper presents an updating of model that proposes improvements to the regulation of Spline MPPT with tuning PID controller by using Levy Invasive Weed optimization (LIWO)technique. A rapid, accurate, and straightforward approach for determining the (MPPT) of PV systems under consistent irradiation and partial shade, as well as wind turbines, is presented using the Spline- MPPT technique. The model of this paper employs LIWO in conjunction with a PID controller to improve the selection of PID gains. Moreover, is applied to generate the optimal values of duty cycle of the model. The comprehensive system design depicted has been simulated using MATLAB Simulink to verify the functionality of the system. The model has attained an accuracy of 93%. The outcomes of this model contribute greatly to our understanding of the suitability and efficacy of both AI and traditional MPPT controllers. This modeling will be beneficial to the renewable energy industry.

关键词： Maximum power point trackers Photovoltaic systems Renewable energy sources Accuracy Software packages Mathematical models Wind turbines Splines (mathematics) Optimization Tuning

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A Rapid GBDT-BiLSTM Based Damage Detection Technique in Bridges using Accurate Parameters

A Rapid GBDT-BiLSTM Based Damage Detection Technique in Brid...

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Babu, Uppara Raghu Patil, Deepak T. Qasim, Jameela Soni, Mukesh Sharma, Neelam Bhoopathy, V. Srinivasa Ramanujan Institute of Technology Andhra Pradesh Anantapur India Bharati Vidyapeeth College of Architecture University of Mumbai Maharashtra Navi Mumbai India Department of Bridge Engineering School of Civil Engineering Tongji University Shanghai China Department of Research and Development Lovely Professional University Phagwara India Physical Education Department Lovely Professional University Punjab India Department of Computer Science and Engineering Sree Rama Engineering College Tirupathi India

ISBN: (纸本)9798350374933

Conventional methods for diagnosing bridge damage have centred on tracking changes in modal-based Damage Sensitive Features (DSFs), which are strongly related to structural stiffness. Environmental and operational variations, inefficient use of machine learning approaches for damage detection, and an overall reliance on modal-based DSFs are some of the limits and hurdles that the system still faces, despite substantial progress towards practical deployment. According to the proposed method, the initial three steps are data preparation, feature extraction, and model training. In order to identify damage during the preprocessing step, the suggested approach utilises anomaly scores. Features in the time-frequency domain allow for parallel processing of signals in the signal-to-feature extraction pipeline. After the features have been extracted, the data is used to train GBDT-BiLSTM models. The proposed approach achieves better results than the well-known alternatives, GBDT and BiLSTM. © 2024 IEEE.

关键词： Bridges

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Reliable Multihop Routing and Congestion Aware Chicken Swarm Optimization in Vehicular Ad-Hoc Network 3

Reliable Multihop Routing and Congestion Aware Chicken Swarm...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Anitha, Cuddapah Al-Tarazi, Dalia Vignesh, G.D. Vasuki, A. Vinotha Giri, Jayant Dinesh, M. School of Computing Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Department of Computer Science and Engineering Tirupati India Zarqa University Faculty of Engineering Department of Architecture Engineering Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia St. Joseph's College of Engineering Department of Electronics and Communication Engineering Chennai India J.P. College of Engineering Department of Computer Science and Engineering Tenkasi India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Department of Vlsi Microelectronics Chennai India

ISBN: (纸本)9798331508456

Background: Vehicular Ad Hoc Networks (VANETs) play a crucial role in intelligent transportation by facilitating communication between vehicles and vehicles with infrastructure-based models. They encounter problems such as significant movement, overcrowding, and loss of data. This research presents a novel deep reinforcement learning-based resource allocation and congestion optimization (DRLRCO) framework aimed at improving communication efficiency and high reliability using an effective learning process. Method Used: The DRLRCO framework employs agent-based learning to ensure precise data transmission, AdMAC Protocol for dynamic packet delivery, and Congestion-Aware Chicken Swarm Optimization (CSO) to enhance network performance. Result: The DRLRCO framework surpasses reinforcement learning models for comprehensive testing. Significant enhancements involve improved accuracy, reduced data loss, minimized overhead, increased throughput, and shorter average delays for real-time communication. Conclusion: The DRLRCO framework successfully tackles congestion and data loss in vehicular communication. Future studies might involve Artificial Intelligence (AI) for traffic forecasting, experimentation among high-speed vehicles and investigating blockchain for enhanced security. © 2025 IEEE.

关键词： Deep reinforcement learning

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Using Swarm Intelligence Algorithms for Optimization in IoT Applications 10

Using Swarm Intelligence Algorithms for Optimization in IoT ...

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10th IEEE Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems, ICCC 2022

作者： Roshanzamir, Mohamad Nematollahi, Mohammad Ali Darbandy, Mohammad Tayarani Roshanzamir, Mahdi Alizadehsani, Roohallah Shoeibi, Afshin Ahmadian, Davood Fasa University Faculty of Engineering Department of Computer Engineering Fasa74617-81189 Iran Fasa University Faculty of Science Department of Computer Sciences Fasa74617-81189 Iran Islamic Azad University Taft School of Architecture Taft*** Iran University of Tabriz Department of Electrical and Computer Engineering Tabriz Iran Victoria Australia K. N. Toosi University of Technology FPGA Laboratory Faculty of Electrical Engineering Tehran Iran University of Tabriz Faculty of Mathematics Statistics and Computer Sciences Tabriz Iran

ISBN: (数字)9781665481779

ISBN: (纸本)9781665481779

Internet of Things (IoT) is considered as the next industrial revolution in the years ahead. Many devices will have been connected to the Internet and more and more devices were added to them. The number of these types of devices is increased rapidly. So, management of them needs advanced technologies. Optimization of different problems in IoT is an essential subject of many researches and Swarm Intelligence algorithms (SI) are one of the most successful methods in this field. They were inspired by the collective behavior of simple creatures which communicate directly and indirectly with each other. Although they are considered as simple agents, their collective behavior is smart. They can overcome most problems in their life using collective behavior. In this research, we investigated some of the most common optimization problems in IoT and the SI algorithms which are used to solve them. © 2022 IEEE.

关键词： Internet of things

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Investigating human-robot cooperation in a hospital environment: Scrutinising visions and actual realisation of mobile robots in service work 21

Investigating human-robot cooperation in a hospital environm...

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2021 ACM Designing Interactive Systems Conference: Nowhere and Everywhere, DIS 2021

作者： Tornbjerg, Kristina Kanstrup, Anne Marie Skov, Mikael B. Rehm, Matthias Department of Planning Aalborg University Denmark Department of Computer Science Aalborg University Denmark Department of Architecture Design and Media Technology Aalborg University Denmark

ISBN: (纸本)9781450384766

This study analysed work activity in a hospital basement where humans and robots interacted and cooperated on logistics tasks. The robots were deployed to automate parts of courier processes and improve the work environment for the hospital's kitchen staff. Human-robot cooperation was studied through ethnographic fieldwork relating to mobile service robots and hospital kitchen staff. The results highlighted problems arising through the assumption that the gplug and play' service robots could effectively automate work tasks. The analysis revealed the complexity of human-robot interaction in dynamic work settings such as hospitals and identified contradictions between the envisioning and realisation of robots at work, as well as the visible and invisible procedures underpinning human-robot cooperation. Consequently, we emphasise the importance of considering robots as agents of change and draw attention to the new work practices that arise when robots assume the roles of workers in dynamic work settings. © 2021 Owner/Author.

关键词： Hospitals

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Co-design of virtual reality exergames for balance rehabilitation

Co-design of virtual reality exergames for balance rehabilit...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE Conference on

作者： Signe Toftgaard Henriksen Ali Adjorlu Stefania Serafin Marius George Onofrei Federico Fontana Kasper Søndergaard Department of Architecture Design and Media Technology Aalborg University Copenhagen Denmark Department of Mathematics Computer Science and Physics University of Udine Udine Italy Department of Occupational and Physical Therapy University Hospital Herlev and Gentofte Hellerup Denmark

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Balance disorders, particularly in the elderly population, pose a significant public health challenge due to the associated risk of falls. Exercise-based therapies are effective for reducing this risk but face limitations like cost, accessibility, and sustaining patient engagement. By enabling personalized rehabilitation through engaging exergames, Virtual Reality (VR) offers a promising, cost-effective solution. This paper presents the collaborative design and preliminary evaluation of two VR-based games targeting specific balance skills. Developed in collaboration with a physiotherapist with extensive experience with patients with balance disorders, the games align with a rehabilitation protocol used by the therapist that categorizes training based on individual balance skills. Inspired by traditional physiotherapy exercises, the gameplay aims to train the same skills. Six health professionals agreed on the games’ therapeutic potential, while recommending improvements in usability, difficulty adjustment and monitoring of patient progress.

关键词： Training Three-dimensional displays Protocols Collaboration Virtual reality Games User interfaces Usability Public healthcare Older adults

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Landslide Disaster Assessment with Integration of Seismic, Social Media and Remote Sensing Data 6

Landslide Disaster Assessment with Integration of Seismic, S...

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6th International Conference on Signal Processing and Information Security, ICSPIS 2023

作者： Rawat, Deepak Sharma, M.L. Kumar, Roshan Saxena, Nishant Kumar, Atul Kadir, Abdul Indian Institute of Technology Roorkee Centre of Excellence in Disaster Mitigation and Management Uttarakhand Roorkee India Indian Institute of Technology Roorkee Department of Earthquake Engineering Roorkee Uttarakhand Roorkee India Miami College Henan University Department of Electronics and Information Technology Kaifeng Henan China Indian Institute of Technology Roorkee Department of Architecture and Planning Uttarakhand Roorkee India Indian Institute of Technology Roorkee Computer Science and Engineering Department Uttarakhand Roorkee India

ISBN: (纸本)9798350329599

On February 7, 2021, a rockfall in the Rishiganga Valley killed about 200 people. For the integration of seismic, social media, and remote sensing, a case study on this tragedy has been conducted. This study explores the role of social media in managing Himalayan landslides in conjunction with remote sensing data analytics. We look at how these technologies can enhance damage management, quick mobilization, and early warning systems. A literature review and case studies of the successful use of these technologies in other disaster-prone areas will support these suggestions. The intention is to equip decision-makers and experts in disaster management with the practical knowledge they need to effectively prepare for and respond to Himalayan landslide events, saving lives and minimizing the impact of natural hazards. © 2023 IEEE.

关键词： Remote sensing

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