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SSRN 2024年

作者： Adiprabowo, Arya Bhaskara Muharto, Bambang Prabowo, Wargiantoro Saputro, Frendy Rian Anggoro, Trisno Masfuri, Imron Sugeng, Dhani Avianto Rosyadi, Erlan Lang, Zi-Qiang KST BJ Habibie Energy Building 620-625 Indonesia Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Department of Electrical Engineering Mathematics and Computer Science University of Twente Enschede7522 NB Netherlands Vehicle System Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia Department of Chemical and Environmental Engineering Malaysia Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia

Pyrolysis is a prominent technique to harvest energy while addressing the global waste problem. Product yield relies heavily on precise reactor temperature control in a pyrolysis process;thus, a representative mathematical model is necessary to design and evaluate the control system. Hence, this research aims to create a data-driven model of a 1 kg/h Auger-based pyrolysis (APR) plant and design a robust controller accordingly. The system is excited by using a pseudo-random binary signal (PRBS) to trigger process response and is recorded for 2 hours. Various models with different orders, such as Auto Regressive Exogeneous (ARX), Auto Regressive Moving Average Exogeneous (ARMAX), Box-Jenkins (BJ), and Output Error (OE) were created from the obtained data. The models were examined using best-fit percentage, final prediction error (FPE) and mean square error (MSE) criteria and validated using cross-correlation and auto-correlation functions. Two widely used and purpose-fit controllers, Proportional-Integral-Derivate (PID) and Model Predictive Control (MPC), with output constraints, were designed and tuned for this application. Several operational scenarios were investigated, such as setpoint tracking and disturbance rejection. The best-fit models were selected and validated for TIC-3, TIC-4 and TIC-5, with 96.22%, 97.4% and 84.83% fitness criteria, respectively. Both controllers successfully satisfied all the tests with less than 2% steady-state error. However, MPC surpassed PID controllers in all aspects, such as 5-7 times faster settling time, negligible overshoot, and reduced integral absolute error (IAE) and integral square error (ISE) up to 44.75% and 5.45%, respectively. Nevertheless, MPC with input and output constraints performance pales compared to other controllers despite some adjustments with massive ISE and settling time above 3000 seconds. As a result, a recommendation to change the input actuator will be beneficial to unleash the benefit of MPC fully. © 2

关键词： Model predictive control

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Assessment of Convolutional Neural Networks for Asset Detection in Dynamic Automation Construction Environments

Assessment of Convolutional Neural Networks for Asset Detect...

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CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： Robert Guamán-Rivera Oswaldo Menéndez Tito Arevalo-Ramirez Katherine Aro Alvaro Prado Rodrigo García-Alvarado Fernando Auat-Cheein Institute of Engineering Sciences Universidad de O'Higgins Rancagua Chile Computer and Systems Engineering Universidad Católica del Norte Antofagasta Chile Faculty of Engineering Pontificia Universidad Católica de Chile Santiago Chile Department of Design and theory of Architecture Universidad del Bio-Bio Concepción Chile School of Engineering and Physical Sciences Heriot-Watt University Edinburgh UK

Integrating social robotics into the construction industry, particularly in the context of Industry 5.0, faces several challenges in creating complex environments that seamlessly blend human and machine interactions. In this regard, the emergence of intelligent and expert systems holds promising technologies to enhance construction tasks focused on robots and workers in 3D printing applications. This work compares several methods of convolutional neural network-based object detectors designed to identify distinct construction assets and workers within the dynamic environment of 3D printing. To this end, different versions of the You Only Look Once v8 (YOLO v8) algorithm have been implemented, trained, and experimentally tested using several images captured within dynamic construction environments. Furthermore, we present an in-depth comparison between YOLO v8 and its preceding versions, namely YOLO v7 and YOLO v5. Experimental results disclosed the high performance of the proposed approach in effectively detecting three distinct entities (workers, robotic platforms, and building elements), achieving a precision rate of up to 98.8%.

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Edge Computing-Based Joint Client Selection and Networking Scheme for Federated Learning in Vehicular IoT

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China Communications 2021年第6期18卷 39-52页

作者： Wugedele Bao Celimuge Wu Siri Guleng Jiefang Zhang Kok-Lim Alvin Yau Yusheng Ji School of computer science and information engineering Hohhot Minzu CollegeHohhot 010051China Graduate School of Informatics and Engineering The University of Electro-Communications1-5-1ChofugaokaChofu-shiTokyo182-8585 Japan Institute of Intelligent Media Technology Communication University of ZhejiangZhejiang 310018China School of Science and Technology Sunway University5Jalan UniversitiBandar Sunway47500 Petaling JayaSelangorMalaysia Information Systems Architecture Research Division National Institute of Informatics2-1-2HitotsubashiChiyoda-kuTokyo 101-8430 Japan

In order to support advanced vehicular Internet-of-Things(IoT)applications,information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular *** learning(FL),which is a type of distributed learning technology,has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user ***,client selection and networking scheme for enabling FL in dynamic vehicular environments,which determines the communication delay between FL clients and the central server that aggregates the models received from the clients,is still *** this paper,we propose an edge computing-based joint client selection and networking scheme for vehicular *** proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach,and uses the edge vehicles as FL clients to conduct the training of local models,which learns optimal behaviors based on the interaction with *** clients also work as forwarder nodes in information sharing among network *** client selection takes into account the vehicle velocity,vehicle distribution,and the wireless link connectivity between vehicles using a fuzzy logic algorithm,resulting in an efficient learning and networking *** use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.

关键词： vehicular IoT federated learning client selection networking scheme

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Recent progress on structural coloration

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Photonics Insights 2024年第2期3卷 1-30页

作者： Yingjie Li Jingtian Hu Yixuan Zeng Qinghai Song Cheng-Wei Qiu Shumin Xiao Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of TechnologyShenzhenChina Pengcheng Laboratory ShenzhenChina Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuanChina

Structural coloration generates colors by the interaction between incident light and micro-or nanoscale *** has received tremendous interest for decades,due to advantages including robustness against bleaching and environmentally friendly properties(compared with conventional pigments and dyes).As a versatile coloration strategy,the tuning of structural colors based on micro-and nanoscale photonic structures has been extensively explored and can enable a broad range of applications including displays,anti-counterfeiting,and ***,scholarly research on structural colors has had limited impact on commercial products because of their disadvantages in cost,scalability,and *** this review,we analyze the key challenges and opportunities in the development of structural *** first summarize the fundamental mechanisms and design strategies for structural colors while reviewing the recent progress in realizing dynamic structural *** promising potential applications including optical information processing and displays are also discussed while elucidating the most prominent challenges that prevent them from translating into technologies on the ***,we address the new opportunities that are underexplored by the structural coloration community but can be achieved through multidisciplinary research within the emerging research areas.

关键词： structural coloration metasurfaces nanophotonics

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Mixed Motivation Driven Social Multi-Agent Reinforcement Learning for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2025年第6期12卷 1272-1282页

作者： Long Chen Peng Deng Lingxi Li Xuemin Hu State Key Laboratory of Multimodal Artificial Intelligence Systems and the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing WAYTOUS Inc. Beijing Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China School of Computer Science and Information Engineering Hubei University Wuhan China Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA School of Artificial Intelligence Hubei University Wuhan Key Laboratory of Intelligent Sensing System and Security (Hubei University) Ministry of Education Wuhan China

Despite great achievement has been made in autonomous driving technologies, autonomous vehicles (AVs) still exhibit limitations in intelligence and lack social coordination, which is primarily attributed to their reliance on single-agent technologies, neglecting inter-AV interactions. Current research on multi-agent autonomous driving (MAAD) predominantly focuses on either distributed individual learning or centralized cooperative learning, ignoring the mixed-motive nature of MAAD systems, where each agent is not only self-interested in reaching its own destination but also needs to coordinate with other traffic participants to enhance efficiency and safety. Inspired by the mixed motivation of human driving behavior and their learning process, we propose a novel mixed motivation driven social multi-agent reinforcement learning method for autonomous driving. In our method, a multi-agent reinforcement learning (MARL) algorithm, called Social Learning Policy Optimization (SoLPO), which takes advantage of both the individual and social learning paradigms, is proposed to empower agents to rapidly acquire self-interested policies and effectively learn socially coordinated behavior. Based on the proposed SoLPO, we further develop a mixed-motive MARL method for autonomous driving combined with a social reward integration module that can model the mixed-motive nature of MAAD systems by integrating individual and neighbor rewards into a social learning objective for improved learning speed and effectiveness. Experiments conducted on the MetaDrive simulator show that our proposed method outperforms existing state-of-the-art MARL approaches in metrics including the success rate, safety, and efficiency. More-over, the AVs trained by our method form coordinated social norms and exhibit human-like driving behavior, demonstrating a high degree of social coordination.

关键词： Measurement Reinforcement learning Safety Driver behavior Autonomous vehicles Optimization

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Blockchain-based Secure Outsourcing Data Integrity Auditing for Internet of Things in Cloud-edge Environment

Blockchain-based Secure Outsourcing Data Integrity Auditing ...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Yangfei Lin Celimuge Wu Yusheng Ji Jie Li Zhi Liu Graduate School of Informatics and Engineering The University of Electro-Communications Chofu-shi Tokyo Japan Information Systems Architecture Research Division National Institute of Informatics Tokyo Japan Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

Internet of Things enables devices to communicate, collect and exchange data with the network. As the number of IoT devices keeps growing, the volume of data they produce is also increasing exponentially. Given the feature of limited computing and storage resources of IoT, it is inevitable to store data in the cloud for better services. However, for users to effectively and efficiently inspect those data over the cloud is a critical and open problem. Most public integrity auditing over the cloud schemes requires the user to do a sheer amount of preprocessing work on the local devices, which is unsuitable for IoT devices. With the development of edge computing extending cloud computing, it can provide computing capability for resource-constrained devices in close geographic proximity. In this paper, we design an auditing scheme based on secure computation outsourcing assisted by edge computing, in which the data preprocessing work can be offloaded to the edge server. The experiments show that it reduces the computing load on the devices and improves the efficiency of task processing.

关键词： Cloud computing Data privacy Data integrity Outsourcing Sensors Performance analysis Internet of Things

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Non-convex potential games for finding global solutions to sensor network localization

arXiv

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arXiv 2023年

作者： Xu, Gehui Chen, Guanpu Hong, Yiguang Fidan, Baris Parisini, Thomas Johansson, Karl H. Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden Department of Control Science and Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom Department of Engineering and Architecture University of Trieste Trieste34127 Italy

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Sensor networks

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Yan Zeng ChengChuang Huang YiJie Ni ChunBao Zhou JiLin Zhang Jue Wang MingYao Zhou MeiTing Xue YunQuan Zhang School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory for Modeling and Simulation of Complex Systems Ministry of Education Hangzhou China Data Security Governance Zhejiang Engineering Research Center Hangzhou China School of ITMO Joint Institute Hangzhou Dianzi University Hangzhou China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing China HuaWei State Key Laboratory of Computer Architecture Institute of Computing Technology of the Chinese Academy of Sciences Beijing China

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network’s dataflow graph and device cluster’s topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method.

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Nature-Based Solutions Can Potentially Contribute to Biomass Density, Heat Stress Mitigation, and Biodiversity

SSRN

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SSRN 2023年

作者： Kim, Eun Sub Hyun, Jung Hee Kim, Na Yeon Heo, Su Jeong Kim, Shin Woo Kim, Da Sle Lee, Dong Kun Interdisciplinary Program in Landscape Architecture Seoul National University Seoul08826 Korea Republic of Integrated Major in Smart City Global Convergence Program Seoul National University Seoul08826 Korea Republic of Specialized Graduate School of Intelligent Eco-Science 4 Dept. of Landscape Architecture Seoul National University Seoul08826 Korea Republic of Systemic Risk and Resilience Research Group Advancing Systems Analysis International Institute for Applied Systems Analysis Austria Department of Landscape Architecture and Rural System Engineering Seoul National University Seoul08826 Korea Republic of

Nature-based solutions (NBS) are actions to protect, sustainably manage, or restore natural ecosystems. They are increasingly recognized worldwide as a key strategy for sustainable development, integrating climate change adaptation and mitigation and biodiversity conservation. NBS is fundamental to the quality of life of residents, and urban planning often includes strategies that are directly or indirectly related to greening. Although numerous studies have been conducted to quantitatively evaluate the benefits of NBS, analysis of the potential effect of NBS remains insufficient. Therefore, we developed a spatial decision-making support model that optimizes the location of NBS on multiple effects (biomass density, urban heat stress mitigation, and landscape connectivity) using a Non-Sorting dominated Genetic Algorithm-II (NSGA-II). Potential was assessed by comparing the NBS plan considering co-benefits with NBS strategy scenarios focused on individual objectives connectivity, biomass density, heat stress based scenario(CBS, BBS, and HBS). The model was applied to Suwon City, South Korea, demonstrating the potential of an integrated approach to maximize co-benefits simultaneously. The analysis revealed a trade-off between NBS benefits and implementation costs, with performance improvement in one objective often leading to decreased performance in others. Correlation analysis revealed significant positive correlations among the three objectives, with heat stress showing the lowest correlation. Simulations under four distinct scenarios highlighted the diverse potential arrangements of NBS and their effects. An integrated strategy demonstrated a consistently high overall value (a 221% improvement), which proved to be the most efficient approach when considering all aspects collectively. This study underscores the potential benefits of integrating multiple objectives into urban green space planning, thereby providing valuable insights for sustainable urban development.

关键词： Biodiversity

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Transforming the public transport sector in the Philippines through service contracts: A program evaluation study

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Transportation Research Procedia 2025年 82卷 890-907页

作者： Varsolo Sunio Wilhansen Li Joemier Pontawe Albert Dizon Alexis Fillone Science Engineering and Management Research Institute University of Asia and the Pacific Pasig City Metro Manila 1600 Philippines Toulan School of Urban Studies and Planning Portland State University Oregon 97201 United States Sakay Mobility Philippines Corporation Quezon City Metro Manila 1110 Philippines Department of Information Systems and Computer Science School of Science and Engineering Ateneo de Manila University Quezon City Metro Manila 1108 Philippines School of Architecture and Planning The University of Auckland New Zealand Civil Engineering Department De La Salle University Manila Metro Manila 1004 Philippines

We evaluate two schemes of service contracting (SC) program implemented for the first time in the Philippines: gross-cost and net-cost. Using an automatic vehicle location (AVL) dataset generated using a mobile application, we examine the supply and performance of jeepney, a form of paratransit, on 20 routes during the pandemic. Ten of these routes are under gross-cost, and the other ten are under net-cost. Our evaluation suggests that gross-cost SC has resulted in more kilometer-run travelled, more arrivals at the stop, shorter headway duration, which are indicative of increased supply, compared to net-cost. However, we obtain mixed results for metrics associated with performance (headway regularity, dwell time and route compliance) for gross- and net- cost. We recommend that for SC to maximize its impact and raise performance, the government should set standards on metrics associated with fleet management and enforce strict compliance. Since SC is typically applied for the management of formal public transport, our work represents a novel contribution on the application of SC on the management of paratransit in the Global South.

关键词： service contract public transport reform Global South paratransit

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