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Toward parallel intelligence: An interdisciplinary solution for complex systems

The Innovation 2023年第6期4卷 152-164页

作者： Yong Zhao Zhengqiu Zhu Bin Chen Sihang Qiu Jincai Huang Xin Lu Weiyi Yang Chuan Ai Kuihua Huang Cheng He Yucheng Jin Zhong Liu Fei-Yue Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Hunan Institute of Advanced Technology Changsha 410073China Shanghai Institute of Infectious Disease and Biosecurity Shanghai 200032China Institute of Epidemiology Helmholtz Zentrum Minchen-German Research Center for Environmental Health(GmbH)NeuherbergGermany Department of Computer Science Hong Kong Baptist UniversityHong KongChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and *** meet these demands,the parallel systems method rooted in the artificial systems,computational experiments,and parallel execution(ACP)approach has been *** method cultivates a cycle termed parallel intelligence,which iteratively creates data,acquires knowledge,and refines the actual *** the past two decades,the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines,offering vers atile interdisciplinary solutions for complex systems across diverse *** review explores the origins and fundamental concepts of the parallel systems method,showcasing its accomplishments as a diverse array of parallel technologies and applica-tions while also prognosticating potential *** posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.

关键词： execution artificial offering

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Consensus Control of Leader-Following Multi-Agent systems in Directed Topology With Heterogeneous Disturbances

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 423-431页

作者： Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049and also with Qingdao Academy of Intelligent IndustriesQingdao 266109China the Department of Computer and Electrical Engineering and Computer Science Florida Atlantic UniversityBoca Raton FL33431 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and TechnologyMacao 999078China

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

关键词： Consensus control directed topology external disturbance multi-agent(MA)systems

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Exploring ERP User Behaviour in Developing Countries: Integrating Self-efficacy and UTAUT Perspectives 5

Exploring ERP User Behaviour in Developing Countries: Integr...

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5th International Conference on Advancement in Data Science, E-Learning and Information systems, ICADEIS 2023

作者： Syamsuar, Dedy Oktaharisetia, Muhammad Angga Witarsyah, Deden Luthfi, Ahmad Dell, Peter Permana, Yudistira Sira Antoni, Darius Bina Nusantara University School of Information Systems Information Systems Department Indonesia Universitas Bina Darma Program Pasca Sarjana Palembang Indonesia Telkom University School of Industrial Engineering Bandung Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Indonesia Curtin University School of Management and Marketing Faculty of Business and Law Australia Politeknik Sekayu Teknik Informatika Sekayu Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia

ISBN: (纸本)9798350303414

ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts. © 2023 IEEE.

关键词： Enterprise resource planning

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Rainfall Forecasting Using Machine Learning Algorithms for Localized Events

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Computers, Materials & Continua 2022年第6期71卷 6333-6350页

作者： Ganapathy Pattukandan Ganapathy Kathiravan Srinivasan Debajit Datta Chuan-Yu Chang Om Purohit Vladislav Zaalishvili Olga Burdzieva Centre for Disaster Mitigation and Management Vellore Institute of TechnologyVellore632014India School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India Department of Computer Science and Information Engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Service Systems Technology Center Industrial Technology Research InstituteHsinchuTaiwan School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Geophysical Institute of Vladikavkaz Scientific Centre Russian Academy of Sciences(RAS)VladikavkazRussian Federation

A substantial amount of the Indian economy depends solely on ***,on the other hand,plays a significant role in agriculture–while an adequate amount of rainfall can be considered as a blessing,if the amount is inordinate or scant,it can ruin the entire hard work of the *** this work,the rainfall dataset of the Vellore region,of Tamil Nadu,India,in the years 2021 and 2022 is forecasted using several machine learning *** engineering has been performed in this work in order to generate new features that remove all sorts of autocorrelation present in the *** removal of autocorrelation,the data could be used for performing operations on the time-series data,which otherwise could only be performed on any other regular regression *** work uses forecasting techniques like the AutoRegessive Integrated Moving Average(ARIMA)and exponential smoothening,and then the time-series data is further worked on using Long Short Term Memory(LSTM).Later,regression techniques are used by manipulating the *** work is benchmarked with several evaluation metrics on a test dataset,where XGBoost Regression technique outperformed the *** uniqueness of this work is that it forecasts the daily rainfall for the year 2021 and 2022 in Vellore *** work can be extended in the future to predict rainfall over a bigger region based on previously recorded time-series data,which can help the farmers and common people to plan accordingly and take precautionary measures.

关键词： Time-series ARIMA LSTM regression rainfall

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Improving Land Cover Segmentation Using Multispectral Dataset 8

Improving Land Cover Segmentation Using Multispectral Datase...

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8th International Conference on Informatics and Computing, ICIC 2023

作者： Herlawati, Herlawati Handayanto, Rahmadya Trias Heryadi, Yaya Abdurachman, Edi Soeparno, Haryono Irwansyah, Edy Miranda, Eka Informatics Universitas Bhayangkara Jakarta Raya Jakarta Indonesia Universitas Islam 45 Computer Engineering Bekasi Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Trisakti Institute of Transportation and Logistic Jakarta13410 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350342604

Computer vision has been used in many areas such as medical, transportation, military, geography, etc. The fast development of sensor devices inside camera and satellite provides not only red-greed-blue (RGB) images but also multispectral dataset with some channels including RGB, infrared, short-wave, and thermal wave. Most of the dataset is panchromatic (black and white) and RGB, for example Google Map and other satellite-based map applications. This study examines the effects of multispectral dataset for semantic segmentation of land cover. The comparison between RGB with band 2 to band 7 of Landsat 8 Satellite shows an improvement of accuracy from 90.283 to 94.473 for U-Net and from 91.76 to 95.183 for DeepLabV3+. In addition, this research also compares two well-known semantic segmentation methods, namely U-Net and DeepLabV3+, that shown that DeepLabV3+ outperformed U-Net regarding to speed and accuracy. Testing was conducted in the Karawang Regency area, West Java, Indonesia. © 2023 IEEE.

关键词： Landsat

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An Accurate Estimate of Effective Thermal-Mechanical Properties of Coreless Circuit Substrate for Advanced Packaging

An Accurate Estimate of Effective Thermal-Mechanical Propert...

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International Conference on Electronics Packaging (ICEP)

作者： W. Y. Jhu H. C. Cheng Department of Aerospace and Systems Engineering Feng Chia University Taichung Taiwan Ph.D Program of Mechanical and Aeronautical Engineering Feng Chia University Taichung Taiwan

This study aims to give an accurate estimate of the effective thermal-mechanical properties of a coreless circuit substrate for advanced IC packages. To achieve the goal, a subdomain-based effective method is proposed, incorporating a sub-domain three-dimensional (3D) copper trace mapping and modeling (TMM) method, a volume-averaging rule of mixture (ROM) technique and finite element modeling. Furthermore, the proposed effective method is combined with an FEA-based process simulation framework to investigate the process-induced warpage of a flip-chip chip scale package during fabrication. At last, parametric analysis is performed to identify the crucial factors influencing the process-induced warpage of the package.

关键词： Solid modeling Three-dimensional displays Predictive models Packaging Electronic packaging thermal management Finite element analysis Flip-chip devices

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Pursuing overall welfare in federated learning through sequential decision making 24

Pursuing overall welfare in federated learning through seque...

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Proceedings of the 41st International Conference on Machine Learning

作者： Seok-Ju Hahn Gi-Soo Kim Junghye Lee Department of Industrial Engineering Ulsan National Institute of Science and Technology (UNIST) Ulsan South Korea Department of Industrial Engineering and Artificial Intelligence Graduate School Ulsan National Institute of Science and Technology (UNIST) Ulsan South Korea Technology Management Economics and Policy Program and Graduate School of Engineering Practice and Institute of Engineering Research Seoul National University (SNU) Seoul South Korea

In traditional federated learning, a single global model cannot perform equally well for all clients. Therefore, the need to achieve the client-level fairness in federated system has been emphasized, which can be realized by modifying the static aggregation scheme for updating the global model to an adaptive one, in response to the local signals of the participating clients. Our work reveals that existing fairness-aware aggregation strategies can be unified into an online convex optimization framework, in other words, a central server's sequential decision making process. To enhance the decision making capability, we propose simple and intuitive improvements for suboptimal designs within existing methods, presenting AAggFF. Considering practical requirements, we further subdivide our method tailored for the cross-device and the cross-silo settings, respectively. Theoretical analyses guarantee sublinear regret upper bounds for both settings: O(√T log K) for the cross-device setting, and O(K log T) for the cross-silo setting, with K clients and T federation rounds. Extensive experiments demonstrate that the federated system equipped with AAggFF achieves better degree of client-level fairness than existing methods in both practical settings. Code is available at https://***/vaseline555/AAggFF.

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Model Predictive Control of a Hybrid VA v for Parcel Delivery Applications 1

Model Predictive Control of a Hybrid VA v for Parcel Deliver...

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1st AIRPHARO Workshop on Aerial Robotic systems Physically Interacting with the Environment, AIRPHARO 2021

作者： Konyalioglu, Turan Alnipak, Sinan Altug, Erdinc İstanbul Technical University System Dynamics and Control Graduate Program İstanbul Technical University Autonomous Systems Research Laboratory Department of Mechanical Engineering İstanbul Turkey

ISBN: (纸本)9781665433891

Within the last decade, e-commerce has increased at an extraordinary level. The widespread use of Unmanned Aerial Vehicles (VAVs) in the logistics sector can reduce traffic density, improve delivery time, and can provide contactless delivery. This work proposes a new hybrid VAV, that combines the benefits of vertical take-off and land vehicle and a fixed-wing aircraft. It can carry multiple packages, which can decent automatically towards the recipients. This approach eliminates time-consuming landing maneuvers of the VA V for delivery. This work focuses on the design of the vehicle, and the challenges of the transitions from VTOL to aircraft modes and vice versa with a Model Predictive Controller. © 2021 IEEE.

关键词： Fixed wings

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Current Issues in Flexible Manufacturing Using Multicriteria Decision Analysis and Ontology Based Interoperability in an Advanced Manufacturing Environment 10th

Current Issues in Flexible Manufacturing Using Multicriteria...

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10th International Conference of Production Research - Americas, ICPR-Americas 2020

作者： Canciglieri, M.B. Leite, A. F. C. S. de M. Rocha Loures, E. de F. Canciglieri, O. Monfared, R.P. Goh, Y.M. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Paraná Brazil School of Mechanical Electrical and Manufacturing Engineering Loughborough University Loughborough Leicestershire United Kingdom

ISBN: (纸本)9783030763060

The manufacturing industry is undergoing a major transformation based on the emerging industry 4.0 technologies, such as cloud computing, big data, internet of things and cyber-physical systems. These novelty technologies aim at providing central management for the user’s flexible manufacturing requirements and information. Also, the advent of these technologies has transformed the process planning and became crucial for the building of knowledge-based process planning environments. However, current praxis cannot deal with all semantic issues within this new paradigm, as requirements must be clear, consistent, measurable, stand-alone, testable, unambiguous, unique and verifiable. In this context, multicriteria decision analysis models have gained focus of the scientific and industrial communities as a support tool for the decision-making process in the product development and advanced manufacturing as these processes excel in environments with numerous and conflicting alternatives, providing the optimal alternative. Therefore, the main objective of this research is to highlight the current issues and research tendencies regarding ontology-based interoperability systems, multicriteria decision analysis and their integration. To achieve this goal, it will be applied a literature review on the targeted technologies, discussing the current tendencies of the field and the main issues regarding their implementation and integration. Finally, the paper points themes for further research and indicates viable concepts that can compose a solution for the gaps in a systematic manner. © 2021, Springer Nature Switzerland AG.

关键词： Flexible manufacturing systems

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Expert-level sleep staging using an electrocardiography-only feed-forward neural network

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Computers in Biology and Medicine 2024年 176卷 108545-108545页

作者： Jones, Adam M. Itti, Laurent Sheth, Bhavin R. Neuroscience Graduate Program University of Southern California Los AngelesCA United States Department of Electrical & Computer Engineering University of Houston HoustonTX United States Center for NeuroEngineering and Cognitive Systems University of Houston HoustonTX United States

Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomnography (PSG). Unfortunately, PSG is an expensive and cumbersome process involving numerous electrodes, often conducted in an unfamiliar clinic and annotated by a professional. Although commercial devices like smartwatches track sleep, their performance is well below PSG. To address these disadvantages, we present a feed-forward neural network that achieves gold-standard levels of agreement using only a single lead of electrocardiography (ECG) data. Specifically, the median five-stage Cohen's kappa is 0.725 on a large, diverse dataset of 5 to 90-year-old subjects. Comparisons with a comprehensive meta-analysis of between-human inter-rater agreement confirm the non-inferior performance of our model. Finally, we developed a novel loss function to align the training objective with Cohen's kappa. Our method offers an inexpensive, automated, and convenient alternative for sleep stage classification—further enhanced by a real-time scoring option. Cardiosomnography, or a sleep study conducted with ECG only, could take expert-level sleep studies outside the confines of clinics and laboratories and into realistic settings. This advancement democratizes access to high-quality sleep studies, considerably enhancing the field of sleep medicine and neuroscience. It makes less-expensive, higher-quality studies accessible to a broader community, enabling improved sleep research and more personalized, accessible sleep-related healthcare interventions. © 2024 Elsevier Ltd

关键词： Electrocardiography

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