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Innovative Research in Applied Science, Engineering and Technology (IRASET),Conference on

作者： Goudali Lina Akkouri Nacer Latifa Elfarissi Mustapha Jammoukh Abdellah Zamma Laboratory: Modeling and Simulation of Intelligent Industrial Systems (M2S2I) Higher Normal School of Technical Education of Mohammedia Hassan II University of Casablanca Casablanca Morocco R&D Department Technical Center for Plastics and Rubber (CTPC) Complex of Moroccan Industrial Technical Centers Casablanca Morocco

A wide part of scientific research in the food-packaging sector has shown interesting challenges in assuring food shelf-life extension. Conventional plastic is mostly used for food packaging, hence has major environmental drawbacks by being non-degradable and accumulating over the years due to its elimination process. Biodegradable food packaging polymers have contributed to overcoming these challenges and diverted from the environmental concern. In the light of the sustainable development goals, implementing green technology in current industries help secure the consumer's safety by minimizing food loss and reducing plastic waste, thus attaining environmental sustainability. Whey protein isolate (WPI) has been considerably investigated lately and used in packaging formulation for its functional properties. This work aims to produce a biopolymer film destined for food packaging based on the crosslinking of whey protein isolate using glycerol as a plasticizer. The thermal properties of the film samples were investigated. Other aspects of the WPI biopolymer can be studied for other potential uses, more additives can be added to develop further properties depending on the final use of the film. The developed polymer can potentially be used in the food packaging industry under various conservation conditions.

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FedAG:A Federated Learning Method Based on Data Importance Weighted Aggregation

FedAG:A Federated Learning Method Based on Data Importance W...

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IEEE International Conference on Communications in China (ICCC)

作者： Mengchu Xu Yan Zeng Meiting Xue Ji-Lin Zhang Jian Wan Mingyao Zhou Yilin Wen Yukun Shi School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou China Zhejiang Engineering Research Center of Data Security Governance Hangzhou China School of Cyberspace Hangzhou Dianzi University Hangzhou China Huawei Enterprise Communication Technology Co Hangzhou China

Federated learning is a distributed machine learning approach that trains models with multiple clients and data locally. However, the existing methods ignore the differences between local models caused by the data heterogeneity, and give a high aggregation weight for the low-quality local model, which leads to low accuracy of the global model. For this problem, we propose a federated learning method based on data importance weighted aggregation, FedAG. It constructs an evaluation model of data importance based on the data distribution skewness, data volume, and data quality of clients, and aggregates local models with different weights computed by the evaluation model of data importance into a global model. We make experiments on five datasets including EMNIST, MNIST, and CIFAR-10. The results show that the accuracy of FedAG is respectively improved by 6.5%, 1.8%, 1.3% and 2.1%, compared with FedAvg, FedProx, FedVar, and Scaffold algorithms.

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Short-Term Traffic Flow Prediction Method Based on Spatio-Temporal Characteristics of complex Road Network

Short-Term Traffic Flow Prediction Method Based on Spatio-Te...

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作者： Huawei ZHU Yihao MAO Yiming ZHAO Liyuan SHI Yanli SHAO School of Information and Electrical Engineering Zhejiang University City College Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and TechnologyHangzhou Dianzi University

With the development of urbanization,the number of residents' motor vehicles has increased sharply,and traffic congestion problem has become increasingly *** construction of Intelligent Traffic System(ITS) has become the main means to alleviate traffic ***-term traffic flow prediction has guiding significance for residents' travel planning and intelligent management of transportation,and has become one of the research hotspots in intelligent transportation ***,A short-term traffic flow prediction method based on the spatio-temporal characteristics of complex road networks is proposed to further improve the prediction accuracy and reduce the prediction ***,a graph convolutional network(GCN) capable of processing non-Euclidean data structures is used to extract the spatial characteristics of traffic flow ***,the long and short-term memory(LSTM) neural network is used to process the time ***,the two are combined to realize the effective processing of the spatio-temporal characteristics of traffic flow *** results on the real traffic flow dataset prove the feasibility and effectiveness of the proposed method,and can provide a basis for intelligent traffic control and smart city construction.

关键词： Traffic Flow Prediction Spatio-temporal GCN LSTM

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Corrigendum to “Multi-instance learning based on representative instance and feature mapping” [Neurocomputing 216 (2016) 790–796/1]

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Neurocomputing 2022年 471卷 60-60页

作者： Xingqi Wang Dan Wei Hui Cheng Jinglong Fang Ministry of Education Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou 310018 China

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Numerical Study of Performance of T-Micromixer with Helical Elements for the Energetic Application of Microfluidics

SSRN

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SSRN 2023年

作者： Mahammedi, Abdelkader Tayeb, Naas Toufik Rahmani, Kouider Al-Kassir, Awf Cuerda-Correa, Eduardo Manuel Department of Technology Ziane Achour University of Djelfa Djelfa17000 Algeria Gas Turbine Joint Research Team University of Djelfa Djelfa17000 Algeria Research Laboratory Modeling Simulation and Optimization of Real Complex Systems Djelfa17000 Algeria Departamento de Química Orgánica e Inorgánica Facultad de Ciencias Universidad de Extremadura Avenida de Elvas s/n Badajoz06006 Spain

Mixing index, pressure drop, and kinematic measurements within the T-micromixer with helical elements and their related mixing performances have been studied and validated using CFD, for different values of Reynolds number (0.1 - 60) for laminar Newtonian miscible fluid. Geometrical characteristics were further examined to improve the mixing performance. Various values of twisted angles were evaluated and compared to choose the optimal angle. Two new parameters, Q and λ, were introduced to represent the ratio of vorticity square over the sum of vorticity square and deformation square intensities. Furthermore, the results of the numerical simulation were compared with the given data in the literature, showing a significant agreement, in addition to the fact that a high-quality mixture can be created with a geometry angle of 90°, and a mixing index above 0.99 can be obtained at low Reynolds numbers. The numerical investigation of the flow regimes of miscible fluid in the T-microkenics with the proposed angle can be utilized to develop the mixing performance of the micromixers in a wide variety of processes. © 2023, The Authors. All rights reserved.

关键词： Vorticity

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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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DeepDir: a deep learning approach for API directive detection

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Science China(Information Sciences) 2021年第9期64卷 238-240页

作者： Jingxuan ZHANG He JIANG Shuai LU Ge LI Xin CHEN College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics State Key Laboratory for Novel Software Technology Nanjing University Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Software Dalian University of Technology School of Electronic Engineering and Computer Science Peking University School of Computer Science and Technology Hangzhou Dianzi University

Dear editor,Software developers tend to reuse existing libraries to facilitate their development process and implement certain functionalities by invoking application programming interfaces(APIs) [1]. However, it remains a challenging task for developers to correctly use APIs [2], so they often consult API learning resources [3, 4]. As one of the most important API learning resources,

关键词： Information systems and Communication Service

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Frequency and Voltage Computation on Protection Settings in Renewable Resources 4

Frequency and Voltage Computation on Protection Settings in ...

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4th IEEE Workshop on Power Electronics and Power Quality Applications (PEPQA)

作者： Arias-Guzman, S. Ustariz-Farfan, A. J. Cano-Plata, E. A. McCann, Roy Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou China Computing Center Shanghai University Shanghai China

ISBN: (纸本)9781728116266

The presence of inverter based renewable resources has introducing new challenges on transmission systems due sudden loss of several MW after voltage and frequency excursions. These sudden disconnections have been related with a fault ride through control in voltage and frequency excursions following PRC-024 standard. The NERC Inverter-Based Resource Performance Task Force has expressed the necessity for a full ride-through standard with clear requirements as to how the resource can behave in terms on control and protection aspects. In consequence, this article addresses the problem to define the control and protection that can be taken under frequency and voltage excursions to avoid disconnections. For this purpose, this article proposes a new magnitude and frequency computation with computations delays under 16 ms and the use of new detection techniques to add new control and protection functions to the inverter based renewable resources.

关键词： Momentary Cessation Protection systems Frequency computation Estate estimation Renewable resources

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A Fast Algorithm for Solving a Class of the Linear Complementarity Problem in a Finite Number of Steps

Abstract and Applied Analysis

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Abstract and Applied Analysis 2020年第none期2020卷 1-8页

作者： Achik, Yamna Idmbarek, Asmaa Nafia, Hajar Agmour, Imane El Foutayeni, Youssef Analysis Modeling and Simulation Laboratory Hassan II University Morocco Unit for Mathematical and Computer Modeling of Complex Systems IRD France

The linear complementarity problem is receiving a lot of attention and has been studied extensively. Recently, El foutayeni et al. have contributed many works that aim to solve this mysterious problem. However, many results exist and give good approximations of the linear complementarity problem solutions. The major drawback of many existing methods resides in the fact that, for large systems, they require a large number of operations during each iteration;also, they consume large amounts of memory and computation time. This is the reason which drives us to create an algorithm with a finite number of steps to solve this kind of problem with a reduced number of iterations compared to existing methods. In addition, we consider a new class of matrices called the E-matrix. © 2020 Yamna Achik et al.

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Itinerary Recommendation for User Groups in Temporary Social Network 15th

Itinerary Recommendation for User Groups in Temporary Social...

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15th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2019

作者： Xia, Jing Li, Yu Yin, Yuyu School of Computer Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation of Ministry of Education Hangzhou310018 China

ISBN: (纸本)9783030301453

Temporary social network has been a increasing popular field in the last few years where people form a temporary social group for a short time period with common interests or purposes in the same area. When a user attends an event or conference in a new city, he/she can join the temporary social networks with his/her social account. Users who attend the same academic conference or activity may have similar interests and time schedules, so they are willing to travel together. Recently, renting cars to travel has become very common, since it helps improve user experience as well as save travel costs (e.g., renting and oil costs). Thus, we propose a group-wise itinerary planning framework to minimize the travel costs for each user in a temporary social network. Experimental results conducted on real-world data sets confirm the efficiency and effectiveness of our proposed framework. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Mobile computing

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