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Graph-based reinforced multi-objective optimization for distributed heterogeneous flexible job shop scheduling problem under nonidentical time-of-use electricity tariffs

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Expert systems with Applications 2025年 290卷

作者： Qichen Zhang Weishi Shao Zhongshi Shao Dechang Pi School of Computer and Electronic Information/School of Artificial Intelligence Nanjing Normal University Nanjing China Key Laboratory of Numerical Simulation for Large Scale Complex Systems Ministry of Education China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China School of Computer Science Shaanxi Normal University Xi’an China

With the rapid development of industrial globalization and diversification, the application of distributed and heterogeneous systems in production scheduling has become increasingly widespread. This paper studies a distributed heterogeneous flexible job shop scheduling problem under nonidentical time-of-use electricity tariffs (DHFJSP-NTOU) that uniquely integrates three underexplored dimensions: heterogeneous factories with time-dependent processing capabilities, geographically varying time-of-use electricity tariffs, and dual optimization of production efficiency and energy sustainability. A mixed-integer linear programming (MILP) model for DHFJSP-NTOU is established. To solve the DHFJSP-NTOU, a graph-reinforced multi-objective optimization algorithm (GRMO) is developed, which features three innovations: a hybrid initialization strategy balancing greedy heuristics and solution diversity, a graph neural network (GNN) framework dynamically encoding operational interdependencies and factory-specific constraints, and a reinforcement learning-driven adaptive operator selection mechanism using proximal policy optimization (PPO) for intelligent search guidance. Finally, comprehensive experiments are carried out to assess the performance of both the MILP model and the components of the GRMO. The experimental outcomes indicate that the GRMO outperforms several of the most recent high-performance methods in solving the DHFJSP-NTOU problem. The structural analysis further validates that the GNN-based feature extraction enhances search efficiency compared to conventional methods. These innovations provide a new paradigm for addressing the challenges of sustainable scheduling in distributed manufacturing systems with heterogeneous resources.

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Spectral-Driven Pansharpening Using Adaptive Image Segmentation to Reduce Color Distortion

Spectral-Driven Pansharpening Using Adaptive Image Segmentat...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Jiao Jiao Xiangwu Gong Lingda Wu Xiangli Meng Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

Extraction and injection of spatial details from the panchromatic (PAN) image and preservation of the spectral characteristics of the multispectral (MS) image are the key issues in pansharpening methods, which are of great significance for the application of image interpretation and target recognition. In this paper, a spectral-driven pansharpening method in which the injection detailed coefficients are estimated over each component segmented by the adaptive K-means algorithm is proposed. The pansharpening method relies on a multi-resolution framework, generalized Laplacian pyramid (GLP) technique, which is applied for the extraction of detail image. The fused image is used as the feedback element, its distance from the original MS image is used to adjust the number of segments adaptively so as to reduce the spectral distortion. Experiments carried out on GeoEye-1 and QuickBird data sets demonstrate the efficiency and effectiveness of our proposed method.

关键词： Image segmentation Spatial resolution Satellites Estimation Nonlinear distortion

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Key Technique of Constructing Collaborating Environment Based on OPENMBEE

Key Technique of Constructing Collaborating Environment Base...

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International Conference on Computer and Communications (ICCC)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Yanhong Jiang Shuying Xu Hongyan Quan State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China School of Software Engineering East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

With the development of integrated design and manufacturing technology, it is necessary to consider how to integrate a variety of modeling tools in the procedure of complex product design driven by the model-centric conception. In this work, we explored the development technology of multi-tool integration based on the Open Model Based Engineering Environment (OpenMBEE). We provide a multi-tool integration system solution, in which the integration schemes under different environments of LAN and virtual machine are designed, and the system scheme of multi-tool integration is also studied. From the idea of model design conception, we integrate the requirement analysis tools Cameo. On the basis, Model Management system (MMS) and View Editor(VE), as well as the specific model analysis tool MATLAB and 3D visual simulation tool Creo are also integrated seamlessly. The effectiveness of the proposed integration strategies is verified by some practical instances. That is verified that our study can provide an effective design idea for complex production.

关键词： Analytical models Solid modeling Computational modeling Tools Product design Mathematical model Matlab

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Continuous and comprehensive atmospheric observations in Beijing:a station to understand the complex urban atmospheric environment

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Big Earth Data 2020年第3期4卷 295-321页

作者： Yongchun Liu Chao Yan Zemin Feng Feixue Zheng Xiaolong Fan Yusheng Zhang Chang Li Ying Zhou Zhuohui Lin Yishou Guo Ying Zhang Li Ma Wenshuo Zhou Zhikun Liu Lubna Dada Kaspar Dallenbach Jenni Kontkanen Runlong Cai Tommy Chan Biwu Chu Wei Du Lei Yao Yonghong Wang Jing Cai Juha Kangasluoma Tom Kokkonen Joni Kujansuu Anton Rusanen Chenjuan Deng Yueyun Fu Rujing Yin Xiaoxiao Li Yiqun Lu Yiliang Liu Chaofan Lian Dongsen Yang Weigang Wang Maofa Ge Yuesi Wang Douglas R.Worsnop Heikki Junninen Hong He Veli-Matti Kerminen Jun Zheng Lin Wang Jingkun Jiang Tuukka Petaja Federico Bianchi Markku Kulmala Aerosol and Haze Laboratory Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijingChina Institute for Atmospheric and Earth System Research/Physics Faculty of ScienceUniversity of HelsinkiHelsinkiFinland State Key Joint Laboratory of Environment Simulation and Pollution Control State Environmental Protection Key Laboratory of Sources and Control of Air Pollution ComplexSchool of EnvironmentTsinghua UniversityBeijingChina State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijingChina Department of Environmental Science&Engineering Fudan UniversityShanghaiChina State Key Laboratory for Structural Chemistry of Unstable and Stable Species Beijing National Laboratory for Molecular SciencesInstitute of ChemistryChinese Academy of SciencesBeijingChina Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Nanjing University of Information Science&TechnologyNanjingChina State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina Aerodyne Research Inc. BillericaMassachusettsUSA Institute of Physics University of TartuTartuEstonia Joint International Research Laboratory of Atmospheric and Earth System Sciences School of Atmospheric SciencesNanjing UniversityNanjingChina

Due to profound impact on climate and human health,air quality has attracted attention from all levels of the civil *** key step in the provision of required tools for the society to tackle the complex air quality problem is to characterize it in a comprehensive manner with a long-term ***,we describe a continuous and comprehensive observation station and its accompanying state-ofthe-art instrumentation that was established to investigate the complex urban atmospheric environment in a rapidly developing Chinese *** station,located in downtown Beijing,aims to study air quality by identifying the major atmospheric pollutants and key processes determining their formation and loss mechanisms.A few hundreds of parameters are continuously measured with the state-of-the-art instruments,including trace gas concentrations,aerosol particle size distributions,and mass concentrations,covering aerosol particle chemical composition from molecules to micrometer-sized aerosol *** produced long-term,comprehensive big data with around 1�10^(11)bytes per *** this paper,we provide an overview on the facilities of the station,the instrumentation used,the workflow of continuous observations and examples of results from 2018 to 2019 and a basis for establishing a modern long-term,comprehensive atmospheric urban observation station in other megacities.

关键词： Continuous and comprehensive atmospheric observation air pollution complex photochemical smog haze new particle formation

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Ship Target Signature Indication based on complex Signal Kurtosis in SAR Images

Ship Target Signature Indication based on Complex Signal Kur...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiangguang Leng Kefeng Ji Boli Xiong Gangyao Kuang State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and technology National University of Defense Technology Changsha China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Recently, complex signal kurtosis (CSK) is found to be a vital indicator of ship detection in synthetic aperture radar (SAR) images. Since CSK can be used as an indicator of ship detection, we consider it can also be used to indicate ship target signature. One of the basic rationales is that the higher the CSK is, the easier it is to be detected and thus the more obvious its characteristics are as a ship. Presence of sidelobes and defocusing are two common problems that affect the quality of ship targets. They are discussed in this paper from the perspective of CSK. Experimental results show that CSK can be used to indicate and improve ship quality. We believe that ship detection and recognition can benefit from the CSK indicator.

关键词： Marine vehicles Radar polarimetry Synthetic aperture radar Azimuth Remote sensing Random variables Spaceborne radar

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Stability and energetics of two-dimensional surface crystals in liquid AuSi thin films and nanoscale droplets

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Physical Review Materials 2021年第7期5卷 074003-074003页

作者： Hailong Wang Mengyuan Wang Alireza Shahabi Alain Karma Moneesh Upmanyu CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics CAS Center for Excellence in Complex System Mechanics University of Science and Technology of China Hefei Anhui 230027 China Group for Simulation and Theory of Atomic-Scale Material Phenomena (stAMP) Department of Mechanical and Industrial Engineering Northeastern University Boston Massachusetts 02115 USA Department of Physics Northeastern University Boston Massachusetts 02115 USA

We employ atomic-scale computational frameworks to study the surface crystallization in AuSi films and droplets as a function of composition, temperature, and size. Above the melting point, the surfaces of both thin films and droplets undergo a first-order transition from a two-dimensional (2D) Au2Si crystalline phase to a laterally disordered yet stratified layer. The thin film surfaces exhibit an effective surface tension that increases with temperature and decreases with Si concentration, while for droplets in the size range 10–30 nm, the bulk Laplace pressure alters the surface segregation as it occurs with respect to a strained bulk. Above the transition, the size effect on the surface tension due to the stratified surface layer is small, while the crystalline surface layer below the transition is strained and composed of 2D crystallites separated by extended grain boundary scars that lead to large fluctuations in its energetics. As a specific application, all-atom simulations of AuSi droplets on Si(111) substrate subject to Si surface flux show that the supersaturation dependent surface tension destabilizes the contact line via formation of a precursor wetting film on the solid-vapor interface and has ramifications for size selection during droplet-catalyzed routes for nanowire growth. Our study sheds light on the interplay between stability and energetics of surfaces in this unique class of binary alloys and offers pathways for exploiting their surface structure for varied applications such as catalytic nanocrystal growth, dealloying, and polymer crystallization.

关键词： Crystal forms Growth Interface & surface thermodynamics Nanocrystals Structural phase transition 2-dimensional systems Surfaces Molecular dynamics

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Magnetic and magnetocaloric effect in a stuffed honeycomb polycrystalline antiferromagnet GdInO3

arXiv

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arXiv 2021年

作者： Wu, Yao-Dong Duan, Wei-Wei Li, Qiu-Yue Qin, Yong-Liang Zi, Zhen-Fa Tang, Jin Universities Joint Key Laboratory of Photoelectric Detection Science and Technology in Anhui Province Anhui Province Key Laboratory of simulation and design for Electronic information system School of Physics and Materials Engineering Hefei Normal University Hefei230601 China Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions High Magnetic Field Laboratory HFIPS Anhui Chinese Academy of Sciences Hefei230031 China University of Science and Technology of China Hefei230026 China

The magnetic and magnetocaloric properties were studied in a stuffed honeycomb polycrystalline antiferromagnet GdInO3. The onset temperature of antiferromagnetic ordering was observed at ~ 2.1 K. Negligible thermal and magnetic hysteresis suggest a reversible magnetocaloric effect (MCE) in the GdInO3 compound. In the magnetic field changes of 0–50 kOe and 0–70 kOe, the maximum magnetic entropy change values are 9.65 J/kg K and 18.37 J/kg K, respectively, near the liquid helium temperature, with the corresponding relative cooling power values of 115.01 J/kg and 211.31 J/kg. The MCE investigation of the polycrystalline GdInO3 serves to illuminate more exotic properties in this frustrated stuffed honeycomb magnetic system. © 2021, CC BY.

关键词： Honeycomb structures

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Comparison Study of Multitemporal PolSAR Classification Using Convolutional Neural Networks

Comparison Study of Multitemporal PolSAR Classification Usin...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chen-Song Tao Si-Wei Chen Shun-Ping Xiao State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System School of Electronic Science National University of Defense Technology Changsha China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Target classification is a main application of polarimetric synthetic aperture radar (PolSAR). With the PolSAR images of the same region observed on various dates, multitemporal classification plays an important role in crop discrimination and growth monitoring. However, due to the crop growth change, classification methods with good generalization are imperative. Recently, advanced deep learning techniques have achieved breakthroughs in optical image processing. Among them, convolutional neural networks (CNNs) can greatly improve accuracies in classification tasks. Because their multilayer architectures can extract the abstract feature with strong robustness to characterize the kinds' difference. In this vein, the multilayer architectures may be able to lead to the higher accuracies, as well as the better generalization in multitemporal PolSAR classification. So, this work aims to investigate multitemporal PolSAR classification using five CNNs of AlexNet, VGG16, Inception, ResNet50, and MobileNet. In detail, four roll-invariant features and two hidden features in the rotation domain are selected as inputs. Comparison experiment based on four temporal UAVSAR data with seven land covers validates the efficiency of these CNNs. For the train-used temporal, Inception can achieve the higher overall accuracies. While, for the train-not-used temporal, ResNet50 is with the better generalization.

关键词： Feature extraction Convolution Training Agriculture Convolutional neural networks Task analysis Veins

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An Efficient Water Segmentation Method for SAR Images

An Efficient Water Segmentation Method for SAR Images

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Muchen Dai Xiangguang Leng Boli Xiong Kefeng Ji State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Water segmentation is a fundamental step for the information processing of SAR image, which plays an important role in ship detection, disaster monitoring and other applications. Because of the complexity of scenario in the SAR images, water segmentation of SAR image is a challenging task. Fewer convolutional neural networks (CNNs) have been developed for SAR image water segmentation in recent years, the accuracy and speed of CNN for water segmentation can be further improved. In this paper, we established a SAR water segmentation dataset based on the GF3 satellite data. then an improved water segmentation network based on Bilateral Segmentation Network (BiSeNet) is proposed. Further we propose a loss function based on edge area and a novel training data generation method to improve the segmentation ability of the network. Experimental results based on water segmentation dataset show that the proposed segmentation method has better segmentation accuracy and speed.

关键词： Image segmentation Radar polarimetry Image edge detection Training data Training Synthetic aperture radar Marine vehicles

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A multi-layer network topology visualization layout based on Louvain community detection 3

A multi-layer network topology visualization layout based on...

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3rd IEEE International Conference on Data science in Cyberspace, DSC 2018

作者： Zhang, Xitao Wu, Lingda Yao, Zhonghua Yu, Shaobo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9781538642108

Community is one of the most important structure features of complex networks. It has important research significance for topological structure analysis, behavior prediction, cascading failure, percolation and spreading of multi-layer networks. Aiming at the problem that the existing multi-layer network visualization can't clearly show the community structure, a multi-layer network topology visualization layout based on Louvain community detection is proposed. Firstly, a complex network community discovery algorithm (Louvain) is used to perform the multi-layer network nodes at each layer and the community affiliation of the nodes is obtained at each layer;then, based on the traditional force-directed layout, the community force is added to the internal nodes of the community, so that all the nodes that belong to the same community are gathered to the community center, so as to achieve the effect of displaying the network community structure. The simulation results show that the algorithm has the characteristics of faster convergence and clearer community structure than the traditional visual layout algorithm. © 2018 IEEE.

关键词： Network topology

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