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2022 International Conference on Networking and Network Applications, NaNA 2022

作者： Yu, Han Zhan, Jie Libin, Jiao Han, Jun-Mei School of Physics and Electronic Science Hunan University of Science and Technology Xiangtan412001 China Science and Technology on Communication Networks Laboratory Shijiazhuang050081 China National Key Laboratory for Complex Systems Simulation Department of Systems General Design Institute of Systems Engineering Beijing100101 China

ISBN: (数字)9781665461313

ISBN: (纸本)9781665461313

IEEE 802.11 Wireless Local Area Network (WLAN) is a popular way for mobile devices to access the Internet. Operators and service providers often increase the density of wireless access points in order to provide users with better connections and user experience. As a result, WLAN users find themselves covered by multiple access points. In traditional wireless multi-hotspot networks most user terminals choose the access point with the strongest signal without considering the existing load on that access point, leading to severe congestion and load imbalance problems. This paper proposes an improved NSGA-II-based load balancing strategy for wireless multi-hotspot networks, which determines which hotspot should be associated with each user terminal by taking into account the current access point load, the received signal strength and the throughput size of the user terminal. The simulation results show that compared with the traditional strongest signal First (SSF) strategy, the proposed load balancing strategy can improve the network throughput by more than 30%. © 2022 IEEE.

关键词： IEEE Standards

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Effect of Different Migration Strategies on Evolution of Cooperation in Spatial Prisoner's Dilemma Game

Effect of Different Migration Strategies on Evolution of Coo...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Hong Ding Xiangyu Chen Benyun Shi Yanming Ye Yizhi Ren School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China Key Lab. of Complex Syst. Modeling & Simulation Dianzi Univ. Hangzhou China

Many migration strategies have been proposed forPrisoner's Dilemma game on square lattice, such as randommigration, success-driven migration and adaptive migration. Inthis paper, we introduce three novel migration strategies: failure driven migration, hate-driven migration and global-scope migration. Based on the length of migration, individual with one of the first two strategies decides when and where to move into empty nearby places based on its performance in current site, while individual with a global-scope migration can move to anywhere. Then we compare them with the cases of no migration, random migration and success-driven migration. The simulations show that the failure-driven migration has the best performance in most circumstances. While defectors dominate in success-driven migration cases.

关键词： High definition video Big data

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MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segmentation 19th

MD-TransUNet: TransUNet with Multi-attention and Dilated C...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Xu, Jie Wan, Jian Zhang, Xin School of Computer Science and Technology Hangzhou Dianzi University Zhejiang310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Ministry of Education Beijing China School of Information and Electronic Engineering Zhejiang University of Science and Technology Zhejiang China Key Laboratory of Marine Ecosystem Dynamics Second Institute of Oceanography Ministry of Natural Resources Hangzhou China

ISBN: (纸本)9783031545276

The accurate segmentation of stroke lesion regions holds immense significance in shaping treatment strategies and rehabilitation protocols. Due to the large difference in the volume of stroke lesion areas and the great similarity between lesion areas and normal tissues, most of the existing methods for lesion segmentation cannot deal with these problems well. This paper proposes a novel network named MD-TransUNet for the segmentation of stroke lesions, whose framework is based on the UNet architecture. To fully obtain deep image features, it uses ResNet50 for downsampling. MD (multi-dilated) module is employed as the skip connection to gain more receptive fields. Different receptive fields can adapt to varying volumes of lesion areas. Then, a feature extraction module with multi-level attention mechanism is designed using ConvLSTM, non-local spatial attention, and channel attention modules to suppress useless information expression in skip connections and upsampling processes while focusing more on effective spatial and channel information in features. The experiments show that our proposed network gets superior performance than benchmark methods and indicates the generalization and effectiveness of the proposed model. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Convolution

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"Why not looking backward?" a robust two-step method to automatically terminate Bayesian optimization 23

"Why not looking backward?" a robust two-step method to auto...

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Shuang Li Ke Li Wei Li Control and Simulation Center Harbin Institute of Technology China and National Key Laboratory of Modeling and Simulation for Complex Systems China Department of Computer Science University of Exeter Exeter UK

Bayesian Optimization (BO) is a powerful method for tackling expensive blackbox optimization problems. As a sequential model-based optimization strategy, BO iteratively explores promising solutions until a predetermined budget, either iterations or time, is exhausted. The decision on when to terminate BO significantly influences both the quality of solutions and its computational efficiency. In this paper, we propose a simple, yet theoretically grounded, two-step method for automatically terminating BO. Our core concept is to proactively identify if the search is within a convex region by examining previously observed samples. BO is halted once the local regret within this convex region falls below a predetermined threshold. To enhance numerical stability, we propose an approximation method for calculating the termination indicator by solving a bilevel optimization problem. We conduct extensive empirical studies on diverse benchmark problems, including synthetic functions, reinforcement learning, and hyperparameter optimization. Experimental results demonstrate that our proposed method saves up to ≈ 80% computational budget yet is with an order of magnitude smaller performance degradation, comparing against the other peer methods. In addition, our proposed termination method is robust in terms of the setting of its termination criterion.

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Design and Development of a simulation Model Validation Tool 21st

Design and Development of a Simulation Model Validation Tool

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21st Asia simulation Conference, AsiaSim 2022

作者： Su, Hongjia Lu, Zhifeng Liu, Fei Li, Rufei Ye, Feng South China University of Technology Guangdong Guangzhou510006 China Shanghai Electro-Mechanical Engineering Institute Shanghai201109 China National Key Laboratory for Complex Systems Simulation Beijing100000 China

ISBN: (纸本)9789811991974

Model validation is one of the core issues in modeling and simulation, which aims to check whether the model output correctly reflects the output of the corresponding real system. Model validation is also a complicated process, which requires powerful software to achieve its purpose. In this paper, we describe a simulation model validation tool (shortly SMVT) that we developed recently for the validation purpose of complex simulation models. We first talk about the functions and architectural design of SMVT and then employ a missile simulation model to demonstrate the application of SMVT. This tool has so far been widely used in many scenarios. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： modeling and simulation simulation model validation Validation tool

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Construction of dimeric hTSPO protein model using homology modeling and molecular dynamics 45

Construction of dimeric hTSPO protein model using homology m...

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45th Vietnam Conference on Theoretical Physics, VCTP 2020

作者： Lai, Hien T. T. Nguyen, Toan T. Key Laboratory for Multiscale Simulation of Complex Systems VNU University of Science Viet Nam Vietnam National University - Hanoi 334 Nguyen Trai street Thanh Xuan district Hanoi Viet Nam

A model for the dimeric form of the human TSPO (hTSPO) protein is constructed homologically using the RsTSPO dimer template. Then, Molecular dynamics simulation of 1μs is carried out on the model to investigate its stability as well as to study its various physicochemical properties. Our model shows good stability, with various important conserved residues involving in monomer-monomer interactions, in good agreements with available experimental data. Several functioning motifs are well demonstrated. This model hence can serve as a good basis for further study of this system as well as for discoveries of candidate radioligands targeting TSPO protein as a biotracer for medical imaging of brain inflamation. © Published under licence by IOP Publishing Ltd.

关键词： Proteins

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Architecture Transformation Research on Joint Border Defense systems-of-systems

Architecture Transformation Research on Joint Border Defense...

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作者： Mengmeng Zhang Shuanghui Yi Menglong Lin Honghui Chen Science and Technology on Information Systems Engineering Laboratory National Key Laboratory for Complex System Simulation

Currently,with the deepening of development and open of China's border,issues of border joint defense become increasingly *** means of cooperation and coordination are far from being able to align requirements;information systems of different joint defense units are difficult to interconnect and interoperate;the previous results of joint defense informatization are difficult to *** main reason is the lack of border joint defense information construction with a top-level design *** the lens of top-level design,this paper establishes a multi-viewpoint architecture framework and transformation process,develops the as-is and to-be joint defense architecture,and finally analyzes transformation principles from the as-is architecture to to-be *** paper mainly explores the architecture transformation mechanisms under the border joint defense scenario.

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Background-Driven and Foreground-Refined Network for Weakly-Supervised Change Detection

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Liu, Fang Zhang, Peng Liu, Jia Yang, Jingxiang Tang, Xu Xiao, Liang Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing 210094 China Jiangsu Province Engineering Research Center of Airborne Detecting and Intelligent Perceptive Technology Nanjing 210049 China Ministry of Industry and Information Technology Key Laboratory of Analysis of Mathematical Theory and Modeling of Complex Systems Nanjing 210094 China Xidian University School of Artificial Intelligence Xi’an 710071 China

Change detection (CD) in remote sensing aims to reveal meaningful surface changes and has been flourishing in recent years. Compared with fully-supervised methods based on pixel-level labels, image-level labels are easy to acquire, which reduces manual labor to a large extent. However, image-level labels lack spatial-and-shape information while containing the least semantic information, which poses a great challenge to the weakly-supervised CD task. Motivated by the prior that bi-temporal images have background semantic consistency, we propose Background-Driven and Foreground-Refined (BDFR-Net) to ameliorate the above problem. Specifically, there are two key components in the proposed method: the Background-Driven Reconstruction (BDR) with image-level supervision and the Foreground-Refined Learning (FRL) with affinity learning. The former generates changed regions of foreground and background separation, which activates the foreground from image-level supervision and constrains the foreground by maintaining spatial and semantic consistency in background regions. The latter introduces Complementary Fusion and Label Adaption (CFLA) strategies to further refine the foreground, which can mine complementary information from foreground sequences and suppress false activations. In addition, affinity learning is proposed to stabilize and supervise the above process. Complementary relationships between foreground and background are fully utilized. Tested on two popular CD datasets, the results demonstrate that our proposed BDFR-Net produces completely changed regions with clear boundaries and outperforms state-of-the-art weakly-supervised methods. © 1980-2012 IEEE.

关键词： background Change detection foreground weakly-supervised learning

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Photo Aesthetic Quality Assessment via Label Distribution Learning

Photo Aesthetic Quality Assessment via Label Distribution Le...

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IEEE International Conference on systems, Man, and Cybernetics

作者： Xiaowei Zhang Fei Gao Di Huang Min Tan Jun Yu key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781509018987

Automatic prediction of photo aesthetic quality is useful for many practical purposes. Current computational approaches typically solved this problem by assigning a categorical label (good or bad) to a photo. However, due to the subjectivity and complexity of humans aesthetic judgments, only a categorical label is insufficient to represent humans perceived aesthetic quality of a photo. This paper focuses on an interesting problem: is it possible to predict the crowed opinions about the aesthetic quality of a photo? The crowed opinion here is expressed by the distribution of scores given by a number of subjects. For each given photo, a deep convolutional neural network (DCNN) is utilized to calculate its feature representation. Afterwards, the crowed opinion prediction problem is formulated as one of label distribution learning (LDL). Experiments show that the proposed method is highly effective and outperforms state-of-the-art algorithms.

关键词： label distribution support regressor photo quality assessment convolutional neural network deep learning label distribution learning

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An improved functional dependency network model for information systems effectiveness analysis 2020

An improved functional dependency network model for informat...

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2020 International Conference on Wireless Communication and Sensor Networks, icWCSN 2020

作者： Luo, Aimin Yi, Shuanghui Liu, Junxian Kou, Yuxiao Gao, Lanlan Zhang, Mengmeng Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha Hunan410073 China National Key Laboratory for Complex System Simulation Beijing China Academy of Military Science of the PLA Beijing100000 China

ISBN: (纸本)9781450377638

To address the limitations of the FDNA approach, in this paper, we analyze the dependency of the receiver node on the feeder nodes as well as the impact of the node's operability level on the system effectiveness, and improve the FDNA approach. We also propose a computing method for system effectiveness based on an improved FDNA model, and conduct relevant case verification. © 2020 ACM.

关键词： Information systems

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