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23rd Asia simulation Conference, AsiaSim 2024

作者： Yang, Fan Ma, Ping Li, Wei Tao, Chao Yang, Ming Zhang, Jianchao Cheng, Huichuan Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Modeling and Simulation Harbin150080 China Chinese Aeroengine Research Institute Beijing101304 China

ISBN: (纸本)9789819772247

Validation for complex system simulation faces the challenges of a large amount of validation data, which comes in the form of extensive samples and prolonged time series. To address this issue, this paper proposes an intelligent simulation result validation method based on Variational Autoencoder (VAE), achieving model validation through intelligent feature extraction and feature consistency metrics. Initially, we present the overall validation framework, which consists of feature extraction and simulation result validation, and detail the steps of the validation process. Subsequently, the principles and procedures of the feature extraction and simulation result validation methods are thoroughly discussed. The feature extraction is achieved by learning the distribution parameters of the latent space using a VAE model. Feature differences across various aspects are measured by three distance metrics and are further converted into simulation credibility. Finally, the effectiveness and superiority of this method are demonstrated through a case study on validating a drone delivery model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital elevation model

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Discovering API Directives from API Specifications with Text Classification

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Journal of Computer Science & Technology 2021年第4期36卷 922-943页

作者： Jing-Xuan Zhang Chuan-Qi Tao Zhi-Qiu Huang Xin Chen College of Compute Science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016China Key Laboratory of Safety-Critical Software(Nanjing University of Aeronautics and Astronautics) Ministry of Industry and Information TechnologyNanjing 210016China Key Laboratory of Complex Systems Modeling and Simulation(Hangzhou Dianzi University) Ministry of Education Hangzhou 310018China School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou 310018China

Application programming interface(API)libraries are extensively used by *** correctly program with APIs and avoid bugs,developers shall pay attention to API directives,which illustrate the constraints of ***,API directives usually have diverse morphologies,making it time-consuming and error-prone for developers to discover all the relevant API *** this paper,we propose an approach leveraging text classification to discover API directives from API ***,given a set of training sentences in API specifications,our approach first characterizes each sentence by three groups of ***,to deal with the unequal distribution between API directives and non-directives,our approach employs an under-sampling strategy to split the imbalanced training set into several subsets and trains several *** a new sentence in an API specification,our approach synthesizes the trained classifiers to predict whether it is an API *** have evaluated our approach over a publicly available annotated API directive *** experimental results reveal that our approach achieves an F-measure value of up to 82.08%.In addition,our approach statistically outperforms the state-of-the-art approach by up to 29.67%in terms of F-measure.

关键词： Application programming interface(API)directive API specification imbalanced learning text classification

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Energy efficiency analysis of heterogeneous platforms: Early experiences 7

Energy efficiency analysis of heterogeneous platforms: Early...

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7th International Green and Sustainable Computing Conference, IGSC 2016

作者： Li, Youhuizi Shi, Weisong Jiang, Congfeng Zhang, Jilin Wan, Jian Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University China Mobile and Internet Systems Laboratory Wayne State University United States School of Information and Electronic Engineering Zhejiang University of Science and Technology China

ISBN: (纸本)9781509051175

Heterogeneous multi-core platforms, e.g., ARM's ***, are a promising trend to improve the performance and energy efficiency of future mobile systems. However, the immediate benefits and the challenges to take advantage of the heterogeneity are still not clear. In this paper, we present our early experiences about the energy efficiency of the two *** heterogeneous platforms: ODROID XU+E and ODROID XU3. We quantified compared them with homogeneous platforms through multiple benchmarks which include popular mobile applications and high-performance parallel benchmarks. Besides, we analyzed the scheduling impact on the energy consumption of the heterogeneous platforms and the migration cost is also discussed. Based on the results, several insights, such as fine-granularity power control and thread level parallelism, related to hardware, application and system design are derived. © 2016 IEEE.

关键词： Energy utilization

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Deep Point Convolutional Approach for 3D Model Retrieval

Deep Point Convolutional Approach for 3D Model Retrieval

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhenzhong Kuang Jun Yu Jianping Fan Min Tan Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University

With the increasing popularity of 3D models, retrieving deformable 3D objects is becoming a crucial task. The state-of-the-art methods use complex deep neural networks to address this problem, which require lots of computational resources. In this paper, we develop a more effective solution by using point convolution. Our algorithm takes local point descriptors as the input and produces a global vector for shape retrieval. To save the efforts of designing complex deep convolutional neural network (CNN), we first use intrinsic point descriptors to describe the shape deformations. Then, a simple but effective point CNN network is developed to integrate the local shape information by performing subspace compression and fusion, which depends on an end-to-end learning process to link the local and global information for discriminative shape representation. The experimental results on popular benchmarks have verified that our algorithm is able to outperform the state-of-the-art methods.

关键词： Shape Three-dimensional displays Solid modeling Heating systems Strain Machine learning Feature extraction

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Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

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Journal of Environmental Sciences 2019年第9期31卷 8-20页

作者： Tao Ma Fengkui Duan Kebin He Yu Qin Dan Tong Guannan Geng Xuyan Liu Hui Li Shuo Yang Siqi Ye Beiyao Xu Qiang Zhang Yongliang Ma State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing Key Laboratory of Indoor Air Quality Evaluation and Control Tsinghua University Beijing 100084 China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing 100084 China National Satellite Meteorological Center Beijing 100081 China College of Resources and Environmental Sciences China Agricultural University Beijing 100094 China

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O3,decreased. Spatially, the PM2.5, PM10, SO2, and CO concentrations were higher in the northern YRD region, and NO2 and O3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM2.5 was the largest contributor to air pollution in the YRD region, followed by O3, PM10, and ***, particulate matter pollution has declined gradually, while O3 pollution *** conditions mainly influenced day-to-day variations in pollutant concentrations. PM2.5 concentration was inversely related to wind speed, while O3 concentration was positively correlated with temperature and negatively correlated with relative *** air quality improvement in recent years was mainly attributed to emission *** 2014–2016, PM2.5, PM10, SO2, NOx, CO, NH3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.

关键词： Air pollution Spatiotemporal variation Meteorological condition Emission inventory Regional transport Yangtze River Delta

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Zhou, Renjie Jin, Zhenming Wan, Jian Zhang, Jilin Guo, Xingyu Liu, Qiang Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou China Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Itmo Joint Institute Hangzhou China Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou China Zhejiang Police College Dept. of Computer and Information Technology Hangzhou China

ISBN: (纸本)9798350304855

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user's shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods. © 2023 IEEE.

关键词： Forecasting

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Mitigating overtrust towards robot in mixed reality interfaces 1

Mitigating overtrust towards robot in mixed reality interfac...

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1st International Conference on Artificial Intelligence and Human-Computer Interaction, ArtInHCI 2023

作者： He, Di Zhao, Changshun Zhang, Kaiyue Yang, Hongrong Liu, Ying University of Electronic Science and Technology of China Chengdu China National Key Laboratory for Complex Systems Simulation Beijing China Officers College of PAP Chengdu China

ISBN: (纸本)9781643685083

This research focuses on the role of trust in human-agent interaction, particularly in the context of home robot systems. The study found that participants were more likely to collaborate when they understood the agent's intentions. The research involved 36 participants working with an agent across three different interfaces to complete household tasks. The results showed that clear agent intentions can increase cooperation and calibrate trust to an appropriate level. © 2024 The Authors.

关键词： Human robot interaction

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Automatic term recognition method for military domain 3

Automatic term recognition method for military domain

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2021 3rd International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2021

作者： Song, Ani Jia, Xiaoxia Jiang, Wei North China Institute of Computing Technology Beijing100083 China National Key Laboratory for Complex Systems Simulation Department of Systems General Design Institute of Systems Engineering AMS Beijing100083 China

With the development of military intelligence, higher requirements are put forward for automatic term recognition in military field. In view of the characteristics of flexible and diverse naming of military requirement documents without annotated corpus, the method of this paper uses the existing military domain core database, and matches the data set and core database by Aho-Corasic algorithm and word segmentation technology, so that the terms to be recognized in the data set can be divided into three *** possible rules of word formation of military terms are summarized and phrases that conform to the rules of word formation are found in the documents as the term candidate set. The core library and TF-IDF method are used to calculate the value of the candidate terms, and the candidate terms whose value is greater than the threshold are selected iteratively as the real terms. The experimental results show that the F1 value of this method reaches 0.719, which is better than the traditional C-value method. Therefore, the method proposed in this paper can achieve better automatic term recognition effect for military requirement documents without annotation. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Iterative methods

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TaxiCast: Efficient Broadcasting of Multimedia Advertisements in Vehicular Ad-Hoc Networks

TaxiCast: Efficient Broadcasting of Multimedia Advertisement...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Peng Liu Jia Xu Biao Xu Tingting Fu Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou

ISBN: (纸本)9781509053827

Traditional vision based vehicular advertising methods can only support planar advertisements. If there are obstacles blocking the line-of-sight between the advertiser and customers, the efficiency drops quickly. With the proliferation of vehicular ad-hoc networks (VANETs), advertisements can be disseminated through wireless means. However, the utility of advertisements still decay over time so that the advertiser will require fast delivery to achieve higher rewards. In this paper, we consider a taxi based multimedia advertisements broadcasting scenario where the taxis act as the advertising sources. To solve the contradiction between limited communication capacity and big data size, we propose TaxiCast which can achieve very good performance. It first applies signal strength based coding and decoding to obtain the demandings of the surrounding vehicles. Then it solves the advertisements selection process as a knapsack problem. We also consider the reward decay of advertisements and conflicts between the taxis. We conduct simulations in both fixed reward case and decayed reward case. The result shows that our scheme achieves better performance than the existing strategies.

关键词： Advertising Vehicles Public transportation Multimedia communication Ad hoc networks Digital multimedia broadcasting

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Toward activity mapping for Artifact-Centric business process

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International Journal of u- and e- Service, Science and Technology 2016年第6期9卷 421-432页

作者： Yin, Yuyu Zhu, Zhengshuang Gao, Min Song, Aihua College of Electrical Engineering Zhejiang University HangzhouZhejiang310027 China School of Computer Science and Technology Hangzhou Dianzi University HangzhouZhejiang310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education HangzhouZhejiang310018 China

The existing method of task mapping between process models is mostly based on the similarity of labels to get the similarity between tasks, which is affected by a single factor and easy to cause errors. This paper proposes a task mapping method for Artifact-Centric business process analyzes the data operation in business process execution. At first we add the description of data operation to EZ-Flow model. Secondly select the similar artifact attributes of the two business artifact by whole artifacts similarity calculation and based them to calculate two tasks’ similarity by label similarity, artifact operation similarity and context similarity calculations. Finally, the task mapping comes from the optimal selection of tasks’ similarities. Experimental results verify the effectiveness of the method, and show that the method reflects the data operation characteristics of business process model, as artifact task mapping of the process model provides a feasible method. © 2016 SERSC.

关键词： Mapping

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