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arXiv 2019年

作者： Zhan, Yibing Yu, Jun Yu, Ting Tao, Dacheng Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University China UBTECH Sydney AI Centre School of Computer Science FEIT University of Sydney DarlingtonNSW2008 Australia

In visual relationship detection, human-notated relationships can be regarded as determinate relationships. However, there are still large amount of unlabeled data, such as object pairs with less significant relationships or even with no relationships. We refer to these unlabeled but potentially useful data as undetermined relationships. Although a vast body of literature exists, few methods exploit these undetermined relationships for visual relationship detection. In this paper, we explore the beneficial effect of undetermined relationships on visual relationship detection. We propose a novel multi-modal feature based undetermined relationship learning network (MF-URLN) and achieve great improvements in relationship detection. In detail, our MF-URLN automatically generates undetermined relationships by comparing object pairs with human-notated data according to a designed criterion. Then, the MF-URLN extracts and fuses features of object pairs from three complementary modals: Visual, spatial, and linguistic modals. Further, the MF-URLN proposes two correlated subnetworks: One subnetwork decides the determinate confidence, and the other predicts the relationships. We evaluate the MF-URLN on two datasets: The Visual Relationship Detection (VRD) and the Visual Genome (VG) datasets. The experimental results compared with state-of-the-art methods verify the significant improvements made by the undetermined relationships, e.g., the top-50 relation detection recall improves from 19.5% to 23.9% on the VRD dataset. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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An optimal control problem for a spatiotemporal SIR model

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International Journal of Dynamics and Control 2018年第1期6卷 384-397页

作者： El-Alami Laaroussi, Adil Rachik, Mostafa Elhia, Mohamed Laboratory of Analysis Modeling and Simulation Department of Mathematics and Computer Science Faculty of Sciences Ben M’Sik Hassan II University Mohammedia Sidi Othman BP 7955 Casablanca Morocco Modelling Laboratory for economics and management Department of Mathematics and Computer Science Faculty of Law Economics and Social Sciences Beausite Ain Sebaa BP 2634 Casablanca Morocco

In this paper, an SIR spatiotemporal epidemic model is formulated as a system of parabolic partial differential equations with no-flux boundary conditions. Immunity is forced through vaccine distribution considered a control variable. Our principal objective is to characterize an optimal control that minimizes the number of infected individuals and the costs associated with vaccination over a finite space and time domain. The existence of solutions to the state system and the existence of an optimal control is proved. An optimal control characterization in terms of state and adjoint functions is provided. Furthermore, a second condition of optimality is given. The optimality systems are solved based on an iterative discrete scheme that converges following an appropriate test similar the one related to the forward–backward sweep method. Numerical results are provided to illustrate the effectiveness of our approach for several scenarios. © 2016, Springer-Verlag Berlin Heidelberg.

关键词： Numerical methods

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MobileEdge: Enhancing On-Board Vehicle Computing Units Using Mobile Edges for CAVs

MobileEdge: Enhancing On-Board Vehicle Computing Units Using...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Lin Wang Qingyang Zhang Youhuizi Li Hong Zhong Weisong Shi School of Computer Science and Technology Anhui University Hefei China Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China Department of Computer Science Wayne State University Detroit MI USA

ISBN: (纸本)9781728125848

As the rapid growth of connected and autonomous vehicles (CAVs) and 5G intensifies, more third-party applications are increasingly being deployed on CAVs. They not only improve user experience but also provide more helpful services, for example, enhancing public safety by recognizing criminals in real-time videos. Current CAVs prefer to process collected data on the vehicle to avoid long transmission latency and extra network cost. However, due to the limitations of the on-board vehicle computing unit (VCU) and increasing use of computing-intensive in-vehicle applications, the burden of on-board VCU has sharply increased, which may affect driving safety. In particular, for existing vehicles on the road, adding more computing devices is a challenge if not impossible due to cost concerns. Inspired by edge computing, we propose a novel platform, MobileEdge, to enhance the computing capability of the unchangeable on-board VCU, which leverages mobile devices as edge nodes, e.g., the passengers' smartphones, by offloading computing tasks to them for collaboratively computing. Moreover, MobileEdge provides the dynamic management of mobile devices, monitoring device status and interfaces for customizable task offloading strategies and eventually achieves optimal task scheduling. We build a prototype to demonstrate the designed platform and evaluate three task offloading strategies which were implemented based on the developed interfaces. The results show that MobileEdge significantly reduces the application response latency. Compared with the baseline which does not employ task offloading, the response latency is almost near real-time when more computing resources are available. In addition, the proposed shortest response latency strategy outperforms the best overall task scheduling among the three strategies.

关键词： Edge computing Vehicular data analysis Distributed computing Connected and autonomous vehicles Distributed computing TASK SCHEDULING Response Latency UNLOADING vehicle vinyl chloride-urethane copolymer Mobile devices unchangeable quasi-realtime language Public safety

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First-principles study of structural, elastic, electronic, and thermal properties of the ternary intermetallic GdTiGe and GdTiSi

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Hyperfine Interactions 2019年第1期240卷 1-1页

作者： Akel, O. Abbar, B. Meghoufel, Z.F. Abbassa, H. Benatia, M. Benkadour Modeling and Simulation in Materials Science Laboratory Djillali Liabès University Sidi Bel-Abbes22000 Algeria Exact Sciences and Computer Sciences Faculty University of Abdelhamid Ibn Badis Mostaganem27000 Algeria Laboratory of Exact Sciences and Computer Sciences Faculty University of Abdelhamid Ibn Badis Mostaganem27000 Algeria

The full-potential linearized augmented plane wave (FP-LAPW) method using the generalized-gradient approximation (GGA) and the local density approximation (LDA) within the framework of density functional theory (DFT) is applied to the study of structural, elastic, electronic and thermal properties of CeScSi-type GdTiGe and CeFeSi-type GdTiSi intermetallic compounds. Elastic constants are calculated to investigate stability criteria and the mechanical nature of the studied materials. Both compounds are found to be mechanically anisotropic, and ductile, and meet the elastic stability criteria. To complete the fundamental characteristics of both compounds, we have analyzed the thermodynamic properties using the quasi-harmonic Debye model. The obtained results are in a favorable agreement with available experimental and theoretical data. © 2019, Springer Nature Switzerland AG.

关键词： Silicon compounds

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Power Characterization of Memory Intensive Applications: Analysis and Implications 1st

Power Characterization of Memory Intensive Applications: Ana...

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1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Qiu, Yeliang Jiang, Congfeng Fan, Tiantian Wang, Yumei Zhang, Liangbin Wan, Jian Shi, Weisong Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou310037 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310037 China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science Wayne State University DetroitMI48202 United States

ISBN: (纸本)9783030328122

DRAM is a significant source of server power consumption especially when the server runs memory intensive applications. Current power aware scheduling assumes that DRAM is as energy proportional as other components. However, the non-energy proportionality of DRAM significantly affects the power and energy consumption of the whole server system when running memory intensive applications. Thus good knowledge of server power characterization under memory intensive workloads can help better workload placement with power reduction. In this paper, we investigate the power characteristics of memory intensive applications on real rack servers of different generations. Through comprehensive analysis we find that (1) Server power consumption changes with workload intensity and concurrent execution threads. However, fully utilized memory systems are not the most energy efficient. (2) Powered memory modules of installed memory capacity, i.e. the memory capacity per processor core has significant impact on the application’s performance and server power consumption even if the memory system is not fully utilized. (3) Memory utilization is not always a good indicator for server power consumption when it is running memory intensive applications. Our experiments show that hardware configuration, workload types, as well as concurrently running threads have significant impact on a server’s energy efficiency when running memory intensive applications. Our findings presented in this paper provide useful insights and guidance to system designers, as well as data center operators for energy efficiency aware job scheduling and power reductions. © 2019, Springer Nature Switzerland AG.

关键词： Energy efficiency

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Scalability Evaluation of Big Data Processing Services in Clouds 1st

Scalability Evaluation of Big Data Processing Services in Cl...

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1st International Symposium on Benchmarking, Measuring, and Optimization, Bench 2018

作者： Zhou, Xin Jiang, Congfeng Qiu, Yeliang Fan, Tiantian Wang, Yumei Zhang, Liangbin Wan, Jian Shi, Weisong Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou Dianzi University Hangzhou310037 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310037 China College of Big Data and Software Engineering Zhejiang Wanli University Ningbo China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China Department of Computer Science Wayne State University DetroitMI48202 United States

ISBN: (纸本)9783030328122

Currently, many cloud providers deploy their big data processing systems as cloud services, which helps users conveniently manage and process their data in clouds. Among different service providers’ big data processing services, how to evaluate and compare their scalability is an interesting and challenging work. Most traditional benchmark tools focus on performance evaluation of big data processing systems, such as aggregated throughput and IOPS, but fail to conduct a quantitative analysis of their scalability. In this paper, we propose a measurement methodology to quantify the scalability of big data processing services, which makes the cloud services scalability comparable. We conduct a group of comparative experiments on AliCloud E-MapReduce and Baidu MRS, and collect their respective scalability characteristics under Hadoop and Spark workloads. The scalability characteristics observed in our work could help cloud users choose the best cloud service platform to set up an optimized big data processing system to achieve their specific goals more successfully. © 2019, Springer Nature Switzerland AG.

关键词： Big data

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ActivityNet-QA: A dataset for understanding complex web videos via question answering

arXiv

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arXiv 2019年

作者： Yu, Zhou Xu, Dejing Yu, Jun Yu, Ting Zhao, Zhou Zhuang, Yueting Tao, Dacheng Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China College of Computer Science Zhejiang University Hangzhou China UBTECH Sydney AI Centre SIT FEIT University of Sydney Australia

Recent developments in modeling language and vision have been successfully applied to image question answering. It is both crucial and natural to extend this research direction to the video domain for video question answering (VideoQA). Compared to the image domain where large scale and fully annotated benchmark datasets exists, VideoQA datasets are limited to small scale and are automatically generated, etc. These limitations restrict their applicability in practice. Here we introduce ActivityNet-QA, a fully annotated and large scale VideoQA dataset. The dataset consists of 58,000 QA pairs on 5,800 complex web videos derived from the popular ActivityNet dataset. We present a statistical analysis of our ActivityNet-QA dataset and conduct extensive experiments on it by comparing existing VideoQA baselines. Moreover, we explore various video representation strategies to improve VideoQA performance, especially for long videos. The dataset is available at https://***/MILVLG/ activitynet-qa. Copyright © 2019, The Authors. All rights reserved.

关键词： modeling languages

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Hierarchical convolutional features for end-to-end representation-based visual tracking

Hierarchical convolutional features for end-to-end represent...

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作者： Zhu, Suguo Fang, Zhenying Gao, Fei Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China

Recently, deep learning is widely developed in computer vision applications. In this paper, a novel simple tracker with deep learning is proposed to complete the tracking task. A simple fully convolutional Siamese network is applied to capture the similarity between different frames. Nevertheless, the detailed information from lower layers, which is also important for locating the target object, is not considered into the tracking task. In this paper, the detailed information from two lower layers is considered into the response map to improve the performance and not to increase much time spent. This leads more significant improvement for feature representation and localization of the target object. The experimental results demonstrate that the proposed algorithm is efficient and robust compared with the baseline and the state-of-the-art trackers. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Deep neural networks

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Multimodal unified attention networks for vision-and-language interactions

arXiv

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arXiv 2019年

作者： Yu, Zhou Cui, Yuhao Yu, Jun Tao, Dacheng Tian, Qi Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University China UBTECH Sydney AI Centre School of Computer Science Faculty of Engineering University of Sydney Australia Noah's Ark Lab Huawei China

Learning an effective attention mechanism for multimodal data is important in many vision-and-language tasks that require a synergic understanding of both the visual and textual contents. Existing state-of-the-art approaches use co-attention models to associate each visual object (e.g., image region) with each textual object (e.g., query word). Despite the success of these co-attention models, they only model inter-modal interactions while neglecting intra-modal interactions. Here we propose a general 'unified attention' model that simultaneously captures the intra- and inter-modal interactions of multimodal features and outputs their corresponding attended representations. By stacking such unified attention blocks in depth, we obtain the deep Multimodal Unified Attention Network (MUAN), which can seamlessly be applied to the visual question answering (VQA) and visual grounding tasks. We evaluate our MUAN models on two VQA datasets and three visual grounding datasets, and the results show that MUAN achieves top level performance on both tasks without bells and whistles. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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Adjustment submersible cages for optimal fish farming: improved spatiotemporal Lotka–Volterra model for n species in partitioned area

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International Journal of Dynamics and Control 2018年第3期6卷 919-928页

作者： Bouaine, Amine Rachik, Mostafa Laboratory of Analysis Modeling and Simulation Faculty of sciences Ben M’Sik Department of Mathematics and Computer Science Hassan II University BP 7955 Sidi Othman Casablanca Morocco Department of Industrial Engineering École Nationale Supérieure de Mines de Rabat Rabat Morocco

The first goal of this research is to set improved spatiotemporal discrete Lotlka–Volterra model including n different species which occupy three dimensional area Ω and obey to any complex marine food chain. The area Ω is partitioned into R subregions, each subregion includes at least two species, and each species can occupy more than one subregion. The next concern is to increase production of special species which survive in a target subregion, taking into account the financial cost and the severe consequences on the environment. So, we propose two different approaches: optimal farming intra-subregion and optimal farming inter-subregions. One the one hand, we develop optimal program of farming intra-subregion in order to rise the growth rate of the concerned species. On the other hand, we aim to protect the concerned species by optimal adjustment of grids constituting the submersible cage in order to control the local interaction between the target subregion and its neighboring subregions. To the best of our knowledge, it’s the first time when permeability of submersible cages will be modeled and introduced in predator–prey models. To end, adequate numerical illustrations are implemented and discussed to prove the effectiveness of each approach. © 2017, Springer-Verlag Berlin Heidelberg.

关键词： Fish

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