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检索条件"任意字段=23rd IEEE International Conference on Automation and Computing, ICAC 2017"

共 111 条记录，以下是61-70 订阅

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Extracting Spatio-Temporal Texture signatures for crowd abnormality detection 23

Extracting Spatio-Temporal Texture signatures for crowd abno...

引用

23rd ieee international conference on automation and computing, icac 2017

作者： Hao, Yu Wang, Jing Liu, Ying Xu, Zhijie Fan, Jiulun School of Communication and Information Engineering Xi'An University of Posts and Telecommunication Xi'an China School of Computing and Engineering University of Huddersfield Huddersfield United Kingdom

ISBN: (纸本)9780701702618

In order to achieve automatic prediction and warning of hazardous crowd behaviors, a Spatio-Temporal Volume (STV) analysis method is proposed in this research to detect crowd abnormality recorded in CCTV streams. The method starts from building STV models using video data. STV slices - called Spatio-Temporal Textures (STT) - can then be analyzed to detect crowded regions. After calculating the Gray Level Co-occurrence Matrix (GLCM) among those regions, abnormal crowd behavior can be identified, including panic behaviors and other behavioral patterns. In this research, the proposed STT signatures have been defined and experimented on benchmarking video databases. The proposed algorithm has shown a promising accuracy and efficiency for detecting crowd-based abnormal behaviors. It has been proved that the STT signatures are suitable descriptors for detecting certain crowd events, which provide an encouraging direction for real-time surveillance and video retrieval applications. © 2017 Chinese automation and computing Society in the UK - CACSUK.

关键词： automation

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A study on creative elements detection in application domain workflow based on educational psychology theories 23

A study on creative elements detection in application domain...

引用

23rd ieee international conference on automation and computing, icac 2017

作者： Liu, Qinyun Che, Hongming Zou, Lin Yang, Hongji Zhang, Chi Liu, Ligang Centre for Creative Computing Bath Spa University Bath United Kingdom Collaborative Innovation Centre of EToutism Beijing Union University China Dirct. of the Academic Committee and the Academic Degrees Committee of Business School of Liaoning University Liaoning China

ISBN: (纸本)9780701702618

Creativity is considered as a very important element of the society development. Having entered the big data era, people have been focusing on finding a pathway developing creativity for all applications. In the psychology and education domain, various approaches have been attempted, such as divergent thinking and brain storming. The psychology domain has researched on human's cognitive development and influential elements. However, existing approaches are unable to present a specific guidance for an individual to develop creativity. This research aims at apply psychology, education and creative computing research outcomes to seek for a reliable workflow to generate a feasible education scheme through detecting creative elements from the history of a target application domain. In this way, people can be clear for both negative and positive elements. The workflow also implements computing algorithms to make the data processing more accurate and scientific. The whole workflow includes three stages: searching for the history, selecting theorists' classification, and results matching and integrating. The final outcome will be an education scheme containing both positive and negative elements for the user. © 2017 Chinese automation and computing Society in the UK - CACSUK.

关键词： automation

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H∞ state estimation for discrete time-delayed stochastic genetic regulatory networks with known sojourn probabilities 23

H∞ state estimation for discrete time-delayed stochastic ge...

引用

23rd ieee international conference on automation and computing, icac 2017

作者： Wan, Xiongbo Wang, Zidong Ren, Chuanyu School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Department of Computer Science Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom

ISBN: (纸本)9780701702618

This paper investigates the problem of H∞ state estimation for discrete-time stochastic genetic regulatory networks (GRNs) with switching parameters, time-varying delays, and exogenous disturbances. A new discrete-time stochastic GRN model with switching parameters is proposed by assuming that the sojourn probability of each subsystem of the GRN under consideration is known. By using the stochastic analysis approach, sufficient conditions are derived under which the augmented estimation error system is stochastically stable and satisfies a prescribed H∞ disturbance attenuation level γ. The gain matrices of the desired state estimator can be obtained by solving a matrix inequality. A numerical example is given to illustrate the effectiveness of the designed state estimator. © 2017 Chinese automation and computing Society in the UK - CACSUK.

关键词： State estimation

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Nonlinear dynamic predictive model selection and interference using information criteria 23

Nonlinear dynamic predictive model selection and interferenc...

引用

23rd ieee international conference on automation and computing, icac 2017

作者： Gu, Yuanlin Wei, Hua-Liang Balikhin, Michael A. Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9780701702618

Model selection is a crucial step in choosing a best model from a series of candidate models for data based modelling problems. The commonly used Akaike information criterion (AIC) and Bayesian information criteria (BIC) may not be effective for many real-world modelling problems when the true system model structure is unknown and therefore not included in the candidate model set. This study investigates the model selection issue using AIC, BIC and an adjustable prediction error sum of squares (APRESS) for nonlinear dynamic predictive modelling. Results from simulation and real data modelling case studies show that both BIC and APRESS produce good models for nonlinear modelling problems. The APRESS works slightly better than BIC in achieving a parsimonious representation of the studied system. In addition, a model averaging method is introduced, which is capable to provide an averaged model that is more robust in generalization (i.e. in representing future data) than any single model. © 2017 Chinese automation and computing Society in the UK - CACSUK.

关键词： automation

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Security analysis and enhancement of model compressed deep learning systems under adversarial attacks 18

Security analysis and enhancement of model compressed deep l...

引用

23rd Asia and South Pacific Design automation conference, ASP-DAC 2018

作者： Liu, Qi Liu, Tao Liu, Zihao Wang, Yanzhi Jin, Yier Wen, Wujie Florida International University United States Syracuse University United States University of Florida United States

ISBN: (纸本)9781509006021

Thanks to recent machine learning model innovation and computing hardware advancement, the state-of-the-art of Deep Neural Network (DNN) is presenting human-level performance for many complex intelligent tasks in real-world applications. However, it also introduces ever-increasing security concerns for those intelligent systems. For example, the emerging adversarial attacks indicate that even very small and often imperceptible adversarial input perturbations can easily mislead the cognitive function of deep learning systems (DLS). Existing DNN adversarial studies are narrowly performed on the ideal software-level DNN models with a focus on single uncertainty factor, i.e. input perturbations, however, the impact of DNN model reshaping on adversarial attacks, which is introduced by various hardware-favorable techniques such as hash-based weight compression during modern DNN hardware implementation, has never been discussed. In this work, we for the first time investigate the multi-factor adversarial attack problem in practical model optimized deep learning systems by jointly considering the DNN model-reshaping (e.g. HashNet based deep compression) and the input perturbations. We first augment adversarial example generating method dedicated to the compressed DNN models by incorporating the software-based approaches and mathematical modeled DNN reshaping. We then conduct a comprehensive robustness and vulnerability analysis of deep compressed DNN models under derived adversarial attacks. A defense technique named 'gradient inhibition' is further developed to ease the generating of adversarial examples thus to effectively mitigate adversarial attacks towards both software and hardware-oriented DNNs. Simulation results show that 'gradient inhibition' can decrease the average success rate of adversarial attacks from 87.99% to 4.77% (from 86.74% to 4.64%) on MNIST (CIFAR-10) benchmark with marginal accuracy degradation across various DNNs. © 2018 ieee.

关键词： Deep neural networks

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Design and implementation of interactive system for Tujia brocade virtual weaving based on kinect 23

Design and implementation of interactive system for Tujia br...

引用

23rd ieee international conference on automation and computing, icac 2017

作者： Gang, Zhao Bingbing, Di Wenjuan, Zhu Yali, Yu Hui, Zan School of Educational Information Technology Central China Normal University Wuhan430079 China National Engineering Research Center for E-Learning Central China Normal University Wuhan430079 China

ISBN: (纸本)9780701702618

Tujia brocade craft, as a kind of famous folk handcraft of Youshui watershed in China, cannot be contacted by the public personally except through pictures, text, videos due to its regional distribution and the closure inheritance way. So people are unable to get better understanding of the entity and the essence of Tujia brocade craft, which seriously hampered the development and inheritance of this folk treasure. To solve this problem, this paper develops interactive system for Tujia brocade virtual weaving based on Kinect combining the Tujia brocade protection with somatosensory interaction technology, which provides three main function modules, that is, tools display, traditional craft display and virtual weaving. It is expected that this system will help the public to identify and master the basic processes of Tujia brocade weaving. © 2017 Chinese automation and computing Society in the UK - CACSUK.

关键词： automation

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Container Live Migration for Latency Critical Industrial Applications on Edge computing

Container Live Migration for Latency Critical Industrial App...

引用

ieee international conference on Emerging Technologies and Factory automation

作者： Keerthana Govindaraj Alexander Artemenko Robert Bosch GmbH Renningen Corporate Sector Research and Advance Engineering Germany

A new level of factory automation demands processing vast amounts of data, complex orchestration of cyberphysical systems, and coordination of computation as well as communication resources in real-time. Virtualization and decentralized computation is becoming a de-facto solution for factory automation. Edge computing (EC) is a promising approach to achieve the low latencies required by many industrial systems. It employs resource rich edge servers distributed within a factory that are placed close to end devices and assist them in executing computation intensive tasks and also in coordinating with each other. This paper discusses the requirements and challenges of EC for factory automation applications. In a distributed EC infrastructure, safe and timely operation of industrial applications require load balancing and mobility support and thus a seamless service migration between the edge servers. With the recent advances in virtualization and due to its advantages, virtual machine (VM) and container technologies are pavings its way into factory. Though containers have some distinctive advantages over VMs in EC, the service live migration has comparatively high downtime. This paper proposes a novel live migration scheme called redundancy migration that reduces the downtime by a factor of 1.8 compared to the stock migration in linux containers.

关键词： Containers Factory automation Downtime Latency Stateful Migration

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A Survey of Internet of Things and Big Data Integrated Solutions for Industrie 4.0

A Survey of Internet of Things and Big Data Integrated Solut...

引用

ieee international conference on Emerging Technologies and Factory automation

作者： Khaled Al-Gumaei Kornelia Schuba Andrej Friesen Sascha Heymann Carsten Pieper Florian Pethig Sebastian Schriegel Fraunhofer IOSB-INA Lemgo Germany

The industrial internet of things (IIoT) is growing at an exponential rate generating massive amounts of industrial data. This data must be leveraged to support business and operational goals. As a result, there is an urgent need for adopting big data technologies to enable data analytics in industrial automation. This paper explores interrelations between IIoT and big data technologies and how they work together to generate business insights from industrial data. Additionally, requirements for cloud-based solutions are derived from the Industrie 4.0 use case scenario value-based-services, focusing on condition monitoring and predictive maintenance services. A survey of selected cloud-based platforms is conducted to examine how these platforms meet the requirements derived from the use case. Results show that existing general cloud platforms should adopt more IIoT applications and platforms, while existing industrial cloud platforms should add big data frameworks to their portfolio. Finally, an architecture for integrating cloud-based IIoT and big data solutions is introduced and issues regarding the use of public cloud for IIoT applications are discussed.

关键词： Big Data Cloud computing Internet of Things (IoT) Industrial IoT (IIoT) Industrie 4.0 Industrial automation

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conference committees

Conference committees

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international conference on automation and computing (icac)

Provides a listing of current committee members and society officers.

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Virtual Machine Placement for Hybrid Cloud using Constraint Programming 23

Virtual Machine Placement for Hybrid Cloud using Constraint ...

引用

23rd ieee international conference on Parallel and Distributed Systems (ICPADS)

作者： Coullon, Helene Le Louet, Guillaume Menaud, Jean-Marc IMT Atlantique Ascola INRIA LS2NDAPI Nantes France

ISBN: (纸本)9781538621295

Cloud computing is the widely spread paradigm of utility-computing that offers an "on-demand" internet-based access to configurable resources available within data centers. On one hand, public Cloud providers are well suited for highly available access to IT resources (infrastructure, platform and software), for sporadic use, or for elastic demands. On the other hand, private clouds could sometimes be preferred for security or privacy reasons, or for cost reasons due to a high frequency usage of services. However, in many cases a choice between public or private clouds does not fulfill all requirements of companies, and hybrid cloud infrastructures should be preferred. A hybrid cloud solution could, for example, answer sudden workload increase in private clouds, security or fault tolerance requirements, or even latency issues thanks to data-locality. Solutions have already been proposed to address hybrid cloud infrastructures, however most of the time the placement of a distributed software on such infrastructure has to be indicated manually. For this reason, the automation of software deployment on hybrid clouds is still under research. In this paper we propose new specific placement constraints and objectives adapted to hybrid clouds infrastructures within our placement solution, namely OptiPlace, and we address this problem through constraint programming. Furthermore, we evaluate the expressivity and performance of the proposed solution on a real case study.

关键词： Hybrid Cloud Virtual Machines Placement Constraint Programming

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