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A new B2B platform based on cloud computing

A new B2B platform based on cloud computing

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Xiong, Gang Hou, Jiachen Dong, Xisong Nyberg, Timo R. State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan 523808 China Jiang Su China Sciences Intelligent Engineering Co. Ltd. Enterprise Academician Workstation 215000 China BIT Research Centre Aalto University Finland

ISBN: (纸本)9781467324007

With the fast development of Internet and its data scale, B2B (Business to Business), whose speed and high availability advantage is based on Internet, is eroding more and more market share of traditional business. In recent years, the new data processing technologies, such as cloud computing, assure the enhancement of computer's computing capacity;it has become possible for researchers to process and analyze the massive business data, including large scale customer data, and large scale commodity information. A new B2B platform frame, based on cloud computing with less running time and better response efficiency, is proposed here to promote transaction handle efficiency. By adoption of complex network theory and cloud computing technology, the new platform has been evaluated to decrease transaction handle time, and make more benefits. © 2012 IEEE.

关键词： Complex networks

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Parallel matching-based estimation - a case study on three different hardware architectures

Parallel matching-based estimation - a case study on three d...

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IEEE Symposium on intelligent Vehicle

作者： Benjamin Ranft Timo Schoenwald Bernd Kitt Intelligent Systems and Production Engineering (ISPE) research division FZI Research Centre for Information Technology Germany Department of Measurement and Control Karlsruhe Institute of Technology Germany

Many advanced driver assistance systems (ADAS) and autonomous vehicles require 3D information available from (stereo) camera systems. The corresponding task of estimating disparity or optical flow is computationally demanding, so meeting real-time update rates at high image resolutions has proven to be challenging. Modern parallel hardware seems suitable for this task only if its processing power can be efficiently accessed by parallel software implementations. In this paper we present a case study comparing different hardware platforms by two variants of block matching-based estimation. These platforms include two x86-compatible multicore systems, a graphics processing unit (GPU) and a 64-core embedded design. We introduce relevant features of each architecture and describe their effects on the applied algorithms, parallelization approaches and implementations. Target platforms are evaluated concerning computational performance, energy efficiency and programmer productivity.

关键词： Graphics processing unit Instruction sets Pixel Hardware Cameras Optical imaging Estimation

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An Ontological Study of Data Purpose for Privacy Policy Enforcement

An Ontological Study of Data Purpose for Privacy Policy Enfo...

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IEEE International Conference on and IEEE International Confernece on Social Computing (SocialCom) Privacy, Security, Risk and Trust (PASSAT)

作者： Shan Chen Mary-Anne Williams Innovation and Enterprise Research Laboratory Centre of Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney Australia

Data purpose is a central concept in modeling privacy requirements. Existing purpose-based approaches for privacy protection have mainly focused on access control. The problem of ensuring the consistency between data purpose and data usage has been under-addressed. In an attempt to bridge this research gap, we develop a grounded understanding of data purpose and relevant key concepts that is fundamental to address the problem. We propose a Minimum Action Permission Principle as a basic guideline to establish a path to solutions to the consistency problem for privacy management.

关键词： Privacy Data privacy Licenses Vehicles Equations Access control Data models

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Boundary control of a flexible marine riser with vessel dynamics

Boundary control of a flexible marine riser with vessel dyna...

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作者： He, Wei Voon Ee How, Bernard Ge, Shuzhi Sam Choo, Yoo Sang Department of Electrical and Computer Engineering Centre for Offshore Research and Engineering National University of Singapore Singapore 117576 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Institute of Intelligent Systems and Information Technology University of Electronic Science and Technology of China Chengdu 610054 China Department of Civil Engineering Centre for Offshore Research and Engineering National University of Singapore Singapore 117576 Singapore

ISBN: (纸本)9781424474264

In this paper, boundary control of a flexible marine riser with vessel dynamics is developed to reduce the riser's vibrations. To provide an accurate and concise representation of the riser's dynamic behavior, the distributed parameter model of the flexible marine riser with vessel dynamics is described by a partial differential equation (PDE) coupled with ordinary differential equations (ODEs) involving functions of space and time. Boundary control is developed at the top boundary of the riser based on Lyapunov's direct method to regulate the riser's vibrations. With the proposed boundary control, uniform boundedness is achieved. The boundary control is implementable with actual instrumentation since all the signals in the control can be measured by sensors or calculated by a backwards difference algorithm. Simulations are provided to illustrate the effectiveness of the proposed control. © 2010 AACC.

关键词： Dynamics

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Mobile manipulator tracking control based on observer design

Mobile manipulator tracking control based on observer design

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World Congress on intelligent control and Automation (WCICA)

作者： Yuwei Ren Hong Wang Institute of automation Chinese Academy and Sciences China Research Center of Automation Northeastern University Shenyang China The Control Systems Centre School of Electricaland Electronic Engineering University of Manchester Institute of Science and Technology UK

This paper studies the tracking control problem of mobile manipulators based on state observer. The proposed tracking controller ensures that the full state of the system can asymptotically track the given desired trajectory globally in the presence of the system coupling. Extensive simulations presented in the paper show the effectiveness of the proposed approach.

关键词： Observers Manipulators Automation Mobile communication Couplings Trajectory

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Kinematic control of a redundant manipulator using inverse-forward adaptive scheme

Kinematic control of a redundant manipulator using inverse-f...

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IET Irish Signals and systems Conference (ISSC 2009)

作者： Swagat Kumar Laxmidhar Behera Martin McGinnity Department of Electrical Engineering Indian Institute of Technology Kanpur India Intelligent Systems Research Centre University of Ulster UK

The inverse kinematic (IK) relationship of a manipulator is a one-to-many map which can not be learnt using a feed-forward neural network (FFN). The usual method is to learn the forward kinematic relationship using a FFN and then obtaining the IK solution through inversion of the approximate forward model. The accuracy of the inverse kinematic solution thus obtained is limited by the accuracy of the forward model. However, it is not possible to learn the forward kinematic map accurately even with a large network size and a large training data set. Moreover, one needs to resolve redundancy while solving IK in order to make use of available dexterity effectively. These limitations of a conventional network inversion-based scheme are overcome by using an inverse-forward adaptive scheme where the idea is to learn a local solution around the current joint angle configuration rather than trying to learn the global solution through an accurate forward model. It is shown that the accuracy of the IK solution thus obtained, is almost independent of the accuracy of the forward model. The redundancy is resolved by using a KSOM-SC network architecture as a hint generator for initializing the inverse-forward adaptive scheme. The efficacy of the proposed scheme is demonstrated through simulations and real-time experiment on a 7 DOF PowerCube manipulator. A simple obstacle avoidance task is performed to demonstrate the redundancy resolution process.

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Reinforcement _recurrent fuzzy rule based system based on brain emotional learning structure to predict the complexity dynamic system

Reinforcement _recurrent fuzzy rule based system based on br...

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International Conference on Digital Information Management (ICDIM)

作者： Mahboobeh Parsapoor Caro Lucas Saeid Setayeshi Islamic Azad University Science and Research Tehran Iran Centre Of Excellence control and intelligent processing ECE facultyCollege of engineering University of Tehran Iran Department of Physics and Nuclear Science Amirkabir University of Technology Tehran Iran

In this study, new approach based on brain emotional Learning process is presented to predict chaotic system more accurate than other learning models. So the main scope of this paper is to reveal the advantages of this learning model that imitate the internal representation of brain emotional learning model to provide a correct response to stimuli to state a purposeful predicting system. The convergence theory is clarified by utilizing the model to predict the complex dynamical Lorenz system. Also the consequence of using this method to forecast such a complex system is compared with obtained results from other related studies that examine other methods such as Locally Linear Model Tree(LOLIMOT) and radial basis function (RBF) Neural network with Orthogonal lest square (OLS ) for predicting the Lorenz chaotic time series. The comparison indicates the superior performance of presented method to make the multi step ahead prediction. Also the effect of noise on the performance of the techniques is also considered. In deed, the learning methods could deal with predicting the future state of complex system with limited training data as well as large data set.

关键词： Fuzzy systems Knowledge based systems Predictive models Brain modeling Chaos Learning systems Biological neural networks Training data Fuzzy sets Process control

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Robust adaptive control of valve mechanism with unknown backlash nonlinearity

Robust adaptive control of valve mechanism with unknown back...

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2007 IEEE 22nd International Symposium on intelligent control, ISIC 2007

作者： Zhou, Jing Er, Meng Joo Department of Engineering Cybernetics Faculty of Information Technology Mathematics and Electrical Engineering Norwegian University of Science and Technology 7491 Trondheim Norway Intelligent Systems Centre Nanyang Technological University Research TechnoPlaza Singapore 637553 Singapore

ISBN: (纸本)142440441X

In this paper, two robust adaptive backstepping control algorithms are developed for valve control mechanism of a liquid tank. Unlike some existing control schemes for systems with backlash, the developed backstepping controllers do not require the uncertain parameters within known intervals. Also no knowledge is assumed on the bound of the 'disturbance-like' term, a combination of the external disturbances and a term separated from the hysteresis model. It is shown that the proposed controllers not only can guarantee global stability, but also transient performance. © 2007 IEEE.

关键词： Uncertain systems

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Stereo Vision based Relative Pose and Motion Estimation for Unmanned Helicopter Landing

Stereo Vision based Relative Pose and Motion Estimation for ...

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International Conference on Information and Automation (ICIA)

作者： Cui Xu Liankui Qiu Ming Liu Bin Kong Yunjian Ge Department of Automation University of Science and Technology Hefei Anhui China Center for Biomimetic Sensing and Control Research Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China Department of Electrical and Computer Systems Engineering Monash University Melbourne VIC Australia

In this paper, we present a real-time stereo vision based pose and motion estimation system that will be used for landing an unmanned helicopter on a moving target such as a ship deck. The vision algorithm mainly consists of a feature extraction task and a pose and motion estimation task. The 2D planer target with regular features defined can significantly simplify the feature extraction task such as corner detection and feature points matching. To effectively estimate the distance between the camera carrier and target a stereo camera system is applied. By means of sub-pixel corner location the precisions of pose estimation and relative motion detection can be improved. We present results from semi-physical simulation which show that our vision algorithm is accurate and robust. The methodology provides an effective subsystem for the development of autonomous robot helicopter that will land on a given target under the guide of vision.

关键词： Stereo vision Motion estimation Helicopters Feature extraction Cameras Robot vision systems Real time systems Marine vehicles Metalworking machines Computer vision

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Optimal design of alloy steels using evolutionary computing 4

Optimal design of alloy steels using evolutionary computing

引用

4th International Conference on Knowledge-Based intelligent engineering systems and Allied Technologies, KES 2000

作者： Mahfouf, M. Tenner, J. Linkens, D.A. Abbod, M.F. Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldSI 3JD United Kingdom Corus Research Development and Technology Swinden Technology Centre Moorgate Rotherham United Kingdom

ISBN: (纸本)0780364007

Over the last four years efforts have been devoted towards the development and validation of mechanical test result models relating to a range of alloy steels. Several neural-network based models have been developed, two of which are related to the mechanical test results of Ultimate Tensile Strength (UTS) and Reduction of Area (ROA). The ultimate aim of developing these models is to pave the way to process optimisation through better predictions of mechanical properties. In this research we propose to exploit such neural network models in order to determine the optimal alloy composition and heat treatment temperatures required, given certain predefined mechanical properties such as the UTS and ROA. Genetic Algorithms are used for this purpose. The results obtained are very encouraging. © 2000 IEEE

关键词： Alloy steel

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