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Smart Innovation, systems and Technologies 2010年 4卷 143-152页

作者： Zhang, Ruijun Wei, Jizhong Lu, Jie Zhang, Guangquan School of Management Wuhan University of Science and Technology Wuhan China Decision Systems and E-Service Intelligence research Research laboratoryLaboratory Centre for Quantum Computing and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney POBOX 123 Broadway NSW2007 Australia

In iron and steel enterprises, it is difficult to obtain the lowest-cost optimal solution to an ore blending problem for blast furnaces by using the traditional trial-fault-trial (TFT) method because of the complexity of materials and burden of workflow. Here, we develop a set of decision support systems (DSS) software to solve the problem. Using the basics of analyzing business flow and the working process of ore blending, we pre-process the data for materials and elements, abstract a non-linear model of ore blending for a blast furnace, design the architecture for ore blending cost optimization DSS which integrates a database, a model base and a knowledge base, and solve the problem. The system has made economic gains since it was implemented in Xiangtan Iron & Steel Group Co. Ltd., China, in September 2008. © Springer-Verlag Berlin Heidelberg 2010.

关键词： Blast furnaces

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High sensitivity initial slip sensor for dexterous grasp

High sensitivity initial slip sensor for dexterous grasp

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Seiichi Teshigawara Kenjiro Tadakuma Aiguo Ming Masatoshi Ishikawa Makoto Shimojo Mechanical Engineering and Intelligent Systems University of Electro-Communications Chofu Tokyo Japan Department of Mechanical Engineering Graduate School of Engineering Osaka University Suita Osaka Japan Department of Information Physics and Computing Graduate School of Information Science and Technology University of Tokyo Bunkyo Tokyo Japan

Slip-detecting tactile sensors are essential for achieving human-like gripping motion with a robot hand. In previous research, we developed a flexible, thin and lightweight slip sensor that exploits the characteristics of pressure conductive rubber. However, using this sensor, it was difficult to distinguish between object slip and a change in the normal force. Therefore, in the present research, we investigated a method for identifying object slip by analyzing the frequency components of the output signal from the sensor. As a result, we found that high-frequency components of 1 kHz or more are included in the complex voltage signal generated by object slip. Therefore, by using this high-frequency component, we developed a simple sensor that distinguished between both contact and initial slip with high sensitivity.

关键词： Sensor phenomena and characterization Tactile sensors Robot sensing systems Humanoid robots Rubber Force sensors Signal analysis Frequency Signal processing Voltage

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Adaptive Inference-based Learning and Rule Generation Algorithms in Fuzzy Neural Network for Failure Prediction

Adaptive Inference-based Learning and Rule Generation Algori...

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The 2010 International Conference on intelligent systems and Knowledge engineering(第五届智能系统与知识工程国际会议)

作者： Vahid Behbood Jie lu Guangquan Zhang Decision Systems & E-Service Intelligence Research Laboratory Center for Quantum Computing and Intelligent System School of Software Faculty of Engineering and Information Technology University of Technology Sydney Sydney POBOX123 Broadway NSW2007 Australia

Creating an applicable and precise failure prediction system is highly desirable for decision makers and regulators in the finance industry. This study develops a new Failure Prediction (FP) approach which effectively integrates a fuzzy logic-based adaptive inference system with the learning ability of a neural network to generate knowledge in the form of a fuzzy rule base. This FP approach uses a preprocessing phase to deal with the imbalanced data-sets problem and develops a new Fuzzy Neural Network (FNN) including an adaptive inference system in the learning algorithm along with its network structure and rule generation algorithm as a means to reduce prediction error in the FP approach.

关键词： Accuracy Inference algorithms Fuzzy neural networks Prediction algorithms Pragmatics Artificial neural networks Clustering algorithms

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A secure and improved self-embedding algorithm to combat digital document forgery

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SIGNAL PROCESSING 2009年第12期89卷 2324-2332页

作者： Cheddad, Abbas Condell, Joan Curran, Kevin Mc Kevitt, Paul [a]School of Computing and Intelligent Systems Faculty of Computing and Engineering University of Ulster at Magee BT48 7JL Northern Ireland UK

The recent digital revolution has facilitated communication, data portability and on-the-fly manipulation. Unfortunately, this has brought along some critical security vulnerabilities that put digital documents at risk. The problem is in the security mechanism adopted to secure these documents by means of encrypted passwords;however, this security shield does not actually protect the documents which are stored intact. We propose here a solution to this real world problem through a ID hash algorithm coupled with 2D iFFT (irreversible Fast Fourier Transform) to encrypt digital documents in the 2D spatial domain. Further by applying an imperceptible information hiding technique we can add another security layer which is resistant to noise and to a certain extent JPEG compression. We support this assertion by showing a practical example which is drawn from our set of experiments. This work exploits Jarvis' kernel to generate the error diffusion signal and the Wavelet-based Inverse Halftoning via De-convolution (WInHD) to recover the approximation of the original signal. Our method not only points out forgery but also allows legal or forensics expert gain access to the original document despite being manipulated. This would undoubtedly be very useful in cases of disputes or claims. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Image processing Steganography Information hiding Self-embedding Encryption Document forgery Security

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Improving Student Engagement and Retention Through Small Group Tutorials

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Innovation in Teaching and Learning in Information and Computer Sciences 2010年第1期9卷

作者： Anthony McCourt Dr. Caitriona Carr School of Computing and Intelligent Systems Faculty of Computing and Engineering University of Ulster Magee a.mccourt@ulster.ac.uk School of Computing and Intelligent Systems Faculty of Computing and Engineering University of Ulster Magee c.carr@ulster.ac.uk

For some time now retention has become a major issue in terms of the number of students failing to progress or dropping out from their studies. In addition to this lecturers are also concerned at the lack of student engagement they experience in the classes. This is particularly evident among first year students and, consequently, has a knock on effect for subsequent years. Staff at the school of computing and intelligent systems (SCIS) in University of Ulster have addressed this issue by the implementation of small group tutorials for first year students studying computer science, computer games and electronics engineering. Students exhibited a willingness to participate and were appreciative of the individual attention they received. The results show that these small group tutorials are an effective teaching tool, as its use can enhance student engagement by increasing their participation in class, give lecturers valuable feedback on student understanding, make the classroom more ‘enjoyable’ while re-enforcing learning.

关键词： Retention Small group tutorials Student drop-out rates Student engagement and Participation

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Multi-objective optimization conceptual design of solar energy product based on hybrid genetic algorithm

Multi-objective optimization conceptual design of solar ener...

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International Conference on Computer Design and Applications (ICCDA)

作者： Tingting Zhao Zhenhe Ju Xiaopeng Wei Shi Zhang Shuaijie Wang Xiaoxiao Li School of Management Dalian University of Technology Dalian China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China New Energy Center Shenyang Institute of Engineering Shenyang China Institute of Systems Engineering College of Information Science and Engineering Northeastern University Shenyang China Department of study Liaoning Solar Energy R and D Company Limited Shenyang China

ISBN: (纸本)9781424471645;9781424471638

For research on conceptual design of the complex product, it is necessary that a reliable theory is found to decide if the design structure is suit for custom requirement. The correlation matrixes among requirements, functions and structures are proposed. A block diagonal matrix of correlation matrix between functions and structures is given. The mathematical models of multi-object optimization structure design are provided, and then calculated by the hybrid genetic algorithm. An example for solar energy automobile is given to show that this method is able to realize optimization structure design fitting for the requirements. In addition, the approaches can provide good Pareto optimization solutions.

关键词： Design optimization Algorithm design and analysis Solar energy Genetic algorithms Genetic engineering Design engineering Power engineering and energy Mathematics Pareto optimization Reliability engineering

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computing with Biologically Inspired Neural Oscillators: Application to Colour Image Segmentation

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Advances in Artificial Intelligence 2010年第1期2010卷

作者： Ammar Belatreche Liam Maguire Martin McGinnity Liam McDaid Arfan Ghani Intelligent Systems Research Centre School of Computing and Intelligent Systems Faculty of Computing Engineering University of Ulster Magee Campus Northland Road Northern Ireland Derry BT48 7JL UKulster.ac.uk

This paper investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to grey scale and colour image segmentation, an important task in image understanding and object recognition. A proposed neural system that exploits the synergy between neural oscillators and Kohonen self-organising maps (SOMs) is presented. It consists of a two-dimensional grid of neural oscillators which are locally connected through excitatory connections and globally connected to a common inhibitor. Each neuron is mapped to a pixel of the input image and existing objects, represented by homogenous areas, are temporally segmented through synchronisation of the activity of neural oscillators that are mapped to pixels of the same object. Self-organising maps form the basis of a colour reduction system whose output is fed to a 2D grid of neural oscillators for temporal correlation-based object segmentation. Both chromatic and local spatial features are used. The system is simulated in Matlab and its demonstration on real world colour images shows promising results and the emergence of a new bioinspired approach for colour image segmentation. The paper concludes with a discussion of the performance of the proposed system and its comparison with traditional image segmentation approaches.

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A T-S fuzzy based adaptive critic for continuous-time input affine nonlinear systems

A T-S fuzzy based adaptive critic for continuous-time input ...

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2009 IEEE International Conference on systems, Man and Cybernetics, SMC 2009

作者： Prem, Kumar P. Behera, Laxmidhar Siddique, Nazmul H. Prasad, Girijesh Department of Electrical Engineering Indian Institute of Technology Kanpur Kanpur India School of Computing and Intelligent Systems University of Ulster United Kingdom

ISBN: (纸本)9781424427949

This paper proposes a novel scheme of a Takagi-Sugeno (T-S) fuzzy based adaptive critic for the optimal control of the continuous-time input affine nonlinear system. A novel learning strategy is proposed to update the weights of critic network which resolves the issue of under-determined weight update equations discussed in [1]. The T-S Fuzzy based critic network approximates the global optimal cost as fuzzy average of local costs associated with local linear subsystems. This work clearly demonstrates that the optimal cost of a nonlinear system can be represented as the fuzzy cluster of optimal costs of locally valid linear models in a T-S framework. The proposed scheme has been simulated for four different dynamic systems. Simulation results clearly demonstrate that the T-S Fuzzy approximates the optimal cost, with subsystems in each fuzzy zone represents the optimal cost of locally valid linear model. ©2009 IEEE.

关键词： Nonlinear systems

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Adaptive critic based redundancy resolution scheme for robot manipulators

Adaptive critic based redundancy resolution scheme for robot...

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2009 IEEE International Conference on systems, Man and Cybernetics, SMC 2009

作者： Prem, Kumar P. Behera, Laxmidhar Prasad, Girijesh Department of Electrical Engineering Indian Institute of Technology Kanpur Kanpur India School of Computing and Intelligent Systems University of Ulster United Kingdom

ISBN: (纸本)9781424427949

A novel adaptive critic based kinematic control scheme for a redundant manipulator has been proposed in this paper. The redundancy resolution has been formulated as a discrete-time optimal control problem. A Takagi-Sugeno (T-S) fuzzy based critic network is proposed to predict the global costate dynamics as fuzzy average of local costate dynamics. The integral cost function is used in the literature earlier, to achieve global optimum in contrast to instantaneous cost functions which gives local optimum. But both the approaches require the computation of pseudo-inverse which is computationally complex and suffers from numerical instability. In contrast, the proposed scheme does not require computation of pseudo-inverse of the Jacobian which makes the method computationally efficient. The proposed scheme is tested on 7 degree of freedom (7DOF) PowerCube manipulator from Amtec Robotics. ©2009 IEEE.

关键词： Cost functions

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MemoryLane: Reminiscence for older adults

MemoryLane: Reminiscence for older adults

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1st International Workshop on Reminiscence systems, RSW 2009

作者： McCarthy, Sheila Sayers, Heather McKevitt, Paul McTear, Mike Intelligent Systems Research Centre School of Computing and Intelligent Systems University of Ulster Magee BT48 7JL Derry Londonderry United Kingdom Faculty of Computing and Engineering Department School of Computing and Mathematics University of Ulster Jordanstown BT48 7JL Newtownabbey United Kingdom

Reminiscence plays an important role in the lives of older adults [8]. Many perfect the art of storytelling and enjoy its social benefits. The telling of stories of past events and experiences defines family identities and is an integral part of most cultures. Losing the ability to recollect past memories is not only disadvantageous, but can prove quite detrimental, especially to many older adults. In this paper we introduce MemoryLane, a Personal Digital Assistant (PDA) based application being developed to enhance the reminiscence capabilities of older adults. Using abilities and preferences as a basis, MemoryLane employs Artificial Intelligence (AI) techniques to adapt its multimodal interface to accommodate the needs of differing older users and to compose and recount user life-cached multimedia as memory stories. Copyright 2009 ACM.

关键词： Personal digital assistants

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