School of Advanced Technology

School of Advanced Technology
Xi'an Jiaotong-Liverpool University
111 Ren'ai Road Suzhou Dushu Lake Science and Education Innovation District , Suzhou Industrial Park
Suzhou,Jiangsu Province,P. R. China,215123
1. Solution framework for open communication with Self-Modifying Protocols

Author:Guan,Sheng Uei;Jiang,Zhiqiang;Yao,Wenbing

Source:International Journal of Applied Systemic Studies,2007,Vol.1

Abstract:A Self-Modifying Protocol (SMP) is a set of instructions, rules, or conventions that can be changed by the systems that communicate with the help of that protocol. This concept is expected to be of great importance for the next generation of intelligent distributed systems. At this time, the idea is still difficult to be captured into working computer code. In this paper, Self-Modifying Automata (SMA) is adopted for the description and design of such protocols. We illustrate the idea of using SMA for protocol design through some solid examples. A solution framework is suggested for incorporating SMPs. One self-regulating and self-modifying communication mechanism is presented for implementing SMPs. In addition, real-time on-the-fly data-driven code is proposed to implement the prototypes of these ‘autonomous protocols’. © 2007 Inderscience Enterprises Ltd.
2. Cogbroker - A cognitive approach to intelligent product brokering for e-commerce

Author:Guan,Sheng Uei;Tan,Wen Pin;Liu,Fei

Source:International Journal of Computational Intelligence and Applications,2008,Vol.7

Abstract:Researchers have proposed intelligent product-brokering applications to help facilitate the m-commerce shopping process. However, most algorithms require explicit, user-provided feedback to learn about user preference. In practical applications, users may not be motivated to provide unrewarded and time-consuming feedback. By adopting a cognitive approach, this paper investigates the possibility of replacing user feedback with user behavioral data analysis during product browsing. By means of evolutionary algorithms, the system is able to derive corresponding models that simulate the user's shopping behavior. User group profiling is also implemented to help identify the user's shopping patterns. Upon simulations of trial cases with consistent and rational shopping patterns, our experimental results confirm this approach being promising. The system shows high accuracy in detecting the preferences of the user. The algorithms are also portable and effective across different products. © Imperial College Press.
3. Classification Of Cerebral Palsy Gait By Kernel Fisher Discriminant Analysis

Author:Bai-ling Zhang;Yanchun Zhang

Source:International journal of hybrid intelligent systems,2008,Vol.

Abstract:Cerebral palsy (CP) is generally considered as a non-progressive neuro-developmental condition that occurs in early childhood and is associated with a motor impairment, usually affecting mobility and posture. Automatic accurate identification of cerebral palsy gait has many potential applications, for example, assistance in diagnosis, clinical decision-making and communication among the clinical professionals. In previous studies, support vector machine (SVM) and some other pattern classification methods like neural networks have been applied to classify CP gait patterns. The objective of this study is to first further investigate different classification paradigms in the CP gait analysis, particularly the Kernel Fisher Discriminant Analysis (KFD) which has been successfully applied to many pattern recognition problems and identified as a strong competitor of SVM. The component obtained by KFD maximally separates two classes in the feature space, thus overcoming the limitations of linear discriminant analysis of being unable to extract nonlinear features representing higher-order statistics. Using a publicly available CP gait dataset (68 normal healthy and 88 with spastic diplegia form of CP), a comprehensive performances comparison was presented with different features including the two basic temporal-spatial gait parameters (stride length and cadence). Various cross-validation testing show that the KFD offers better classification accuracies than the support vector machine and is superior to a number of other classification methods such as decision tree, multiple layer perceptron and k nearest neighbor.
4. An image indexing and searching system based both on keyword and content

Author:Zhang, N;Song, Y


Abstract:Content-based image retrieval (CBIR) has certain advantages over those pure keyword-based. CBIR indexes images by visual features that are extracted from the images. This may save the effort spent on the manual annotation. However, because low-level visual features, such as colour and texture, often carry no high-level concepts, images retrieved purely based on content may not match with the intention of the user. The work presented in this paper is an image retrieval system that bases both on text annotations and visual contents. It indexes and retrieves images by both keywords and visual features, with the purpose that the keywords may mend the gap between the semantic meaning an image carries and its visual content. Tests were made on the system that have demonstrated that such a hybrid approach did improve retrieval precisions over those pure content-based.
5. Real-time modeling of 3-D soccer ball trajectories from multiple fixed cameras

Author:Ren, J;Orwell, J;Jones, GA;Xu, M


Abstract:In this paper, model-based approaches for real-time 3-D soccer ball tracking are proposed, using image sequences from multiple fixed cameras as input. The main challenges include filtering false alarms, tracking through missing observations, and estimating 3-D positions from single or multiple cameras. The key innovations are: 1) incorporating motion cues and temporal hysteresis thresholding in ball detection; 2) modeling each ball trajectory as curve segments in successive virtual vertical planes so that the 3-D position of the ball can be determined from a single camera view; and 4) introducing four motion phases (rolling, flying, in possession, and out of play) and employing phase-specific models to estimate ball trajectories which enables high-level semantics applied in low-level tracking. In addition, unreliable or missing ball observations are recovered using spatio-temporal constraints and temporal filtering. The system accuracy and robustness are evaluated by comparing the estimated ball positions and phases with manual ground-truth data of real soccer sequences.
6. TADL - An architecture description language for trustworthy component-based systems


Source:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),2008,Vol.5292 LNCS

Abstract:Existing architecture description languages mainly support the specification of the structural elements of the system under design with either only a limited support or no support to specify non-functional requirements. In a component-based development of trustworthy systems, the trustworthiness properties must be specified at the architectural level. Analysis techniques should be available to verify the trustworthiness properties early at design time. Towards this goal we present in this paper a meta-architecture and TADL, a new architecture description language suited for describing the architecture of trustworthy component-based systems. The TADL is a uniform language for specifying the structural, functional, and nonfunctional requirements of component-based systems. It also provides a uniform source for analyzing the different trustworthiness properties. © 2008 Springer-Verlag Berlin Heidelberg.
7. Population Diversity of Particle Swarms

Author:Shi, YH;Eberhart, RC


Abstract:In the field of evolutionary computation, an important attribute of a population is diversity. This paper proposes a method for measuring the diversity of a particle swarm optimization population. It involves the measurement of position and velocity attributes of the particles that comprise the population. The proposed method is computationally straightforward and is adaptable to other evolutionary algorithms.
8. MidSens'09 - International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks, Co-located with the 10th ACM/IFIP/USENIX International Middleware Conference Preface

Author:Michiels, Sam ; Hughes, Danny

Source:MidSens'09 - International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks, Co-located with the 10th ACM/IFIP/USENIX International Middleware Conference,2009,Vol.

9. Classified Vector Quantisation and population decoding for pattern recognition

Author:Bailing Zhang;Sheng-Uei Guan

Source:International journal of artificial intelligence and soft computing: IJAISC,2009,Vol.

Abstract:Learning Vector Quantisation (LVQ) is a method of applying the Vector Quantisation (VQ) to generate references for Nearest Neighbour (NN) classification. Though successful in many occasions, LVQ suffers from several shortcomings, especially the reference vectors are prone to diverge. In this paper, we propose a Classified Vector Quantisation (CVQ) to establish VQ for classification. By CVQ, each data category is represented by its own codebook, which can be implemented by some learning algorithms. In classification process, each codebook offers a generalised NN. The examples of handwritten digit recognition and offline signature verification are used to demonstrate the efficiency of the proposed scheme.
10. An integrated crystal plasticity fe system for microforming simulation

Author:Cao,J.;Zhuang,W.;Wang,S.;Ho,K. C.;Zhang,N.;Lin,J.;Dean,T. A.

Source:Journal of Multiscale Modeling,2009,Vol.1

Abstract:Based on Voronoi tessellation and the probability theory, a VGRAIN system is created for the generation of grains and grain boundaries for micromaterials. This system requires physical parameters obtained from microstructures of materials, such as the average, minimum and maximum grain sizes. Numerical procedures have been established to link the physical parameters of a material to the control variable in a gamma distribution equation and a method has been developed to solve the probability equation. These are the basis for the development of the VGRAIN system, which can be used to generate different grain structures and shapes that follow a certain pattern according to the probability theory. Statistical analyses have been carried out to investigate the distribution of generated virtual grains. The generated virtual microstructure is then implemented in the commercial FE code, ABAQUS, for mesh generation and micromechanics analysis using crystal plasticity (CP) equations for face-centered cubic (FCC) materials, which are implemented in the commercial FE solver, ABAQUS, through the user-defined subroutines, VUMAT/UMAT. FE analyses have been carried out to demonstrate the effectiveness of the integrated system for the investigation of localized straining and necking, encountered in microforming processes, such as extrusion of micropins, deformation of microfilms and hydroforming of microtubes. © 2009 Imperial College Press.
11. Learning kernel subspace classifier for robust face recognition

Author:Zhang,Bailing;Guan,Sheng Uei;Ko,Hanseok

Source:International Journal of Soft Computing,2009,Vol.4

Abstract:Subspace classifiers are very important in pattern recognition in which pattern classes are described in terms of linear subspaces spanned by their respective basis vectors. To overcome the limitations of linear methods, kernel based subspace models have been proposed in the past by applying the Kernel Principal Component Analysis (KPCA). However, the projection variance in the kernel space as applied in the previously proposed kernel subspace methods, is not a good criteria for the data representation and they simply fail in many recognition problems. We address this issue by proposing a learning kernel subspace classifier which attempts to reconstruct data in the input space through the kernel subspace projection. Comparing with the pre-image methods, we emphasize the problem of how to use a kernel subspace as a model to describe input space rather than finding an approximate pre-image for each input by minimization of the reconstruction error in the kernel space. Experimental results on occluded face recognition demonstrated the efficiency of the proposed method. © Medwell Journals, 2009.
12. Gait classification in children with cerebral palsy by Bayesian approach

Author:Zhang, Bai-ling ; Zhang, Yanchun ; Begg, Rezaul K.

Source:Pattern Recognition,2009,Vol.42

Abstract:Cerebral palsy (CP) is a non-progressive neuro-developmental condition that occurs in early childhood and is associated with a motor impairment, usually affecting mobility and posture. Automatic accurate identification of CP gait has many potential applications, for example, assistance in diagnosis, clinical decision-making and communication among the clinical professionals. In previous studies, support vector machine (SVM) and neural networks have been applied to classify CP gait patterns. However, one of the disadvantages of SVM and many neural network models is that given a gait sample, it only predicts a gait pattern class label without providing any estimate of the underlying probability, which is particularly important in computer aided diagnostics applications. The objective of this study is to first investigate different pattern classification paradigms in the automatic gait analysis and address the significance of Bayesian classifier model, and then give a comprehensive performances comparison. Bayesian classification is based on Bayes' decision theory, which compute the probability of a given data point belonging to a class. Then among all classes, we choose the one that has the largest probability, and classify the data point as being of that class. Using a publicly available CP gait data set (68 normal healthy and 88 with spastic diplegia form of CP), different features including the two basic temporal-spatial gait parameters (stride length and cadence) have been experimented. Various hold-out and cross-validation testing show that the Bayesian model offers excellent classification performances compared with some popular classifiers such as random forest and multiple layer perceptron. With many advantages considered, Bayesian classifier model is very significant in establishing a clinical decision system for gait analysis. © 2008 Elsevier Ltd. All rights reserved.
13. Automatic Differentiation Applied to Economics

Author:Tadjouddine, EM


Abstract:This paper discusses the use of the Automatic Differentiation approach in evaluating derivatives of functions represented by computer programs. We then considered a Cournot oligopoly modeled by a system of stochastic differential equations. The setting is that of a set of self-interested firms striving to adjust their productions in the direction of higher profits subject to mistakes or random shocks. The stochastic differential equations are solved by a numerical method and the profits are calculated using a Monte Carlo simulation. Then, Automatic Differentiation is used to propagate sensitivities along each path in an automated fashion. Numerical results have confirmed the intuition one may have that noisy environments can lead to important profit differences between firms as well as higher sensitivities as opposed to less noisy ones.
14. High-k dielectrics' radiation response to X-ray and gamma-ray exposure

Author:Zhao,C. Z.;Wemer,M.;Taylor,S.;Chalker,P. R.;Potter,R. J.;Gaskell,J.

Source:Proceedings of the International Symposium on the Physical and Failure Analysis of Integrated Circuits, IPFA,2009,Vol.

Abstract:Radiation-induced degradation of HfO 2, ZrO 2' LaAIO 3, and NdAIO 3 thin films was studied and compared based on a Fe 55 X-ray source and Cs 137137 γ-ray source . After the X-ray exposure of a total dose of lOOkrad, negative VFB shifts were observed in these thin films, whereas after the γ-ray exposures of the same dose, positive VFB shifts was observed. ©2009 IEEE.
15. A technique for blood detection in wireless capsule endoscopy images

Author:Penna, Barbara ; Tillo, Tammam ; Grangetto, Marco ; Magli, Enrico ; Olmo, Gabriella

Source:European Signal Processing Conference,2009,Vol.

Abstract:Wireless capsule endoscopy is an innovative technology for visualizing anomalies in the gastrointestinal tract, useful to replace traditional endoscopic diagnosis. Its advantages are related to the capability to reach the duodenum and small intestine, while eliminating the discomfort of patients. The time spent by a physician analyzing the results of wireless capsule endoscopy video can vary between 45 and 180 minutes, limiting its widespread diffusion. Therefore, methods able to perform an automatic pre-screening of images of interest are necessary. This paper presents an innovative technique to detect bleeding regions in wireless capsule en-doscopy video. Experimental results show that the proposed algorithm exhibits a low false alarm rate, and is effective at reducing the time needed to analyze video sequences. © EURASIP, 2009.
16. Randomness quality of permuted pseudorandom binary sequences

Author:Tan, SK;Guan, SU


Abstract:This paper uses the DIEHARD statistical test suite to test the randomness quality of "permuted" versions of maximum length sequences generated by linear finite state machines (LFSM) such as cellular automata and linear feedback shift registers. Analysis shows that permuted sequences can be equivalently generated by using time-varying transformations derived from the original LFSM. Based on the above, we suggest the permuted transformation sequence scheme. Experimental results show that DIEHARD results are improved with respect to the original non-permuted sequences-up to seven more tests can be passed (total of 19 tests). Furthermore, a permutation vector is used to generate cyclically distinct permuted sequences and each sequence has a desirable maximum length period of 2(n) - 1. (C) 2008 IMACS. Published by Elsevier B.V. All rights reserved.
17. Hybrid Wyner-Ziv Video Coding Structure for Removing Feedback Channel

Author:Lee, H;Tillo, T;Jeon, B


Abstract:This paper proposes a hybrid Wyner-Ziv video coding scheme without requiring the feedback channel which is a limiting factor for many practical applications. In order to remove the feedback channel, we develop a hybrid structure combining the conventional predictive video coding and the Wyner-Ziv video coding schemes. From the information of the neighboring predictive-coded macro blocks, the proposed hybrid scheme estimates the required channel code rate of the Wyner-Ziv coded macro blocks in order to eliminate the requirement of feedback channel. Experiment results indicate that it achieves good coding performance on sequences having linear and slow motion.
18. Case Studies with Process Analysis Toolkit (PAT)

Author:Man, KL;Krilavicius, T;Leung, HL


Abstract:Ad-hoc approach for the development of electronic systems does not satisfy current needs of industry. Therefore, new approaches and techniques are required. Formal Methods are well-known in Software Engineering for a long time, as a potential tool for a faultless development of safety critical systems. Moreover, Process Algebras are one of the most successful techniques that allow formally specifying and analyzing diverse systems. We exemplify application of formal methods by applying Process Analysis Toolkit (PAT), a toolset based on a CPS-style process algebra, to model and analyze a pipeline process and a TLM buffer. In addition, we present the analysis results of several benchmark systems using PAT, namely asynchronous arbiter, hazardous circuit and four-tap FIR filter.
19. High-k materials and their response to gamma ray radiation

Author:Zhao, CZ;Taylor, S;Werner, M;Chalker, PR;Potter, RJ;Gaskell, JM;Jones, AC


Abstract:The radiation response of four different high-k materials has been investigated by irradiating them using a 979 MBq Cs(137) gamma-ray source and a dose absorption rate of 0.71 rad(Si)/s. Acceptorlike electron traps and donorlike traps were observed in HfO(2) and ZrO(2) metal-oxide-semiconductor capacitors originating from radiation-induced defects. A lower density of donor-like traps were created in LaAlO(3) and NdAlO(3) capacitors, but both electron and hole trapping play a role in shifting the flat band voltage. The radiation hardness of the LaAlO(3) and NdAlO(3) thin films is similar to thermal SiO(2) but better than the HfO(2) and ZrO(2). (C) 2009 American Vacuum Society. [DOI: 10.1116/1.3071848]
20. Dielectric relaxation of lanthanum doped zirconium oxide

Author:Zhao, CZ;Taylor, S;Werner, M;Chalker, PR;Murray, RT;Gaskell, JM;Jones, AC


Abstract:Lanthanum doped zirconium oxide (La-x-Zr1-xO2-delta) films, with La contents, up to x=0.35, were studied. Films were annealed at 900 degrees C to crystallize them into phases with higher kappa-values. Increasing the La content suppressed the monoclinic phase and stabilized the tetragonal or cubic phase. The highest dielectric constant was obtained for a lightly doped film with a La content of x=0.09, for which a kappa-value of 40 was obtained. This was accompanied by a significant dielectric relaxation, following a single Curie-von Schweidler power-law dependency with frequency, changing to a mixed Curie-von Schweidler and Kohlrausch-Williams-Watts relationships after annealing. The dielectric relaxation was most severe for lightly doped films, which had the highest kappa-values. The dielectric relaxation appears to be related to the size of crystal grains formed during annealing, which was dependent on the doping level.
Total 2,057 results found
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