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Full-Text Articles in Physical Sciences and Mathematics
Cmaf - Chris Morphological Adaptive Filter, Przemysław Kupidura
Cmaf - Chris Morphological Adaptive Filter, Przemysław Kupidura
Przemysław Kupidura
The paper presents a new method of CHRIS images filtering. The presented algorithm is based on mathematical morphology operations and allows to correct the main CHRIS images noise types, like missing pixels and vertical stripes caused by a malfunctioning of the device. the algorithm is preceded by the brief discussion on the nature of the noise and the basis of mathematical morphology. The resulting images are compared to the results of application of other types of CHRIS-dedicated algorithms (Settle methods).
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Dr Fok Hing Chi Tivive
We propose a new hierarchical architecture for visual pattern classification. The new architecture consists of a set of fixed, directional filters and a set of adaptive filters arranged in a cascade structure. The fixed filters are used to extract primitive features such as orientations and edges that are present in a wide range of objects, whereas the adaptive filters can be trained to find complex features that are specific to a given object. Both types of filters are based on the biological mechanism of shunting inhibition. The proposed architecture is applied to two problems: pedestrian detection and car detection. Evaluation …
A Polarized Adaptive Schedule Generation Scheme For The Resource-Constrained Project Scheduling Problem, Reza Zamani
A Polarized Adaptive Schedule Generation Scheme For The Resource-Constrained Project Scheduling Problem, Reza Zamani
Dr Reza Zamani
This paper presents a hybrid schedule generation scheme for solving the resource-constrained project scheduling problem. The scheme, which is called the Polarized Adaptive Scheduling Scheme (PASS), can operate in a spectrum between two poles, namely the parallel and serial schedule generation schemes. A polarizer parameter in the range between zero and one indicates how similarly the PASS behaves like each of its two poles. The presented hybrid is incorporated into a novel genetic algorithm that never degenerates, resulting in an effective self-adaptive procedure. The key point of this genetic algorithm is the embedding of the polarizer parameter as a gene …
A Preliminary Investigation Of Complex Adaptive Systems As A Model For Explaining Organisational Change Caused By The Introduction Of Health Information Systems, Kieren Diment, Ping Yu, Karin Garrety
A Preliminary Investigation Of Complex Adaptive Systems As A Model For Explaining Organisational Change Caused By The Introduction Of Health Information Systems, Kieren Diment, Ping Yu, Karin Garrety
Karin Garrety
This paper documents the preliminary development of a framework for evaluating organisational change processes during the implementation of an electronic nursing documentation system in residential aged care facilities. It starts with a brief outline of organisational change processes. This is followed by a more detailed exposition of the principles underlying complex adaptive systems (CAS) theory, where we explain how mathematical concepts can be used to illuminate qualitative research approaches. Finally we present some preliminary findings on the facilitators and barriers for the introduction of the electronic documentation system, explained with reference to the CAS theory, based on analysis of interviews …
Adaptive Task Allocation For P2p-Based E-Services Composition, Jun Shen, Shuai Yuan
Adaptive Task Allocation For P2p-Based E-Services Composition, Jun Shen, Shuai Yuan
Dr Jun Shen
To effectively manage the task allocation, especially when handling with numerous different peers’ qualities, is one of the greatest challenges to be faced in order to guarantee the success of P2P-based e-services composition. In this context, various QoS descriptive frameworks and Web services technologies (such as WSDL and BPEL) are being considered as the most affordable solutions to promote the performance of decentralized e-services, through applying strategies like QoS ontologies and related optimization algorithms globally or locally. Nonetheless, most P2P-based service selection and composition approaches applied nowadays lack dynamism and autonomy. In this paper, we first propose an extension of …
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Associate Professor Golshah Naghdy
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Professor Salim Bouzerdoum
We propose a new hierarchical architecture for visual pattern classification. The new architecture consists of a set of fixed, directional filters and a set of adaptive filters arranged in a cascade structure. The fixed filters are used to extract primitive features such as orientations and edges that are present in a wide range of objects, whereas the adaptive filters can be trained to find complex features that are specific to a given object. Both types of filters are based on the biological mechanism of shunting inhibition. The proposed architecture is applied to two problems: pedestrian detection and car detection. Evaluation …
Motion Estimation With Adaptive Regularization And Neighborhood Dependent Constraint, Muhammad Wasim Nawaz, Abdesselam Bouzerdoum, Son Lam Phung
Motion Estimation With Adaptive Regularization And Neighborhood Dependent Constraint, Muhammad Wasim Nawaz, Abdesselam Bouzerdoum, Son Lam Phung
Professor Salim Bouzerdoum
Modern variational motion estimation techniques use total variation regularization along with the L1 norm in constant brightness data term. An algorithm based on such homogeneous regularization is unable to preserve sharp edges and leads to increased estimation errors. A better solution is to modify regularizer along strong intensity variations and occluded areas. In addition, using neighborhood information with data constraint can better identify correspondence between image pairs than using only a pointwise data constraint. In this work, we present a novel motion estimation method that uses neighborhood dependent data constraint to better characterize local image structure. The method also uses …
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Wavelet-Based Feature-Adaptive Adaptive Resonance Theory Neural Network For Texture Identification, Jiazhao Wang, Golshah Naghdy, Philip Ogunbona
Professor Philip Ogunbona
A new method of texture classification comprising two processing stages, namely a low-level evolutionary feature extraction based on Gabor wavelets and a high-level neural network based pattern recognition, is proposed. The design of these stages is motivated by the processes involved in the human visual system: low-level receptors responsible for early vision processing and the high-level cognition. Gabor wavelets are used as extractors of ‘‘lowlevel’’ features that feed the feature-adaptive adaptive resonance theory (ART) neural network acting as a high-level ‘‘cognitive system.’’ The novelty of the model developed in this paper lies in the use of a self-organizing input layer …
New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona
New Feature-Based Image Adaptive Vector Quantisation Coder, Jamshid Shanbehzadeh, Philip O. Ogunbona
Professor Philip Ogunbona
It is difficult to achieve a good low bit rate image compression performance with traditional block coding schemes such as transform coding and vector quantization, without regard for the human visual perception or signal dependency. These classical block coding schemes are based on minimizing the MSE at a certain rate. This procedure results in more bits being allocated to areas which may not be visually important and the resulting quantization noise manifests as a blocking artifact. Blocking artifacts are known to be psychologically more annoying than white noise when the human visual response is considered. While image adaptive vector quantization …
Secure Compression Using Adaptive Huffman Coding, C. Kailasananathan, Reihaneh Safavi-Naini, Philip Ogunbona
Secure Compression Using Adaptive Huffman Coding, C. Kailasananathan, Reihaneh Safavi-Naini, Philip Ogunbona
Professor Philip Ogunbona
Recent developments in the Internet and Web based technologies require faster communication of multimedia data in a secure form. Standard compression algorithms such arithmetic coding schemes, and propose methods of protecting against these attacks. In the next section we review DHC, and in Section 3 describe DHC encryption scheme and examine possible attacks. In Section 4, we propose an encryption scheme that protects against the attacks and in Section 5 give the results of our experiments. Section 6, concludes the paper. as JPEG and MPEG use an entropy coding stage. By incorporating security in this stage it it possible to …
Shape Vq-Based Adaptive Predictive Lossless Image Coder, Jiazhao Wang, Philip Ogunbona, Golshah Naghdy
Shape Vq-Based Adaptive Predictive Lossless Image Coder, Jiazhao Wang, Philip Ogunbona, Golshah Naghdy
Professor Philip Ogunbona
A new shape adaptive predictive lossless image coder is proposed. Three classes of block shapes are delineated with associated “optimum” predctors. Each image is partitioned into sub-blocks that are classified into one of the three classes using vector quantisation. The encoder then employs the predictor corresponding to the class of the block under consideration. Performance evaluation of the proposed coder in comparison with four other lossless coders includmg lossless JPEG indicates its superiority.
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Adaptive Hierarchical Architecture For Visual Recognition, Fok Hing Chi Tivive, Abdesselam Bouzerdoum, Son Lam Phung, Khan M. Iftekharuddin
Dr Son Lam Phung
We propose a new hierarchical architecture for visual pattern classification. The new architecture consists of a set of fixed, directional filters and a set of adaptive filters arranged in a cascade structure. The fixed filters are used to extract primitive features such as orientations and edges that are present in a wide range of objects, whereas the adaptive filters can be trained to find complex features that are specific to a given object. Both types of filters are based on the biological mechanism of shunting inhibition. The proposed architecture is applied to two problems: pedestrian detection and car detection. Evaluation …
Adaptive Self-Organisation Of Wireless Ad-Hoc Control Networks, Fazel Naghdy, Nathan Simiana
Adaptive Self-Organisation Of Wireless Ad-Hoc Control Networks, Fazel Naghdy, Nathan Simiana
Professor Fazel Naghdy
A novel concept called Wireless ad-hoc Control Networks (WACNets), exploring an ad-hoc approach to networked distributed control, has been under study for the last five years in the research group. Such systems represent a new stage in the evolution of distributed control and monitoring. The work carried out in developing an adaptive self-organisation algorithm for WACNet is reported. The algorithm deploys a distance measure technique while satisfying the rules and assumptions developed for WACNet framework. The effectiveness of the algorithm is verified through computer simulation under a number of given scenarios. The results obtained show that the algorithm effectively drives …
Adaptive Estimation, Douglas G. Steigerwald
Adaptive Estimation, Douglas G. Steigerwald
Douglas G. Steigerwald
No abstract provided.
Uniformly Adaptive Estimation For Models With Arma Errors, Douglas Steigerwald
Uniformly Adaptive Estimation For Models With Arma Errors, Douglas Steigerwald
Douglas G. Steigerwald
A semiparametric estimator based on an unknown density is uniformly adaptive if the expected loss of the estimator converges to the asymptotic expected loss of the maximum likelihood estimator based on the true density (MLE), and if convergence does not depend on either the parameter values or the form of the unknown density. Without uniform adaptivity, the asymptotic expected loss of the MLE need not approximate the expected loss of a semiparamteric estimator for any finite sample. I show that a two-step semiparametric estimator is uniformly adaptive for the parameters of nonlinear regression models with autoregressive moving average errors.
Adaptive Estimation In Timeseries Regression Models, Douglas Steigerwald
Adaptive Estimation In Timeseries Regression Models, Douglas Steigerwald
Douglas G. Steigerwald
I develop adaptive estimators for linear regression with serially correlated errors. The efficiency results hold even when the serial correlation structure is unknown. Simulations indicate that efficiency gains can be substantial with samples of only 50 observations. We apply the method to a study of forward exchange rates.
On The Finite Sample Behavior Of Adaptive Estimators, Douglas Steigerwald
On The Finite Sample Behavior Of Adaptive Estimators, Douglas Steigerwald
Douglas G. Steigerwald
With only 50 observations, the adaptive estimator produces confidence intervals that are 20 to 50 percent shorter than those produced by GLS procedures. The key feature is that the underlying error density is symmetric. Under asymmetry the interval length is shortened by a smaller amount.