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Full-Text Articles in Physical Sciences and Mathematics

Ranking Social Emotions By Learning Listwise Preference, Qishen Wang, Ou Wu, Weiming Hu, Jinfeng Yang, Wanqing Li Dec 2012

Ranking Social Emotions By Learning Listwise Preference, Qishen Wang, Ou Wu, Weiming Hu, Jinfeng Yang, Wanqing Li

Associate Professor Wanqing Li

Abstract-Emotion modeling has received a great attention in recent years. This paper models the online social emotions that are the online users' emotional responds when they are exposed to news articles. Specifically, we rank social emotion labels for online documents. Unlike the existing method, referred to as Pair-LR, which learns pairwise preference and adopts binary classification, we address the problem of ranking social emotions by learning listwise preference. In particular, a novel approach, referred to as List-LR, is proposed to learn a ranking model for social emotion labels of online documents by minimizing the listwise loss defined on instances. Empirical …

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Local Representation Of Faces Through Extended Nmf, Ce Zhan, Wanqing Li, Philip Ogunbona Dec 2012

Local Representation Of Faces Through Extended Nmf, Ce Zhan, Wanqing Li, Philip Ogunbona

Associate Professor Wanqing Li

"Presented is an extension of the non-negative matrix factorisation (NMF) by imposing an orthogonality constraint on the basis matrix and controlling the sparseness of the coefficient matrix for robust learning of compact local part-based representation of face images. The extended NMF is solved by a projected gradient algorithm with a data-driven initialisation scheme. In addition, an indicator is proposed to objectively measure the locality and compactness of local part-based representation and to quantitatively evaluate the efficiency of the extended NMF. Experimental results on benchmark face databases show that the proposed extended NMF is much more effective in learning local part-based …

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Simulation Of Human Motion For Learning And Recognition, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko Dec 2012

Simulation Of Human Motion For Learning And Recognition, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko

Associate Professor Wanqing Li

Acquisition of good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a unique temporal-spatial-temporal decomposition of human body motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and can be simulated based on the kinesiological study. A joint action is formed by proper concatenation of actionlets and an action is a …

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Research Of Unsupervised Posture Modeling And Action Recognition Based On Spatial-Temporal Interesting Points, Chuan-Xu Wang, Yun Liu, Wanqing Li Dec 2012

Research Of Unsupervised Posture Modeling And Action Recognition Based On Spatial-Temporal Interesting Points, Chuan-Xu Wang, Yun Liu, Wanqing Li

Associate Professor Wanqing Li

Posture modeling is critical for action description and recognition,a posture modeling and action recognition method is proposed in this paper.Spatial Temporal Interesting Points (STIPs) are extracted from learning samples,in fact,one posture consists of a set of STIPs;a unsupervised clustering method is adopted to classify salient postures from these posture samples,then a GMM model is established for each clustering result;transitional probability among salient postures are calculated,and a Visible state Markov Model(VMM) is learnt to describe various actions.Bi-gram method is put forward for action recognition,Extensive experiments are conducted and the results prove its robustness and validity.

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Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li Dec 2012

Description Of Evolutional Changes In Image Time Sequences Using Mpeg-7 Visual Descriptors, Lei Ye, Lingzhi Cao, Philip Ogunbona, Wanqing Li

Associate Professor Wanqing Li

Colour and texture visual descriptors have been developed to represent structural features of images, mainly under the Query-by- Example (QBE) image retrieval paradigm. This paper explores applicability of MPEG-7 visual descriptors to describe and measure evolutional changes in image time sequences, using a fruit rotting process as an example. The research found that MPEG-7 visual descriptors can be applied to describe evolutional changes in image time sequences. The experimental results are provided using bananas captured in image time sequences. The results show the desirable monotonicity of description metrics of MPEG-7 similarity matching for image time sequences and their sensitivity to …

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An Improved Template Matching Method For Object Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona Dec 2012

An Improved Template Matching Method For Object Detection, Duc Thanh Nguyen, Wanqing Li, Philip Ogunbona

Associate Professor Wanqing Li

This paper presents an improved template matching method that combines both spatial and orientation information in a simple and effective way. The spatial information is obtained through a generalized distance transform (GDT) that weights the distance transform more on the strong edge pixels and the orientation information is represented as an orientation map (OM) which is calculated from local gradient. We applied the proposed method to detect humans, cars, and maple leaves from images. The experimental results have shown that the proposed method outperforms the existing template matching methods and is robust against cluttered background.

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Regression Analysis Under Probabilistic Multi-Linkage, Gunky Kim, Raymond Chambers Dec 2012

Regression Analysis Under Probabilistic Multi-Linkage, Gunky Kim, Raymond Chambers

Dr Gunky Kim

"Linkage errors can occur when probability-based methods are used to link records from two distinct data sets corresponding to the same target population. Current approaches to modifying standard methods of regression analysis to allow for these errors only deal with the case of two linked data sets and assume that the linkage process is complete, that is, all records on the two data sets are linked. This study extends these ideas to accommodate the situation when more than two data sets are probabilistically linked and the linkage is incomplete."

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Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko Dec 2012

Human Motion Simulation And Action Corpus, Gang Zheng, Wanqing Li, Philip Ogunbona, Liju Dong, Igor Kharitonenko

Dr Igor Kharitonenko

Acquisition of large scale good quality training samples is becoming a major issue in machine learning based human motion analysis. This paper presents a method to simulate continuous gross human body motion with the intention to establish a human motion corpus for learning and recognition. The simulation is achieved by a temporal-spatialtemporal decomposition of human motion into actions, joint actions and actionlets based on the human kinematic model. The actionlet models the primitive moving phase of a joint and represents the muscle movement governed by kinesiological principles. Joint actions and body actions are constructed from actionlets through constrained concatenation and …

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Protection Of Solar Electric Car Dc Motor With Pic Controller, Ahmed Haidar, Ramdan Razali, Ahmed Abdalla, Hazizulden Abdul Aziz, Khaled Noman, Rashad Al-Jawfi Dec 2012

Protection Of Solar Electric Car Dc Motor With Pic Controller, Ahmed Haidar, Ramdan Razali, Ahmed Abdalla, Hazizulden Abdul Aziz, Khaled Noman, Rashad Al-Jawfi

Dr Ahmed Mohamed Ahmed Haidar

The electric car may represent new opportunities for any country and its electric utilities. Widespread use of electric cars can reduce the consumption of both imported and domestic oil, substitute abundant fuels such as coal and nuclear power. Since the charging of electric cars DC motor can be accomplished to a large extent during utility off-peak hours, electric cars can contribute to improve the utility load factors, as a result, reducing the average cost of generation. The problem arising when the DC motor does not stop automatically due to the abnormal condition and cause the loss of energy and the …

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Evaluation Of Transformer Magnetizing Core Loss, Ahmed Haidar, S Taib, I Daut, S Uthman Dec 2012

Evaluation Of Transformer Magnetizing Core Loss, Ahmed Haidar, S Taib, I Daut, S Uthman

Dr Ahmed Mohamed Ahmed Haidar

Loss in transformer core is the electrical power lost in terms of heat within the core of transformer, when core is subjected to AC magnetizing force. It is composed of several types of losses such a s Hysterics loss, eddy current loss within individual laminations and inter-laminar losses that may arise if laminations are not sufficiently insulated from each other. To assess the level of no load loss relative to the occurrence of an inaccurate manufacturing of transformer core, a quantitative measure is often considered. The objective of this research is to study the magnetic behaviour of transformer core and …

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Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim Dec 2012

Electrical Defect Detection In Thermal Image, Ahmed Haidar, Geoffrey Asiegbu, Kamarul Hawari, Faisal Ibrahim

Dr Ahmed Mohamed Ahmed Haidar

Electrical and Electronic objects, which have a temperature of operating condition above absolute zero, emit infrared radiation. This radiation can be measured on the infrared spectral band of the electromagnetic spectrum using thermal imaging. Faults on electrical systems are expensive in terms of plant downtime, damage, loss of production or risk from fire. If the threshold temperature is timely detected, the electrical equipment failures can be avoided. This paper presents a straightforward approach for thermal analysis that examines power loads and large area thermal characteristics. A thermal imaging camera was used to collect thermal pictures of the tested system under …

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Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla Dec 2012

Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla

Dr Ahmed Mohamed Ahmed Haidar

Location of any Hybrid Micro-Grid System requires efficiently prediction of the electromagnetic field strength. This study proposes a novel Electromagnetic Field Strength (EFS) predication based on Probabilistic Neural Network (PNN). Learning data sets have been generated using Electromagnetic Transients Program EMTP. The PNN model has three input nodes representing the Switching Distance, Busbar Interference Voltage and Current waveforms, the output node representing the EFS. Testing datasets have deliberately been chosen outside the region of the learning datasets so as to check the performance of the neural network. The results indicate that the proposed technique can be used successfully to detect …

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A Computational Intelligence-Based Suite For Vulnerability Assessment Of Electrical Power Systems, Ahmed Haidar, Azah Mohamed, Federico Milano Dec 2012

A Computational Intelligence-Based Suite For Vulnerability Assessment Of Electrical Power Systems, Ahmed Haidar, Azah Mohamed, Federico Milano

Dr Ahmed Mohamed Ahmed Haidar

This paper discusses the feasibility of implementing computational intelligence algorithms for power system analysis in an open source environment. The scope is specially oriented to education, training and research. In particular, the paper describes a software package, namely Computational Intelligence Applications to Power System (CIAPS), that implements a variety of heuristic techniques for vulnerability assessment of electrical power systems. CIAPS is based on Matlab and suited for analysis and simulation of small to large size electric power systems. CIAPS is used for solving power flow, optimal power flow, contingency analysis based on artificial neural networks and fuzzy logic techniques. A …

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Vulnerability Control Of Large Scale Interconnected Power System Using Neuro-Fuzzy Load Shedding Approach, Ahmed Haidar, Azah Mohamed, Aini Hussain Dec 2012

Vulnerability Control Of Large Scale Interconnected Power System Using Neuro-Fuzzy Load Shedding Approach, Ahmed Haidar, Azah Mohamed, Aini Hussain

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability control is becoming an essential requirement for security of power systems in the new utility environment. It is a difficult task for system operator who under economic pressure may be reluctant to take preventive action against harmful contingencies in order to guarantee providing continued service. For power systems which are operated closer to their stability limits, it is desirable to use load shedding as a form of vulnerability control strategy. This paper presents a neuro-fuzzy approach for determining the amount of load to be shed in order to avoid a cascading outage. The objective is to develop fast and …

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Utilization Of Pico Hydro Generation In Domestic And Commercial Loads, Ahmed Haidar, Mohod Senan, Abdulhakim Noman, Taha Radman Dec 2012

Utilization Of Pico Hydro Generation In Domestic And Commercial Loads, Ahmed Haidar, Mohod Senan, Abdulhakim Noman, Taha Radman

Dr Ahmed Mohamed Ahmed Haidar

Pico hydro is a term used to distinguish very small-scale hydropower with a maximum electrical output of five kilowatts (5 kW). It is a good technique of providing electricity to the off-grid remote and isolated regions that suffer energy deficit. Typical pico hydro generator is designed and supported by electrical converting system, batteries and safety equipment so that it can be installed at the residential water pipeline. In pico hydro generation, the environmental impact is negligible since large dams are not involved, and the schemes can be managed and maintained by the consumer. This paper is reviewing the application of …

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An Intelligent Load Shedding Scheme Using Neural Networks And Neuro-Fuzzy, Ahmed Haidar, Azah Mohamed, Majid Al-Dabbagh, Aini Hussain, Mohamed Masoum Dec 2012

An Intelligent Load Shedding Scheme Using Neural Networks And Neuro-Fuzzy, Ahmed Haidar, Azah Mohamed, Majid Al-Dabbagh, Aini Hussain, Mohamed Masoum

Dr Ahmed Mohamed Ahmed Haidar

Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power …

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Parameters Evaluation Of Unified Power Quality Conditioner, Ahmed Haidar, C Benachaiba, F Ibrahim, K Hawari Dec 2012

Parameters Evaluation Of Unified Power Quality Conditioner, Ahmed Haidar, C Benachaiba, F Ibrahim, K Hawari

Dr Ahmed Mohamed Ahmed Haidar

The term of “Power Quality” is used to describe the electromagnetic phenomenon in variations of voltage and current in the power system. Most power quality disturbances can come from the facility itself, such as large loads turning on simultaneously, improper wiring and grounding practices, the start-up of large motors and electronic equipments that can be both a source and victim of power quality phenomena or from externally generated, for example, lightning strokes on the power lines. Currently, there are so many industries using a high technology for the manufacturing and requiring a high quality of power supply. Therefore, the paper …

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Artificial Intelligence Application To Malaysian Electrical Powersystem, Ahmed Haidar, Azah Mohamed, Aini Hussain, Norazila Jaalam Dec 2012

Artificial Intelligence Application To Malaysian Electrical Powersystem, Ahmed Haidar, Azah Mohamed, Aini Hussain, Norazila Jaalam

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability assessment and control of a power system is important to power utilities due to the blackouts in recent years in many countries which indicate that power systems today are vulnerable when exposed to unforeseen catastrophic contingencies. A fast and accurate technique to assess the level of system strength or weakness is some of the essential requirements for maintaining security of modern power systems, particularly in competitive energy markets. This paper presents intelligent artificial techniques for vulnerability assessment of Malaysian power system and recommends preventive control measures. Accurate techniques for vulnerability assessment and control of power systems are developed. In …

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Optimal Configuration Assessment Of Renewable Energy In Malaysia, Ahmed Haidar, Priscilla John, Mohd Shawal Dec 2012

Optimal Configuration Assessment Of Renewable Energy In Malaysia, Ahmed Haidar, Priscilla John, Mohd Shawal

Dr Ahmed Mohamed Ahmed Haidar

This paper proposes the use of a PVewindediesel generator hybrid system in order to determine the optimal configuration of renewable energy in Malaysia and to compare the production cost of solar and wind power with its annual yield relevant to different regions in Malaysia namely, Johor, Sarawak, Penang and Selangor. The configuration of optimal hybrid system is selected based on the best components and sizing with appropriate operating strategy to provide a cheap, efficient, reliable and cost-effective system. The various renewable energy sources and their applicability in terms of cost and performance are analyzed. Moreover, the annual yield and cost …

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New Method Vulnerability Assessment Of Power System, Ahmed Haidar, Azah Mohamed, Aini Hussain Dec 2012

New Method Vulnerability Assessment Of Power System, Ahmed Haidar, Azah Mohamed, Aini Hussain

Dr Ahmed Mohamed Ahmed Haidar

Vulnerability assessment in power systems is to determine a power system`s ability to continue to provide service in case of an unforeseen catastrophic contingency. It combines information on the level of system security as well as information on a wide range of scenarios, events and contingencies. To assess the level of system strength or weakness relative to the occurrence of an undesired event, a quantitative measure based on vulnerability index is often considered. In this study, a new vulnerability assessment method is proposed based on total power system loss which considers power generation loss due to generation outage, power line …

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Transient Stability Evaluation Of Electrical Power System Using Generalized Regression Neural Networks, Ahmed Haidar, M Mustafa, Faisal Ibrahim, Ibrahim Ahmed Dec 2012

Transient Stability Evaluation Of Electrical Power System Using Generalized Regression Neural Networks, Ahmed Haidar, M Mustafa, Faisal Ibrahim, Ibrahim Ahmed

Dr Ahmed Mohamed Ahmed Haidar

Transient stability evaluation (TSE) is part of dynamic security assessment of power systems, which involves the evaluation of the system’s ability to remain in equilibrium under credible contingencies. Neural networks (NN) have been applied to the security assessment of power systems and have shown great potential for predicting the security of power systems. This paper proposes a generalized regression neural networks (GRNN) based classification for transient stability evaluation in power systems. In the proposed method, learning data sets have been generated using time domain simulation (TDS). TheGRNN input nodes representing the voltage magnitude for all buses, real and reactive powers …

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Computational Intelligence Applications To Power Systems (Ciaps), Ahmed Haidar Dec 2012

Computational Intelligence Applications To Power Systems (Ciaps), Ahmed Haidar

Dr Ahmed Mohamed Ahmed Haidar

No abstract provided.

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Smart Control Of Upcq Within Microgrid Energy System, C Benachaiba, Ahmed Haidar, O Habab, O Abdelkhalek Dec 2012

Smart Control Of Upcq Within Microgrid Energy System, C Benachaiba, Ahmed Haidar, O Habab, O Abdelkhalek

Dr Ahmed Mohamed Ahmed Haidar

One of the most popular issues in the future power distribution is the quality improvement of microgrid and the development of smart grid (SG). Many applications operating at the microgrid level can be considered as smart grid functions. This paper proposes the application of Fuzzy Logic (FL) technique within microgrid energy system based on the most modern power conditioning equipment devices such as Unified Power Quality Conditioner (UPQC). This technique is working together with the microgrid to track the disturbance of the smart grid and improve the quality of the system with a high flexibility. Furthermore, a control methodology developed …

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Self Organizing Maps For The Clustering Of Large Sets Of Labeled Graphs, Shujia Zhang, Markus Hagenbuchner, Ah Chung Tsoi, Milly Kc Dec 2012

Self Organizing Maps For The Clustering Of Large Sets Of Labeled Graphs, Shujia Zhang, Markus Hagenbuchner, Ah Chung Tsoi, Milly Kc

Dr Markus Hagenbuchner

Graph Self-Organizing Maps (GraphSOMs) are a new concept in the processing of structured objects using machine learning methods. The GraphSOM is a generalization of the Self-Organizing Maps for Structured Domain (SOM-SD) which had been shown to be a capable unsupervised machine learning method for some types of graphstructured information. An application of the SOM-SD to document mining tasks as part of an international competition: Initiative for the Evaluation of XML Retrieval (INEX), on the clustering of XML formatted documents was conducted, and the method subsequently won the competition in 2005 and 2006 respectively. This paper applies the GraphSOM to theclustering …

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Sparsity Issues In Self-Organizing-Maps For Structures, Markus Hagenbuchner, Giovanni Da San Martino, Ah Chung Tsoi, Alessandro Sperduti Dec 2012

Sparsity Issues In Self-Organizing-Maps For Structures, Markus Hagenbuchner, Giovanni Da San Martino, Ah Chung Tsoi, Alessandro Sperduti

Dr Markus Hagenbuchner

Recent developments with Self-Organizing Maps (SOMs) produced methods capable of clustering graph structured data onto a fixed dimensional display space. These methods have been applied successfully to a number of benchmark problems and produced state-of-the-art results. This paper discusses a limitation of the most powerful version of these SOMs, known as probability measure graph SOMs (PMGraphSOMs), viz., the sparsity induced by processing a large number of small graphs, which prevents a successful application of PMGraphSOM to such problems. An approach using the idea of compactifying the generated state space to address this sparsity problem is proposed. An application to an …

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User Identification For Opportunistic Ofdm-Based Multiuser Wireless Communications, Hang Li, Qinghua Guo, Defeng (David) Huang, Yingjun (Angela) Zhang Dec 2012

User Identification For Opportunistic Ofdm-Based Multiuser Wireless Communications, Hang Li, Qinghua Guo, Defeng (David) Huang, Yingjun (Angela) Zhang

Dr Qinghua Guo

Multiuser diversity can be employed in wireless communications to significantly improve system performance by scheduling the channel to the user with the best instantaneous channel-state information (CSI). Conventionally, all users’ CSI must be available at the base station (BS) to achieve the benefit of multiuser diversity, thereby inducing enormous system overhead. To solve the overhead issue, we propose a user identification approach (UIDA) in a generic wireless network and demonstrate its application in the orthogonal frequency-division multiplexing (OFDM) system and the multiple-input multiple-output OFDM (MIMO-OFDM) system. In the UIDA, to find the user with the best CSI, all active users …

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A Lotto Systems Problem, Kenneth Russell, David Atherton Griffiths Dec 2012

A Lotto Systems Problem, Kenneth Russell, David Atherton Griffiths

Professor David Griffiths

No abstract provided.

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A Sparse Implementation Of The Average Information Algorithm For Factor Analytic And Reduced Rank Variance Models, R Thompson, Brian Cullis, A Smith, Arthur Gilmour Dec 2012

A Sparse Implementation Of The Average Information Algorithm For Factor Analytic And Reduced Rank Variance Models, R Thompson, Brian Cullis, A Smith, Arthur Gilmour

Dr Arthur Gilmour

Factor analytic variance models have been widely considered for the analysis of multivariate data particularly in the psychometrics area. Recently Smith, Cullis & Thompson (2001) have considered their use in the analysis of multi-environment data arising from plant improvement programs. For these data, the size of the problem and the complexity of the variance models chosen to account for spatial heterogeneity within trials implies that standard algorithms for fitting factor analytic models can be computationally expensive. This paper presents a sparse implementation of the average information algorithm (Gilmour, Thompson & Cullis, 1995) for fitting factor analytic and reduced rank variance …

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Symmetry Solutions For Transient Solute Transport In Unsaturated Soils With Realistic Water Profile, Maureen Edwards, R Joel Moitsheki, Philip Broadbridge Dec 2012

Symmetry Solutions For Transient Solute Transport In Unsaturated Soils With Realistic Water Profile, Maureen Edwards, R Joel Moitsheki, Philip Broadbridge

Dr Maureen Edwards

No abstract provided.

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The Effect Of Incomplete Mixing Upon Quadratic Autocatalysis, Ahmed Hussein Msmali, Mark Nelson, Maureen Edwards Dec 2012

The Effect Of Incomplete Mixing Upon Quadratic Autocatalysis, Ahmed Hussein Msmali, Mark Nelson, Maureen Edwards

Dr Maureen Edwards

We analyse a model for a continuously stirred tank reactor with imperfect mixing in which the reactor is represented by two well mixed compartments with material transfer between them. These reactors represent `highly agitated' and `less agitated' regions. The chemical model used is a quadratic autocatalytic scheme with linear decay of the autocatalyst. We investigate how the reactor performance depends upon the degree of mixing in the reactor and the size of the less agitated region. Surprisingly, the performance of the reactor with sufficiently small values of mixing is inferior to that with no mixing between the compartments.

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