Behaviour-Based Assistive Robotics for the Home

Meng Q. and Lee M.H., Behaviour-Based Assistive Robotics for the Home, in Proc. SMC2001, IEEE 2001 Int. Conf. on Systems, Man and Cybernetics, Tucson, Arizona, Oct 2001, pp684-689.

On the use of qualitative reasoning to simulate and identify metabolic pathways

King, R.D., Garrett, S.M., Coghill, G.M. (2005). On the use of qualitative reasoning to simulate and identify metabolic pathways. Bioinformatics 21(9):2017-2026 RAE2008

Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough-Based Approaches

R. Jensen and Q. Shen. Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough Based Approaches. IEEE Transactions on Knowledge and Data Engineering, 16(12): 1457-1471. 2004.

Feature Selection based on Rough Sets and Particle Swarm Optimization

X. Wang, J. Yang, X. Teng, W. Xia, and R. Jensen. Feature Selection based on Rough Sets and Particle Swarm Optimization. Pattern Recognition Letters, vol. 28, no. 4, pp. 459-471, 2007.

Rough set based feature selection : A review

Feature selection aims to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. Rough set theory (RST) has been used as such a tool with much success. RST enables the discovery of data dependencies and the reduction of the number of attributes contained in a dataset using the data alone, requiring no additional information. This chapter describes the fundamental ideas behind RST-based approaches and reviews related feature selection methods that build on these ideas. Extensions to the traditional rough set approach are discussed, including recent selection methods based on tolerance rough sets, variable precision rough sets and fuzzy-rough sets. Alternative search mechanisms are also highly important in rough set feature selection. The chapter includes the latest developments in this area, including RST strategies based on hill-climbing, genetic algorithms and ant colony optimization.

Tolerance-based and Fuzzy-Rough Feature Selection.

R. Jensen and Q. Shen, 'Tolerance-based and Fuzzy-Rough Feature Selection,' Proceedings of the 16th International Conference on Fuzzy Systems (FUZZ-IEEE'07), pp. 877-882, 2007.

Fuzzy interpolative reasoning via scale and move transformation

Z. Huang and Q. Shen. Fuzzy interpolative reasoning via scale and move transformation. IEEE Transactions on Fuzzy Systems, 14(2):340-359.

Transformation Based Interpolation with Generalized Representative Values

Z. Huang and Q. Shen. Transformation Based Interpolation with Generalized Representative Values. Proceedings of the 14th International Conference on Fuzzy Systems, pages 821-826.

Subsethood-based Fuzzy Rule Models and their Application to Student Performance

K. Rasmani and Q. Shen. Subsethood-based Fuzzy Rule Models and their Application to Student Performance Classification. Proceedings of the 14th International Conference on Fuzzy Systems, pages 755-760, 2005.

Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers

K. Rasmani and Q. Shen. Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers. Proceedings of the 13th International Conference on Fuzzy Systems, pages 1679-1684, 2004

Subsethood-based fuzzy modelling and classification

K. Rasmani and Q. Shen. Subsethood-based fuzzy modelling and classification. Proceedings of the 2004 UK Workshop on Computational Intelligence, pages 181-188.

Approximation-based feature selection and application for algae population estimation

Q. Shen and R. Jensen, 'Approximation-based feature selection and application for algae population estimation,' Applied Intelligence, vol. 28, no. 2, pp. 167-181, 2008. Sponsorship: EPSRC RONO: EP/E058388/1

Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection

T.Boongoen and Q. Shen. Semi-Supervised OWA Aggregation for Link-Based Similarity Evaluation and Alias Detection. Proceedings of the 18th International Conference on Fuzzy Systems (FUZZ-IEEE'09), pp. 288-293, 2009. Sponsorship: EPSRC

Accurate and Efficient Gesture Spotting via Pruning and Subgesture Reasoning

Gesture spotting is the challenging task of locating the start and end frames of the video stream that correspond to a gesture of interest, while at the same time rejecting non-gesture motion patterns. This paper proposes a new gesture spotting and recognition algorithm that is based on the continuous dynamic programming (CDP) algorithm, and runs in real-time. To make gesture spotting efficient a pruning method is proposed that allows the system to evaluate a relatively small number of hypotheses compared to CDP. Pruning is implemented by a set of model-dependent classifiers, that are learned from training examples. To make gesture spotting more accurate a subgesture reasoning process is proposed that models the fact that some gesture models can falsely match parts of other longer gestures. In our experiments, the proposed method with pruning and subgesture modeling is an order of magnitude faster and 18% more accurate compared to the original CDP algorithm.

Synthesis and characterisation of novel superficially porous silica based stationary phases for use in liquid chromatography

The concept of pellicular particles was suggested by Horváth and Lipsky over fifty years ago. The reasoning behind the idea of these particles was to improve column efficiency by shortening the pathways analyte molecules can travel, therefore reducing the effect of the A and C terms. Several types of shell particles were successfully marketed around this time, however with the introduction of high quality fully porous silica under 10 μm, shell particles faded into the background. In recent years a new generation of core shell particles have become popular within the separation science community. These particles allow fast and efficient separations that can be carried out on conventional HPLC systems. Chapter 1 of this thesis introduces the chemistry of chromatographic stationary phases, with an emphasis on silica bonded phases, particularly focusing on the current state of technology in this area. The main focus is on superficially porous silica particles as a support material for liquid chromatography. A summary of the history and development of these particles over the past few decades is explored, along with current methods of synthesis of shell particles. While commercial shell particles have a rough outer surface, Chapter 2 focuses on the novel approach to growth of smooth surface superficially porous particles in a step-by-step manner. From the Stöber methodology to the seeded growth technique, and finally to the layer-bylayer growth of the porous shell. The superficially porous particles generated in this work have an overall diameter of 2.6 μm with a 350 nm porous shell; these silica particles were characterised using SEM, TEM and BET analysis. The uniform spherical nature of the particles along with their surface area, pore size and particle size distribution are examined in this chapter. I discovered that these smooth surface shell particles can be synthesised to give comparable surface area and pore size in comparison to commercial brands. Chapter 3 deals with the bonding of the particles prepared in Chapter 2 with C18 functionality; one with a narrow and one with a wide particle size distribution. This chapter examines the chromatographic and kinetic performance of these silica stationary phases, and compares them to a commercial superficially porous silica phase with a rough outer surface. I found that the particle size distribution does not seem to be the major contributor to the improvement in efficiency. The surface morphology of the particles appears to play an important role in the packing process of these particles and influences the Van Deemter effects. Chapter 4 focuses on the functionalisation of 2.6 μm smooth surface superficially porous particles with a variety of fluorinated and phenyl silanes. The same processes were carried out on 3.0 μm fully porous silica particles to provide a comparison. All phases were accessed using elemental analysis, thermogravimetric analysis, nitrogen sorption analysis and chromatographically evaluated using the Neue test. I observed comparable results for the 2.6 μm shell pentaflurophenyl propyl silica when compared to 3.0 μm fully porous silica. Chapter 5 moves towards nano-particles, with the synthesis of sub-1 μm superficially porous particles, their characterisation and use in chromatography. The particles prepared are 750 nm in total with a 100 nm shell. All reactions and testing carried out on these 750 nm core shell particles are also carried out on 1.5 μm fully porous particles in order to give a comparative result. The 750 nm core shell particles can be synthesised quickly and are very uniform. The main drawback in their use for HPLC is the system itself due to the backpressure experienced using sub – 1 μm particles. The synthesis of modified Stöber particles is also examined in this chapter with a range of non-porous silica and shell silica from 70 nm – 750 nm being tested for use on a Langmuir – Blodgett system. These smooth surface shell particles have only been in existence since 2009. The results displayed in this thesis demonstrate how much potential smooth surface shell particles have provided more in-depth optimisation is carried out. The results on packing studies reported in this thesis aims to be a starting point for a more sophisticated methodology, which in turn can lead to greater chromatographic improvements.