Parametric Sequence Alignment with Constraints

Approximate matching techniques based on string alignment are important tools for investigating similarities between strings, such as those representing DNA and protein sequences. We propose a constraint based approach for parametric sequence alignment which allows for more general string alignment queries where the alignment cost can itself be parameterized as a query with some initial constraints. Thus, the costs need not be fixed in a parametric alignment query unlike the case in normal alignment. The basic dynamic programming string edit distance algorithm is generalized to a naive algorithm which uses inequalities to represent the alignment score. The naive algorithm is rather costly and the remainder of the paper develops an improvement which prunes alternatives where it can and approximates the alternatives otherwise. This reduces the number of inequalities significantly and strengthens the constraint representation with equalities. We present some preliminary results using parametric alignment on some general alignment queries.     

A Simultaneous Search Problem

We introduce a new search problem motivated by computational metrology. The problem is as follows: we would like to locate two unknown numbers x,y ∈ [0,1] with as little uncertainty as possible, using some given number k of probes. Each probe is specified by a real number r∈ [0,1] . After a probe at r , we are told whether x≤ r or x \geq r , and whether y≤ r or y\geq r . We derive the optimal strategy and prove that the asymptotic behavior of the total uncertainty after k probes is 13/7 2 ^-(k+1)/2 for odd k and 13/10 2 ^-k/2 for even k . Received November 11, 1996; revised October 2, 1997, and July 13, 1998.     

An Effective Technique for Subpixel Image Registration Under Noisy Conditions

This paper proposes an effective higher order statistics method to address subpixel image registration. Conventional power spectrum-based techniques employ second-order statistics to estimate subpixel translation between two images. They are, however, susceptible to noise, thereby leading to significant performance deterioration in low signal-to-noise ratio environments or in the presence of cross-correlated channel noise. In view of this, we propose a bispectrum-based approach to alleviate this difficulty. The new method utilizes the characteristics of bispectrum to suppress Gaussian noise. It develops a phase relationship between the image pair and estimates the subpixel translation by solving a set of nonlinear equations. Experimental results show that the proposed technique provides performance improvement over conventional power-spectrum-based methods under different noise levels and conditions.     

Subband Synthesis for Color Filter Array Demosaicking

This paper presents a new algorithm for demosaicking images captured through a color filter array (CFA). The objective of the CFA demosaicking is to render a full color image from the mosaicked image. This is commonly achieved by estimating the missing color information from the surrounding observed pixels. In this paper, we integrate the observation that color images have a strong intrachannel spatial correlation in low-frequency components and a dominant interchannel correlation in the high- frequency components. A new framework is proposed to utilize this information where the missing pixels in each color channel are estimated from the wavelet subbands. A modified median-filtering operation is then applied in the subband domain. The algorithm is adaptive and produces superior full-resolution images when compared with other methods.     

An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.     

Environmental effects on the coevolution of pursuit and evasion strategies

The game of tag is frequently used in the study of pursuit and evasion strategies that are discovered through competitive coevolution. The aim of coevolution is to create an arms race where opposing populations cyclically evolve in incremental improvements, driving the system towards better strategies. A coevolutionary simulation of the game of tag involving two populations of agents; pursuers and evaders, is developed to investigate the effects of a boundary and two obstacles. The evolution of strategies through Chemical Genetic Programming optimizes the mapping of genotypic strings to phenotypic trees. Four experiments were conducted, distinguished by speed differentials and environmental conditions. Designing experiments to evaluate the efficacy of emergent strategies often reveal necessary steps needed for coevolutionary progress. The experiments that excluded obstacles and boundaries provided design pointers to ensure coevolutionary progress as well as a deeper understanding of strategies that emerged when obstacles and boundaries were added. In the latter, we found that an awareness of the environment and the pursuer was not critical in an evader’s strategy to survive, instead heading to the edge of the boundary or behind an obstacle in a bid to ‘throw-off or hide from the pursuer’ or simply turn in circles was often sufficient, thereby revealing possible suboptimal strategies that were environment specific. We also observed that a condition for coevolutionary progress was that the problem complexity must be surmountable by at least one population; that is, some pursuer must be able to tag an opponent. Due to the use of amino-acid building blocks in our Chemical Genetic Program, our simulations were able to achieve significant complexity in a short period of time.

Projecting CLPR constraints

The presentation of constraints in a usable form is an essential aspect of Constraint Logic Programming (CLP) systems. It is needed both in the output of constraints, as well as in the production of an internal representation of constraints for meta-level manipulation. Typically, only a small subset \(\tilde x\) of the variables in constraints is of interest, and so an informal statement of the problem at hand is: given a conjunction \(c(\tilde x,\tilde y)\) of constraints, express the projection \(\exists \tilde y c(\tilde x,\tilde y)\) ofc onto \(\tilde x\) in the simplest form. In this paper, we consider the constraints of the CLP(R) system and describe the essential features of its projection module. One main part focuses on the well-known problem of projection inlinear arithmetic constraints. We start with a classical algorithm and augment it with a procedure for eliminating redundant constraints generated by the algorithm. A second part discusses projection of the other object-level constraints: equations over trees and nonlinear equations. The final part deals with producing a manipulable form of the constraints, which complicates the projection problem.     

Characteristics and usage patterns of older people in a 3D online multi-user virtual environment

3D online multi-user virtual environments (MUVEs) have a lot of potential in supporting older people in their daily lives, yet little research has been conducted to explore how older people engage with this type of technology. This paper aims to investigate the characteristics, user groups and activity patterns (particularly social networks and gift giving behaviour) of older users within a 3D online multi-user virtual environment. Data from approximately 5000 online user profiles of older and younger users from a 3D MUVE, namely IMVU, was collected for analysis. Overall, we identified several distinct patterns of use (e.g. size of social ties, level of reciprocity, etc.) among older users when compared with younger users. We also found that despite the capabilities of 3D MUVEs to provide the users immersion in alternative realities, a feature well embraced by younger users in this study, older users seemed more interested in activities which serve as an extension to their physical life.     

Disturbance decoupled fault reconstruction using cascaded sliding mode observers

This paper presents a disturbance decoupled fault reconstruction (DDFR) scheme using cascaded sliding mode observers (SMOs). The processed signals from a SMO are found to be the output of a fictitious system which treats the faults and disturbances as inputs; the ‘outputs’ are then fed into the next SMO. This process is repeated until the attainment of a fictitious system which satisfies the conditions that guarantee DDFR. It is found that this scheme is less restrictive and enables DDFR for a wider class of systems compared to previous work when only one or two SMOs were used. This paper also presents a systematic routine to check for the feasibility of the scheme and to calculate the required number of SMOs from the outset and also to design the DDFR scheme. A design example verifies its effectiveness.     

Effects of Weathering on Treatment of Lead Contaminated Soils

Treatment of lead-contaminated material focuses on the reduction of leached lead concentrations in laboratory leaching tests. There has been little study on the chemical stability of treated materials after waste disposal. To investigate the effects of weathering on several solidification/stabilization chemistries, lead-contaminated soil was treated with various agents (cement, phosphates, dithiocarbamate, calcium hydroxide, calcium carbonate, and metallic iron) and subjected to natural weathering for one year. Lead concentrations and pH values in field percolates and leachates from toxicity characteristic leaching procedure (TCLP) and water leaching tests were used to evaluate changes in the treatment effectiveness. Weathering altered the treatment chemistry of several additives—alkaline additives were neutralized, while reduced additives were oxidized. Lead concentrations in field percolates from the untreated soil were around 1.0?mg/L, and did not vary over one year of weathering time. After one year of weathering, lead concentrations in field percolates from most samples were reduced to low levels (<0.15 mg/L). Weathering also affected lead concentrations in the TCLP and water leach test leachates from the treated wastes. Treated wastes in which the alkaline additives were neutralized or reduced additives oxidized gave higher TCLP lead concentrations after weathering than before, in contrast to the decreasing lead concentrations in the field percolates. Water leaching tests on the alkaline treated wastes had lower lead concentrations after weathering than before.