An adaptive and dynamic dimensionality reduction method for high-dimensional indexing

The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approach to overcome degradation in performance with respect to increasing dimensions is to reduce the dimensionality of the original dataset before constructing the index. However, identifying the correlation among the dimensions and effectively reducing them are challenging tasks. In this paper, we present an adaptive Multi-level Mahalanobis-based Dimensionality Reduction (MMDR) technique for high-dimensional indexing. Our MMDR technique has four notable features compared to existing methods. First, it discovers elliptical clusters for more effective dimensionality reduction by using only the low-dimensional subspaces. Second, data points in the different axis systems are indexed using a single B+-tree. Third, our technique is highly scalable in terms of data size and dimension. Finally, it is also dynamic and adaptive to insertions. An extensive performance study was conducted using both real and synthetic datasets, and the results show that our technique not only achieves higher precision, but also enables queries to be processed efficiently. Copyright Springer-Verlag 2005

Obsessive-compulsive disorder across developmental trajectory: Cognitive processing of threat in children, adolescents and adults

Background. While the cognitive theory of obsessive-compulsive disorder (OCD) is one of the most widely accepted accounts of the maintenance of the disorder in adults, no study to date has systematically evaluated the theory across children, adolescence and adults with OCD. Method. This paper investigated developmental differences in the cognitive processing of threat in a sample of children, adolescents and adults with OCD. Using an idiographic assessment approach, as well as self-report questionnaires, this study evaluated cognitive appraisals of responsibility, probability, severity, thought-action fusion (TAF), thought-suppression, self-doubt and cognitive control. It was hypothesised that there would be age related differences in reported responsibility for harm, probability of harm, severity of harm, thought suppression, TAR self-doubt and cognitive control. Results. Results of this study demonstrated that children with OCD reported experiencing fewer intrusive thoughts, which were less distressing and less uncontrollable than those experienced by adolescents and adults with OCD. Furthermore, responsibility attitudes, probability biases and thought suppression strategies were higher in adolescents and adults with OCD. Cognitive processes of TAF, perceived severity of harm, self-doubt and cognitive control were found to be comparable across age groups. Conclusions. These results suggest that the current cognitive theory of OCD needs to address developmental differences in the cognitive processing of threat. Furthermore, for a developmentally sensitive theory of OCD, further investigation is warranted into other possible age related maintenance factors. Implications of this investigation and directions for future research are discussed.

The economics of inclusion body processing

Many recombinant proteins are often over-expressed in host cells, such as Escherichia coli, and are found as insoluble and inactive protein aggregates known as inclusion bodies (IBs). Recently, a novel process for IB extraction and solubilisation, based on chemical extraction, has been reported. While this method has the potential to radically intensify traditional IB processing, the process economics of the new technique have yet to be reported. This study focuses on the evaluation of process economics for several IB processing schemes based on chemical extraction and/or traditional techniques. Simulations and economic analysis were conducted at various processing conditions using granulocyte macrophage-colony stimulating factor, expressed as IBs in E. coli, as a model protein. In most cases, IB processing schemes based on chemical extraction having a shorter downstream cascade demonstrated a competitive economic edge over the conventional route, validating the new process as an economically more viable alternative for IB processing.

Structure repair of a compacted vertisol with wet-dry cycles and crops

We hypothesized that the four rotation crops: wheat (Triticum aestivum L.), sorghum [Sorghum bicolor (L.) Merr.], lablab [Lablab purpureus (L.) Sweet] and mung bean [ Vigna radiata (L.) R. Wilczek] differ in their ability to repair soil structure. The study was conducted on a Typic Haplustert, Queensland, Australia, locally termed a Black Earth and considered a prime cropping soil. Large (0.5-m depth by 0.3-m diam.) soil cores, collected from compacted wheel furrows in an irrigated cotton (Gossypium hirsutum L.) field, were subjected to three, six, or nine wet-dry cycles that simulated local flood irrigation practices. After each cycle, soil profiles were sampled for clod bulk density, image analysis of soil structure, and evapotranspiration. Generally, all crops improved soil structure over the initial field condition but lablab and mung bean gave improvements to greater depths and more rapidly than wheat and sorghum. Mung bean and lablab caused up to a threefold increase in clod porosity in the 0.1- to 0.4-m soil layer after only three wet-dry cycles, whereas sorghum required nine wet-dry cycles to increase clod porosity in only the 0.2- to 0.3-m layer, and wheat gave no improvement even after nine wet-dry cycles. Image analysis of soil structure showed that lablab and mung bean rapidly (by three wet-dry cycles) produced smaller peds with more interconnected pore space than wheat and sorghum. By nine wet-dry cycles, sorghum achieved deep cracking of the soil but the material between the cracks remained large and dense. Evapotranspiration was double under lablab and mung bean compared with wheat and sorghum. Our results indicate greater cycles of wetting and drying under lablab and mung bean than wheat and sorghum that have led to rapid repair of soil compaction.

Biologically inspired visual landmark processing for simultaneous localization and mapping

This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.

A new indexing method for high dimensional dataset

Indexing high dimensional datasets has attracted extensive attention from many researchers in the last decade. Since R-tree type of index structures are known as suffering curse of dimensionality problems, Pyramid-tree type of index structures, which are based on the B-tree, have been proposed to break the curse of dimensionality. However, for high dimensional data, the number of pyramids is often insufficient to discriminate data points when the number of dimensions is high. Its effectiveness degrades dramatically with the increase of dimensionality. In this paper, we focus on one particular issue of curse of dimensionality; that is, the surface of a hypercube in a high dimensional space approaches 100% of the total hypercube volume when the number of dimensions approaches infinite. We propose a new indexing method based on the surface of dimensionality. We prove that the Pyramid tree technology is a special case of our method. The results of our experiments demonstrate clear priority of our novel method.

BM+-tree: A hyperplane-based index method for high-dimensional metric spaces

In this paper, we propose a novel high-dimensional index method, the BM+-tree, to support efficient processing of similarity search queries in high-dimensional spaces. The main idea of the proposed index is to improve data partitioning efficiency in a high-dimensional space by using a rotary binary hyperplane, which further partitions a subspace and can also take advantage of the twin node concept used in the M+-tree. Compared with the key dimension concept in the M+-tree, the binary hyperplane is more effective in data filtering. High space utilization is achieved by dynamically performing data reallocation between twin nodes. In addition, a post processing step is used after index building to ensure effective filtration. Experimental results using two types of real data sets illustrate a significantly improved filtering efficiency.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Hydrostability and Scaling Up Molecular Sieve Silica (MSS) Membranes for H2/CO Separation in Fuel Cell Systems

MSS membranes are a good candidate for CO cleanup in fuel cell fuel processing systems due to their ability to selectively permeate H2 over CO via molecular sieving. Successfully scaled up tubular membranes were stable under dry conditions to 400°C with H2 permeance as high as 2 x 10-6 mol.m-2.s^-1.Pa^-1 at 200 degrees C and H2/CO selectivity up to 6.4, indicating molecular sieving was the dominant mechanism. A novel carbonised template molecular sieve silica (CTMSS) technology gave the scaled up membranes resilience in hydrothermal conditions up to 400 degrees C in 34% steam and synthetic reformate, which is required for use in fuel cell CO cleanup systems.

The Equilibrium Flux Method for the calculation of flows with non-equilbrium chemical reactions

The Equilibrium Flux Method [1] is a kinetic theory based finite volume method for calculating the flow of a compressible ideal gas. It is shown here that, in effect, the method solves the Euler equations with added pseudo-dissipative terms and that it is a natural upwinding scheme. The method can be easily modified so that the flow of a chemically reacting gas mixture can be calculated. Results from the method for a one-dimensional non-equilibrium reacting flow are shown to agree well with a conventional continuum solution. Results are also presented for the calculation of a plane two-dimensional flow, at hypersonic speed, of a dissociating gas around a blunt-nosed body.

Morphosyntactic and syntactic priming: an investigation of underlying processing mechanisms and the effects of Parkinson’s disease

There is now considerable evidence to suggest that non-demented people with Parkinson's disease (PD) experience difficulties using the morphosyntactic aspects of language. It remains unclear, however, at precisely which point in the processing of morphosyntax, these difficulties emerge. The major objective of the present study was to examine the impact of PD on the processes involved in accessing morphosyntactic information in the lexicon. Nineteen people with PD and 19 matched control subjects participated in the study which employed on-line word recognition tasks to examine morphosyntactic priming for local grammatical dependencies that occur both within (e.g. is going) and across (e.g. she gives) phrasal boundaries (Experiments 1 and 2, respectively). The control group evidenced robust morphosyntactic priming effects that were consistent with the involvement of both pre- (Experiment 1) and post-lexical (Experiment 2) processing routines. Whilst the participants with PD also recorded priming for dependencies within phrasal boundaries (Experiment 1), priming effects were observed over an abnormally brief time course. Further, in contrast to the controls, the PD group failed to record morphosyntactic priming for constructions that crossed phrasal boundaries (Experiment 2). The results demonstrate that attentionally mediated mechanisms operating at both the pre- and post-lexical stages of processing are able to contribute to morphosyntactic priming effects. In addition, the findings support the notion that, whilst people with PD are able to access morphosyntactic information in a normal manner, the time frame in which this information remains available for processing is altered. Deficits may also be experienced at the post-lexical integrational stage of processing.

Towards realistic simulations of lava dome growth using the level set method

The level set method has been implemented in a computational volcanology context. New techniques are presented to solve the advection equation and the reinitialisation equation. These techniques are based upon an algorithm developed in the finite difference context, but are modified to take advantage of the robustness of the finite element method. The resulting algorithm is tested on a well documented Rayleigh–Taylor instability benchmark [19], and on an axisymmetric problem where the analytical solution is known. Finally, the algorithm is applied to a basic study of lava dome growth.

A rapid single-step multiplex method for discriminating between Trichogramma (Hymenoptera: Trichogrammatidae) species in Australia

Inaccurate species identification confounds insect ecological studies. Examining aspects of Trichogramma ecology pertinent to the novel insect resistance management strategy for future transgenic cotton, Gossypium hirsutum L., production in the Ord River Irrigation Area (ORIA) of Western Australia required accurate differentiation between morphologically similar Trichogramma species. Established molecular diagnostic methods for Trichogramma identification use species-specific sequence difference in the internal transcribed spacer (ITS)-2 chromosomal region; yet, difficulties arise discerning polymerase chain reaction (PCR) fragments of similar base pair length by gel electrophoresis. This necessitates the restriction enzyme digestion of PCR-amplified ITS-2 fragments to readily differentiate Trichogramma australicum Girault and Trichogramma pretiosum Riley. To overcome the time and expense associated with a two-step diagnostic procedure, we developed a “one-step” multiplex PCR technique using species-specific primers designed to the ITS-2 region. This approach allowed for a high-throughput analysis of samples as part of ongoing ecological studies examining Trichogramma biological control potential in the ORIA where these two species occur in sympatry.