Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Toward efficient multifeature query processing

In many advanced applications, data are described by multiple high-dimensional features. Moreover, different queries may weight these features differently; some may not even specify all the features. In this paper, we propose our solution to support efficient query processing in these applications. We devise a novel representation that compactly captures f features into two components: The first component is a 2D vector that reflects a distance range ( minimum and maximum values) of the f features with respect to a reference point ( the center of the space) in a metric space and the second component is a bit signature, with two bits per dimension, obtained by analyzing each feature's descending energy histogram. This representation enables two levels of filtering: The first component prunes away points that do not share similar distance ranges, while the bit signature filters away points based on the dimensions of the relevant features. Moreover, the representation facilitates the use of a single index structure to further speed up processing. We employ the classical B+-tree for this purpose. We also propose a KNN search algorithm that exploits the access orders of critical dimensions of highly selective features and partial distances to prune the search space more effectively. Our extensive experiments on both real-life and synthetic data sets show that the proposed solution offers significant performance advantages over sequential scan and retrieval methods using single and multiple VA-files.

Quantum optical systems for the implementation of quantum information processing

We review the field of quantum optical information from elementary considerations to quantum computation schemes. We illustrate our discussion with descriptions of experimental demonstrations of key communication and processing tasks from the last decade and also look forward to the key results likely in the next decade. We examine both discrete (single photon) type processing as well as those which employ continuous variable manipulations. The mathematical formalism is kept to the minimum needed to understand the key theoretical and experimental results.

Surface k-NN query processing

A k-NN query finds the k nearest-neighbors of a given point from a point database. When it is sufficient to measure object distance using the Euclidian distance, the key to efficient k-NN query processing is to fetch and check the distances of a minimum number of points from the database. For many applications, such as vehicle movement along road networks or rover and animal movement along terrain surfaces, the distance is only meaningful when it is along a valid movement path. For this type of k-NN queries, the focus of efficient query processing is to minimize the cost of computing distances using the environment data (such as the road network data and the terrain data), which can be several orders of magnitude larger than that of the point data. Efficient processing of k-NN queries based on the Euclidian distance or the road network distance has been investigated extensively in the past. In this paper, we investigate the problem of surface k-NN query processing, where the distance is calculated from the shortest path along a terrain surface. This problem is very challenging, as the terrain data can be very large and the computational cost of finding shortest paths is very high. We propose an efficient solution based on multiresolution terrain models. Our approach eliminates the need of costly process of finding shortest paths by ranking objects using estimated lower and upper bounds of distance on multiresolution terrain models.

Redefining functional models of basal ganglia organisation: Role for the posteroventral pallidum in linguistic processing?

Traditionally the basal ganglia have been implicated in motor behavior, as they are involved in both the execution of automatic actions and the modification of ongoing actions in novel contexts. Corresponding to cognition, the role of the basal ganglia has not been defined as explicitly. Relative to linguistic processes, contemporary theories of subcortical participation in language have endorsed a role for the globus pallidus internus (GPi) in the control of lexical-semantic operations. However, attempts to empirically validate these postulates have been largely limited to neuropsychological investigations of verbal fluency abilities subsequent to pallidotomy. We evaluated the impact of bilateral posteroventral pallidotomy (BPVP) on language function across a range of general and high-level linguistic abilities, and validated/extended working theories of pallidal participation in language. Comprehensive linguistic profiles were compiled up to 1 month before and 3 months after BPVP in 6 subjects with Parkinson's disease (PD). Commensurate linguistic profiles were also gathered over a 3-month period for a nonsurgical control cohort of 16 subjects with PD and a group of 16 non-neurologically impaired controls (NC). Nonparametric between-groups comparisons were conducted and reliable change indices calculated, relative to baseline/3-month follow-up difference scores. Group-wise statistical comparisons between the three groups failed to reveal significant postoperative changes in language performance. Case-by-case data analysis relative to clinically consequential change indices revealed reliable alterations in performance across several language variables as a consequence of BPVP. These findings lend support to models of subcortical participation in language, which promote a role for the GPi in lexical-semantic manipulation mechanisms. Concomitant improvements and decrements in postoperative performance were interpreted within the context of additive and subtractive postlesional effects. Relative to parkinsonian cohorts, clinically reliable versus statistically significant changes on a case by case basis may provide the most accurate method of characterizing the way in which pathophysiologically divergent basal ganglia linguistic circuits respond to BPVP.

High selectivity microporous silica membranes for lactic acid dehydration

Lactic acid (LA) has significant market potential for many industries including food, cosmetics, pharmaceuticals, medical and biodegradable materials. Production of LA usually begins with the fermentation of glucose but subsequent stages for the enrichment of lactic acid are complex and energy intensive and could be minimised using water selective membrane technology. In this work, we trialled a highly selective hydrostable carbonised template molecular sieve silica (CTMSS) membrane for the dehydration of a 15 vol% aqueous lactic acid solution with 0.1 vol% glucose. CTMSS membrane films were developed by dip-coating ceramic substrates with silica sols made using the acid catalysed sol-gel process. Permeation was performed by feeding LA/glucose solution to the membrane cell at 18°C in a standard pervaporation setup. The membrane showed selective transport of water from the aqueous feed to the permeate while glucose was not detected. CTMSS membrane permeate flux stabilised at 0.2 kg.m-2.hr-1 in 3.9 hours, and reduced LA to lower than 0.2 vol%. Flux through the CTMSS micropores was activated, displaying increased initial flux to 1.58 kg.m-2.hr-1 at 60°C. To enrich a 1 l.min-1 stream to 85% LA in a single stage, a minimum membrane area of 324 m2 would be required at 18°C. Increased operating temperature to 80°C significantly reduced this area to 24 m2 but LA levels in the permeate stream increased to 0.5 vol%. The highly selective CTMSS membrane technology is an ideal candidate for LA purification. CTMSS membrane systems operate stably in aqueous systems leading to potential cost reductions in LA processing for future markets.

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.

The Coefficient of Variance as an index of L2 lexical processing skill

The Coefficient of Variance (mean standard deviation/mean Response time) is a measure of response time variability that corrects for differences in mean Response time (RT) (Segalowitz & Segalowitz, 1993). A positive correlation between decreasing mean RTs and CVs (rCV-RT) has been proposed as an indicator of L2 automaticity and more generally as an index of processing efficiency. The current study evaluates this claim by examining lexical decision performance by individuals from three levels of English proficiency (Intermediate ESL, Advanced ESL and L1 controls) on stimuli from four levels of item familiarity, as defined by frequency of occurrence. A three-phase model of skill development defined by changing rCV-RT.values was tested. Results showed that RTs and CVs systematically decreased as a function of increasing proficiency and frequency levels, with the rCV-RT serving as a stable indicator of individual differences in lexical decision performance. The rCV-RT and automaticity/restructuring account is discussed in light of the findings. The CV is also evaluated as a more general quantitative index of processing efficiency in the L2.

Eco-efficiency for the Dairy Processing Industry - Fact Sheet Sumary

This Toolkit was developed for the Australian dairy processing industry on behalf of Dairy Australia. At the conclusion of the project, industry participants gained exclusive access to a comprehensive Eco-Efficiency Manual, which outlined many of the opportunities available to the industry. Summary fact sheets were also prepared as publicly available resources and these are available for download below

Eco-efficiency for the Dairy Processing Industry

This manual has been developed to help the Australian dairy processing industry increase its competitiveness through increased awareness and uptake of eco-efficiency. The manual seeks to consolidate and build on existing knowledge, accumulated through projects and initiatives that the industry has previously undertaken to improve its use of raw materials and resources and reduce the generation of wastes. Where there is an existing comprehensive report or publication, the manual refers to this for further information. Eco-efficiency is about improving environmental performance to become more efficient and profitable. It is about producing more with less. It involves applying strategies that will not only ensure efficient use of resources and reduction in waste, but will also reduce costs. This chapter outlines the environmental challenges faced by Australian dairy processors. The manual explores opportunities for reducing environmental impacts in relation to water, energy, product yield, solid and liquid waste reduction and chemical use.