An EPN-based method for web service composition

Web service composition can be facilitated by an automatic process which consists of rules, conditions and actions. This research has adapted ElementaryPetri Net (EPN) to analyze and model the web services and their composition. This paper describes a set of techniques for representing transition rules, algorithm and workflow that web service composition can be automatically carried out.

Object-based three-dimensional X-ray imaging

A form of three-dimensional X-ray imaging, called Object 3-D, is introduced, where the relevant subject material is represented as discrete ‘objects’. The surface of each such object is derived accurately from the projections of its outline, and of its other discontinuities, in about ten conventional X-ray views, distributed in solid angle. This technique is suitable for many applications, and permits dramatic savings in radiation exposure and in data acquisition and manipulation. It is well matched to user-friendly interactive displays.

Development and validation of a qPCR-based method for quantifying Shiga toxin-encoding and other lambdoid bacteriophages

P>To address whether seasonal variability exists among Shiga toxin-encoding bacteriophage (Stx phage) numbers on a cattle farm, conventional plaque assay was performed on water samples collected over a 17 month period. Distinct seasonal variation in bacteriophage numbers was evident, peaking between June and August. Removal of cattle from the pasture precipitated a reduction in bacteriophage numbers, and during the winter months, no bacteriophage infecting Escherichia coli were detected, a surprising occurrence considering that 1031 tailed-bacteriophages are estimated to populate the globe. To address this discrepancy a culture-independent method based on quantitative PCR was developed. Primers targeting the Q gene and stx genes were designed that accurately and discriminately quantified artificial mixed lambdoid bacteriophage populations. Application of these primer sets to water samples possessing no detectable phages by plaque assay, demonstrated that the number of lambdoid bacteriophage ranged from 4.7 x 104 to 6.5 x 106 ml-1, with one in 103 free lambdoid bacteriophages carrying a Shiga toxin operon (stx). Specific molecular biological tools and discriminatory gene targets have enabled virus populations in the natural environment to be enumerated and similar strategies could replace existing propagation-dependent techniques, which grossly underestimate the abundance of viral entities.

A scalable and extensible segment-event-object-based sports video retrieval system

Sport video data is growing rapidly as a result of the maturing digital technologies that support digital video capture, faster data processing, and large storage. However, (1) semi-automatic content extraction and annotation, (2) scalable indexing model, and (3) effective retrieval and browsing, still pose the most challenging problems for maximizing the usage of large video databases. This article will present the findings from a comprehensive work that proposes a scalable and extensible sports video retrieval system with two major contributions in the area of sports video indexing and retrieval. The first contribution is a new sports video indexing model that utilizes semi-schema-based indexing scheme on top of an Object-Relationship approach. This indexing model is scalable and extensible as it enables gradual index construction which is supported by ongoing development of future content extraction algorithms. The second contribution is a set of novel queries which are based on XQuery to generate dynamic and user-oriented summaries and event structures. The proposed sports video retrieval system has been fully implemented and populated with soccer, tennis, swimming, and diving video. The system has been evaluated against 20 users to demonstrate and confirm its feasibility and benefits. The experimental sports genres were specifically selected to represent the four main categories of sports domain: period-, set-point-, time (race)-, and performance-based sports. Thus, the proposed system should be generic and robust for all types of sports.

Improving prediction interval quality : a genetic algorithm-based method applied to neural networks

The delta technique has been proposed in literature for constructing
prediction intervals for targets estimated by neural networks. Quality of constructed prediction intervals using this technique highly depends on neural network characteristics. Unfortunately, literature is void of information about how these dependences can be managed in order to optimize prediction intervals. This study attempts to optimize length and coverage probability of prediction intervals through modifying structure and parameters of the underlying neural networks. In an evolutionary optimization, genetic algorithm is applied for finding the optimal values of network size and training hyper-parameters. The applicability and efficiency of the proposed optimization technique is examined and demonstrated using a real case study. It is shown that application of the proposed optimization technique significantly improves quality of constructed prediction intervals in term of length and coverage probability.

A naïve, salience-based method for speaker identification in fiction books

This paper presents a salience-based technique for the annotation of directly quoted speech from fiction text. In particular, this paper determines to what extent a naïve (without the use of complex machine learning or knowledge-based techniques) scoring technique can be used for the identification of the speaker of speech quotes. The presented technique makes use of a scoring technique, similar to that commonly found in knowledge-poor anaphora resolution research, as well as a set of hand-coded rules for the final identification of the speaker of each quote in the text. Speaker identification is shown to be achieved using three tasks: the identification of a speech-verb associated with a quote with a recall of 94.41%; the identification of the actor associated with a quote with a recall of 88.22%; and the selection of a speaker with an accuracy of 79.40%.

Projection-pursuit-based method for blind separation of nonnegative sources

This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the inaccessible source matrix is normalized to be column-sum-to-1. Then, the PP method is proposed to solve this new model, where the mixing matrix is estimated column by column through tracing the projections to the mapped observations in specified directions, which leads to the recovery of the sources. The proposed method is much faster than Chan's method, which has similar assumptions to ours, due to the usage of optimal projection. It is also more advantageous in separating cross-correlated sources than the independence- and uncorrelation-based methods, as it does not employ any statistical information of the sources. Furthermore, the new method does not require the mixing matrix to be nonnegative. Simulation results demonstrate the superior performance of our method.

Progressive clustering based method for protein function prediction

In recent years, significant effort has been given to predicting protein functions from protein interaction data generated from high throughput techniques. However, predicting protein functions correctly and reliably still remains a challenge. Recently, many computational methods have been proposed for predicting protein functions. Among these methods, clustering based methods are the most promising. The existing methods, however, mainly focus on protein relationship modeling and the prediction algorithms that statically predict functions from the clusters that are related to the unannotated proteins. In fact, the clustering itself is a dynamic process and the function prediction should take this dynamic feature of clustering into consideration. Unfortunately, this dynamic feature of clustering is ignored in the existing prediction methods. In this paper, we propose an innovative progressive clustering based prediction method to trace the functions of relevant annotated proteins across all clusters that are generated through the progressive clustering of proteins. A set of prediction criteria is proposed to predict functions of unannotated proteins from all relevant clusters and traced functions. The method was evaluated on real protein interaction datasets and the results demonstrated the effectiveness of the proposed method compared with representative existing methods.

A new dempster-shafer theory-based method with fuzzy targets for fuzzy sets ranking

In this paper, a new Fuzzy Set (FS) ranking method (for type-1 and interval type-2 FSs), which is based on the Dempster-Shafer Theory (DST) of evidence with fuzzy targets, is investigated. Fuzzy targets are adopted to reflect human viewpoints on fuzzy ranking. Two important measures in DST, i.e., the belief and plausibility measures, are used to rank FSs. The proposed approach is evaluated with several benchmark examples. The use of the belief and plausibility measures in fuzzy ranking are discussed and compared. We further analyze the capability of the proposed approach in fulfilling six reasonable fuzzy ordering properties as discussed in [9]-[11].

A design-based method for estimating glomerular number in the developing kidney

Low glomerular (nephron) endowment has been associated with an increased risk of cardiovascular and renal disease in adulthood. Nephron endowment in humans is determined by 36 wk of gestation, while in rats and mice nephrogenesis ends several days after birth. Specific genes and environmental perturbations have been shown to regulate nephron endowment. Until now, design-based method for estimating nephron number in developing kidneys was unavailable. This was due in part to the difficulty associated with unambiguously identifying developing glomeruli in histological sections. Here, we describe a method that uses lectin histochemistry to identify developing glomeruli and the physical disector/fractionator principle to provide unbiased estimates of total glomerular number (Nglom). We have characterized Nglom throughout development in kidneys from 76 rats and model this development with a 5-parameter logistic equation to predict Nglom from embryonic day 17.25 to adulthood (r2 = 0.98). This approach represents the first design-based method with which to estimate Nglom in the developing kidney.

An interval type-2 fuzzy logic system-based method for prediction interval construction

This paper introduces a new non-parametric method for uncertainty quantification through construction of prediction intervals (PIs). The method takes the left and right end points of the type-reduced set of an interval type-2 fuzzy logic system (IT2FLS) model as the lower and upper bounds of a PI. No assumption is made in regard to the data distribution, behaviour, and patterns when developing intervals. A training method is proposed to link the confidence level (CL) concept of PIs to the intervals generated by IT2FLS models. The new PI-based training algorithm not only ensures that PIs constructed using IT2FLS models satisfy the CL requirements, but also reduces widths of PIs and generates practically informative PIs. Proper adjustment of parameters of IT2FLSs is performed through the minimization of a PI-based objective function. A metaheuristic method is applied for minimization of the non-linear non-differentiable cost function. Performance of the proposed method is examined for seven synthetic and real world benchmark case studies with homogenous and heterogeneous noise. The demonstrated results indicate that the proposed method is capable of generating high quality PIs. Comparative studies also show that the performance of the proposed method is equal to or better than traditional neural network-based methods for construction of PIs in more than 90% of cases. The superiority is more evident for the case of data with a heterogeneous noise. © 2014 Elsevier B.V.