A data mining based method for discovery of web services and their compositions

Due to the availability of huge number of web services, finding an appropriate Web service according to the requirements of a service consumer is still a challenge. Moreover, sometimes a single web service is unable to fully satisfy the requirements of the service consumer. In such cases, combinations of multiple inter-related web services can be utilised. This paper proposes a method that first utilises a semantic kernel model to find related services and then models these related Web services as nodes of a graph. An all-pair shortest-path algorithm is applied to find the best compositions of Web services that are semantically related to the service consumer requirement. The recommendation of individual and composite Web services composition for a service request is finally made. Empirical evaluation confirms that the proposed method significantly improves the accuracy of service discovery in comparison to traditional keyword-based discovery methods.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

A genetic analysis of cortical thickness in 372 twins

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. In structural equation models fitted to volume values at each surface vertex, we computed components of variance due to additive genetic (A), shared (C) and unique (E) environmental factors, and tested their significance. Cortical regions in the vicinity of the perisylvian language cortex, and at the frontal and temporal poles, showed significant additive genetic variance, suggesting that volume measures from these regions may provide quantitative phenotypes to narrow the search for quantitative trait loci that influence brain structure.

Twist phase in Gaussian-beam optics

The recently discovered twist phase is studied in the context of the full ten-parameter family of partially coherent general anisotropic Gaussian Schell-model beams. It is shown that the nonnegativity requirement on the cross-spectral density of the beam demands that the strength of the twist phase be bounded from above by the inverse of the transverse coherence area of the beam. The twist phase as a two-point function is shown to have the structure of the generalized Huygens kernel or Green's function of a first-order system. The ray-transfer matrix of this system is exhibited. Wolf-type coherent-mode decomposition of the twist phase is carried out. Imposition of the twist phase on an otherwise untwisted beam is shown to result in a linear transformation in the ray phase space of the Wigner distribution. Though this transformation preserves the four-dimensional phase-space volume, it is not symplectic and hence it can, when impressed on a Wigner distribution, push it out of the convex set of all bona fide Wigner distributions unless the original Wigner distribution was sufficiently deep into the interior of the set.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Estimation for the general sample selection models

Consider a general regression model with an arbitrary and unknown link function and a stochastic selection variable that determines whether the outcome variable is observable or missing. The paper proposes U-statistics that are based on kernel functions as estimators for the directions of the parameter vectors in the link function and the selection equation, and shows that these estimators are consistent and asymptotically normal.

Standard errors and covariance matrices for smoothed rank estimators

A 'pseudo-Bayesian' interpretation of standard errors yields a natural induced smoothing of statistical estimating functions. When applied to rank estimation, the lack of smoothness which prevents standard error estimation is remedied. Efficiency and robustness are preserved, while the smoothed estimation has excellent computational properties. In particular, convergence of the iterative equation for standard error is fast, and standard error calculation becomes asymptotically a one-step procedure. This property also extends to covariance matrix calculation for rank estimates in multi-parameter problems. Examples, and some simple explanations, are given.

On the eigenvalues and eigenfunctions of some integral operators

Some properties of the eigenvalues of the integral operator Kgt defined as Kτf(x) = ∫0τK(x − y) f (y) dy were studied by [1.], 554–566), with some assumptions on the kernel K(x). In this paper the eigenfunctions of the operator Kτ are shown to be continuous functions of τ under certain circumstances. Also, the results of Vittal Rao and the continuity of eigenfunctions are shown to hold for a larger class of kernels.

Maturation studies of pecan nuts grown in Queensland

Changes in chemical composition, physical and sensory characteristics were followed in two pecan cultivars Wichita and Western Schley harvested from a commercial orchard at Gatton in Queensland seven times during 1996.Testa colour of both pecan cultivars darkened and opalescence decreased as the nuts matured. Bitterness of Western Schley pecans decreased with maturity. Colour of shuck, shell and kernel of both cultivars developed as the nuts matured. Wichita pecans were larger than Western Schley at all harvest times. Both nut-in-shell and kernel moisture decreased with maturity, whereas oil and sucrose contents increased. Both pecan cultivars had reached advanced maturation by the first harvest on March 18.

CLXXX. Vegetable Proteins. I. The Proteins of Dolichos Lab Lab

The field bean (Dolichos lab lab ; Tamil name, Mochai ; Kanarese, Avarai) is a legume which is widely cultivated in South India often as a mixed crop with cereals. The kernel of the seed enters into the diet of may South Indian households, and in the Mysore State the seed are used as a delicacy when they are green for over four months in the year. The haulm, husk and pods are commonly used a fodder. As the kernel which is widely used as an article of food and considered to be very nutritious, contains about 24% of protein hitherto uninvestigated and as the quality of protein plays an important role in nutrition, the present work was undertaken.

Storage of Macadamia Nut-In-Shell

The effect of moisture content and storage temperature on the high quality storage life on macadamia nut-in-shell (NIS), and the subsequent influence of NIS storage on the shelf-life of roasted kernel, is being investigated. Macadamia integrifolia 'Keauhou" (HAES 246) NIS is being stored at 5°, 25°C and 40°C with a moisture content of 15.0, 12.5, 10.0, 7.5 and 3.5% for a maximum of 12 months. Preliminary results showed that unacceptable levels of visual mould developed on NIS with 15.0 and 12.5% moisture at 25°C following relatively short periods of storage. Discolouration and the production of an off-flavour in the raw kernel resulted after 1 month's storage of NIS with a moisture content of 10.0% at 40°C. Roasting times were reduced with increased storage duration of NIS with a moisture content of 15.0, 12.5 and 10.0% at 25°C, 15.0 and 12.5% at 5°C and 3.5% at 40°C. The percentage of roasted kernel rejects increased with increased storage duration of NIS with a moisture content of 15.0 and 12.5% at 25°C.

Alternative fungicides for controlling husk spot caused by Pseudocercospora macadamiae in macadamia

Husk spot, caused by Pseudocercospora macadamiae is a major fungal disease of macadamia in Australia. Chemicals to control the disease are limited and frequent failure to control the disease is a major concern to growers. The overall goal of this research was to improve the chemical control strategy of P. macadamiae through the provision of fungicides with different modes of action to carbendazim, which is the current industry standard. Husk spot incidence, premature fruit abscission, kernel quality and yield were evaluated following application of different fungicide products in replicated field experiments at three different sites. Results showed significant differences in disease incidence and premature fruit abscission between fungicide treatments, field sites and years. Generally, disease incidence and premature fruit abscission on trees treated with fungicide were significantly (P < 0.05) lower than the untreated control. Pyraclostrobin conferred significantly better protection than trifloxystrobin, reducing disease severity by 70% compared with a 50% reduction by trifloxystrobin. The pyraclostrobin treatment had a similar efficacy to the current industry standard (70% reduction cf. 73% reduction by tank-mixed carbendazim and copper). Higher amounts of immature kernels occurred in the untreated control, followed by difenoconazole and trifloxystrobin. Diseased fruit accounted for 78% of premature fruit abscission, which indicates that husk spot enhances fruit abscission in macadamia. Our results suggest that pyraclostrobin provided similar efficacy to the industry standard and could, therefore, play a key role in the management of husk spot.

Genetic Impacts of the Hull on Barley Grain Quality

Barley hull plays an important role in malt and feed quality and processing. In this study we measured the variation in hull con-tent along with other grain quality traits namely, kernel discolouration and degree of pre-harvest sprouting, in a single map-ping population. There were significant (p < 0.05) genetic as well as environment effects. In addition, heritability was calculated for hull content to be 29% and 47% for two years’ data. From the analysis, major QTL markers were identified in con-trolling the expression of hull content on chromosomes 2 (2H), and 6 (6H) with significant (P < 0.05) LOD scores of 5.4 and 3.46 respectively. Minor QTLs were identified on 1 (7H), 4 (4H), 5 (1H) and 7 (5H). The region at marker Bmac310 on 4(4H) could be associated with dormancy gene SD4. A number of the QTLs also coincided with regions for either kernel discolouration or preharvest sprouting resistance (dormancy). The results indicate that variation exists for hull content, which is influenced by both growing environment as well as genetically, although the genetic variance explained less than half of the total variance. Further, hull content also impacts on other grain quality attributes including dormancy, sprouting resistance and kernel appearance.

Measurement of genetic and environmental variation in barley (Hordeum vulgare) grain hardness

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.

Characterization of tree-to-tree variation in morphological, nutritional and medicinal properties of Canarium indicum nuts

As part of a feasibility study of the commercialization potential of C. indicum nuts as Agroforestry Tree Products in Papua New Guinea, preliminary characterization studies have examined the tree-to-tree variation in morphological traits (nut and kernel mass and kernel:nut ratio), as well as nutritional (carbohydrate, fat, protein, sodium, vitamin E) and medicinal traits (anti-oxidant activity, anti-inflammatory activity and phenolic content) of kernels from 18 to 72 trees in a small number of different villages of Papua New Guinea (East New Britain Province). There was continuous variation in these traits indicating opportunities for multiple trait cultivar development targeted at food and pharmaceutical markets. Certain traits, for example anti-inflammatory activity, in which tree-to-tree variation was highly significant, present greater opportunities than others, such as saturated:unsaturated fatty acid ratio. This intraspecific variation was greater within populations than between populations. The data presented has allowed the development of a strategy to domesticate C. indicum for cultivation in homegardens and cocoa-coconut agroforests, using a participatory approach aimed at the production of agroforestry tree products (AFTPs) to empower small-holders and enhance their livelihoods and income.