FreeS: A fast algorithm to discover frequent free subtrees using a novel canonical form

Web data can often be represented in free tree form; however, free tree mining methods seldom exist. In this paper, a computationally fast algorithm FreeS is presented to discover all frequently occurring free subtrees in a database of labelled free trees. FreeS is designed using an optimal canonical form, BOCF that can uniquely represent free trees even during the presence of isomorphism. To avoid enumeration of false positive candidates, it utilises the enumeration approach based on a tree-structure guided scheme. This paper presents lemmas that introduce conditions to conform the generation of free tree candidates during enumeration. Empirical study using both real and synthetic datasets shows that FreeS is scalable and significantly outperforms (i.e. few orders of magnitude faster than) the state-of-the-art frequent free tree mining algorithms, HybridTreeMiner and FreeTreeMiner.

A fast method of comparing protein structures

Comparative studies on protein structures form an integral part of protein crystallography. Here, a fast method of comparing protein structures is presented. Protein structures are represented as a set of secondary structural elements. The method also provides information regarding preferred packing arrangements and evolutionary dynamics of secondary structural elements. This information is not easily obtained from previous methods. In contrast to those methods, the present one can be used only for proteins with some secondary structure. The method is illustrated with globin folds, cytochromes and dehydrogenases as examples.

Inspiration sources for Australian fast fashion design: Tapping into consumer desire

Purpose The research purpose was to identify both the inspiration sources used by fast fashion designers and ways the designers sort information from the sources during the product development process. Design/methodology/approach This is a qualitative study, drawing on semi-structured interviews conducted with the members of the in-house design teams of three Australian fast fashion companies. Findings Australian fast fashion designers rely on a combination of trend data, sales data, product analysis and travel for design development ideas. The designers then use the consensus and embodiment methods to interpret and synthesise information from those inspiration sources. Research limitations/implications The empirical data used in the analysis were limited by interviewing fashion designers within only three Australian companies. Originality/value This research augments knowledge of fast fashion product development, in particular designers’ methods and approaches to product design within a volatile and competitive market.

Characterisation of cellulose- and lignin-based materials using x-ray scattering methods

Wood is an important material for the construction and pulping industries. Using x-ray diffraction the microfibril angle of Sitka spruce wood was studied in the first part of this thesis. Sitka spruce (Picea sitchensis [Bong.] Carr.) is native to the west coast of North America, but due to its fast growth rate, it has also been imported to Europe. So far, its nanometre scale properties have not been systematically characterised. In this thesis the microfibril angle of Sitka spruce was shown to depend significantly on the origin of the tree in the first annual rings near the pith. Wood can be further processed to separate lignin from cellulose and hemicelluloses. Solid cellulose can act as a reducer for metal ions and it is also a porous support for nanoparticles. By chemically reducing nickel or copper in the solid cellulose support it is possible to get small nanoparticles on the surfaces of the cellulose fibres. Cellulose supported metal nanoparticles can potentially be used as environmentally friendly catalysts in organic chemistry reactions. In this thesis the size of the nickel and copper containing nanoparticles were studied using anomalous small-angle x-ray scattering and wide-angle x-ray scattering. The anomalous small-angle x-ray scattering experiments showed that the crystallite size of the copper oxide nanoparticles was the same as the size of the nanoparticles, so the nanoparticles were single crystals. The nickel containing nanoparticles were amorphous, but crystallised upon heating. The size of the nanoparticles was observed to be smaller when the reduction of nickel was done in aqueous ammonium hydrate medium compared to reduction made in aqueous solution. Lignin is typically seen as the side-product of wood industries. Lignin is the second most abundant natural polymer on Earth, and it possesses potential to be a useful material for many purposes in addition to being an energy source for the pulp mills. In this thesis, the morphology of several lignins, which were produced by different separation methods from wood, was studied using small-angle and ultra small-angle x-ray scattering. It was shown that the fractal model previously proposed for the lignin structure does not apply to most of the extracted lignin types. The only lignin to which the fractal model could be applied was kraft lignin. In aqueous solutions the average shape of the low molar mass kraft lignin particles was observed to be elongated and flat. The average shape does not necessarily correspond to the shape of the individual particles because of the polydispersity of the fraction and due to selfassociation of the particles. Lignins, and especially lignosulfonate, have many uses as dispersants, binders and emulsion stabilisers. In this thesis work the selfassociation of low molar mass lignosulfonate macromolecules was observed using small-angle x-ray scattering. By taking into account the polydispersity of the studied lignosulfonate fraction, the shape of the lignosulfonate particles was determined to be flat by fitting an oblate ellipsoidal model to the scattering intensity.

Development of radiosynthesis methods for 18F-labelled radiopharmaceuticals : General considerations and production of a dopamine transporter radioligand

Positron emission tomography (PET) is a molecular imaging technique that utilises radiopharmaceuticals (radiotracers) labelled with a positron-emitting radionuclide, such as fluorine-18 (18F). Development of a new radiotracer requires an appropriate radiosynthesis method: the most common of which with 18F is nucleophilic substitution with [18F]fluoride ion. The success of the labelling reaction is dependent on various factors such as the reactivity of [18F]fluoride, the structure of the target compound in addition to the chosen solvent. The overall radiosynthesis procedure must be optimised in terms of radiochemical yield and quality of the final product. Therefore, both quantitative and qualitative radioanalytical methods are essential in developing radiosynthesis methods. Furthermore, biological properties of the tracer candidate need to be evaluated by various pre-clinical studies in animal models. In this work, the feasibility of various nucleophilic 18F-fluorination strategies were studied and a labelling method for a novel radiotracer, N-3-[18F]fluoropropyl-2beta-carbomethoxy-3beta-4-fluorophenyl)nortropane ([18F]beta-CFT-FP), was optimised. The effect of solvent was studied by labelling a series of model compounds, 4-(R1-methyl)benzyl R2-benzoates. 18F-Fluorination reactions were carried out both in polar aprotic and protic solvents (tertiary alcohols). Assessment of the 18F-fluorinated products was studied by mass spectrometry (MS) in addition to conventional radiochromatographic methods, using radiosynthesis of 4-[18F]fluoro-N-[2-[1-(2-methoxyphenyl)-1-piperazinyl]ethyl-N-2-pyridinyl-benzamide (p-[18F]MPPF) as a model reaction. Labelling of [18F]beta-CFT-FP was studied using two 18F-fluoroalkylation reagents, [18F]fluoropropyl bromide and [18F]fluoropropyl tosylate, as well as by direct 18F-fluorination of sulfonate ester precursor. Subsequently, the suitability of [18F]beta-CFT-FP for imaging dopamine transporter (DAT) was evaluated by determining its biodistribution in rats. The results showed that protic solvents can be useful co-solvents in aliphatic 18F-fluorinations, especially in the labelling of sulfonate esters. Aromatic 18F-fluorination was not promoted in tert-alcohols. Sensitivity of the ion trap MS was sufficient for the qualitative analysis of the 18F-labelled products; p-[18F]MPPF was identified from the isolated product fraction with a mass-to-charge (m/z) ratio of 435 (i.e. protonated molecule [M+H]+). [18F]beta-CFT-FP was produced most efficiently via [18F]fluoropropyl tosylate, leading to sufficient radiochemical yield and specific radioactivity for PET studies. The ex vivo studies in rats showed fast kinetics as well as the specific uptake of [18F]beta-CFT-FP to the DAT rich brain regions. Thus, it was concluded that [18F]beta-CFT-FP has potential as a radiotracer for imaging DAT by PET.

A fast quasi-Newton method for semi-supervised SVM

Due to its wide applicability, semi-supervised learning is an attractive method for using unlabeled data in classification. In this work, we present a semi-supervised support vector classifier that is designed using quasi-Newton method for nonsmooth convex functions. The proposed algorithm is suitable in dealing with very large number of examples and features. Numerical experiments on various benchmark datasets showed that the proposed algorithm is fast and gives improved generalization performance over the existing methods. Further, a non-linear semi-supervised SVM has been proposed based on a multiple label switching scheme. This non-linear semi-supervised SVM is found to converge faster and it is found to improve generalization performance on several benchmark datasets. (C) 2010 Elsevier Ltd. All rights reserved.

A fast algorithm for finding frequent episodes in event streams

Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the frequency of an episode is some suitable measure of how often the episode occurs in the data sequence. Recently,we proposed a new frequency measure for episodes based on the notion of non-overlapped occurrences of episodes in the event sequence, and showed that, such a definition, in addition to yielding computationally efficient algorithms, has some important theoretical properties in connecting frequent episode discovery with HMM learning. This paper presents some new algorithms for frequent episode discovery under this non-overlapped occurrences-based frequency definition. The algorithms presented here are better (by a factor of N, where N denotes the size of episodes being discovered) in terms of both time and space complexities when compared to existing methods for frequent episode discovery. We show through some simulation experiments, that our algorithms are very efficient. The new algorithms presented here have arguably the least possible orders of spaceand time complexities for the task of frequent episode discovery.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

AIWIN - A fast and jigless inspection technique for machined parts

Precision inspection of manufactured components having multiple complex surfaces and variable tolerance definition is an involved, complex and time-consuming function. In routine practice, a jig is used to present the part in a known reference frame to carry out the inspection process. Jigs involve both time and cost in their development, manufacture and use. This paper describes 'as is where is inspection' (AIWIN), a new automated inspection technique that accelerates the inspection process by carrying out a fast registration procedure and establishing a quick correspondence between the part to inspect and its CAD geometry. The main challenge in doing away with a jig is that the inspection reference frame could be far removed from the CAD frame. Traditional techniques based on iterative closest point (ICP) or Newton methods require either a large number of iterations for convergence or fail in such a situation. A two-step coarse registration process is proposed to provide a good initial guess for a modified ICP algorithm developed earlier (Ravishankar et al., Int J Adv Manuf Technol 46(1-4):227-236, 2010). The first step uses a calibrated sphere for local hard registration and fixing the translation error. This transformation locates the centre for the sphere in the CAD frame. In the second step, the inverse transformation (involving pure rotation about multiple axes) required to align the inspection points measured on the manufactured part with the CAD point dataset of the model is determined and enforced. This completes the coarse registration enabling fast convergence of the modified ICP algorithm. The new technique has been implemented on complex freeform machined components and the inspection results clearly show that the process is precise and reliable with rapid convergence. © 2011 Springer-Verlag London Limited.

Fast Likelihood Computation in Speech Recognition using Matrices

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for Large Vocabulary Continuous Speech Recognition (LVCSR) systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication. In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on 1,138 work vocabulary RM1 task and 6,224 word vocabulary TIMIT task using Sphinx 3.7 system show that, for a typical case the matrix multiplication based approach leads to overall speedup of 46 % on RM1 task and 115 % for TIMIT task. Our low-rank approximation methods provide a way for trading off recognition accuracy for a further increase in computational performance extending overall speedups up to 61 % for RM1 and 119 % for TIMIT for an increase of word error rate (WER) from 3.2 to 3.5 % for RM1 and for no increase in WER for TIMIT. We also express pairwise Euclidean distance computation phase in Dynamic Time Warping (DTW) in terms of matrix multiplication leading to saving of approximately of computational operations. In our experiments using efficient implementation of matrix multiplication, this leads to a speedup of 5.6 in computing the pairwise Euclidean distances and overall speedup up to 3.25 for DTW.

Fast acoustic likelihood computation using low-rank matrix approximation

Acoustic modeling using mixtures of multivariate Gaussians is the prevalent approach for many speech processing problems. Computing likelihoods against a large set of Gaussians is required as a part of many speech processing systems and it is the computationally dominant phase for LVCSR systems. We express the likelihood computation as a multiplication of matrices representing augmented feature vectors and Gaussian parameters. The computational gain of this approach over traditional methods is by exploiting the structure of these matrices and efficient implementation of their multiplication.In particular, we explore direct low-rank approximation of the Gaussian parameter matrix and indirect derivation of low-rank factors of the Gaussian parameter matrix by optimum approximation of the likelihood matrix. We show that both the methods lead to similar speedups but the latter leads to far lesser impact on the recognition accuracy. Experiments on a 1138 word vocabulary RM1 task using Sphinx 3.7 system show that, for a typical case the matrix multiplication approach leads to overall speedup of 46%. Both the low-rank approximation methods increase the speedup to around 60%, with the former method increasing the word error rate (WER) from 3.2% to 6.6%, while the latter increases the WER from 3.2% to 3.5%.

A fast NMR method for resonance assignments: application to metabolomics

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled (C-12) or C-13-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D C-13, H-1] HSQC-TOCSY, (2) 2D H-1-H-1 TOCSY and (3) 2D C-13-H-1 HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D C-13, H-1] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete H-1 and C-13 assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.

On Fast Bilateral Filtering Using Fourier Kernels

It was demonstrated in earlier work that, by approximating its range kernel using shiftable functions, the nonlinear bilateral filter can be computed using a series of fast convolutions. Previous approaches based on shiftable approximation have, however, been restricted to Gaussian range kernels. In this work, we propose a novel approximation that can be applied to any range kernel, provided it has a pointwise-convergent Fourier series. More specifically, we propose to approximate the Gaussian range kernel of the bilateral filter using a Fourier basis, where the coefficients of the basis are obtained by solving a series of least-squares problems. The coefficients can be efficiently computed using a recursive form of the QR decomposition. By controlling the cardinality of the Fourier basis, we can obtain a good tradeoff between the run-time and the filtering accuracy. In particular, we are able to guarantee subpixel accuracy for the overall filtering, which is not provided by the most existing methods for fast bilateral filtering. We present simulation results to demonstrate the speed and accuracy of the proposed algorithm.

Methods of Obtaining Instantaneous Modulus of Viscoelastic Solids Using Displacement-Controlled Instrumented Indentation with Axisymmetric Indenters of Arbitrary Smooth Profiles

We derive a relationship between the initial unloading slope, contact depth, and the instantaneous relaxation modulus for displacement-controlled indentation in linear viscoelastic solids by a rigid indenter with an arbitrary axisymmetric smooth profile. While the same expression is well known for indentation in elastic and in elastic–plastic solids, we show that it is also true for indentation in linear viscoelastic solids, provided that the unloading rate is sufficiently fast. When the unloading rate is slow, a “hold” period between loading and unloading can be used to provide a correction term for the initial unloading slope equation. Finite element calculations are used to illustrate the methods of fast unloading and “hold-at-the-maximum-indenter-displacement” for determining the instantaneous modulus using spherical indenters.

Methods of Obtaining Instantaneous Modulus of Viscoelastic Solids Using Displacement-Controlled Instrumented Indentation with Axisymmetric Indenters of Arbitrary Smooth Profiles

We derive a relationship between the initial unloading slope, contact depth, and the instantaneous relaxation modulus for displacement-controlled indentation in linear viscoelastic solids by a rigid indenter with an arbitrary axisymmetric smooth profile. While the same expression is well known for indentation in elastic and in elastic-plastic solids, we show that it is also true for indentation in linear viscoelastic solids, provided that the unloading rate is sufficiently fast. When the unloading rate is slow, a "hold" period between loading and unloading can be used to provide a correction term for the initial unloading slope equation. Finite element calculations are used to illustrate the methods of fast unloading and "hold-at-the-maximum-indenter-displacement" for determining the instantaneous modulus using spherical indenters.