Feature selection and the concept of immediate neighborhood in the context of clustering techniques

The concept of feature selection in a nonparametric unsupervised learning environment is practically undeveloped because no true measure for the effectiveness of a feature exists in such an environment. The lack of a feature selection phase preceding the clustering process seriously affects the reliability of such learning. New concepts such as significant features, level of significance of features, and immediate neighborhood are introduced which result in meeting implicitly the need for feature slection in the context of clustering techniques.

Development and psychometric properties of the DCDDaily: a new test for clinical assessment of capacity in activities of daily living in children with developmental coordination disorder

Objective To develop the DCDDaily, an instrument for objective and standardized clinical assessment of capacity in activities of daily living (ADL) in children with developmental coordination disorder (DCD), and to investigate its usability, reliability, and validity. Subjects Five to eight-year-old children with and without DCD. Main measures The DCDDaily was developed based on thorough review of the literature and extensive expert involvement. To investigate the usability (assessment time and feasibility), reliability (internal consistency and repeatability), and validity (concurrent and discriminant validity) of the DCDDaily, children were assessed with the DCDDaily and the Movement Assessment Battery for Children-2 Test, and their parents filled in the Movement Assessment Battery for Children-2 Checklist and Developmental Coordination Disorder Questionnaire. Results 459 children were assessed (DCD group, n = 55; normative reference group, n = 404). Assessment was possible within 30 minutes and in any clinical setting. For internal consistency, Cronbach’s α = 0.83. Intraclass correlation = 0.87 for test–retest reliability and 0.89 for inter-rater reliability. Concurrent correlations with Movement Assessment Battery for Children-2 Test and questionnaires were ρ = −0.494, 0.239, and −0.284, p < 0.001. Discriminant validity measures showed significantly worse performance in the DCD group than in the control group (mean (SD) score 33 (5.6) versus 26 (4.3), p < 0.001). The area under curve characteristic = 0.872, sensitivity and specificity were 80%. Conclusions The DCDDaily is a valid and reliable instrument for clinical assessment of capacity in ADL, that is feasible for use in clinical practice.

The effect of lecithin on the burning rate of AP-Al---polyester propellant

Abstract is not available.

On Minimization of Peak Power for Scan Circuit during Test

Scan circuit generally causes excessive switching activity compared to normal circuit operation. The higher switching activity in turn causes higher peak power supply current which results into supply, voltage droop and eventually yield loss. This paper proposes an efficient methodology for test vector re-ordering to achieve minimum peak power supported by the given test vector set. The proposed methodology also minimizes average power under the minimum peak power constraint. A methodology to further reduce the peak power below the minimum supported peak power, by inclusion of minimum additional vectors is also discussed. The paper defines the lower bound on peak power for a given test set. The results on several benchmarks shows that it can reduce peak power by up to 27%.

Malaria rapid diagnostic test performance: Results of WHO product testing of malaria RDTs: Round 6 (2014-2015)

Overview This report, published in conjunction with a summary overview of results of rounds 1–6, is the sixth in a series of laboratory-based evaluations of rapid diagnostic tests (RDTs) for malaria. It provides a comparative measure of their performance in a standardized way to distinguish between well and poorly performing tests. It can be used by malaria control programmes and guide WHO procurement recommendations for these diagnostic tools. The evaluation reported here was a joint project of the WHO Global Malaria Programme, the Foundation for Innovative New Diagnostics (FIND) and the United States Centers for Disease Control and Prevention (CDC) within the WHO-FIND Malaria RDT Evaluation Programme. The project was financed by FIND through a grant from UNITAID.

Aircraft trajectory clustering techniques using circular statistics

This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

Two-level k-means clustering algorithm for k-tau relationship establishment and linear-time classification

Partitional clustering algorithms, which partition the dataset into a pre-defined number of clusters, can be broadly classified into two types: algorithms which explicitly take the number of clusters as input and algorithms that take the expected size of a cluster as input. In this paper, we propose a variant of the k-means algorithm and prove that it is more efficient than standard k-means algorithms. An important contribution of this paper is the establishment of a relation between the number of clusters and the size of the clusters in a dataset through the analysis of our algorithm. We also demonstrate that the integration of this algorithm as a pre-processing step in classification algorithms reduces their running-time complexity.

Free and ATP-bound structures of Ap(4)A hydrolase from Aquifex aeolicus V5

Asymmetric diadenosine tetraphosphate (Ap(4)A) hydrolases degrade the metabolite Ap(4)A back into ATP and AMP. The three-dimensional crystal structure of Ap(4)A hydrolase (16 kDa) from Aquifex aeolicus has been determined in free and ATP-bound forms at 1.8 and 1.95 angstrom resolution, respectively. The overall three-dimensional crystal structure of the enzyme shows an alpha beta alpha-sandwich architecture with a characteristic loop adjacent to the catalytic site of the protein molecule. The ATP molecule is bound in the primary active site and the adenine moiety of the nucleotide binds in a ring-stacking arrangement equivalent to that observed in the X-ray structure of Ap(4)A hydrolase from Caenorhabditis elegans. Binding of ATP in the active site induces local conformational changes which may have important implications in the mechanism of substrate recognition in this class of enzymes. Furthermore, two invariant water molecules have been identified and their possible structural and/or functional roles are discussed. In addition, modelling of the substrate molecule at the primary active site of the enzyme suggests a possible path for entry and/or exit of the substrate and/or product molecule.

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

Evaluation of Vestibular Function with Visual Feedback Posturography and Motorized Head Impulse Test.

Objectives: To evaluate the applicability of visual feedback posturography (VFP) for quantification of postural control, and to characterize the horizontal angular vestibulo-ocular reflex (AVOR) by use of a novel motorized head impulse test (MHIT). Methods: In VFP, subjects standing on a platform were instructed to move their center of gravity to symmetrically placed peripheral targets as fast and accurately as possible. The active postural control movements were measured in healthy subjects (n = 23), and in patients with vestibular schwannoma (VS) before surgery (n = 49), one month (n = 17), and three months (n = 36) after surgery. In MHIT we recorded head and eye position during motorized head impulses (mean velocity of 170º/s and acceleration of 1 550º/s²) in healthy subjects (n = 22), in patients with VS before surgery (n = 38) and about four months afterwards (n = 27). The gain, asymmetry and latency in MHIT were calculated. Results: The intraclass correlation coefficient for VFP parameters during repeated tests was significant (r = 0.78-0.96; p < 0.01), although two of four VFP parameters improved slightly during five test sessions in controls. At least one VFP parameter was abnormal pre- and postoperatively in almost half the patients, and these abnormal preoperative VFP results correlated significantly with abnormal postoperative results. The mean accuracy in postural control in patients was reduced pre- and postoperatively. A significant side difference with VFP was evident in 10% of patients. In the MHIT, the normal gain was close to unity, the asymmetry in gain was within 10%, and the latency was a mean ± standard deviation 3.4 ± 6.3 milliseconds. Ipsilateral gain or asymmetry in gain was preoperatively abnormal in 71% of patients, whereas it was abnormal in every patient after surgery. Preoperative gain (mean ± 95% confidence interval) was significantly lowered to 0.83 ± 0.08 on the ipsilateral side compared to 0.98 ± 0.06 on the contralateral side. The ipsilateral postoperative mean gain of 0.53 ± 0.05 was significantly different from preoperative gain. Conclusion: The VFP is a repeatable, quantitative method to assess active postural control within individual subjects. The mean postural control in patients with VS was disturbed before and after surgery, although not severely. Side difference in postural control in the VFP was rare. The horizontal AVOR results in healthy subjects and in patients with VS, measured with MHIT, were in agreement with published data achieved using other techniques with head impulse stimuli. The MHIT is a non-invasive method which allows reliable clinical assessment of the horizontal AVOR.

Significance of a short-term test drive for prospective plug-in electric vehicle consumers: An exploratory study

The test drive is a well-known step in car buying. In the emerging plug-in electric vehicle (PEV) market, however, the influence of a pre-purchase test drive on a consumer's inclination to purchase is unknown. Policy makers and industry participants both are eager to understand what factors motivate vehicle consumers at the point-of-sale. A number of researchers have used choice models to shed light on consumer perceptions of PEVs, and others have investigated consumer change in disposition toward a PEV over the course of a trial, wherein test driving a PEV may take place over a number of consecutive days, weeks or months. However, there is little written on the impact of a short-term test drive - a typical experience at dealerships or public "ride-and-drive" events. The impact of a typical test drive, often measured in minutes of driving, is not well understood. This paper first presents a synthesis of the literature on the effect of PEV test drives as they relate to consumer disposition toward PEVs. An analysis of data obtained from an Australian case study whereby attitudinal and stated preference data were collected pre- and post- test drive at public "ride-and-drive" event held Brisbane, Queensland in March 2014 using a custom-designed iPad application. Motorists' perceptions and choice preferences around PEVs were captured, revealing the relative importance of their experience behind the wheel. Using the Australian context as a case-study, this paper presents an exploratory study of consumers' stated preferences toward PEVs both before and after a short test drive.

Critical test for Altshuler-Aronov theory: Evolution of the density of states singularity in double perovskite Sr2FeMoO6 with controlled disorder

With high-resolution photoemission spectroscopy measurements, the density of states (DOS) near the Fermi level (E-F) of double perovskite Sr2FeMoO6 having different degrees of Fe/Mo antisite disorder has been investigated with varying temperature. The DOS near E-F showed a systematic depletion with increasing degree of disorder, and recovered with increasing temperature. Altshuler-Aronov (AA) theory of disordered metals well explains the dependences of the experimental results. Scaling analysis of the spectra provides experimental indication for the functional form of the AA DOS singularity.

Molecular phylogeny and biogeography of langurs and leaf monkeys of South Asia (Primates: Colobinae)

The two recently proposed taxonomies of the langurs and leaf monkeys (Subfamily Colobinae) provide different implications to our understanding of the evolution of Nilgiri and purple-faced langurs. Groves (2001) [Groves, C.P., 2001. Primate Taxonomy. Smithsonian Institute Press, Washington], placed Nilgiri and purple-faced langurs in the genus Trachypithecus, thereby suggesting disjunct distribution of the genus Trachypithecus. [Brandon-Jones, D., Eudey, A.A., Geissmann, T., Groves, C.P., Melnick, D.J., Morales, J.C., Shekelle, M., Stewart, C.-B., 2003. Asian primate classification. Int. J. Primatol. 25, 97–162] placed these langurs in the genus Semnopithecus, which suggests convergence of morphological characters in Nilgiri and purple-faced langurs with Trachypithecus. To test these scenarios, we sequenced and analyzed the mitochondrial cytochrome b gene and two nuclear DNA-encoded genes, lysozyme and protamine P1, from a variety of colobine species. All three markers support the clustering of Nilgiri and purple-faced langurs with Hanuman langur (Semnopithecus), while leaf monkeys of Southeast Asian (Trachypithecus) form a distinct clade. The phylogenetic position of capped and golden leaf monkeys is still unresolved. It is likely that this species group might have evolved due to past hybridization between Semnopithecus and Trachypithecus clades.

RACK: RApid Clustering using K-means algorithm

The k-means algorithm is an extremely popular technique for clustering data. One of the major limitations of the k-means is that the time to cluster a given dataset D is linear in the number of clusters, k. In this paper, we employ height balanced trees to address this issue. Specifically, we make two major contributions, (a) we propose an algorithm, RACK (acronym for RApid Clustering using k-means), which takes time favorably comparable with the fastest known existing techniques, and (b) we prove an expected bound on the quality of clustering achieved using RACK. Our experimental results on large datasets strongly suggest that RACK is competitive with the k-means algorithm in terms of quality of clustering, while taking significantly less time.