AN ANALYSIS OF OPTIMAL FARM CAPITAL STRUCTURE

Agricultural Finance,

Soundness and unsoundness of banking sector in Nigeria: a discriminant analytical approach.

This paper set out to determine the factors that discriminate most in the classification of banks into sound and unsound position using method of discriminant analysis. Data used were sourced from the annual report of the Nigerian deposit and insurance corporation. The findings revealed the order of severity of institutional factors that could lead to bank distress. The none performing loans to total loans contributed about 53.4% of the total discriminant scores while capital to risk weighted asset contributed 19 percent to the group separation of the discriminant function. Others, gross loan to deposit ratio (with 14.34%), average liquidity ratio (with 9.25%) and insured deposit to total deposit (with 3.76%) made little discriminating contributions while the rest of the variables made insignificant contributions. Thus, by this reason of contribution, the 25% non scientifically determined (and subjective based judgment) component weight attached to asset quality in the CAMEL rating should be increased to at least 1/3 (30%) of the total weight components since its components are found to dominate the discriminant score.Soundness, Unsoundness, Bank Distress, Non Performing Loan, Capital to Risk Weighted Assets, CAMEL, Discriminant Analysis

Gait recognition based on shape and motion analysis of silhouette contours

This paper presents a three-phase gait recognition method that analyses the spatio-temporal shape and dynamic motion (STS-DM) characteristics of a human subject’s silhouettes to identify the subject in the presence of most of the challenging factors that affect existing gait recognition systems. In phase 1, phase-weighted magnitude spectra of the Fourier descriptor of the silhouette contours at ten phases of a gait period are used to analyse the spatio-temporal changes of the subject’s shape. A component-based Fourier descriptor based on anatomical studies of human body is used to achieve robustness against shape variations caused by all common types of small carrying conditions with folded hands, at the subject’s back and in upright position. In phase 2, a full-body shape and motion analysis is performed by fitting ellipses to contour segments of ten phases of a gait period and using a histogram matching with Bhattacharyya distance of parameters of the ellipses as dissimilarity scores. In phase 3, dynamic time warping is used to analyse the angular rotation pattern of the subject’s leading knee with a consideration of arm-swing over a gait period to achieve identification that is invariant to walking speed, limited clothing variations, hair style changes and shadows under feet. The match scores generated in the three phases are fused using weight-based score-level fusion for robust identification in the presence of missing and distorted frames, and occlusion in the scene. Experimental analyses on various publicly available data sets show that STS-DM outperforms several state-of-the-art gait recognition methods

Sufficient Covariate, Propensity Variable and Doubly Robust Estimation

Statistical causal inference from observational studies often requires adjustment for a possibly multi-dimensional variable, where dimension reduction is crucial. The propensity score, first introduced by Rosenbaum and Rubin, is a popular approach to such reduction. We address causal inference within Dawid's decision-theoretic framework, where it is essential to pay attention to sufficient covariates and their properties. We examine the role of a propensity variable in a normal linear model. We investigate both population-based and sample-based linear regressions, with adjustments for a multivariate covariate and for a propensity variable. In addition, we study the augmented inverse probability weighted estimator, involving a combination of a response model and a propensity model. In a linear regression with homoscedasticity, a propensity variable is proved to provide the same estimated causal effect as multivariate adjustment. An estimated propensity variable may, but need not, yield better precision than the true propensity variable. The augmented inverse probability weighted estimator is doubly robust and can improve precision if the propensity model is correctly specified

Weighted LDA techniques for I-vector based speaker verification

This paper introduces the Weighted Linear Discriminant Analysis (WLDA) technique, based upon the weighted pairwise Fisher criterion, for the purposes of improving i-vector speaker verification in the presence of high intersession variability. By taking advantage of the speaker discriminative information that is available in the distances between pairs of speakers clustered in the development i-vector space, the WLDA technique is shown to provide an improvement in speaker verification performance over traditional Linear Discriminant Analysis (LDA) approaches. A similar approach is also taken to extend the recently developed Source Normalised LDA (SNLDA) into Weighted SNLDA (WSNLDA) which, similarly, shows an improvement in speaker verification performance in both matched and mismatched enrolment/verification conditions. Based upon the results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset, we believe that both WLDA and WSNLDA are viable as replacement techniques to improve the performance of LDA and SNLDA-based i-vector speaker verification

Measuring Small Distances in N=2 Sigma Models

We analyze global aspects of the moduli space of K\"ahler forms for $N$=(2,2) conformal $\sigma$-models. Using algebraic methods and mirror symmetry we study extensions of the mathematical notion of length (as specified by a K\"ahler structure) to conformal field theory and calculate the way in which lengths change as the moduli fields are varied along distinguished paths in the moduli space. We find strong evidence supporting the notion that, in the robust setting of quantum Calabi-Yau moduli space, string theory restricts the set of possible K\"ahler forms by enforcing ``minimal length'' scales, provided that topology change is properly taken into account. Some lengths, however, may shrink to zero. We also compare stringy geometry to classical general relativity in this context.Comment: 62 pp. with 6 figs., LaTeX and epsf.te

Habitat requirements of black mudfish (Neochanna diversus) in the Waikato region, North Island, New Zealand.

Black mudfish (Neochanna diversus) were found at 39 of 80 sites in the Waikato region, New Zealand, ranging from large wetlands to small swampy streams. Of the sites with mudfish, 87% were dry at some time during summer. Sites with mudfish also generally had emergent and overhanging vegetation and tree roots, and showed low to moderate human impact. Black mudfish coexisted at some sites with juvenile eels or mosquitofish, but were absent from all sites with common bullies (Gobiomorphus cotidianus) or inanga (Galaxias maculatus). Sites with mudfish had almost exclusively semi-mineralised substrates or peat; only one site had mineralised substrate. Geometric mean catch rate for the 39 sites with mudfish was 0.70 fish per trap per night. Mean summer water depth was only 2.1 cm at sites with mudfish, compared to 22.6 cm at 41 sites without. Winter and maximum water depths were also less at sites with mudfish than at sites without mudfish. Mean turbidity was 11.5 nephelometric turbidity units (NTU) at sites with mudfish, but 21.3 NTU at sites without mudfish. Mudfish catch rates were negatively correlated with summer water depth, winter water depth, disturbance scale rating, and turbidity. A discriminant function model based on these variables successfully predicted 95% of the sites with mudfish. Habitat preference curves are also presented