Evolutionary methods for unsupervised feature selection using Sammon’s stress function

In this paper, four methods are proposed for feature selection in an unsupervised manner by using genetic algorithms. The proposed methods do not use the class label information but select a set of features using a task independent criterion that can preserve the geometric structure (topology) of the original data in the reduced feature space. One of the components of the fitness function is Sammon’s stress function which tries to preserve the topology of the high dimensional data when reduced into the lower dimensional one. In this context, in addition to using a fitness criterion, we also explore the utility of unfitness criterion to select chromosomes for genetic operations. This ensures higher diversity in the population and helps unfit chromosomes to become more fit. We use four different ways for evaluation of the quality of the features selected: Sammon error, correlation between the inter-point distances in the two spaces, a measure of preservation of cluster structure found in the original and reduced spaces and a classifier performance. The proposed methods are tested on six real data sets with dimensionality varying between 9 and 60. The selected features are found to be excellent in terms of preservation topology (inter-point geometry), cluster structure and classifier performance. We do not compare our methods with other methods because, unlike other methods, using four different ways we check the quality of the selected features by finding how well the selected features preserve the “structure” of the original data.     

A pseudopotential approach to the superconducting state properties of Cu<Subscript>C</Subscript>Zr<Subscript>100-C</Subscript> binary metallic glasses

The theoretical investigation of the superconducting state properties viz. electron-phonon coupling strength λ, Coulomb pseudopotential μ*, transition temperature T _C, isotope effect exponent α and effective interaction strength N ₀ V of ten binary Cu_CZr_100-C (C = 25–60 at%) metallic glasses is performed, using Ashcroft’s empty core model potential. Five local-field correction functions proposed by Hartree (H), Taylor (T), Ichimaru-Utsumi (IU), Farid et al. (F) and Sarkar et al. (S) are used to study the screening influence on the aforesaid properties. It is shown that the electronphonon coupling strength λ and the transition temperature T _C are quite sensitive to the selection of the local-field correction functions, whereas the Coulomb pseudopotential μ*, isotope effect exponent α and effective interaction strength N ₀ V show a weak dependence on the local-field correction functions. The values of T _C obtained from the H-local-field correction function are found to be in qualitative agreement with available theoretical or experimental data and show almost linear behavior with respect to the concentration C of Cu. The present results are shown to be in good agreement with other available theoretical or experimental data. The obtained results confirm the existence of the superconducting phase in the metallic glasses.     

Transport Properties of Si and Ge Liquid Semiconductor Metals

In the present article, we study the electrical resistivity ρ, the thermoelectric power (TEP) α, thermal conductivity σ, Knight-Shifts and temperature coefficient of the Knight-Shifts of the liquid Si and Ge using the well known model potential for the first time. The structure factor used in the present work is derived from the Percus-Yevick (PY) theory. Various local field correction functions are used to study the screening influence. The present results of resistivity are found in qualitative agreement with available experimental and theoretical whenever exists.     

Synthesis,Characterization, and Comparative Study of Some Heterocyclic Compounds Containing Isoniazid and Nicotinic Acid Hydrazide Moieties

Russian Journal of Organic Chemistry - Some new derivatives of six-membered heterocyclic compounds containing isoniazid and nicotinic acid hydrazide fragments have been synthesized according to...     

Identification of Africanized honeybees

Gas chromatography and pattern recognition methods were used to develop a potential method for differentiating European honeybees from Africanized honeybees. The test data consisted of 237 gas chromatograms of hydrocarbon extracts obtained from the wax glands, cuticle, and exocrine glands of European and Africanized honeybees. Each gas chromatogram contained 65 peaks corresponding to a set of standardized retention time windows. A genetic algorithm (GA) for pattern recognition was used to identify features in the gas chromatograms characteristic of the genotype. The pattern recognition GA searched for features in the chromatograms that optimized the separation of the European and Africanized honeybees in a plot of the two or three largest principal components of the data. Because the largest principal components capture the bulk of the variance in the data, the peaks identified by the pattern recognition GA primarily contained information about differences between gas chromatograms of European and Africanized honeybees. The principal component analysis routine embedded in the fitness function of the pattern recognition GA acted as an information filter, significantly reducing the size of the search space since it restricted the search to feature sets whose principal component plots showed clustering on the basis of the bees' genotype. In addition, the algorithm focused on those classes and/or samples that were difficult to classify as it trained using a form of boosting. Samples that consistently classify correctly are not as heavily weighted as samples that are difficult to classify. Over time, the algorithm learns its optimal parameters in a manner similar to a neural network. The pattern recognition GA integrates aspects of artificial intelligence and evolutionary computations to yield a "smart" one-pass procedure for feature selection and classification.     

Superconducting state parameters of Cu C Zr100−C metallic glasses

The theoretical investigation of the superconducting state parameters (SSP) viz. electron-phonon coupling strength λ, Coulomb pseudopotential μ*, transition temperature T _c, isotope effect exponent α and effective interaction strength N ₀ V of ten Cu _C Zr_100?C metallic glasses have been reported using Ashcroft’s empty core (EMC) model potential. Three local field correction functions proposed by Hartree (H), Taylor (T) and Ichimaru-Utsumi (IU) are used in the current investigation to study the screening influence on the aforesaid properties. It is observed that the electron-phonon coupling strength λ and the transition temperature T _C are quite sensitive to the selection of the local field correction functions, whereas the Coulomb pseudopotential μ*, isotope effect exponent α and effective interaction strength N ₀ V show weak dependences on local field correction functions. The T _c obtained from IU-local field correction function are found an excellent agreement with available theoretical or experimental data. Also, the present results are found in qualitative agreement with other such earlier reported data, which confirms the superconducting phase in metallic glasses.