Genetic algorithms for symbolic clustering

This paper introduces a novel methodology for clustering of symbolic objects by making use of Genetic Algorithms (GAs). GAs are a family of computational models inspired by evolution. These algorithms encode potential solutions to specific problems on simple chromosome-like data structures and apply recombination operators to these structures so as to preserve critical information. A new type of representation for chromosome structure is presented here along with a new method for mutation. The efficacy of the proposed method is examined by application to numeric data of known number of classes and also to assertion type of symbolic objects drawn from the domain of fat oil, microcomputers, microprocessors and botany. The validity of the clusters obtained is examined.     

Agglomerative clustering using the concept of mutual nearest neighbourhood

A method for determining the mutual nearest neighbours (MNN) and mutual neighbourhood value (mnv) of a sample point, using the conventional nearest neighbours, is suggested. A nonparametric, hierarchical, agglomerative clustering algorithm is developed using the above concepts. The algorithm is simple, deterministic, noniterative, requires low storage and is able to discern spherical and nonspherical clusters. The method is applicable to a wide class of data of arbitrary shape, large size and high dimensionality. The algorithm can discern mutually homogenous clusters. Strong or weak patterns can be discerned by properly choosing the neighbourhood width.     

Effect of Simulated Microgravity on the Activity of Regulatory Enzymes of Glycolysis and Gluconeogenesis in Mice Liver

Gravity supports all the life activities present on earth. Microgravity environments have effect on the biological functions and physiological status of an individual. The present study was undertaken to investigate the effect of simulated microgravity on important regulatory enzymes of carbohydrate metabolism in liver using HLS mice model. Following hind limb unloading of mice for 11 days the animal’s average body weights were found to be not different, while the liver weights were decreased and found to be significantly different (p < 0.05) from control mice. Further, in liver the specific activity of hexokinase enzyme was reduced (p < 0.02) and the phosphoenolpyruvate carboxykinase activity was significantly increased in simulated microgravity subjected mice compared to control (p < 0.003). Immunoblot analysis show decreased phosphofructokinase-2 activity in HLS mice compared to control. Liver lactate dehydrogenase activity significantly reduced in simulated microgravity subjected mice (p < 0.005). Thus in our study the rodents have adapted to simulated microgravity conditions, with decreased glycolysis and increased gluconeogenesis in liver and reciprocally regulated.     

Cluster detection in a collection of collinear line segments

Two novel methods of clustering of a collection of collinear line segments are presented. Both the methods are of merging type, global in nature and take into account both gap and line segment lengths. The methods are also useful for clustering collinear dot patterns. The efficacy of the algorithms is brought out by successfully applying them on different types of data sets. A comparative study is made by comparing the results of the proposed procedures with that of another procedure already existing.     

A feature reduction and unsupervised classification algorithm for multispectral data

A new scheme, incorporating dimensionality reduction and clustering, suitable for classification of a large volume of remotely sensed data using a small amount of memory is proposed. The scheme involves transforming the data from multidimensional n-space to a 3-dimensional primary color space of blue, green and red coordinates. The dimensionality reduction is followed by data reduction, which involves assigning 3-dimensional samples to a 2-dimensional array. Finally, a multi-stage ISODATA technique incorporating a novel seedpoint picking method is used to obtain the desired number of clusters.

The storage requirements are reduced to a low value by making five passes through the data and storing necessary information during each pass. The first three passes are used to find the minimum and maximum values of some of the variables. The data reduction is done and a classification table is formed during the fourth pass. The classification map is obtained during the fifth pass. The computer memory required is about 2K machine words.

The efficacy of the algorithm is justified by simulation studies using multispectral LANDSAT data.     

Learning with a mutualistic teacher

The concept of a “mutualistic teacher” is introduced for unsupervised learning of the mean vectors of the components of a mixture of multivariate normal densities, when the number of classes is also unknown. The unsupervised learning problem is formulated here as a multi-stage quasi-supervised problem incorporating a cluster approach. The mutualistic teacher creates a quasi-supervised environment at each stage by picking out “mutual pairs” of samples and assigning identical (but unknown) labels to the individuals of each mutual pair. The number of classes, if not specified, can be determined at an intermediate stage. The risk in assigning identical labels to the individuals of mutual pairs is estimated. Results of some simulation studies are presented.     

A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy

Information Systems and e-Business Management - While embracing digitalization that is further accentuated by the Covid-19 pandemic, the real business outcome is achieved through a robust and...     

Metalphthalocyanines Anchored Poly(1,3,4-oxadiazole arylene ether)s: Optical and Electrical Studies

New phenolphthalein based poly(1,3,4-oxadiazole aryl ether) (PHOP) containing side chain carboxylic acid groups derived from 2,5-bis(4-fluorophenyl)-1,3,4-oxadiazole and 2-(bis(4-hydroxyphenyl)methyl)benzoic acid have been synthesized from typical aromatic nucleophilic substitution reaction. The PHOP seizes high dielectric constant (300 at 50 Hz) by the assistance of polar pendants and its findness in advance studies needs some structure modification with high dielectric constant metalphthalocyanine (MPc, M=Co, Ni & Cu) macrocycle to come out as further enhancement of dielectric constant and become photoactive polymer embedded metalphthalocyanine (PPEMP1–9). The molecular weight of PHOP was determined by gel permeation chromatography and is found to be 33375 (M _w/M _n = 2.48). All the tailor-made polymers were well characterized by Solid State UV–Vis, thermogravimetric analysis and XRD analysis. FTIR and NMR spectroscopic techniques confirms MPc units are grafted into the polymer matrix and act as a utmost light catching materials in the visible to near IR region (400–900 nm) with remarkable drop off in optical band gap and exhibited impressive thermal properties. The variation in the AC conductivity was explained by electron hopping model and values are in the range of 3.16 × 10^?5–4.78 × 10^?5 (S/m) at 5 MHz measured at 20 °C.