P A College of Engineering

About: P A College of Engineering is a based out in . It is known for research contribution in the topics: Dihedral angle & Ring (chemistry). The organization has 298 authors who have published 594 publications receiving 4888 citations.

Diagnosis of the Abnormality Extracted MRI Slice Images of a GUI Based Intelligent Diagnostic Imaging System

Abstract: Diagnosis is the Key feature of an Intelligent Diagnostic Imaging System (IDIS). This paper describes the major diagnosis depending on the shape, texture, and area of the abnormality. Abnormality extraction is the vital step in a series of processes aimed at overall image understanding. Region based segmentation is used for abnormality extraction. This paper also describes author defined algorithms for threshold detection for abnormality extraction, which gives excellent result compared to the threshold detection using Otsu's method. Different algorithms are used for T1 and T2 MRI Images. This paper does the comparison of different segmentation techniques. MATLAB tools are used to do the segmentation.

1-(2,4-Difluoro­phen­yl)thio­urea

Abstract: The asymmetric unit of the title compound, C7H6F2N2S, consists of two independent mol­ecules, with comparable geometries. In one mol­ecule, the thio­urea moiety is essentially planar (r.m.s. deviation = 0.014 A) and it forms a dihedral angle of 78.67 (9)° with the benzene ring. The corresponding r.m.s. deviation and dihedral angle for the other mol­ecule are 0.011 A and 81.71 (8)°, respectively. In both mol­ecules, one of the F atoms is disordered over two positions with refined site occupancies of 0.572 (3):0.428 (3) and 0.909 (2):0.091 (2), respectively. In the crystal, mol­ecules are linked via N—H⋯S and C—H⋯F hydrogen bonds into two-dimensional networks parallel to (010).

A Fuzzy Approach for Feature Evaluation and Dimensionality Reduction to Improve the Quality of Web Usage Mining Results

Abstract: Web Usage Mining is the application of data mining techniques to web usage log repositories in order to discover the usage patterns that can be used to analyze the users navigational behavior. During the preprocessing stage, raw web log data is transformed into a set of user profiles. Each user profile captures a set of URLs representing a user session. Clustering can be applied to this sessionized data in order to capture similar interests and trends among users navigational patterns. Since the sessionized data may contain thousands of user sessions and each user session may consist of hundreds of URL accesses, dimensionality reduction is achieved by eliminating the low support URLs. Very small sessions are also removed in order to filter out the noise from the data. But direct elimination of low support URLs and small sized sessions may results in loss of a significant amount of information especially when the count of low support URLs and small sessions is large. We propose a fuzzy solution to deal with this problem by assigning weights to URLs and user sessions based on a fuzzy membership function. After assigning the weights we apply a Fuzzy c-Mean Clustering algorithm to discover the clusters of user profiles. In this paper, we describe our fuzzy set theoretic approach to perform feature selection (or dimensionality reduction) and session weight assignment. Finally we compare our soft computing based approach of dimensionality reduction with the traditional approach of direct elimination of small sessions and low support count URLs. Our results show that fuzzy feature evaluation and dimensionality reduction results in better performance and validity indices for the discovered clusters.

(2E)-1-(2,4-Dichlorophenyl)-3-(2-hydroxy-3-methoxyphenyl)prop-2-en-1-one.

Abstract: The geometric parameters of (2E)-1-(2,4-dichlorophenyl)-3-(2-hydroxy-3-methoxyphenyl)prop-2-en-1-one, C16H12Cl2O3, are in the normal ranges. The central double bond is trans configured. In the crystal structure, mols. are linked into centrosym. O-H···O H-bonded dimers. There is a single I€-I€ stacking interaction between benzene rings of the dichlorophenyl groups. Crystallog. data are given. [on SciFinder(R)]