Informatics Publishing Limited

A. R. Deshpande ¹, R. R. Wavare ¹, Richa Nigam ¹, Sanjay Kubde ², R. A. Kulkarni ³

Affiliations
1 Department of Community Medicine, SAIMS Medical College and P.O. Institute, Indore, IN
2 Department of Community Medicine, IGGMC, Nagpur, IN
3 Department of Biochemistry, SAIMS Medical College and P.O. Institute, Indore, IN

Abstract

To Asses the Self- Help Skills in Mentally Challenged Students. Skilled deficiency is an inevitable and widespread problem in mentally challenged population. It's very important to asses their self help skills (i.e. adaptive behaviour) to know the magnitude of the burden they put on parents and society. Institutional based cross sectional study was earned out with 165 mentally challenged students of Nandanwan School, Nagpur from March -May 2005 Mentally challenged children were lagging behind in all areas like eating, dressing toileting, communication, locomotion, money matters (self direction) as their means in all age groups and in all areas were less. Means social quotient did not increase as per the chronological ages of children. Mentally challenged children faced difficulties m activities of daily living. As the age of children increased their mean social ages increased but their mean social quotient didn't increase with their age hence there is need of special education and training.

Keywords

Self- Help Skills, Mentally Challenged Students.

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P. S. Mahajan ¹, A. R. Deshpande ²

Affiliations
1 Pune Institute of Computer Technology, Dhankawadi, Pune, IN
2 Pune Institute of Computer Technology, Pune, IN

Abstract

Today, the enterprise landscape faces voluminous amount of data. The information gathered from these data sources are useful for improving on product and services delivery. However, it is challenging to perform searching activities on these data sources because of its unstructured nature, also the traditional solutions only supports single keyword search which perform poorly over unstructured data. Hence to improve the search accuracy and efficiency the searching based on multiple keyword is desirable, in which index entries are stored not only for single term but also for set of terms combination. This technique reduces the overhead for intersecting the inverted lists of keys in multi-term queries, by storing combinations of terms as keys in the index.

Keywords

Multiterm Keyword Searching.

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N. S. Sheth ¹, A. R. Deshpande

Affiliations
1 Pune Institute of Computer Technology, Dhankawadi, Pune, IN

Abstract

Decision Tree techniques are used to build classification models in data mining. A decision tree is a sequential hierarchical tree structure which is composed of decision nodes corresponding to attributes. A decision tree model is based on attribute selection measure. The paper represents splitting criterion like Information Gain, Gain Ratio, Gini Index, Jaccard Coefficient, and Least Probable Intersections. In decision tree construction, the splitting criterion is heuristic for best attribute selection that partitions node dataset. Attribute with best score is chosen as a splitting attribute for a node. Best score is based on either impurity reduction or purity gain. This paper gives comparative study of attribute selection measures for top down induction of decision tree.

Keywords

Decision Tree, Splitting Criterion, Attribute Selection.

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