Informatics Publishing Limited

R. Suganthi ¹, P. Kamalakannan ²

Affiliations
1 Department of Computer Applications, Valluvar College of Science and Management, Karur, Tamilnadu, IN
2 Department of Computer Science, Government Arts College, Namakkal, Tamilnadu, IN

Abstract

Nowadays, A multi database mining is a important role between head quarters company and their corresponding branch offices in various places among the world. It allows to forward their branch office local patterns to the head quarters which will be synthesized for taking decision in multi databases. we propose a new approach to finding exceptional patterns and compared with the previous methods in multiple databases. the result is compared with the various methodologies yields high performance result than the other methods. it perform well with multiple dataset and it is simple and effective. it yields high outstanding accuracy and the resulting data could be used for further mining.

Keywords

Exception Patterns, Machine Learning, Multi Database, Local Patterns.

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R. Suganthi ¹, P. Kamalakannan ²

Affiliations
1 Department of Computer Applications, Valluvar College of Science and Management, Karur - 639003, Tamil Nadu, IN
2 Department of Computer Science, Government Arts College, Namakkal - 637 001, Tamil Nadu, IN

Abstract

The information from multiple local databases can be mined together to make global patterns. More global decisions will be based on synthesized patterns and exceptional patterns using clustering technique. To take better decision in organization head quarter level, exceptional patterns also need to be analyzed for non profitable things which help for continuous company growth. Our new strategy is developed considering both clustering the frequent items also exceptional patterns. Various experiments are conducted with 10 sample datasets and the results are recorded in experimental section, with this the significance and limitations behind those approaches can be made clear.

Keywords

Exceptional Patterns, Frequency Item Sets, Global Patterns, Multi Database Mining

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P. Kamalakannan ¹, R. Suganthi ²

Affiliations
1 Arignar Anna Government Arts College, Namakkal-637002, IN
2 Valluvar College of Science & Management, Karur-639006, IN

Abstract

The notion of Multi Database Mining has been recognised as an important area in data mining community for determining various novel patterns among item sets that co-occur frequently. This paper shows the kinds of High level patterns, Exceptional Patterns and Suggested patterns and their applications. For giving a comfortable and easy usage, we constructed the multi database mining designed by fusing local patterns and universal techniques. After designing with new fusion, it helps much and provides the company many advantages. In order to improve the performance of various patterns, many multi database mining techniques used which leads to take a fruitful decision in the interstate companies.

Keywords

Association Rule, Patterns, Local Patters, Synthesized Patterns.

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R. Suganthi ¹, S. Manonayaki ², J. F. Benazir ¹

Affiliations
1 School of Biotechnology, Dr. G. R. Damodaran College of Science, Coimbatore (T.N.), IN
2 Department of Advanced Animal Sciences and Biotechnology, Emeral Heights College, Ooty (T.N.), IN

Abstract

Idiopathic infertility is a condition of couples unable to conceive for more than two years, with no abnormalities seen on repeated investigations of tubes or as regard with ovulation, luteal phase, cervical mucus, semen, sperm-oocyte interaction or intercourse. Among the major causes of infertility, chromosomal abnormalities, microdeletions, cystic fibrosis transmembrane conductance regulator (CFTR) mutations and other genetic factors (Follicle stimulating hormone (FSH) receptor mutation) are important. Genetic factors cause about 10% of male infertility. Among these, genes in AZF regions including AZFa, AZFb, AZFc and AZFd on the long arm of Y chromosome are considered to be the most important for spermatogenesis. Deletions in these regions are thought to be pathogenetically involved in some cases of male infertility associated with azoospermia or oligozoospermia. The aim of this study was to determine the incidence of AZF deletions among male infertile patients. We analyzed a total of 215 azoospermic infertile men for the presence of 12 sequence tagged site (STS) markers, 3 markers for each AZF region including AZFa, AZFb and AZFc, on the Y chromosome using multiplex PCR. Among the patient group the observed frequency of deletions was about 11.1%, among them the azoospermic men showed more significant deletions (7.4%) than the severe oligospermic men (3.7%) selected for the study. The deletion in AZFa region was 20.83% of the total deletions. The relative frequency of deletions in AZF a, b and c regions in infertile men in this study is AZFa in 1/24 (4.16%); AZFb in 5/24 (20.8%); AZFc in 11/24 (45.83%); AZF a+c in 2/24 (8.3%); AZF b+c in 3/24 (12.5%); AZF a+b+c in 2/24 (8.3%). No microdeletions were found in the control group. According to relatively high incidence of Y chromosome microdeletions among azoospermic patients, molecular screening for detection of these microdeletions seems to be very informative, since different types of these deletions have prognostic value in predicting the outcome of testicular sperm retrieval for assisted reproduction.

Keywords

Infertility, AZF Region, Microdeletion, Y Chromosome.

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