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Yasodha, S.
- An Enhanced Classification Technique for Talent Management Using CACC-SVM
Authors
1 Department of Computer Science and Engineering, Sona College of Technology, Salem, Tamilnadu, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 6 (2012), Pagination: 298-302Abstract
Classification of data is becoming a major challenge in Human Resource Management (HRM). The talent management problem in HRM is commonly solved through several classification techniques available in data mining. However the goal of the classification process is to classify the data in a highly accurate manner. Hence in this paper we propose a hybrid classification technique CACC-SVM for classifying data. The concept of discretization and classification are combined. This effectively increases the classification accuracy. The Class Attribute Contingency Coefficient (CACC) is a static, global, incremental, supervised & top down discretization algorithm. This produces concise summarization of continuous attributes which makes the classification process more accurate. The discretized data are then classified using high performing generalized classifier Support Vector Machine (SVM). The result of the proposed algorithm is compared with several traditional classification algorithms. Performance of the algorithms is measured through accuracy rate and error rate. The accuracy rates are higher and error rates are lower for the proposed algorithm.Keywords
Talent Management, Classification, Support Vector Machines (SVM), Class-Attribute Contingency Coefficient (CACC), Sequential Minimal Optimization (SMO).
- Scrutiny of Antagonistic Microbial and Cytotoxic Promises of Fungal Endophyte Secluded from Pisonia grandis R. Br
Authors
1 Jeppiaar Institute of Technology, Sriperumbudur, IN
2 Gurunank College, Chennai, IN
3 Royal Bio Research Center, Chennai, IN
Source
Research Journal of Pharmacy and Technology, Vol 10, No 3 (2017), Pagination: 647-662Abstract
In the past decades, hundreds of bioactive natural products had been isolated from endophytic fungi among which over 51% were chemically novel. But to this day, only a small population of the endophytic fungi have been investigated for the bioactivity assessment and production of natural compounds. So the possibility to find bioactive endophytic fungal strains and bioactive natural products with chemically novel structures from them is still high. In the present study we aim to isolate and identify fungal endophytes from Pisonia grandis R. Br. and to analyse their Antimicrobial, Antioxidant and Anticancer potential. One out of the four different endophytic fungi obtained was selected for studies on bioactivity and was identified as Neurospora crassa. On evaluating the bioactivities, the fungus exhibited moderate to good Antimicrobial activity against the Assessment organisms and more than 50% antioxidant activity. The data obtained from Cytotoxicity studies revealed a dose-dependent cytotoxic activity. The compounds present in the extract were identified through GC-MS analysis.Keywords
Pisonia grandis R. Br., Endophytic Fungi, Neurospora crassa, Bioactivity Assay, GC-MS.- Prevalence of Poly Cystic Ovarian Syndrome (PCOS) in Obese Females in a Tertiary Care Centre in South India‑An Observational Study
Authors
1 Department of OBG, Sri Lakshmi Narayana Institute of Medical Sciences (SLIMS), Affiliated to Bharath Institute of Higher Education and Research, IN
Source
Indian Journal of Public Health Research & Development, Vol 10, No 12 (2019), Pagination: 192-196Abstract
Background: Poly cystic ovarian syndrome (PCOS) is more common among obese females. It has many dimensions which is still being explode many studies have tried to characterise the exact presentation of the disease. This study analysed the prevalence of PCOS in obese females. Along with this, the prevalence of acanthosisnigricans which is a surrogate maker of insulin resistance and Hirsuitism has been simultaneously studied.
Methodology: It was a cross sectional study which is carried out among medical students in a tertiary care centre in South India for one year. Questionnaire was designed and study was done. It comprised sample size of 113 females. All these candidates had high Body mass index (BMI) and all of them fall under obese category. The candidates who were participating in this study were aware of the PCOS condition and a brief session on PCOS was given before the start of this study. Along with this, Cutaneous manifestations were also assessed based on the severity of the symptoms.
Results: This study found that the prevalence rate of PCOS among obese females was 85.8%. More than half of the study patients has acanthosisnigricans (57.5%) and Hirsuitism (59.2%). These results were based on Rotterdamn criteria. In this 93.8% of hyperandrogenism, 57.5% had Acanthosisnegucans and 59.2% had hirsiutism. In this study 50.4% had fulfilled all three criteria according to Rotterdam criteria according to Rotterdam and 35.3% has fulfilled 2 out of 3 criteria and 14.1% faced to fulfillatleast 2 criteria(Figure 3). Thus from the above study we conclude that there is great prevalence rate for PCOS in obese females aged 18 to 22.
Conclusion: With 85.8% prevalence rate of PCOS among obese females, it strongly proves that there is a association between the two. Thus increase in BMI causes increased risk of PCOS among females.