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Smitha, P.
- Stress and Personality of College Teachers
Authors
1 Department of Psychology, Avinashilingam University for Women, Coimbatore, IN
Source
Indian Journal of Health and Wellbeing, Vol 3, No 3 (2012), Pagination: 695-698Abstract
Teaching is a complex profession. Depending on the type of college or university, teachers may have many responsibilities such as fulfilling teaching and research requirements at research colleges and universities. Personality characteristics of an individual to a large extent are responsible for appraising a situation as stressful. Several studies have clearly indicated that certain personality types are stress prone. Though personality traits are fairly constant in an adult, awareness of one's stress level and the personality type can help the individual consciously mobilize coping strategies and manage the stress well. Present study was conducted to examine relationship between stress and personality of college teachers. Data were collected from 300 college teachers in six institutions. The results of correlation showed that the stress levels and personality types of the sample are independent of each other. It could be inferred that, for the present sample of college teachers, the personality types are fairly stable, not depending on their stress levels. This supports the fact that personality traits are more enduring, independent of the situational stressors.- Feature Extraction from Immunohistochemistry Images to Classify ER/PR Scores
Authors
1 Department of Computer Science and Engineering, College of Engineering, Karunagappally, Kollam - 690523, Kerala, IN
2 TocH Institute of Science and Technology, Arakkonam, Ernakulam - 682313, Kerala, IN
3 Division of Research, Regional Cancer Centre, Thiruvananthapuram - 695011, Kerala, IN
Source
Indian Journal of Science and Technology, Vol 8, No 34 (2015), Pagination:Abstract
Objectives: Abnormalities of protein receptors in the cell induce cancer. Detection of protein receptors such as Estrogen Receptor (ER)/Progesterone Receptor (PR) helps in hormone treatment, which improves the prognosis factor. Methods: Immunohistochemistry stained breast cytology images are used for finding the protein receptors. Separate stains are used for finding each receptor status. The presence of receptors is identified based on the brown color present in the nucleus. Brown color extracted through the channel separation, thresholding and relevant features are obtained from Gray Level Co-occurrence Matrix (GLCM). Based on these feature values an Artificial Neural Network (ANN) will classify the scores. Findings: Manual procedure for ER/PR scoring is based on the value of HSCORE, which is calculated by counting the brown colored nuclei and its intensity levels by the pathologist. This is a subjective procedure and has the risk of human fatigue errors. The medical expert decides the treatment plan based on the scores. Here we developed a new technique by which the manual scoring process could be imitated using the optimal set of features through an Artificial Neural Network (ANN), and obtained a result of 95.52 percent. Application: This could be a step towards the automation of Immunohistochemistry images and help in the survival of the patients. Hormone treatments are costlier procedure because of, the large amount of data to be processed manually.Keywords
Estrogen Receptors, Feature Extraction, Immunohistochemistry, Progesterone Receptors- Comparison of Performance of Selected Open-Ended Equity and Debt Mutual Fund Schemes
Authors
1 Assistant Professor, Department of Commerce, Loyola College, Chennai., IN
Source
Parikalpana: KIIT Journal of Management, Vol 19, No 2 (2023), Pagination: 128-141Abstract
Purpose: The numerous organisations that provide a range of funds are making it difficult for retail investors to choose an investment that is acceptable to them. During the pandemic, global market systems were disturbed, notably hurting market returns.
Design: Evaluate the open-ended schemes’ performance concerning equity and debt in mutual funds. The sample contains 10 schemes chosen from ten of the BSE 30 corporate schemes from January 2018 to December 2022. The performance of selected funds is examined to determine various statistical tools such as the daily average return, standard deviation, beta, and risk-adjusted value (Treynor and Jensen ratios). A benchmark index has also been created for analysis.
Findings: The results of the performance evaluation showed that equity schemes had a comparatively better return with moderate risk compared to debt schemes, but at the same time, the risk would be lower in debt schemes compared to equity. This study will help investors to identify good schemes and asset management firms should enhance the performance of their equity schemes to attract investors who are eager to pick the market’s portfolio structure. It is critical to identify and investigate the reasons for changes in time and market structure.
Keywords
Mutual funds, risk analysis, Jenson alpha, beta, market return, NAV.References
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