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Boominathan, P.
- Work Place Motivation and Job Burnout of Employees Working in Private Banking Sector in Coimbatore District, South India
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Authors
Affiliations
1 Anna University of Technology, Coimbatore, IN
1 Anna University of Technology, Coimbatore, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 6 (2012), Pagination: 284-289Abstract
Job Burnout is emotional, physical, intellectual and spiritual exhaustion. High levels of stress can ultimately cause exhaustion and break-down. Excess stress can lead to Burnout, the fall-out being low levels of Job Involvement or rather low levels of Job Involvement leading to Burnout. The study found emotional exhaustion to have significant effects on employees' intent to stay in the organization directly and through the mediation of affective commitment. Job burnout is considered an outcome of organizational politics due to the influence of various independent variables like job attitude, job involvement etc on the same. Like the proverbial chicken and egg story, it is difficult to establish a cause effect relationship between Burnout and Job Involvement. Burnout can have serious implications for the managers in affecting their productivity and thereby affect the organizations adversely. It is not the complacent, easy going individual who runs the highest risk of Burnout. Instead, it is those with high expectations and a sense of purpose who are the greatest victims, people with high standards for themselves and for others. Findings of the study provide strong implications for banking management to have careful insight about the attitudinal and behavioral problems of the employees. The limitations and future area of research are also discussed in the study.Keywords
Job Motivation, Stagnation, Detachment, Job Burnout and Emotionally Exhausted.
- Effect of Salinity and Alleviating Role of PGRs and Nutrients for Improving the Morphological Traits of Tomato Cultivars under Salinity Condition
Abstract Views :208 |
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Authors
Affiliations
1 Department of Crop Physiology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, IN
1 Department of Crop Physiology, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, IN
Source
Nature Environment and Pollution Technology, Vol 17, No 1 (2018), Pagination: 107-110Abstract
Salinity has deleterious effects on many crops, especially in morphology of the plants. A research was conducted to study the effect of salinity on tomato genotypes (PKM 1 and TNAU THCO 3) and alleviation by using plant growth regulators (PGRs) and nutrients in the Department of Crop Physiology, TNAU, Coimbatore. Salinity was imposed by using NaCl at 100 mM concentration. The responses of two tomato genotypes under salinity were studied. Among two genotypes, PKM 1 was affected more by salinity than TNAU THCO 3. Foliar application of plant growth regulators like brassinolide (0.5 ppm), salicylic acid (100 ppm), benzyl amino purine (50 ppm), ascorbic acid (100 ppm), glutathione (50 ppm), KNO3 (0.5%) + FeSO4 (0.3%) + Borax (0.2%) and nutrient PGR concoction (K2SO4 (0.5%) + CaSO4 (0.5%) + Borax (0.2%) + NAA (20 ppm) were carried out at 20 and 40 DAT. Significant variations and adaptability among stressed and non-stressed plants were observed in both the genotypes. The study revealed that, among the treatments, brassinolide showed the premier observations like plant height (73.40 cm), ischolar_main length (18.60 cm), ischolar_main volume (133.25 cc), leaf area (1275.54 cm2) and total dry matter production (TDMP) (88.42 g plant-1) followed by salicylic acid when compared to control. Among the two genotypes used in this study, TNAU THCO 3 responded better for the application plant growth regulators and nutrients than PKM 1 under salinity.Keywords
Tomato Cultivars, Salinity, Plant Growth Regulators, Plant Height, Root Length, Leaf Area, Total Dry Matter Prodution.Full Text
References
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- Gomez, K.A. and Gomez, A.A. 1984. Statistical Procedures for Agricultural Research. 2nd Ed., John Wiley and Sons, New York, USA, pp. 680.
- Hayat, Q., Hayat, S. Irfan, M. and Ahmad, A. 2010. Effect of exogenous salicylic acid under changing environment: A review. Environ. Exp. Bot., 68: 14-25.
- Homa Mahmood, Z. and Massoumeh Bemani, N. 2007. Effects of salinity stress on the morphology and yield of two cultivars of canola (Brassica napus L.). J. Agron., 6(3): 409-414.
- Khripach, V.A. Zhabinskii, V.N. and Deegischolar_main, A.E. 2000. Twenty years of brassinosteroids: steroidal plant hormones warrant better crops for the XXI century. Ann. Bot., 86: 441-447.
- Misra, N. and Saxena, P. 2009. Effect of salicylic acid on proline metabolism in lentil grown under salinity stress. Plant Sci., 177: 181-189.
- Mostafa, G.G. and Abou Al-Hamed, M.F. 2011. Effect of gibberellic acid and indole-3 acetic acid on improving growth and accumulation of phytochemical composition in Balanites aegyptica plants.Am. J. Plant Physio., 6: 36-43.
- Shakirova, F.M., Sakhabutdinova, A.R. Bezrukova, M.V. Fathkutdinova, R.A. and Fathkutdinova, D.R. 2003. Changes in the hormonal status of wheat seedlings induced by salicylic acid and salinity. Plant Sci., 164: 317-322.
- Shen, X.Y., Dai, J.Y., Hu, A.C., Gu, W.L., He, R.Y. and Zheng, B. 1990. Studies on physiological effects of brassinolide on drought resistance in maize. J. Shenyang Agri. University, 21: 191-195.
- Tuna, A.L., Kaya, C., Ashraf, M., Altunlu, H., Yokas, I. and Yagmur, B. 2007. The effect of calcium sulphate on growth, membrane stability and nutrient uptake of tomato plants grain under salt stress. Environ. Exp. Bot., 59: 173-178.
- Wang, T.W., Cosgrove, D.J. and Arteca, R.N. 1993. Brassinosteroid stimulation of hypocotyls elongation and wall relaxation in pakchoi (Brassica chinensis cv. Lei-Choi). Plant Physiol., 101: 965-968.
- Zhou, X.M., Mackeuzie, A.F., Madramootoo, C.A. and Smith, D.L.J. 1999. Effects of some injected plant growth regulators with or without sucrose on grain production, biomass and photosynthetic activity of field grown corn plants. Agri. Crop Sci., 183: 103-110.
- Diabetic Medical Data Classification using Machine Learning Algorithms
Abstract Views :210 |
PDF Views:0
Authors
Affiliations
1 School of Computer Science and Engineering, VIT University, Vellore-632014, IN
1 School of Computer Science and Engineering, VIT University, Vellore-632014, IN
Source
Research Journal of Pharmacy and Technology, Vol 11, No 1 (2018), Pagination: 97-100Abstract
Data mining is the process of analyzing data from different perspectives and summarizing it into a useful information. In this paper we propose a different classification algorithm to identify the accuracy on diabetic data sets. The diabetic person has risk and leads to other disease such as blood vessel damage, blindness, heart diseases, nerve damage and kidney diseases. Diabetics also classified as two types such as type insulin diabetes and non-insulin dependent, diabetes is a disease in which the blood glucose increases which is due to the defects of secretion of insulin, or its action or both. Diabetes is a prolonged medical disease. In diabetes the cells of person produce insufficient amount of insulin or defective insulin or may insulin or may unable use insulin properly and efficiently that further leads to hyperglycemia and type-2 diabetes. We are proposing an efficient two level for classifying data. During initial phase we use training data for analyzing the optimality of dataset then new dataset is formed as optimal training dataset now we apply our classification mechanism on new diabetic datasets. The data mining methods and techniques will be explored to identify suitable methods and techniques for efficient classification on diabetic data set and in mining it in useful patterns.Keywords
Data Mining, Diabetic Dataset, Classification, Naive Bayes Classification, Random Forest.References
- Rahman, R. M. and Afroz, F. Comparison of various classification techniques using different data mining tools for diabetes diagnosis. Journal of Software Engineering and Applications, 2013; 6(03): 85-97.
- R. S. Kamath, Weka Approach for Exploration Mining in Diabetic Patients Database, Chatrapati Shahu Institute of Business Education and Research Kolhapur,India.2013
- Labatut, V and Cherifi, H. Evaluation of performance measures for classifiers comparison. Ubiquitous Computing and Communication Journal, 2011; 6, 2011:21-34
- Kumari, M., Vohra, R., and Arora, A. Prediction of Diabetes Using Bayesian Network, International Journal of Computer Science and Information Technologies, 2014; 5(4) : 5174-5178.
- Keerthana, G., and Srividhya, V. (2014). Performance Enhancement of Classifiers using Integration of Clustering and Classification Techniques. International Journal of Computer Science Engineering 2014;3(3) : 200-203.
- Marom, N. D., Rokach, L., and Shmilovici, A. Using the confusion matrix for improving ensemble classifiers. In 26th Convention of Electrical and Electronics Engineers in Israel (IEEEI), 2010:555-559.