Volume-07 , Special Issue-03 , Feb - 2019 Go Back

Cloud computing has emerged as a new computing platform for providing fast and low cost services to the individual ,organizations ,government etc. over the internet and is a future generation technology. Cloud computing model means to increase the opportunities for cloud user by accessing leased infrastructure and software application from anywhere and anytime manner. Cloud computing mainly consist there service model as Software as a Service (Saas), Platform as a Service (PaaS) and Infra structure as a Service (IaaS). These service models are being provided by many cloud services provider and a user can choose any one of them based on various parameters .which many differ from one service provider to another service provider and is a challenging and tedious task for an end user to select the best one. This paper provides an approach to select cloud services among the available alternatives to the IT users using two popular Multi Criteria Decision Making (MCDM) Techniques: Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution(FTOPSIS) with special reference to triangular fuzzy membership function for experimental hypothetical alternatives as and services are considered with identified criteria. Selection process MCDM techniques are enough capable to find out the best alternatives as cloud service, a hypothetical cloud services as alternatives, used on identified criteria where ranked and found satisfactory.

Cloud services, Fuzzy analytic hierarchy process (FAHP), Fuzzy technique for order preference by similarity to ideal solution

[1] R. Buyya, C.S. Yeo, S. Venugopal, J. Broberg, and I.B. Randic, “Cloud computing and emerging IT platform: vision, hype, and reality for delivering computing as the 5thutility”,Future Generation Computing system,Vol.25,No. 6,pp.599-616,2009.
[2] R. Buyya, C.S. Yeo, S. Venugopal, “Market-Oriented Cloud Computing: Vision, Hope, and Reality for Delivering IT services as computing Utilities”, IEEE,2008
[3] O. Boutkhoum, M. Hanine and T. Agouti, “Selection problem of cloud solution for big data accessing: fuzzy AHP-PROMETHEE as a proposed methodology”, JDIM,2016.
[4] S. K. Garg, S. Versteeg and R. Buyya,“A framework for ranking of cloud computing services”, Elsevier,2013.
[5] A.C. Kutlu, M. Ekmekcioglu, “Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP”, Expert Systems with Applications, Elsevier, Vol.39, pp. 61–67,2012.
[6] S. Pearson, “Taking Account of privacy when Designing Cloud computing Services”, HP Laboratories,2009.
[7] R.V. Rao, “Decision making in the manufacturing environment”, Springer-Verlag London Limited,2007.
[8] S.S. Kaur, Y. Brar And K.N. Singhand, “Multi Criteria Decision Making Approach for Selecting Effort Estimation Model”,International Journal of Computer Applications (0975 – 8887),Volume 39– No.1,pp.10-17,2012
[9] T.L. Satty, “The Analytical Hierarchy Process”, McGraw Hill, New York ,1980.
[10] G. Wei, A.V. Vasilakos, Y. Zheng And N. Xiong, “A game –theoretical method of fair resource allocation for cloud computing services”, Springers ,2009.
[11] M. Whaiduzzaman, A. Gani, N.B. Anuar, M. Shiraz, M.N. Haque and I.T. Haque, “Cloud services selection using multicriteria decision analysis”, The Scientific world Journal volume, article ID pp.459-3375,2014.
[12] Qi. Zhang, Lu. Cheng, R. Boutaba, “Cloud computing: state- of- the- art and research challenges”, Springers,2010.

S. Pavani, R. Shukla, "Cloud Service Selection Using Integrated Approach Of Fuzzy AHP And Fuzzy Topsis", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.48-54, 2019.

The aim of the study was to predict the effect of service quality on perceived value, customer satisfaction and customer loyalty in hospitals of Chhattisgarh. A 22 item scale (under five dimensions namely tangibility, reliability, responsiveness, assurance, empathy) of service performance developed by Cronin and Taylor, 1994 was used to access the service quality of hospitals under study. Self-structured questionnaire was administered for measuring the perceived value, customer satisfaction and customer loyalty of hospitals under study. Data collection was made with the help of 120 respondents having fulfilled the inclusion criteria of research. Five different hospitals were chosen for the purpose of the study. Purposive sampling technique for data collection. The hypothetical model was evaluated by the help of structural equation modelling and the result was a good model fit. The result concludes that service quality has positive and direct effect on customers perceived value, customer’s satisfaction and customer loyalty in hospitals of Chhattisgarh.

Service quality, perceived value, customer satisfaction customer loyalty, Structural equation modelling

[1] R. C.Lewis, & H. Booms.Bernard, “The Marketing Aspects of Service Quality. In Emerging Perspectives on Services Marketing”, American Marketing Association, pp. 99-107, 1983.
[2] R. L. Oliver, P. S. Balakrishnan, & B. Barry, “Outcome Satisfaction in Negotiation: A test of Expectancy Disconfirmation”, Organizational Behavior and Human Decision Processes, Vol. 60 Issue 2, pp. 252-275, 1994.
[3] H. Arasli, E. Haktan Ekiz&, S. Turan Katircioglu“Gearing Service Quality into Public and Private Hospitals in Small Islands: Empirical Evidence from Cyprus”, International journal of Health Care Quality Assurance, Vol. 21Issue 1, pp. 8-23,2008.
[4] A. Majeed Alhashem, H. Alquraini, & R. I. Chowdhury, “Factors Influencing Patient Satisfaction in Primary Healthcare Clinics in Kuwait”, International Journal of Health Care Quality Assurance, Vol. 24Issue 3, pp. 249-262,2011.
[5] J. J. Cronin Jr, M. K. Brady, & G. T. M. Hult, “Assessing the Effects of Quality, Value, and Customer Satisfaction on Consumer Behavioral Intentions in Service Environments”, Journal of retailing, Vol.76Issue 2, pp. 193-218, 2000.
[6] M. K. Brady, & J. J. Cronin Jr, “Some new Thoughts on Conceptualizing Perceived Service Quality: a Hierarchical Approach”, Journal of marketing, Vol.65Issue 3, pp. 34-49, 2001.
[7] F. Lai, M. Griffin,& B. J. Babin, “How Quality, Value, Image, and Satisfaction Create Loyalty at a Chinese Telecom” Journal of Business Research, Vol. 62 Issue 10, pp. 980-986, 2009.
[8] J. J. Cronin Jr, & S.A. Taylor,“Measuring Service Quality: a ReExamination and Extension”, The journal of Marketing, pp. 55-68,1992.
[9] U. Yavas, Z. Bilgin, & D. J. Shemwell, “Service Quality in The Banking Sector in an Emerging Economy: A Consumer Survey”, International Journal of Bank Marketing, Vol. 15 Issue 6, pp. 217-223, 1997.
[10] A. Jamal, & K. Naser, “Customer Satisfaction and Retail Banking: An Assessment of Some of The Key Antecedents of Customer Satisfaction in Retail Banking”, International journal of Bank Marketing, Vol. 20Issue 4, pp. 146-160, 2002.
[11] K. S. Choi, W. H. Cho, S. Lee,H. Lee, & C. Kim, “The Relationships Among Quality, Value, Satisfaction and Behavioral Intention in Health Care Provider Choice: A South Korean Study”, Journal of Business Research, Vol. 57 Issue 8, pp. 913-921, 2004.
[12] O. M. Karatepe, “Service Quality, Customer Satisfaction and Loyalty: The Moderating role of gender”, Journal of Business Economics and Management, 12 Issue 2, pp. 278-300, 2011.
[13] K. S. Choi, H. Lee, C. Kim,&S. Lee, The Service Quality Dimensions and Patient Satisfaction Relationships in South Korea: Comparisons Across Gender, Age and Types of Service. Journal of Services Marketing, Vol. 19Issue3, pp. 140-149,2005.
[14] H. Zaim, N. Bayyurt, & S. Zaim, Service Quality and Determinants of Customer Satisfaction in Hospitals: Turkish experience. The International Business & Economics Research Journal, Vol. 9Issue5, pp.51, 2010.
[15] C. M. Chen,S. H. Chen, & H. T. Lee, “Inter-Relationships Between Physical Environment Quality, Personal Interaction Quality, Satisfaction and Behavioural Intentions in Relation to Customer Loyalty: The Case of Kinmen`s Bed and Breakfast Industry”, Asia Pacific Journal of Tourism Research, Vol. 18Issue 3, pp. 262-287, 2013.
[16] S. W. Mercer, M. Neumann, M. Wirtz, B. Fitzpatrick,& G. Vojt, “General Practitioner Empathy, Patient Enablement, and Patient-reported Outcomes in Primary Care in an Area of High Socio-economic Deprivation in Scotland—A Pilot Prospective Study Using Structural Equation Modelling”, Patient Education andCounselling, Vol.73Issue2, pp. 240-245,2008.
[17] L. Moret, A. Rochedreux, S. Chevalier, P. Lombrail,& I. Gasquet, “Medical Information Delivered to Patients: Discrepancies Concerning Roles as Perceived by Physicians and Nurses set Against Patient Satisfaction”, Patient Education and Counseling, Vol. 70Issue1, pp. 94-101,2008.
[18] A. G. Dawn, & P. P. Lee, “Patient Expectations for Medical and Surgical care: A Review of the Literature and Applications to Ophthalmology”, Survey of Ophthalmology, Vol. 49 Issue 5, pp. 513-524.2004.
[19] C. C. Wu, “The Impact of Hospital Brand Image on Service Quality, Patient Satisfaction and Loyalty” African Journal of Business Management, Vol. 5 Issue 12, pp. 4873, 2011.
[20] S. S. Andaleeb, “Service Quality Perceptions and Patient Satisfaction: A Study of Hospitals in A Developing Country”, Social Science & Medicine, Vol. 52 Issue 9, PP. 1359-1370,2001.
[21] P. Padma, C. Rajendran, & P. Sai Lokachari, “Service Quality and Its Impact on Customer Satisfaction in Indian Hospitals: Perspectives of Patients and Their Attendants”, Benchmarking: An International Journal, Vol. 17Issue 6, PP. 807-841,2010.
[22] P. A. Dabholkar,C. D. Shepherd, & D. I. Thorpe, “A Comprehensive Framework for Service Quality: An Investigation of Critical Conceptual and Measurement Issues Through a Longitudinal Study”, Journal of Retailing, Vol. 76Issue 2, PP. 139-173, 2000.
[23] P. Lei,& A. Jolibert, “A Three-Model Comparison of The Relationship Between Quality, Satisfaction and Loyalty: An Empirical Study of the Chinese Healthcare System”, BMC Health Services Research, Vol. 12 Issue 1, pp. 436, 2012.
[24] M. Amin, Z. Yahya, W. F. A. Ismayatim, S. Z., & E. Kassim, “Service Quality Dimension and Customer Satisfaction: An Empirical Study in The Malaysian Hotel Industry”, Services Marketing Quarterly, Vol.34 Issue 2, pp. 115-125, 2013.
[25] C. Oliver, “Sustainable competitive advantage: Combining institutional and resource-based views”, Strategic management journal, pp. 697-713,1997.
[26] P. G. Patterson, “A Contingency Approach to Modeling Satisfaction with Management Consulting Services”, Journal of Service Research, Vol. 3Issue2, pp. 138-153,2000.
[27] J. Wirtz,& A. Mattila“Exploring the Role of Alternative Perceived Performance Measures and Needs‐Congruency in the Consumer Satisfaction Process” Journal of Consumer Psychology, Vol. 11Issue3, pp. 181-192,2001.
[28] J. Wirtz, & M. C. Lee,“An Examination of the Quality and Context-specific Applicability of Commonly used Customer Satisfaction Measures”, Journal of Service Research, Vol. 5Issue4, pp. 345-355, 2003.
[29] F. F. Reichheld, & J. W. Sasser, “Zero Defections: Quality Comes to Services”, Harvard business review, Vol. 68Issue5, pp. 105-111.1990.
[30] M. Holmlund, & S. Kock, “Relationship Marketing: The Importance of Customer-Perceived Service Quality in Retail Banking” Service Industries Journal, Vol. 16 Issue 3, pp. 287-304,1996.
[31] A. Wong,& A. Sohal, “An Examination of the Relationship Between Trust, Commitment and Relationship Quality” International Journal of Retail & Distribution Management, Vol.30Issue1, pp. 34-50,2002.
[32] E. Jasinskas, D. Reklaitiene & B. Svagzdiene, “Evaluation of Service Quality in Fitness centres” Transformation in Business & Economics, Vol. 12Issue1.2013.
[33] M. Balciunas, E. Jasinskas, & E. Koisova, “Economic Contribution of Sports Event: Analysis of Eurobasket 2011 Example” Transformation in Business & Economics, Vol. 13 Issue 2.2014.
[34] V. Hunter,& J. Michl, “Maximizing Customer Satisfaction and Loyalty to Drive Growth and Profitability”, Velocity, 2, pp. 124-132, 2000.
[35] R. L. Oliver, “A Conceptual Model of Service Quality and Service Satisfaction: Comparative Goals, Different Concepts”, Advances in Service marketing and management, 2, pp. 65-85, 1993.
[36] T. Leinonen, H. Leino‐Kilpi, M. R. Ståhlberg, & K. Lertola, “The Quality of Perioperative care: Development of a Tool for the Perceptions of Patients”, Journal of Advanced Nursing, Vol. 35Issue2, pp. 294-306, 2001.
[37] S. De Man, P. Gemmel, P. Vlerick, P. Van Rijk,& R. Dierckx, “Patients` and Personnel`s Perceptions of Service Quality and Patient Satisfaction in Nuclear Medicine”, European Journal of Nuclear Medicine and Molecular Imaging, Vol. 2Issue9, pp. 1109-1117,2002.
[38] V. S. Folkes,& V. M. Patrick, “The Positivity Effect in Perceptions of Services: Seen one, Seen Them all?”, Journal of Consumer Research, Vol. 30Issue1, pp. 125-137,2003.
[39] B. Laohasirichaikul, S. Chaipoopirutana, & H. Combs, “Effective customer relationship management of health care: a study of hospitals in Thailand”, Journal of Management and Marketing Research, Vol. 6 Issue1, 2011.
[40] V. A. Zeithaml, L. L. Berry, & A. Parasuraman, “The Behavioral Consequences of Service Quality”, The Journal of Marketing, pp. 31-46, 1996.
[41] A. Wilson,V. A. Zeithaml, M. J., Bitner, & D. D. Gremler, “Services marketing: Integrating customer focus across the firm (No. 2nd Eu)”, McGraw Hill.H, 2012.
[42] Lee, Y. Lee,& D. Yoo, “The Determinants of Perceived Service Quality and its Relationship with Satisfaction”, Journal of Services marketing, Vol. 14Issue3, pp. 217-231,2000.
[43] A. Parasuraman, V. A Zeithaml, & L. L. Berry, “Reassessment of expectations as a comparison standard in measuring Service Quality: implications for further research”, the Journal of Marketing, pp.111-124.1994.
[44] M. Zineldin, “The Quality of health care and Patient Satisfaction: An Exploratory Investigation of the 5Qs Model at some Egyptian and Jordanian Medical Clinics”, International Journal of Health Care Quality Assurance, Vol. 19Issue1, pp. 60-92,2006.
[45] E. Babakus, & G.W. Boller,“An empirical assessment of the SERVQUAL scale”, Journal of Business research, Vol. 24Issue3, pp. 253-268,1992.
[46] R. E. DuWors Jr, & G. H. Haines Jr, “Event history Analysis measures of brand Loyalty”, Journal of Marketing Research, pp. 485-493,1990.
[47] Foscht, T., Maloles III, C., Swoboda, B., Morschett, D. and Sinha, I., “The Impact of Culture on Brand Perceptions: a six-nation study”, Journal of Product & Brand Management, Vol. 17 Issue 3, pp.131-142, 2008.
[48] L. L. Berry, D. R. Bennett,& C. W. Brown, “Service Quality: A Profit Strategy for Service Institutions”, Dow Jones-Irwin, Homewood, IL.1989.
[49] R.T. Rust, &A.J. Zahorik,“Customer Satisfaction, Customer Retention, and Market Share”, Journal of Retailing, Vol. 69 Issue 2, pp. 193-215, 1993.
[50] R. A. Spreng, & R. D. Mackoy, “An Empirical Examination of a model of Perceived Service Quality and Satisfaction”, Journal of Retailing, Vol. 72 Issue 2, pp. 201-214, 1996.
[51] G. D. Kang, & J. James, “Service Quality dimensions: an Examination of Grönroos’s Service Quality Model”, Managing Service Quality: An International Journal, Vol. 14Issue 4, pp. 266-277, 2004.
[52] S. Yoon, &H. Suh, “Ensuring IT consulting SERVQUAL and user Satisfaction: a modified measurement tool”, Information Systems Frontiers, Vol.6 Issue 4, pp. 341-351, 2004.
[53] R.T. Rust, &R.W. Oliver, “The death of Advertising”, Journal of Advertising, Vol. 23 Issue 4, pp. 71-77,1994.
[54] S. M. Goldstein, &S. B. Schweikhart,” Empirical Support for the Baldrige Award Framework in US Hospitals”, Health care management review, Vol. 27 Issue 1, pp. 62-75.2002.
[55] J.J. Cronin Jr, &S.A. Taylor, “SERVPERF versus SERVQUAL: Reconciling Performance-based and Perceptions-minus-expectations Measurement of Service Quality”, The Journal of marketing, pp.125-131, 1994.
[56] J. J. Hair, R. Anderson, R. Tatham,& W. Black, Multivariate data Analysis. Peasrson Education, 2003.
[57] R. B. Kline, Methodology in the Social Sciences.2005.
[58] J. H. Steiger, “Understanding the limitations of global fit assessment in structural equation Modeling”, Personality and Individual Differences, Vol. 42 Issue 5, pp. 893-898, 2007.
[59] L. T. Hu,& P. M. Bentler, “Cutoff criteria for fit indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives”, Structural Equation Modelling: a multidisciplinary journal, Vol. 6 Issue 1, pp. 1-55, 1999.
[60] P. Barrett,“Structural Equation Modelling: Adjudging Model fit”, Personality and Individual Differences, Vol. 42 Issue 5, pp.815-824, 2007.
[61] M. Shevlin,& J. N. Miles, “Effects of sample size, Model Specification and Factor Loadings on the GFI in Confirmatory Factor Analysis”, Personality and Individual Differences, Vol. 25Issue 1, pp. 85-90,1998.
[62] J.P. Choi“The influence of Service Quality on Customer Satisfaction and repurchase at Fitness Clubs in South Korea. Doctoral Dissertation, the University of New Mexio. 2001.
[63] Liu Yi-Chin. “An Analysis Service Quality, Customer Satisfaction and Customer Loyalty of Commercial Swim Clubs in Taiwan” Dissertation of faculty of the United States Sports Academy.2008.
[64] Seyyed Javadein, Seyyed Reza, Khanlari, Amir, Esniri Mehrdad. “Model the Impact of Service Quality on Customer Loyalty of Sports”, Olympic Journal, Vol. 40, 2010,
[65] Bonsebordi Ali. “Examined the Quality of Service, Satisfaction and Loyalty Club Members Karaj Aerobics”, Fitness and Aerobics Abstracts International Conference Karaj, Vol. 46, 2010.
[66] J. Hak Lee “The influence of Service Quality on Satisfaction and Intention: A gender segmentation strategy”, Sport Management Review xxx, 2010.
[67] Mosaheb N, Solmon M. “Consumer trut, value and loyalt in Relationship Exchanges”, Journal of Marketing, 2010.
[68] Saatchiyan Vahid. “The impact of Service Quality, Satisfaction, Customer Loyalty and future Behavioral Decision to Participate in Fitness and Aerobics Centre”, Fitness and Aerobics Abstracts International Conference Karaj, pp. 126, 2010.
[69] Mohammadi Rouhollah. “The link Between Service Quality and Perceived value, Customer Satisfaction and Return Isfahan Indoor pools, Master Thesis”, Allameh Tabatabai University, Faculty of Psychology and Educational Sciences2010.
[70] Yazd Fazeli, Mohammad Ali. “The Relationship Between Service Quality and Customer Satisfaction and Loyalty swimming pools in Mashhad, Master Thesis, Islamic Azad University of Central Tehran.2011.
[71] Ameri, Mir Hassan, Bahrami, Souran, Sayyadi, Mohammad Amin. “Examine the Relationship Between Service Quality and Customer Satisfaction and Loyalty Indoor Public and Private areas of Urmia, applied research and Biological Science in Sport Management. 2012,
[72] D. Nicholas, Avourdiadou. Sevastia,“The development of Loyalty Among Novice and Experienced Customers of Sport and Fitness Centres”, Sport Management Review, pp. 419-431, 2014.
[73] Shojaei Soheila. “The Relationship Between Service Quality, Perceived value and Customer Loyalty and Satisfaction in Pools of Tehran”, MA thesis Payam Noor University of Tehran, Faculty of Educational Sciences.2012.
[74] J. Yuan, SC. Jang“Expectations, Satisfaction and Loyalty in Health and Fitness Clubs”, International Journal of Sport management and marketing Vol. 5 Issue 4, pp. 450-464, 2013.
[75] M. R. Najafzadeh,& F. Shiri, “The Relationship Between Service Quality and Perceived Value with Customer Loyalty and Aerobic Fitness Clubs in Tabriz. International Journal of Physical Education, Sports and Health, Vol. 1 Issue 6, pp. 69-73, 2015.
[76] G. H. Mc Dougall,& T. Levesque, “Customer Satisfaction with Services: Putting Perceived Value into the Equation”, Journal of Services marketing, Vol. 14Issue 5, pp. 392-410, 2000.
[77] A. Baldwin, & A. Sohal, “Service Quality factors and Outcomes in Dental Care”, Managing Service Quality: An International Journal, Vol. 13 Issue 3, pp. 207-216, 2003.
[78] A. Krepapa, P. Berthon,D. Webb, & L. Pitt, “Mind the gap: An Analysis of Service Provider Versus Customer Perceptions of Market Orientation and The Impact on Satisfaction”, European Journal of Marketing, Vol. 37 Issue 1/2, pp. 197-218, 2003.
[79] Oly Ndubisi, N., & Kok Wah, C. “Factorial and Discriminant Analyses of the Underpinnings of Relationship Marketing and Customer Satisfaction”, International Journal of Bank Marketing, Vol. 23Issue7, pp. 542-557, 2005.
[80] A. Wilson, V. A. Zeithaml,M. J. Bitner, & D. D. Gremler, “Services marketing: Integrating Customer focus across the firm”, No. 2nd Eu, McGraw Hill, 2012.
[81] S. Ozturkcan, S. Aydin, M. Ates, & A. Tansel Cetin, “Effects of Service Quality on Customer Satisfaction and Customer Loyalty: example of Marmara University Hospital”2009.
[82] A. George,& G. G. Kumar, “Impact of Service Quality Dimensions in Internet Banking on Customer Satisfaction”, Decision, Vol. 41 Issue 1, pp. 73-85, 2014.
[83] M. S. Shanka, “Bank Service Quality, Customer Satisfaction and Loyalty in Ethiopian Banking sector”, Journal of Business Administration and Management Sciences Research, Vol. 1 Issue 1, pp. 01-09, 2012.
[84] C. S. Chang, S. Y. Chen,& Y. T. Lan, “Service Quality, Trust, and Patient Satisfaction in Interpersonal-Based Medical Service Encounters”, BMC Health Services Research, Vol. 13Issue 1, pp. 22,2013.
[85] H. M. Al-Borie,& A. M. Sheikh Damanhouri, “Patients` Satisfaction of Service Quality in Saudi Hospitals: a SERVQUAL Analysis”, International Journal of health care Quality assurance, Vol. 26 Issue 1, pp. 20-30, 2013.
[86] F. S. Alghamdi, “The Impact of Service Quality Perception on Patient Satisfaction in Government Hospitals in Southern Saudi Arabi”, Saudi medical journal, Vol. 35 Issue 10, pp. 1271, 2014.
[87] A. Ismail, H. O. Zaki,& I. R. Rose, “Interlinkages Between Service Quality, Customer Satisfaction and Customer Loyalty in Malaysia: A case study of Armed Forces Medical Organizations”, Geografia-Malaysian Journal of Society and Space, 12Issue 7, 2017.
[88] B. Pouragha,& E. Zarei, “The Effect of outPatient Service Quality on Patient Satisfaction in Teaching Hospitals in Iran”, Materia socio-medica, Vol. 28 Issue 1, pp. 21, 2016.
[89] A.Wong,& A.Sohal, “Service Quality and Customer Loyalty Perspectives on Two Levels of Retail Relationships”, Journal of Services Marketing, Vol. 17Issue 5, pp. 495-513, 2003.
[90] D. Dharmayanti, “Analisis dampak Service performance Dan Kepuasan Sebagai Moderating Variable Terhadap loyalitas Nasabah (Studi pada Nasabah Tabungan Bank Mandiri Cabang Surabaya)”, Jurnal Manajemen Pemasaran, Vol. 1 Issue 1, 2006.
[91] S. Akbar, A. P. M. Som, F. Wadood,& N. J. Alzaidiyeen, “Revitalization of Service Quality to Gain Customer Satisfaction and Loyalty”, International Journal of Business and Management, Vol. 5Issue 6, pp. 113, 2010.
[92] S. Hafeez, & B. Muhammad,“The Impact of Service Quality, Customer Satisfaction and Loyalty Programs on Customer`s Loyalty: Evidence from Banking Sector of Pakistan”, International Journal of Business and Social Science, Vol. 3 Issue16, 2012.
[93] O. Kitapci, I. Taylan Dortyol, Z. Yaman,& M. Gulmez, “The Paths from Service Quality Dimensions to Customer Loyalty: An application on Supermarket Customers”, Management Research Review, Vol. 36 Issue 3, pp. 239-255, 2013.
[94] A.K. Rai, & M. Srivastava, “Exploring Dependent Relationship of Teacher`s Motivation on Quality of Teaching”,ASBM Journal of Management, Vol.6 Issue 2, pp. 1-10, 2013.
[95] F. Ye, Barrefelt, Å. Barrefelt, H. Asem, M. Abedi-Valugerdi, I. El-Serafi, M. Saghafian, & M. Hassan,“Biodegradable Polymeric Vesicles Containing Magnetic Nanoparticles, Quantum Dots and Anticancer Drugs for Drug Delivery and Imaging” Biomaterials, Vol. 35 Issue 12, pp. 3885-3894, 2014.
[96] P. Wantara, “The Relationships Among Service Quality, Customer Satisfaction, and Customer Loyalty in Library Services”, International Journal of Economics and Financial Issues, Vol. 5 Issue 1, 2015.
[97] D.Pandey & P.Shrivastava, “Psychometric properties and confermatory factor analysis of the social support scale”, International Journal of Indian Psuchology,Vol.4, PP. 191-198,2016.

Pushkar Dubey, Satish Kumar Sahu, "Effect of Service Quality on Perceived Value, Satisfaction and Loyalty of Customers: A Study on Selected Hospitals of Chhattisgarh", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.55-62, 2019.

Continuous discharge of the organic pollutants from different industry into the environment has resulted in building up their high levels in various aquatic systems. River Hasdeo is largest tributary of Mahanadi, serves as the major sources of municipal water supplies for domestic, irrigation and industrial purpose for korba town. Samples of water at four location from the river were collected and analyzed for different physicochemical parameters and 9 heavy metal concentration. Throughout the study, the result from the current investigation revealed that most of the physical and chemical parameters were exceeded from their prescribed limits which suggests all the samples are suitable for irrigation purpose but not for drinking use. Of course, stringent control is further required on the physico chemical parameters of the effluents.

Hasdeo river, Heavy metals, industrial effluents, Sampling points

[1] Inter press services (IPS), “Most River in the World are polluted; Washington D.C.” Inter – press service wore services, pp. 38-41. 1999
[2] A. Agarwal, M. Saxena, “Assessment of pollution by physicochemical water parameters.” Advanced applied science research, 2, pp. 185-189, 2011.
[3] CPCB (Central Pollution Control Board) “Comprehensive environmental assessment of industrial cluster. Report.” Ecological Impact Assessment Series, EIAS/5/2009-2010.
[4] D. Singh, J.P.Singh, A.K.Jangde, “Characterization of water and sediment quality of river ahiran in korba” research journal of recent sciences, 3, pp 21-25,2014.
[5] M.M.Vaishnav, M. Hait, P.K. Rahangdale, “Paper mill pollution hazards on ground and surface water bodies of adjoining areas of hasdeo river Champa.” Indian Journal of Science and research (IJSR) pp 1146-1151, 2014.
[6] M. Upadhyay, B. L. Sahu, O. P. Pardhi, G. Prajapati, S. Sriwas, “Physico-chemical characteristics of Hasdeo River at Korba.” International Journal of Arts, Humanities and Social Sciences, pp 1-3, 2014.
[7] Bureau of Indian Standard (BIS) “Indian Standard specification for drinking water.” BIS publication No. IS:10500, New Delhi, 2005.
[8] R. Bhutiani, D. R. Khanna, “Ecological study of river Suswa: Modeling DO and BOD.” Environmental monitoring and Assessment, pp 183-195, 2007.
[9] WHO “Sodium in drinking water.” Background document for preparation of WHO guideline for Drinking – waterquality, WHO/SDE/WSH/03-04/15.
[10] Monika Bhaskar, A.K. Dixit, “Water quality appraisal of Hasdeo River at Korba.” International Journal of Science and Research (IJSR), pp1252-1258, 2013.

Kiran Thakur, Praveen Yadav, "Heavy Metal Pollution of River Hasdeo of Chhattisgarh at Different Places in Korba District", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.63-66, 2019.

Curcuma caesia Roxb. (Kali Haldi) is commonly used as folklore medicine in Chhattisgarh state. Curcuma species contains curcumin, which is responsible for its pharmacological activities. This compound is subject of interest due to its potential use in prevention and treatment of cancer, HIV Infection and Alzheimer`s disease. This plant-specific research has always been hampered due to limited resources but with the development of turmeric EST database by David Gang`s group, the molecular and functional analysis is now possible in different curcuma species. In this study, the EST regions of the major gene CURS (Curcumin synthase) from previously reported expressed sequence tag sequences (NCBI accession numbers DY384950 and DY386934) in C. longa were used, for studies in C. caesia, the amplicon generated of CURS EST sequence in C. caesia (DY384950) was sequenced using cycle sequencer. The sequence was then analysed for similarity by using BLASTn in NCBI. The expressed sequence showed 98% similarity with the CURS1 of C. longa. Identification of candidate genes using functional genomics and bioinformatics tools can significantly contribute to understanding the biosynthesis of curcumin in Curcuma caesia.

Curcumin, Curcumin synthase, database, Expressed Sequence Tags, gene

[1] V. Sharma, I. N. Sarkar, “Bioinformatics Opportunities for Identification And Study Of Medicinal Plants”, Briefings in Bioinformatics, vol. 14. pp. 238 -250, 2012.
[2] D. C. Hao, P. G. Xiao (2015), “Genomics and Evolution in Traditional Medicinal Plants: Road to a Healthier Life”, Evolutionary Bioinformatics, vol. 11, pp. 197–212, 2015.
[3] Y. Katsuyama, T. Kita, S. Horinouchi, “Identification and Characterization of Multiple Curcumin Synthases from the Herb Curcuma Longa”, FEBS Letters, vol. 583, pp. 2799–2803, 2009b.
[4] I. Abe, I. H. Morita, “Structure And Function Of The Chalcone Synthase Superfamily Of Plant Type III Polyketide Synthases”, Natural Product Report, vol. 27, pp. 809–838, 2010.
[5] Y. Katsuyama, T. Kita, N. Funa, S. Horinouchi, “Curcuminoid Biosynthesis by Two Type III Polyketide Synthases in the Herb Curcuma longa”, Biological Chemistry, vol. 284, pp.11160–11170, 2009a.
[6] H. J. Koo et al., “Ginger and Turmeric Expressed Sequence Tags Identify Signature Genes for Rhizome Identity and Development and the Biosynthesis of Curcuminoids, Gingerols And Terpenoids”. BMC Plant Biology, vol. 13, pp. 1471-2229, 2013.
[7] Neha Behar, K.L. Tiwari, S.K. Jadhav, “Semi Quanitative Expression Studies Of Gene Involved In Biosynthesis Of Curcuminoids In Curcuma Caesia Roxb. Indian journal of biotechnology”, vol. 15, pp. 491-494, 2016.
[8] J. Parkinson, “Expressed Sequence Tags (ESTs) Generation and Analysis”, Humana Press, 2009.
[9] Y. Li et al., “EST Analysis Reveals Putative Genes Involved In Glycyrrhizin Biosynthesis”. BMC Genomics, vol. 11, pp.1471-2164, 2010.
[10] S. F. Altschul, T.L. Madden, A. A. Schaffer, J. Zhang, Z. Zhang, W. Miller, D.J., “Gapped BLAST and PSI-BLAST: a new generation of protein database search programs”, Nucleic Acids Research, vol. 25, pp. 389-402, 1997.
[11] R. K. Joshi, A. Kuanar, S Mohanty, E. Subudhi, S. Nayak, “Mining and characterization of EST derived microsatellites in Curcuma longa L”. Bioinformation, vol. 5, issue, 3, pp. 128-131, 2010.
[12] T.E. Sheeja, K. Deepa, R. Santhi, B. Sasikumar, “Comparative Transcriptome Analysis of Two Species of Curcuma Contrasting in a High-Value Compound Curcumin: Insights into Genetic Basis and Regulation of Biosynthesis”, Plant Molecular Biology Reports, vol.33, issue 6, pp. 1825–1836 2015.

Neha Behar, K. L. Tiwari, S. K. Jadhav, "EST Based Studies For Identification Of Curcumin Synthase Gene In Curcuma caesia Roxb.", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.67-69, 2019.

In mobile network several user causing data packet from a network one user to different user, unremarkably user send datain any direction. In mobile Ad hoc network user send data request frequentlywithin the network the provision loss and enormousquantity of power. During the paper, we have a tendency to discuss multiple chunk (part of information segment) throughout the information process mistreatment buffer refreshment to boost data accessibility and data accessibility for durablewithin the network. Ad hoc network is a server consumerprimarily depend network, host user acts as server to satisfydifferent user request. each mobile user to carry temporary storage information chunk and request send Multi node , at that point initial request is ask for distributed to its (requester) the nearest point, the user initial coordinate demand information section with holed copy of information section, if it`s match the request ask are response by the closest user otherwise request resend to mobile server.

Ad hoc networks, mobile node, replication, routing protocols, mobile server, buffer

[1] J. Broch, D. A. Maltz, D. B. Johnson, Y.C. Hu, J. G. Jetcheva. "A performance comparison of multi-hop wireless ad hoc network routing protocols." In Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking Texas, USA, pp. 85-97. 1998.
[2] M. Shinohara, T. Hara,S. Nishio. "A data transmission method using multicast in mobile ad hoc networks." Tenth International Conference on Mobile Data ManagementSystems, Services and Middleware,Taiwan pp. 232-237, 2009.
[3] T. Hara, S. K. Madria. "Data replication for improving data accessibility in ad hoc networks." IEEE transactions on mobile computing Vol. 5, Issue. 11, pp.1515-153, 2006.
[4] M. Shinohara, T. Hara, S. Nishio"Data replication considering power consumption in ad hoc networks."International Conference on Mobile Data Management, Germany, pp.118-125, 2007.
[5] http://en.wikipedia.org[online] [accessed: may 15, 2017] .
[6] G. Jayakumar,G. Ganapathy. "Performance comparison of mobile ad-hoc network routing protocol." International Journal of Computer Science and Network Security (IJCSNS) Vol.7, Issue.11, pp.77-84, 2007.
[7] C. E.Perkins, E.M. Belding, S. Das. “Ad hoc on-demand distance vector (AODV) routing”, In proceedings of 2nd Workshop on Mobile Computing Systems and Applications , USA, No. RFC 3561. 2006.
[8] A. H. Rahman, Z. A. Zukarnain. "Performance comparison of AODV, DSDV and I-DSDV routing protocols in mobile ad hoc networks." European Journal of Scientific Research, Vol.31, Issue. 4,pp.566-576, 2009.
[9] L. Junhai, X. Liu, Y. Danxia. "Research on multicast routing protocols for mobile ad-hoc networks", Computer Networks: The International Journal of Computer and Telecommunications Networking Computer Networks,Vol.52, Issue.5 pp. 988-997, 2008.
[10] J. Abdulai, M. Ould-Khaoua,L. M. Mackenzie. "Improving probabilistic route discovery in mobile ad hoc networks." 32nd IEEE Conference on Local Computer Networks, Ireland, pp.739-746, 2007.
[11] W. Main,N. M. Shekokar. "Study of DSR and AODV under Sinkhole Attack and its Proposed Prevention Technique." Int. Journal of Engineering Research and Applications, Vol.4, Issue.3, pp.1-42017.
[12] V. Tank,A. Lathigar, "To Detect and Overcome Sinkhole Attack in Mobile Ad hoc Network." Journal of Mobile Computing, Communications and Mobile Networks, Vol.2, Issue.3, pp.1-8, 2015.
[13] Kavitha N.S. , Malathi P.,.Lavanya R. and Mathew PhilipJim), “Efficient load balancing algorithm for manet”, International Journal of Applied Engineering Research, Vol. 9, Issue 21. 2014

M. Mahto, A.K. Shrivas, "Removal of the Load Traffic in Cellular Network and Data Availability to Maintain Load Balancing", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.70-75, 2019.

In a present time data is king for any organization. IT industry or any organization is based on data for making any type of decision like how to grow on the organization, market analysis, and consumer relationship analyses so on. In Present time data characters are changes in form of data to big data. Data is very helpful for making the decision for any organization through data mining. Big Data mining is the process of extract interesting knowledge from huge streams based databases, which hold characteristics of Big data volume, variability, velocity, variability, value, veracity, and visualization. When applying to data mining algorithm in the big dataset it gave some useful information and some not because our data mining algorithm is can’t handle all characteristics of big data at a time. This paper presented to how to data converted tradition to big data, basic characteristics of big data, suitable big data mining algorithm. We can also propose HRDSD theory for Big data mining which is useful on developing new big data mining algorithm and framework.

Big data, Data mining, Mining Algorithm, HRDSD, 3V

[1]. Fan Wei and Bifet Albert (2012): “Mining Big Data: Current Status, and Forecast to the Future”, ACM SIGKDD Explorations Newsletter, V-14, I-2, pp 1-5.
[2]. Pal Kaushika and Saini R. (2013): “A Study of Current State of Work and Challenges in Mining Big Data”, International Journal of Advanced Networking Applications (ISSN No: 0975-0290), V-12, I-3, pp 73-76.
[3]. Tiwarkhed A.S. and Kakde Vinit (2013): “ A Review Paper on Big Data Analytics”, International Journal of Science and Research (ISSN 2319-7064), V-4, I-4, pp 845-848.
[4]. Sagiroglu Seref and Sinanc Duygu (2013): “Big Data Review”, Published in the Proc. Of International Conference on Collaboration Technologies and Systems (CTS), Published By IEEE, held in San Diego, CA, the USA at 20-24 May 2013, pp 42-47.
[5]. Gandomi Amir and Haider Murtaza (2015): “Beyond the hype: Big data concepts, methods, and analytics”, International Journal of Information Management, Published By Elsevier, V-35, pp 137-144.
[6]. Parmar Vinti and Gupta Itisha (2015): “ Big data analytics vs Data Mining analytics”, International Journal in IT and Engineering(ISSN: 2321 –1776), V-3, I-3, pp 258-263.
[7]. Laney D. (2001): “3-D Data Management: Controlling Data Volume, Velocity, and Variety”, META Group Research Note Published By Springer, V- 6, pp 34-42.
[8]. Fayyad Usama and Piatetsky Shapiro Gregory (1996): “From Data Mining to Knowledge Discovery in Databases” Artificial Intelligence Magazine, V-17, I-3, pp 37-54.
[9]. K.U. Jaseena and David M. (2014): “Issue Challenges and Solution: Big Data Mining”, Published in the Proc. Of SMTP-2014, Published By AIRCC Publishing Corporation, held in Chennai, India on 27-28 Dec 2014, pp 131-140.
[10] Pandey Kamlesh (2014): “An Analytical and Comparative Study of Various Data Preprocessing Method in Data Mining” International Journal of Emerging Technology and Advanced Engineering (ISSN 2250-2459), V-4, I-10, pp 174-180.
[11]. Arun K.and Jabasheela L. (2014): “Big Data: Review, Classification and Analysis Survey”, International Journal of Innovative Research in Information Security(ISSN: 2349-7009), V-1, I-3, pp 17-23.
[12]. Manisha R. Thakare, S. W. Mohod (2015): “ Various Data-Mining Techniques for Big Data” Proceedings of the International Conference on Quality Up-gradation in Engineering, Science and Technology Published By IJCA Held on Wardha India in 9-13 October 2015.
[13]. A Sherin, Uma S and K Saranya K (2014): “Survey on BIG Data Mining Platforms, Algorithm, and Challenges”, International Journal of Computer Science & Engineering Technology(ISSN:2229-3345), V-5, I-9, pp 854-862.
[14]. D. L. A Araujo., H. S. Lopes, A. A. Freitas (1999), “A parallel genetic algorithm for rule discovery in large databases”, Published in the Proc. Of IEEE Systems Man and Cybernetics Conference, Published By IEEE at Tokyo, V-3, pp 940-945.
[15].Mr. D. V. Patil, Prof. Dr. R. S. Bichkar (2006),“A Hybrid Evolutionary Approach To Construct Optimal Decision Trees with Large DataSets”, Published in the Proc. Of IEEE International Conference on Industrial Technology, Published By in IEEE, Held in Mumbai, India on 15-17 Dec.
[16] Jiang Heling and An Yang (2016): “Research on Pattern Analysis and Data Classification Methodology for Data Mining and Knowledge Discovery”, International Journal of Hybrid Information Technology(ISSN:1738-9968), V-9, I-3, pp 179-188.
[17]. Han Jiawei, Kamber Micheline and Pei Jian (2011):“Data Mining: Concepts and Techniques” Published By Morgan Kaufmann, ISBN 978-9380931913.
[18]. Jiang Heling and An Yang (2016):“Research on Pattern Analysis and Data Classification Methodology for Data Mining and Knowledge Discovery”, International Journal of Hybrid Information Technology(ISSN:1738-9968), V-9, I-3, pp 179-188.
[19]. T. Zhang, R. Ramakrishnan, and M. Livny (1996), “An efficient data clustering method for very large databases” Published in the Proc. Of ACM SIGMOD international conference on Management of data, held on Montreal, Quebec, Canada, V-25, pp 103–114.
[20]. A. Hinneburg and D. A. Keim (1998). “An efficient approach to clustering in large multimedia databases with noise”, Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, held on New York on 27-31 August, pp 58–65.
[21]. A. Hinneburg, D. A. Keim (1999), “Optimal grid-clustering: Towards breaking the curse of dimensionality in high-dimensional clustering”. Proceedings of the 25th International Conference on Very Large Data Bases held in the USA at 7-10 Sep pp 506–517.
[22]. Pandey Kamlesh (2018),: “Mining on Relationship in Big Data era Using Appiori Algorithm”, Published in the Proc. Of National Conference on Data Analytics, Machine Learning and Security to be held on 15-16 February 2018 by Department of CSIT, GGV, Bilaspur, C.G, India, ISBN : 978-93-5291-457-9.

Kamlesh Kumar Pandey, Diwakar Shukla, RamMilan, "Data Mining Algorithm and New HRDSD Theory for Big Data", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.76-81, 2019.

The present study attempts to find the impact of issues related to online admission on satisfaction in higher educational institutions Bilaspur. A proposed model covering eight different dimensions namely student satisfaction, transparency and efficiency, information access, ease of use, safety and security, resource utilization and value for money was tested in the study. The participants were the enrolled students of first year group of higher educational institutions who were practicing online system of admission. With the help of 100 participants data were collected and analyzed. Structural equation modeling with the help of AMOS was done to find the result and model fit. The outcome revealed that student satisfaction, transparency and efficiency, information access, ease of use, resource utilization, safety and security and value for money directly and positively affected the students satisfaction. The proposed model was found to be a good fit.

Online admission, satisfaction, higher educational institutions, structural equation modeling

[1] P. J. Singh, Recommendations for meaningful and successful e-governance in India.2008.
[2] R. B.Kline, Methodology in the social sciences.2005.
[3] J. H. Steiger,“Understanding the limitations of global fit assessment in structural equation modeling”
Personality and Individual differences, Vol. 42, Issue.5,pp.893-898, 2007.
[4] L. T. Hu,& P. M.Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives” Structural equation modeling: a multidisciplinary journal, Vol. 6, Issue.1, pp.1-55, 1999.
[5] C.N. McIntosh, “Rethinking fit assessment in structural equation modelling” A commentary and elaboration on Barrett. Personality and Individual Differences, 42(5), pp.859-867,2007.
[6] M.Shevlin, & J.N. Miles, “Effects of sample size, model specification and factor loadings on the GFI in confirmatory factor analysis.” Personality and Individual differences, Vol. 2, Issue.1, pp.85-90,1998.

P. Dubey, D.K.Pandey, "A Study on Use of ICT in Online Admission Process in Higher Educational Institutions in Chhattisgarh", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.82-86, 2019.

Nowadays ample amount of data including personal data is being collected by government and private sector. This data in turn helps in running countries and their economy effectively and efficiently. In order to achieve this, private as well as government institutions collect clients or consumers data. To be more specific, in retail sector, we can say, the more data they gather, the better will be the results. But, the more personal data which is collected and analyzed, the more individuals are at risk of crimes. One must be aware of privacy invasions and its rules. As coin has two sides, same goes with data mining; it too has positive and negative aspects. Nowadays, technology is advancing and so more of the awareness is required from the customers’ side. In this paper I look at the perception of customers towards privacy invasion with reference to data mining and how Customer tracking technology work in offline Retail Stores.

Data mining, retail, customer privacy, Personal Data, micro data, information

[1] V. Ciriani, S. De Capitani di Vimercati, S. Foresti, P. Samarati, "Microdata protection", Secure Data Management in Decentralized Systems, pp. 291-321, 2007.
[2] Culnan, Mary J. and Pamela K. Armstrong. 1999. "Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation." Organization Science 10 (1): 104-115.
[3] Eastlick, Mary Ann, Sherry L. Lotz, and Patricia Warrington. 2006. "Understanding Online B-to-C Relationships: An Integrated Model of Privacy Concerns, Trust, and Commitment." Journal of Business Research 59 (8): 877-886.
[4] Foxman, Ellen R. and Paula Kilcoyne. (1993). "Information Technology, Marketing Practice, and Consumer Privacy: Ethical Issues." Journal of Public Policy & Marketing 12 (1): 106-119.
[5] Goodwin, Cathy. (1991). "Privacy: Recognition of a Consumer Right." Journal of Public Policy & Marketing 10 (1): 149-166.
[6] Milne, George R. and Andrew J. Rohm. 2000. "Consumer Privacy and Name Removal Across Direct Marketing Channels: Exploring Opt-In and Opt-Out Alternatives." Journal of Public Policy & Marketing 19 (2): 238- 249.
[7] Nowak, Glen J. and Joseph Phelps. (1997). "Direct Marketing and the Use of Individual-Level Consumer Information: Determining How and When `Privacy` Matters." Journal of Direct Marketing 11 (4): 94-108.
[8] Phelps, Joseph E., Giles D`Souza, and Glen J. Nowak. 2001. "Antecedents and consequences of consumer privacy concerns: An empirical investigation." Journal of Interactive Marketing 15 (4): 2-17.
[9] Sheehan, Kim Bartel and Mariea Grubbs Hoy. (2000). "Dimensions of Privacy Concern Among Online Consumers." Journal of Public Policy & Marketing 19 (1): 62-73.
[10] WANG,P. (2010) Survey on Privacy Preserving Data Mining, International Journal of Digital Content Technology and its Applications Volume 4, Number 9, December
[11] Zwick, Detlev and Nikhilesh Dholakia. 2004. "Whose Identity Is It Anyway? Consumer Representation in the Age of Database Marketing." Journal of Macromarketing 24 (1): 31-43.

D Kumar, Ankita, "Data Mining: Perception of Customers towards Privacy Invasion", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.87-91, 2019.

Availability of water is one of the important factor which determine the colonization of Arbuscular mycorrhizal fungus (AMF) in the roots of higher plant. Triticum aestivum plant is selected to study effect of water stress on root colonization pattern. Monocot plants are known for having 90% AMF colonization. AMF colonization pattern has been studies under drought condition, water logged condition and control condition. Under drought condition and control condition AMF colonization pattern is more or less similar while under drought condition AMF colonization percent is significantly reduced. AMF hyphal network and sporulation both are highly influence under water logged condition. Under drought condition sporulation was more in comparison to water logged and control condition. AMF colonization pattern was more extensive and prominent under drought conditions, while sporulation was comparatively low in waterlogged condition in comparison to drought condition. Various type of hyphal structures were also varied due to availability of water. Hypahl netwrok was more extensive and prominent under drought condition. Absorbing and runner hyphae extended quite long under drought condition in comparison to waterlogged condition. Appressoria formation was also prominent under drought condition. Under water logged condition only spores of Acaulospora species was found associated with the roots while under drought and control condition spores of Genus Glomus. Entrophospora and Acaulospora were found to associate with the roots. The results present study revealed that water is one of the important factor which regulated the colonization pattern of AM fungi.

Arbuscular mycorrhizal fungi, Hyphae, Acaulospora, Glomus, sporulation

[1] N.S.A. Bolan, “Critical review of the role of mycorrhizal fungi in the uptake of phosphorus by plants”. Plant and Soil, Vol. 134 (2):189–207, 1991.
[2] P. Pfeffer, D. Douds, G. Becard, and Y. Shachar-Hill, "Carbon Uptake and the Metabolism and Transport of Lipids in an Arbuscular Mycorrhiza", Plant Physiology, Vol. 120 (2):587–598, 1999.
[3] K. Akiyama, K. Matsuzaki and H. Hayashi, “Plant sesquiterpenes induce hyphal branching in arbuscular mycorrhizal fungi”, Nature, Vol. 435:824-827, 2005.
[4] C. Azcon-Aguliar and J.M. Barea, “Applying mycorrhizal biotechnology to horticulture: significance and potentials”. Sci. Hort, Vol. 68: 1-24, 1997.
[5] H.G. Mena-Violante, O. Ocampo-Jimenez, L. Dendooven, G. Martinez-Soto, J. Gonzalez- Castaneda, F.T. Davies, and V. Olalde-Portugal, “Arbuscular mycorrhizal fungi enhanced fruit growth and quality of chile ancho (Capsicum annuum L. cv San Luis) plants exposed to drought”, Mycorrhiza, Vol. 16:261-267, 2006.
[6] M. Miransari, “Contribution of arbuscular mycorrhizal symbiosis to plant growth under different types of soil stress” Plant Biol. Vol. 12:563- 569, 2010.
[7] S.P. Miller, “Arbuscular mycorrhizal colonization of semi-aquatic grasses along a wide hydrologic gradient”. New Phytologist, Vol.145: 145-155, 2000.
[8] K.J. Stevens and L.R. Peterson, “The effect of a water gradient on the vesicular-arbuscular mycorrhizal status of Lythrum salicaria L. (purple loosestrife)”, Mycorrhiza, Vol. 6: 99-104, 1996.
[9] I. Ipsilantis, and D.M. Sylvia, “Interactions of assemblages of mycorrhizal fungi with two Florida wetland plants” Appl. Soil Ecol., Vol. 35: 261–271, 2007.
[10] T. Aziz, D.M. Sylvia, and R.F. Doren, “Activity and species composition of arbuscular mycorrhizal fungi following soil removal”. Ecol. Appl., Vol. 5: 776–784, 1995.
[11] S.D. Turner, J.P. Amon, R.M. Schneble and C.F. Friese, “Mycorrhizal fungi associated with plants in ground-water fed wetlands”. Wetlands, Vol. 20: 200-204, 2000.
[12] J.M. Phillips, and D.S. Hayman, “Improved procedures for clearing roots and staining parasitic and vesicular-arbusular mycorrhizal fungi for rapid assessment of infection”. Trans. Br. Mycol. Soc., Vol. 55:158-161, 1970.
[13] P.P. Kormanik, W.C. Bryan, and R.C. Schultz, “Procedures and equipment for staining large numbers of plant roots for endomycorrhizal assay”. Can J Microbiol, Vol. 26:535–538, 1980.
[14] M. Giovannetti, and M. Mosse, “An evaluation of techniques for measuring vesicular-arbuscular mycorrhizal infection in roots”. New Phytologist, Vol. 84, 489-500, 1980.
[15] D.H. Rickerl, F.O. Sancho, and S. Ananth, “Vesicular–arbuscular endomycorrhizal colonization of wetland plants” J Environ Qual, Vol. 23:913–916, 1994.
[16] J.M. Ruiz-Lozano, “Arbuscular mycorrhizal symbiosis and alleviation of osmotic stress: New perspectives for molecular studies” Mycorrhiza. Vol. 13(6):309-17, 2003.
[17] M. IJdo, S. Cranenbrouck and S. Declerck, “Methods for large-scale production of AM fungi: past, present, future” Mycorrhiza, Vol. 21:1–16, 2011.
[18] S.P. Miller, and R.R. Sharitz, “Manipulation of flooding and arbuscular mycorrhiza formation influences growth and nutrition of two semiaquatic grass species”, Functional Ecology, Vol. 14:738–748, 2000.
[19] L.M. Carvalho, P.M. Correia, I. Caçador, and M.A. Martins-Louçao, “Effects of salinity and flooding on the infectivity of salt marsh arbuscular mycorrhizal fungi in Aster tripolium L”, Biol. Fert. Soils, Vol. 38: 137–143, 2003.
[20] X. Duan, D.S. Newman, J.M. Reibee, C.D. Green, A.M. Saxton and R.M. Augé, “Mycorrhizal influence on hydraulic and hormonal factors implicated in the control of stomatal conductance during drought”.Journal of Experimental Botany, Vol. 47:1541–1550, 1996.
[21] R.M. Auge, A.J.W. Stodola, J.E. Tims, and A.M. Saxton, “Moisture retention properties of a mycorrhizal soil”. Plant Soil, Vol. 230:87–97, 2001.

Bhaskar Chaurasia, Golden Tripathi, "Effect of Water Stress Condition on Architecture of Root Colonizing Arbuscular Mycorrhizal Fungi", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.92-96, 2019.

This work is carried out to study the effect of various process parameters upon plant efficiencies in order to prioritise them for posssible improvement in utilisation of input energy. In the process a flow sheet computer program “Cycle Tempo 5” has been used for modeling and simulation of a 250MW coal fired thermal power plant. Effects of individual parameters upon plant energy and exergy efficiency are investigated and the energy and exergy balance diagram is also drawn. The condenser pressure is found to be the most influencing factor which on changing from 0.1bar to 0.12bar both the energy and exergy efficiency reduces by 0.4%. Main steam pressure, reheat steam temperature and pressure are also affecting the performance considerably while main steam temperature is found to be the least affecting parameter among the studied one. Energy balance diagram clearly shows that the major portion of energy loss takes place at condenser while boiler is the component causing major exergy loss as seen from the exergy balance diagram.

Process parameters, Efficiencies, Simulation, Cycle Tempo, Energy and exergy balance

[1] Executive Summary, Power Sector, Central Electricity Authority, Ministry of Power, Government of India. pp. 29-31, April 2017, accessable on www.cea.nic.in, accessed on 30th Dec.2017, pp. 29-31, 2017.
[2] M. V. J. J. Suresh, K. S. Reddy, Ajit Kumar Kolar, “Energy and Exergy Based Thermodynamic Analysis of a 62.5MWe Coal-Based Thermal Power Plant – A Case Study”. International Conference on Energy and Environment, Bangi Selangor, Malaysia, pp. 24-29, 2006.
[3] M. S. Jamel, A. Abd Rahman, A. H. Shamsuddin, “Simulation of existing gas-fuelled conventional steam power plant using Cycle Tempo”. 4th International Conference on Energy and Environment, pp. 1-5, 2013.
[4] Badi U. K. W. and Rijal Fathoni, “Thermodynamic Study on a Combined Cycle Power Plant of 500MW under Various Loads Using Cycle Tempo”, Proceedings of the International Mechanical Engineering and Engineering Education Conferences, pp. 030021-1-030021-6, 2016.
[5] P. Ravindra Kumar, V. Ramchandra Raju, N. Ravi Kumar, “Simulation and parametric optimization of thermal power plant cycles”, Recent Trends in Engineeering and Material Sciences, Science Direct, Perspectives in Science, pp. 304-306, 2016.
[6] Mukesh Gupta and Raj Kumar, “Thermoeconomic Optimization of a Boiler Used in a Coal Fired Thermal Power Plant Based on Hot Air Temperature”, International Journal of Recent advances in Mechanical Engineering , Vol.4, No.2, pp. 39-44, 2015.
[7] Gholam Reja Ahmadi and Davood Toghraie, “Energy and Exergy analysis of Montazeri Steam Power Plant in Iran”, Elsevier, Renewable and Sustainable Energy Reviews 56, pp. 454-463, 2016.
[8] M. M. Rashidi, A. Aghagoli and M. Ali, “Thermodynamic Analysis of a Steam Power Plant with Double Reheat and Feed Water Heaters”, Hindavi Publishing Corporation, Advances in Mechanical Engineering, Vol. 2014, pp. 1-11, 2014.
[9] Salari Mehdi, Vosough Amir, “The Effect of Ambient Temperature to Power Plant Efficiency” 2nd International Conference on Mechanical, Production and Automobile Engineering, Singapore, pp. 248-252, 2012.
[10] Abtin Ataei and Chang Kyoo Yoo, “Combined pinch and exergy analysis for energy efficiency optimization in a steam power plant”, International Journal of the Physical Sciences, Vol. 5(7), pp. 1110-1123, 2010.
[11] Harshal D Akolekar, P Srinivasan, Jagat Sesh Challa, “Development of a Simulation Program to Optimise Process Parameters of Steam Power Cycles”, Int. J. of Thermal and Environmental Engineering, Volume 8, No. 1, pp. 55-61, 2014.
[12] Dr. Mohammed Yunus, Mohammed Asadullah, Dr. Hamza A., Ghulman, Dr. J. Fazlur Rahman, Mohammed Irfan, “Energy Based Analysis of a Thermal Power Station for Energy Efficiency Improvement”, International Journal of Modern Engineering Research, Vol. 4, Issue 3, pp. 72-78, 2014.
[13] Ankur Geete and A. I. Khandwawala, “Exergy Analysis for 120MW Thermal Power Plant with Different Inlet Temperature Conditions”, International Journal of Research in Engineering and Technology, Volume. 2, Issue. 1, pp. 21-30, 2014.
[14] Marc A. Rosen, Raymond Tang, “Assessing and improving the efficiencies of a steam power plant using exergy analysis, Part II: assessment”, Int. J. Exergy, Vol. 3, No. 4, pp. 362-376, 2006.
[15] Isam H. Aljundi, “Energy and Exergy Analysis of a Steam Power Plant in Jordan”, Elsevier, Applied Thermal Engineering, Vol. 29, pp. 324 – 328, 2009.
[16] Amir Vosough, Alireza falahat, Sadegh vosough, Hasan nasr esfehani, Azam behjat and Roya naseri rad, “Improvement of Power Plant Efficiency with Condenser Pressure”, International Journal of Multidisciplinary Sciences and Engineering, Vol. 2, No. 3, 2011.
[17] Vosough Amir, “Improving Steam Power Plant Efficiency through Exergy Analysis: Ambient Temperature”, 2nd International Conference on Mechanical, Production and Automobile Engineering, Singapore, April 28-29, 2012.
[18] Vosough Amir and Sadegh vosough, “Consideration the Important Factor to Power Plant Efficiency”, International Journal of Multidisciplinary Sciences and Engineering, Vol. 2, No.9, pp. 56-59, 2011.
[19] J. Soundhar, M. Thambi Durai, R. Vijay, M. Siva, “Parametric Study and Analysis of Varying the Condenser Pressure in Thermal Power Plant”, International Journal for Research in Applied Science and Engineering Technology, Volume 3, Issue XII, pp. 181- 189, 2015.
[20] Adeyinka O. Adeoye, Christian O. Osueke, Anthony O. Onokwai, Chinedu A. K. Ezugwu, “Enhancing the Performance of 75MW Steam Power Plant with Second Law Efficiency, Condenser Pressure and Rankine Cycle”, The International Journal Of Engineering And Science, Volume 4, Issue 9, pp. 18-29, 2015.
[21] Marc A. Rosen, Raymond Tang , “Improving steam power plant efficiency through exergy analysis: effects of altering excess combustion air and stack-gas temperature”, Int. J. Exergy, Vol. 5, No. 1, pp. 31-50, 2008.
[22] P. Regulagadda, I. Dincer, G. F. Naterer , “Exergy analysis of a thermal power plant with measured boiler and turbine losses”, Applied Thermal Engineering, 30, pp. 970 –976, 2010.
[23] S. S. L. Patel and G. K. Agrawal, “Performance Improvement Through Energy Audit of a 250MW Coal Fired Thermal Power Plant”, International Journal of Advance Engineering and Research Development, Vol. 4, Issue 4, pp. 35-43, 2017.
[24] Cycle-Tempo release 5, Delft University of Technology (TU Delft), Netherlands. www.Cycle-Tempo.nl, 2006.

S. S. L. Patel, G. K. Agrawal, "Investigation of Influencing Process Parameters to Energy and Exergy Efficiencies of a Coal Fired Thermal Power Plant using Cycle Tempo", International Journal of Computer Sciences and Engineering, Vol.07, Issue.03, pp.97-104, 2019.