Operational behaviour and reliability measures of a viscose staple fibre plant including deliberate failures

Sengar, Surabhi,Singh, S.B. The Korean Reliability Society 2012 International Journal of Reliability and Applicati Vol.13 No.1

This Paper deals with the stochastic behavior and failure analysis of a Viscose Staple Fibre Plant which produces fibre for making clothes. The fibre making plant is a complex system with various subsystems as: Vendor (supplies Charcoal and Sulphur, raw materials for the process), Carbon di sulphide Plant, Acid Plant, Pulp Plant and Processing Plant. The considered system can completely fail due to failure of any of the subsystems. The Carbon di Sulphide Plant can fail in two different ways, due to lack of Sulphur or Charcoal. Processing Plant has the configuration 5-out-of-10: d and 6-out-of-10: f. It is also assumed that the system can fail due to workers strike and catastrophic failure. All failures follow exponential time distribution whereas all repairs follow general time distribution. Preventive Maintenance policy has been applied to reduce the failure in the system. Various reliability characteristics such as transition state probabilities, steady state behavior, reliability, availability, M.T.T.F and the cost analysis have been obtained using supplementary variable technique and Gumbel-Hougaard copula methodology.

Will psychological empowerment and role satisfaction influence motivation? Evidence from public sector organizations in India

Ruby Sengar Malhotra,P. S. Vohra,Santosh Rangnekar 강원대학교 경영연구소 2014 Asia-Pacific Journal of Business Vol.5 No.2

This paper aims to propose a conceptual model that empirically examines the relationship of psychological empowerment & role satisfaction and their dimensions with motivation in an Indian context. 176 executives/managers from many public sector organizations in India were approached. Cronbach alpha, correlation and regression analyses were applied to check the research hypotheses. Only meaning was found to be important predictor of motivation. Interestingly, achievement and extension were also observed to be the determinants of motivation. This paper would help researchers and practitioners to work on these variables in some other sectors also. Improvement in the psychological empowerment and role satisfaction will enhance the motivation among Indian business executives/managers which will improve the overall performance of the organization. It is an innovative attempt to utilize psychological empowerment and role satisfaction independently to improve motivation in an Indian framework.

MODELLING THE DRIVERS FOR RURAL (EMERGING) MARKETS: A CASE OF INDIA

Anita Sengar,Rajat Agrawal,Vinay Sharma,Kumkum Bharti 글로벌지식마케팅경영학회 2016 Global Marketing Conference Vol.2016 No.7

Rural markets, especially in countries like India hold strong potential as emerging markets. The aim of this paper is to identify and analyse factors acting as drivers for companies to enter and serve rural markets and also to identify interrelationships among them along with their driver and dependence power, with special reference to India. A total of 13 enablers were identified on the basis of focused group discussions and interviews with experts from academics and industry. An interpretative structural modelling (ISM) and fuzzy MICMAC analysis were used to identify levels of hierarchical relationship among the drivers. The findings show that government policies and regulations are some of the most important drivers in rural markets.

SURVEY : Reputation and Trust Management in VANETs

Jitendra Singh Sengar 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.1

This paper concerns reputation and trust computation in vehicular ad hoc networks (VANETs). Various survey and implemented work has been studied and analyzed to form a new survey on trust model to VANET. In this survey it is observed that there are lot of new techniques are possible to form a new trust model in VANET to provide better security with trust concern over the entire environment of trust management in VANET. Trust management in VANET (TMV) is one well know concept and basic need to maintain a reliable secure faith full VANET on which node may believe through their close eye and could drive for safe journey with ultimate faith.

Two Segment Approach to Find Tumor Affected Area from Brain MRI

Jitendra Singh Sengar 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.3

Two region graph cut image partitioning after mapping entire image of brain in brain MRI. It is seen that piecewise constant model of the graph cut formulation becomes applicable when the image data is transformed by a main function. The proposed function contains data term to evaluate the deviation of the transformed data within two segmentation region, from the piecewise constant model, and a smoothness boundary preserving regularization term. Using a common function, energy minimization typically consists of iterating image partitioning by graph cut iterations and evaluations of region parameters via fixed point computation. The method results in good segmentations and runs faster the graph cut methods. The segmentation of MRI image is challenging due to the high diversity in appearance of tissue among the patient. An automatic interactive brain MRI image segmentation system with the ability to adjust operator control is achieved through this method.

SURVEY : Reputation and Trust Management in VANETs

Jitendra Singh Sengar 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.4

This paper concerns reputation and trust computation in vehicular ad hoc networks (VANETs). Various survey and implemented work has been studied and analyzed to form a new survey on trust model to VANET. In this survey it is observed that there are lot of new techniques are possible to form a new trust model in VANET to provide better security with trust concern over the entire environment of trust management in VANET. Trust management in VANET (TMV) is one well know concept and basic need to maintain a reliable secure faith full VANET on which node may believe through their close eye and could drive for safe journey with ultimate faith.

Growing teratoma syndrome in a post laparoscopic excision of ovarian immature teratoma

Anju Rani Sengar,Jagdeesh Narhar Kulkarni 대한부인종양학회 2010 Journal of Gynecologic Oncology Vol.21 No.2

A 26-year-old girl was referred to us in December 2008 with progressive pelvic mass while on chemotherapy. In May 2008, she presented with large adnexal mass and high alpha-fetoprotein (AFP, 265.7 ng/mL; normal range, 0 to 10). She underwent laparoscopic right salpingo-oophorectomy with staging. Since histology was immature teratoma grade I, FIGO stage 1 she was kept on surveillance. In September 2008, she developed recurrent pelvic mass with AFP levels of 2,400 ng/mL. Three courses of chemotherapy (bleomycin-etoposide-cisplatin) were given. Post-chemotherapy AFP normalized but tumor size increased. CT-scan (abdomen-pelvis) showed a large pelvic mass with calcification specks;infiltrating the sigmoid colon and abdominal wall. With provisional diagnosis of growing teratoma syndrome she had exploratory laparotomy with excision of pelvic mass along with sigmoid colon, excision of right pelvic and subcutaneous deposits, omentectomy and sigmoid anastomosis. Left ovary, left tube and uterus appeared normal and were preserved. Histology of all masses showed mature teratoma, no immature elements. At six months follow up she is disease free and has resumed menstruation. Growing teratoma syndrome is a clinico-pathological presentation during/post-chemotherapy in malignant ovarian germ cell tumor where mature teratoma grows and requires complete surgical excision. Our case highlights the safety and adequacy concerns of laparoscopic management of malignant ovarian tumor. Literature review suggests good prospects of resumption of menses, child bearing and five year survival in case of growing teratoma syndrome.

Review : A Survey on Brain Tumor Extraction from MRI

Jitendra Singh Sengar,Priyanka Chanderiya 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.6

It is survey over various approaches applied on brain tumor extraction & detection from magnetic resonance image (MRI). Some of them are completely elaborated below with their strength & weaknesses. Magnetic resonance brain image are segmented & synthetically colored to represent original data through modified fuzzy c-means algorithm, supervised computational neural network approach (SCNNA), knowledge based technique (KBT), fractal-based brain tumor detection (FBTD), automatic segmentation of brain tumor (ASBT).

Will psychological empowerment and role satisfaction influence motivation? Evidence from public sector organizations in India

Malhotra, Ruby Sengar,Vohra, P.S.,Rangnekar, Santosh KNU The Institute of Management Economy Research 2014 Asia-Pacific Journal of Business Vol.5 No.2

This paper aims to propose a conceptual model that empirically examines the relationship of psychological empowerment & role satisfaction and their dimensions with motivation in an Indian context. 176 executives/managers from many public sector organizations in India were approached. Cronbach alpha, correlation and regression analyses were applied to check the research hypotheses. Only meaning was found to be important predictor of motivation. Interestingly, achievement and extension were also observed to be the determinants of motivation. This paper would help researchers and practitioners to work on these variables in some other sectors also. Improvement in the psychological empowerment and role satisfaction will enhance the motivation among Indian business executives/managers which will improve the overall performance of the organization. It is an innovative attempt to utilize psychological empowerment and role satisfaction independently to improve motivation in an Indian framework.

Enhanced Artificial Neural Network Approach to Identify Specific Binary Pattern

Jitendra Singh Sengar 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.6

The main focus of this paper is to design a Artificial Neural Network Modal to identify specific binary pattern. This pattern will work at binary level to recognize that the received data is authentic at low level, through this work we are able to design a specific binary pattern and it would apply directly to the input layer to check accuracy in data at binary mean at low level. In this paper we have four bit data and user may arrange it in his own specific pattern, then ANN Modal will train for the given pattern then it will apply to check the pattern is found and data is authentic.