Search results for: Suchitra Chnadrashekhar

Authors: Suchitra Chnadrashekhar

Abstract:

Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.

Keywords: hydrocarbon, information technology, SAS, predictive analytics

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Authors: Somorjeet Sharma Shamurailatpam, Rabindra Das, A. Suchitra Devi

Abstract:

Computer and video display users might complain about Asthenopia, burning, dry eyes etc. The management of dry eyes is often not in the lines of severity. Following systematic evaluation and grading, dry eye disease is one condition that can be practiced at all levels of ophthalmic care. In the present study, different spectrum causing dry eye and prevalence of dry eye disease in computer users of Manipur, India are determined with 600 individuals (300 cases and 300 control). Individuals between 15 and 50 years who used computers for more than 3 hrs a day for 1 year or more were included. Tear break up time (TBUT) and Schirmer’s test were conducted. It shows that 33 (20.4%) out of 164 males and 47 (30.3%) out of 136 females have dry eye. Possible explanation for the observed result is discussed.

Keywords: asthenopia, computer vision syndrome, dry eyes, Schirmer's test, TBUT

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Authors: Suchitra Pal, Arjun Mitra

Abstract:

Objective: The purpose of this empirical study is to ascertain if gender, personality traits and social support predict the self-esteem amongst business school students. Method: The study was conducted through an online survey administered on 160 business school students of which equal-number of males and females were taken, with controls for education and family income status. The participants were contacted through emails. Data was gathered and statistically analyzed to determine the relationship between the variables. Results: The results showed that gender was not associated with self-esteem. Whilst all the personality and social support factors were found to be significantly inter-correlated with self-esteem, only extraversion, openness to new experiences, conscientiousness, emotional stability and total perceived social support were found to predict self-esteem. Conclusion: The findings were explained in the light of existing conceptualizations in the field of self-concept. Recommendations for early identification and interventions for a population with lower self-esteem levels have been made based on findings of the study. Major implications for researchers and practitioners are discussed.

Keywords: self-esteem, personality, social support, gender, self-concept

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Authors: Y. Suchitra Devi, L. Hemchandra Singh

Abstract:

Background: Because of its geographical location, Manipur lies in the conventional goiter endemic belt. During the post salt iodization period, endemic goiter was prevalent in the valley districts of Manipur without iodine deficiency. Objectives: The present study aim at the prevalence of goiter among school children (6-12 years) and women of reproductive age group (above 20 years) of Andro Assembly Constituency, Imphal- East, Manipur, India. Method: A total of 3992 individuals were clinically examined for thyroid enlargement. Hormones like TSH, FT₄, FT₃, and Anti-TPO, Anti-Tg were tested, UIC, USCN, testing of iodine in water and salt. Result: Total goiter prevalence was found to be 13.98%, median urinary iodine level was 166.0 µg/l, mean urinary thiocyanate concentration was 0.726 ± 0.408, mean water iodine concentration was 3.843 ± 2.291, and all the salt samples were above 15ppm. 6 out of 41 children and 93 out of 176 women were auto antibody positive. 41 children and 176 women were tested for TSH, FT₄, and FT₃, which shows disturbance in hormone level. Conclusion: The present study showed that the region is mildly goiter endemic without biochemical iodine deficiency.

Keywords: goiter, TSH, FT₄, FT₃, anti-TPO, anti-Tg, UIC, USCN, school children and women of reproductive age

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

Abstract:

The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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