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ThesisItem Open Access A study of thermo-magnetic effects on static state of cholesteric liquid crystal between two hot co-axial circular cylinders(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2009-06) Gangwar, Sukhdev Singh; Sharma, A.K.Liquid crystal the fourth state of matter is observed between the crystalline solid and amorphous liquid states. It exihibits the properties of liquids as well as that of crystalline solid state. In the present study we have considered an infinite static layer of cholesteric liquid crystal lying between two infinite hot co-axial circular cylinders in the presence of azimuthal magnetic field when both the cylinders are held at different temperatures and are lying at rest. We have examined the thermo-magnetic effects in this problem. After obtaining the system of governing differential equations we have solved it numerically by Newton Raphson method. The results are then graphically plotted. It has been observed that orientation of molecules varies with the variation of magnetic field and temperature gradient parameters.ThesisItem Open Access A study on effects of uniform magnetic field on flow of cholesteric liquid crystals between two relativaly moving parallel hot plates(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2004-06) Meena Kumari; Sharma, A.K.A study has been conducted on the flow of an incompressible cholesteric liquid crystals with director of unit magnitude between two infinite relatively moving parallel hot plates with the objective: To examine the effects of uniform magnetic field in (x,y,z) directions in the plane of the lower plate which is at rest while the upper plate is motion with a uniform horizontal velocity and the two plates are maintained at different temperature. Differential equations governing the two components of horizontal velocity ( u) and (v) , orientations of directors (θ ) and (Φ) have been formed and solved by using couple stress boundary conditions. In the solution of these equations, we observe that there is no effect of magnetic field on the two velocity components, but they increase with the increase in thermal gradient parameter (E1).The effect of magnetic field on the orientation of molecules (θ) and (Φ) causes variation in their profile.ThesisItem Open Access A study on effects of uniform magnetic field on flow of cholesteric liquid crystals between two relativaly moving parallel hot plates(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2004-06) Meena Kumari; Sharma, A.K.A study has been conducted on the flow of an incompressible cholesteric liquid crystals with director of unit magnitude between two infinite relatively moving parallel hot plates with the objective: To examine the effects of uniform magnetic field in (x,y,z) directions in the plane of the lower plate which is at rest while the upper plate is motion with a uniform horizontal velocity and the two plates are maintained at different temperature. Differential equations governing the two components of horizontal velocity ( u) and (v) , orientations of directors (θ ) and (Φ) have been formed and solved by using couple stress boundary conditions. In the solution of these equations, we observe that there is no effect of magnetic field on the two velocity components, but they increase with the increase in thermal gradient parameter (E1).The effect of magnetic field on the orientation of molecules (θ) and (Φ) causes variation in their profile.ThesisItem Open Access Multi-trait selection indices for improving egg mass in egg type chicken(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2004-06) Santhosh, M.; Bais, R.K.S.The poultry industry is the fastest growing sector among Indian agriculture sectors and today India occupies 4th and 6th place in the world for egg and broiler production, producing 41 billion eggs and 1000 million broilers every year. The impact of such a massive growth of the poultry production has not been felt by masses because of the population explosion. The per capita availability of 40 eggs and 1 kg meat is far behind the ICMR recommendations and the gap can be bridged by developing superior layers following appropriate breeding strategies. In view of the above, the present study was undertaken to construct and evaluate the multi-trait selection indices for improving egg mass in a pure strain (N) of White Leghorn maintained by a commercial poultry heeding organization. The phenotypic and genetic parameters were estimated in the flock under study. The heritability estimates were found to be low for EM40, EP40, EW40 and ASM, whereas the moderate heritability estimates were reported for BW20 and BW40. The egg mass was having a high positive correlation with egg production while egg weight had lower positive association with egg mass. Thus, selection for egg mass seems to be appropriate for improving both egg number and weight. A total of fifty seven multi-trait selection indices were constructed in different combinations incorporating six, five, four, three and two traits as the selection criteria with the selection objective in all the cases being improvement of egg mass only which comprises the aggregate genotype. The multi-trait selection index (IMT1) including all the six traits was found to be the most desirable with the gain in all the individual traits in favourable direction. Based on the estimates of genetic cost of restriction of different traits, the egg mass was found to the have the highest contribution followed by EW40, EP40, BW20, BW40 and ASM. The direct and correlated responses in performance traits from individual selection of pullets were estimated and on comparing with the best index (IMT1), the selection for 20 week body weight was found to be the most desirable with respect to relative accuracy/ efficiency and gain in individual traits particularly the egg number and egg weight for the population under study.ThesisItem Open Access Mathematical modeling of impact evaluation and phytoremediation of pulp and paper industry effluent(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2004-06) Sanjeev Kumar; Dube, K.K.The problem of pollution as a consequence of increased industrialization is, by now, a well-known phenomenon. In case of pollution in water, the problem is more serious. Not only industrial wastes, but also discharge of domestic waste water and sewage can be major pollutant. In present investigation three mathematical models first on the impact of pulp and paper mill effluent on soil microbial biomass, second on the effluent impact on soil microbial activities and third on phytoremediation of pulp and paper mill effluent employing Eichhornia crassipes have been developed. In first and second models the variates taken into consideration decreased exponentially with increase in the distance from the source of pollution, whereas in the third model similar decrease was observed with the increase in duration of phytoremediation. The former two models are valid for only point source pollution impact and not for non-point source pollution where varieties of unknown factors contribute towards ill impact of pollutants. The third model is equally prominent for devising technique to get rid off the ill impact of the industrial effluent. The mathematical model presented here provides a fairly accurate prediction of the ill impact of pollutant present in pulp and paper mill effluent and its remedial measure employing plant like Eichhornia crassipes. These models could be used for predicting the ill impact of other industrial waste water and their removal through phytoremediation technique, as well.ThesisItem Open Access Intuitionistic fuzzy and hesitant fuzzy sets based time series forecasting methods(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-12) Bisht, Kamlesh; Sanjay KumarIn the present research work, various time series forecasting methods using intuitionistic fuzzy, hesitant fuzzy and dual hesitant fuzzy sets are developed to address issue of non stochastic uncertainty and non-stochastic hesitation. These methods are presented in form of various models. Model [1] and Model [4] are computational algorithm based higher order fuzzy time series forecasting models which are based on intuitionistic fuzzy and hesitant fuzzy respectively. Model [2] and Model [3] use hesitant fuzzy set to handle hesitancy in fuzzy time series forecasting. In the present research work, methodology of hesitant fuzzy time series forecasting method is also developed and presented in Model [5]. Model [6] is intuitionistic fuzzy time series forecasting model which is based on dual hesitant fuzzy set. Model [2], Model [3], Model [5] and Model [6] use max-min composition operation. Performance of these developed models over existing fuzzy time series and intuitionistic fuzzy time series forecasting methods is verified by implementing them on two time series data of University of Alabama and SBI share price. The outperformance of all models is tested using RMSE and AFER error measures. Validity of the developed models id tested using correlation coefficients, tracking signal, evaluation parameter and performance parameters. Superiority of developed models is also tested using two tailed t-test at the confidence level 1% and 5%. In forecasting enrollments of University of Alabama, the performance of Model [4] in terms of both RMSE and AFER is found better than model [1], Model [2], Model [3], Model [5] and Model [6]. In forecasting share prices of SBI, the performance of Model [6] in terms of both RMSE and AFER is found better than Model [1], Model [2], Model [3], Model [4] and Model [5]. In forecasting enrollments of University of Alabama, Model [1] outperforms over Model [2] but its performance is equally good as of Model [3], Model [4], Model [5] and Model [6]. Model [2] outperforms over Model [4] and Model [5] but its performance is good as Model [3] and Model [6]. Model [3] performs equally good as Model [4], Model [5] and Model [6]. Model [4] outperforms over Model [6] but its performance is good as Model [5]. Model [5] is equally good in performance as the Model [6]. In forecasting SBI share prices, Model [1] outperforms over Model [2], Model [3] but its performance is good as Model [4], Model [5]. Model [2] outperforms over Model [4], Model [5] and Model [6] but its performance is good as Model [3]. Model [3] outperforms over Model [4], Model [5] and Model [6]. Model [4] performed equally good as Model [5] and Model [6]. Model [5] outperforms over Model [6]. All developed models not only handle the non-stochastic uncertainty and hesitation but also enhance the accuracy in forecasted enrollments and financial time series data of SBI share price.ThesisItem Open Access Statistical evaluation of body paramaters in adolescent girls(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2016-07) Joshi, Bhawana; Shukla, A.K.Adolescence is a developing stage and the transition period of adolescence encompasses multiple significant changes like physical, psychological and social that takes place between childhood and adulthood. Body composition & anthropometric parameters are the surrogate measures of metabolic changes that occur in this period of growth and maturation. The assessment of these parameters provides key information to understand the current as well as future health of adolescents. In India, adolescent girls need special attention in view of their role in shaping the health and well being of the present and future generations. Therefore, the present study was undertaken with the major objectives to find distribution pattern of several body parameters, study of inter-relationship between body composition and anthropometric parameters, comparison of body parameters in different age groups and development of prediction models for BF% using different body parameters of adolescent girls. Secondary data of adolescent girls related to Age, Height (H), Weight (W), Body Mass Index (BMI), Waist Circumference (WC), Hip Circumference (HC), Waist-to-Height Ratio (WHtR), Waist-to-Hip Ratio (WHR), Total Body Water Percentage (TBW%), Body Density (BD), and Body Fat Percentage (BF%) were used in this investigation. Data were analysed with help of various parametric and non-parametric statistical techniques using different software namely SAS, IBME SPSS Statistics 20, EasyFit 5.6 Professional and JMP. The following conclusions were drawn from this study. • None of the body parameters under study follow Normal Distribution in the Combined Age Group (13-17 years) as well as in different segments of age groups of adolescent girls which revealed that for statistical study of these parameters non-parametric test procedures should be preferably used by the researchers and nutritionist for more reliable results. • Best fitted distribution of BF% and BMI in different segments of age groups were found appropriate for the prediction of proportion of adolescent girls in different health status categories. Therefore, these distributions could be effectively used to examine the health status of adolescent girls in different populations. • Age, TBW% and BD showed significant negative correlation with BF% whereas W, BMI, WC, HC, WHR and WHR were significantly positively correlated with BF% in adolescent girls of Combined Age Group (13-17 years). • TBW% and BD showed a significant negative partial correlation with BF% when the effect of other body parameters were controlled together. • Significant difference were observed in different segments of age groups with respect to H,W ,BMI, HC,WHR, BF% and TBW% whereas no significant difference was observed with respect to WHtR & WC. • The best prediction model for BF% could be achieved using Multiple Linear Regression Models as compared to Linear Regression and Non Linear Regression Models. The findings of the present study are expected to provide a new direction to health planners and nutritionists for decision making in health related issues of adolescent girls.ThesisItem Open Access Fuzzy rule based modeling to study effect of distillery effluent on crop economic field(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-07) Dhyani, Makrand; Sanjay KumarThesisItem Open Access Analysis and forecasting of financial time series using artificial neural network(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2017-07) Chauhan, Shikha; Pal, A.K.Present work entitled “ANALYSIS AND FORECASTING OF FINANCIAL TIME SERIES USING ARTIFICIAL NEURAL NETWORK” treated the issue of developing an artificial neural network model which generates a buying signal based on Golden crossover and sell signal if 50 DMA crosses below 200 DMA and also, forecasts the stock index for future. Artificial neural networks are very good in the stock market prediction as they are non-linear and complex models. In this work, we have used the artificial neural network to predict the stock index and behavior (buy or sell signal) of financial time series. The presented study comprises five chapters. The first chapter is aimed to fulfill the basic need of introducing time series, artificial neural network and the use of neural network in the time series forecasting. Chapter two accomplished majority of passed research work related with the present work. Chapter three covers the material and methods used for the present study. We have presented the neural network for the prediction and simulated it in MATLAB software. Chapter four describes the result and discussion of the encountered taken in chapter three. The work has been summarized in chapter five. Along with the finding of the study, the literature used in the course of the study has been referred under the section of literature cited. The related study may be helpful for the investors of stock market to make wise decisions so that they can have maximum profit.