Open Access Original Research Article

Comparative Performance of Multiple Linear Regression and Artificial Neural Network Based Models in Estimation of Evaporation

Neeraj Kumar, Ganesh Upadhyay, Pankaj Kumar

Advances in Research, Page 1-11
DOI: 10.9734/AIR/2017/36473

Evaporation is an integral part of water cycle. The measurement of evaporation plays a significant role in water management planning, irrigation requirement and to know the water availability in storage system. Considering the complexity in estimation of evaporation by empirical formulas, this study was undertaken to develop regression and neural network based models for estimation of evaporation from climatic variables. The parameters viz. average temperature (), wind speed (W), average relative humidity () and sunshine hours (S) were used as predictors and evaporation was considered as response variable. Mean squared error (MSE) and correlation coefficient (r) were used to judge the performance of developed models. The multiple linear regression (MLR) model exhibited MSE 1.12 and 0.92 whereas with artificial neural network (ANN) model, MSE was found to be 0.56 and 0.68 in training and testing phase, respectively. In training period, correlation coefficient was 0.92 for MLR model as compared to 0.96 with ANN model. The correlation coefficient in testing phase was found to be 0.95 and 0.97 for MLR and ANN model, respectively. The developed ANN model outperformed MLR model in estimation of evaporation from climatic variables.

Open Access Original Research Article

Analysis of Carbide Tool Wear of EN38 Steel

C. H. Achebe, J. L. Chukwuneke, T. D. Otobo, P. S. Aguh

Advances in Research, Page 1-11
DOI: 10.9734/AIR/2017/36441

This research work analyzed carbide tool wear of the single point cutting tool used in the turning operation of EN38 steel. Sixteen experiments were conducted, to determine how feed rate, depth of cut and spindle speed of the tool, made of tungsten carbide, caused tool wear at varying machining parameters. Feed rate of 1.0, 1.5, 2.0, 2.5, and 3.0, rev/min and depth of cut of 0.2, 0.3, 0.4, 0.5, 0.6, mm and Spindle speed 400, 600, 800, 1000, 1200, rpm, were considered. Temperature and weight loss were equally measured during the experimental processes with a constant time of 15munites. With the data obtained, various graphs were plotted to show the variation of feed rate, weight loss, depth of cut, spindle speed and temperature. Regression analysis using partial least square method was used to determine the regression coefficient of temperature and weight loss. The probability value of 0.004 and optimal R-square value of 0.9957 were consequently obtained from the regression analysis. It was observed that temperature increase and weight loss depend on feed rate, spindle speed and depth of cut and also that an increase in feed rate, spindle speed and axial depth of cut had a significant effect on tool wear, revealing that the alpha value of 0.05 is greater than the probability value of 0.004 from the regression analysis.

Open Access Original Research Article

Evaluation of Variation in Macronutrients of Soils in Harda District, Madhya Pradesh, India - A Geostatistical Approach

Subhash ., G. S. Tagore, Debabrata Nath, M. Mohanty, Nishant K. Sinha

Advances in Research, Page 1-13
DOI: 10.9734/AIR/2017/35391

GPS based three hundred and three surface soil samples (0-15 cm) were collected from dominant cropping system and analyzed for different soil characteristics in laboratory using standard procedures. The results were statistically interpreted that the N, P, K, and S were found to be deficient in 56.77, 31.68, 6.6 and 52.48 percent soil samples, respectively. Geo-statistical results revealed that the exponential model was found best fit for available N, P, K, and S. Spatial distribution maps showed that soil pH, EC, organic carbon, calcium carbonate, N, P, K, and S spatially varied and were deficient in Hundia, Timarani, Khirkiya and Sirrali. These maps will be helpful for farmer’s to decide the quantity of fertilizer to be added to soil to improve fertility status for sustainable crop production and environmental protection.

Open Access Original Research Article

Effect of Instructor Quality and Availability on Ghanaian Students’ Interest in Mathematics Using Regression and Principal Component Analysis

Yarhands Dissou Arthur, Samuel Asiedu-Addo, Charles K. Assuah

Advances in Research, Page 1-11
DOI: 10.9734/AIR/2017/34570

The study investigated the effect of instructor quality and availability on Ghanaian students’ interest in Mathematics. The study used structured questionnaire to randomly select 1,263 students from 10 public secondary schools in the Ashanti Region of Ghana. The study performed principal component analysis on the instructor quality and availability construct as well as regression analysis to ascertain the contribution of instructor quality on students’ interest development. Here, the results showed that the instructor quality construct with Cronbach’s alpha value of 0.699 can be further categorized into two principal components with the first component explaining 41.7% while the second component explains 12.8% with a total cumulative variance of 54.5%. The results from the multiple regression analysis showed significant (p<0.0001) in predicting students’ interest in Mathematics. The model could predict 7.4% of the variability in students’ interest in Mathematics. The study finally concluded that students’ interest in Mathematics can be enhanced through quality of instruction and availability of qualified instructors. The study recommends to the education ministry to take cognizance of the result in their recruitment of Mathematics teachers for the various levels of education especially in the first and second cycle schools.


Open Access Original Research Article

Evaluation of Existing, Desired Competencies and Skills of Apple Growers in Low and High Altitude Regions of Shopian, Jammu & Kashmir, India

Zahoor Ahmad Shah, Rekhi Singh, Mushtaq Ahmad Dar, Jehangir Muzaffar Matoo, Rufaida Mir

Advances in Research, Page 1-10
DOI: 10.9734/AIR/2017/35604

The present study was conducted in low and high altitude areas comprising of villages viz. Keegam, Tikora and Tengwani (low altitude areas) and Imam-Sahab, Hillow and Nagbal (high altitude areas) of district Shopian of Jammu and Kashmir with sample size of 120 apple growers. The district Shopian was purposively selected, because of the potentiality for the development of horticulture, mainly because 90 per cent area of the district was under apple plantation. It has been observed that most of the apple growers were not able to perform different tasks (not skilled) regarding apple cultivation and as such they were of the opinion that they need special training sessions in order to be enough competent to perform different tasks in apple cultivation, some apple growers were eager to get trainings on priority basis. It has also been observed that the skills and competencies of the fruit growers regarding expert guidance planning, layout planning, weed management, pest and disease management, intercultural operations, soil testing etc. were low and as such fruit growers need trainings mostly in soil and water testing, pest and disease management, physiological disorder management among others.