European Journal of Advances in Engineering and Technology

1-4

Authors: Mustafa A Rijab, Ali I Al-Mosawi, Muhannad A Al-Najar and Shaymaa Abbas Abdulsada

This paper was focused on intervening variables in wire cut process such as pulse on time, pulse off time, voltage, type of wire which is used in experiments, They Show that 98.9% of the observed variability in MRR could be explained by the independent variables. This means that the correlation coefficient between the observed value of the dependent variable and the predicted value based on the regression model is high as this means that the statistical model could predict the Ra with about 98.5 % and 95.9 % accuracy of the testing data set for coated wire respectively.

12-20

Authors: Tadbeer Kaur and Rinkesh Mittal

The OCR system is computerized scanning system that enables user to scan a text document into an electronic computer file that can be edited, usually the OCR system’s performance gets badly affected due to the presence of hand drawn underlines (straight, curved, touched, untouched, bent, broken, elliptical etc) and annotations lines of various forms (such as straight lines, circular lines, elliptical, strokes or embossed lines etc). Such underlines and annotations are drawn by reader in free hand to memorize text, so this need to be removed from the scanned text, so as to make text legible thereby improving OCR efficiency. In this paper, we will discuss the merits and demerits of techniques used for detection and removal of underlines and annotations proposed earlier. Also an efficient technique to detect and remove different types of annotations and underlines is proposed in this paper which is based on Artificial Neural Network and Fuzzy C-means clustering.

26-33

Authors: Minal Punjo Bharambe and S C Dharmadhikari

Big Data concern with large amount of data which is complex and continuously increasing. We can relate such Big Data with Stock Market Prediction System. It becomes the challenging task for time series prediction of financial market. It will predict the future for stock prices, whether increase or decrease. There are numbers of machine learning techniques applied to predict the stock market such as Genetic Algorithm (GA), Support Vector Machines (SVM) and Artificial Neural Network (ANN). We can get more accurate prediction value with the help of artificial neural network. We have used multilayer perceptron neural network. Artificial Neural Network can recollect information of any number of years and it can foresee the element in view of the past information. If we co-relate data mining with neural network then we can get lots of achievements. Utilizing these facilities for big data is not yet deployed. So we are just trying to utilize them and come up with the solution which is suitable for Stock Market Analysis.

40-42

Authors: Anu Nair P, Vincy John and Kiran G Kumar

Energy saving is the controversy one. The main of doing this work is cost reduction of production. This can be effectively done by reducing the power Consumption. For this, the best suitable method is by diverting prime power from motor to turbine. This is done by utilization of surplus steam obtained from the Sulphuric acid plant. Since all the reactions in the Sulphuric acid plants are exothermic, a large amount of heat is generated and this is used for generating steam which is used to drive the turbine. This project aims to couple turbine with DH fan which is currently driven by 600kw motor, thus to save a huge amount of electric charges and then by reducing cost. Since steam is available in company at free cost, this method can be chosen as one of the best methods for reduction of cost of production.

47-55

Authors: N Saidulu and A Venkata Lakshmi

The present paper is devoted to describing the boundary layer flow of a non-Newtonian Casson fluid accompanied by heat and mass transfer towards a porous exponentially stretching sheet with velocity slip and thermal slip conditions in presence of thermal radiation, suction/blowing, viscous dissipation, heat source/sink and chemical reaction effects. The governing partial differential equations are reduced to a set of highly non-linear ordinary differential equations by using suitable similarity transformations and solved numerically by an implicit finite difference scheme known as the Keller box method. In the present work the effects of the non-dimensional governing parameters on velocity, temperature and concentration profiles have been discussed and presented graphically. As well as for the local skin-friction coefficient, Nusselt number and Sherwood numbers exhibited and examined. It is found that the temperature and concentration profiles are increasing to higher value when the Casson parameter increases but reverse is true for the velocity distribution. Finally, the velocity and temperature profiles are decreasing with the increasing values of the velocity slip and thermal slip parameters respectively.

62-65

Authors: Swacheta Dutta, Tasher Ali Sheikh, Smriti Baruah, Pooja Sharma and Sahadev Roy

Many automobile accidents could be control if the exact amount of distance, speed, force can maintain and calculated at the appropriate time. In this paper, discuss different algorithm and shear-force for accident avoidance in emergency time. The fuzzy controller algorithm reduces the system error approximate to zero, So that the driver need not to identify the system model, only they have to maintain the operating range of the actuator to define the membership function and to minimize the control action and provided robustness to the control system and allowing the commercial application through user interference. Which means that accident can be minimize up to 100% using these algorithm. Collision can avoid by using those algorithms to tune the fuzzy parameters. The PID methods is highly intended and produces zero overshoot with enhance transient response.