VOLUME 1 ISSUE 12

VOLUME 1 ISSUE 12

IJATSER Volume 1 – Issue 12, November 2016 Edition

All listed papers are published after full consent of respective author or co-author(s).
For any discussion on research subject or research matter, the reader should directly contact to undersigned authors.

IJATSER-Nov16-1EXPERIMENTAL STUDY OF USING WASTE MARBLE POWDER AND STEEL FIBRES FOR PREPARATION OF CEMENT CONCRETE

AUTHORS : Er. Vishendra Pund, Prof. Shailesh Kushwah , Prof. Kapil Soni

ABSTRACT: Concrete is currently one of the most widely used construction material. One of the recent advancement in construction industry is replacement of materials in concrete. The replacement of materials offers cost reduction, energy savings and protection of environment. On the other hand leaving the waste materials to the environment directly can cause environmental problem. Hence the reuse of waste material has been emphasized. Waste can be used to produce new products or can be used as admixtures so that natural resources are used more efficiently and the environment is protected from waste deposits. There are several reuse and recycling solutions for this industrial by-product, both at an experimental phase and in practical applications. However the concrete produced from the waste composition can be produced more durable by the application of steel wires for enhancing the tensile properties of concrete. To counter the tensile limitation, concrete is ordinarily assorted with steel reinforcement. The tensile reinforcement compensates for the lack of tensile ability, increased brittleness and decreased strain capacity. To achieve this objective we are partially replacing the cement with waste marble powder as partial replacement of cement incorporating with steel fibers. In this research, steel binding wires were used as steel fibers which are locally available at very cheap cost. Steel fibers were added in different percentage i.e. 0.5 %, 1 %, 1.5 % and 2 % along with control samples (0% Fibers) with addition with waste marble powder. For this purpose cubes, cylinders and short beams were casted and checked under Universal Testing Machine for compressive and tensile strength. The research showed that there was slight increase in the strength due to addition of steel fibers.

Keywords: Concrete, Waste Materials, Marble powder, Steel Wires, Durability, Mechanical Properties.

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IJATSER-Nov16-2 : An Effective Approach of Artificial Neural Network Technique for Stock Market Prediction

AUTHORS : Rohit Rai, Mradul Dhakar

Abstract: – In the current scenario stock market prediction is an emerging field that in future the stock price will be increased or decreased. Therefore we can predict the stock market variations such that which companies share value in next time will go high or low. The proposed method can determine unseen pattern from the historic data that have likely predictive ability in their investment decisions. The forecast of stock markets is a demanding task of financial time series prediction. Many researchers provided various method of time series forecasting but the neural network is better solution from others. Because it is depends on learn by example. For this forecasting a huge amount of historical data is used better prediction. There are four indicators (Relative Strength Index (RSI), Rate of Change (ROC), Simple Moving Average (SMA), Linear Regression Indicator (LRI)) were combined in this methods for better performance with the neural network back propagation algorithm. When MLP is trained sufficient data and parameters with optimal Architecture .it can forecast better stock price very well. This model helps to predict next day open price of SBI stock price with less error and good accuracy. The performance is considered by minimum mean square error such as MAE, M.S.E, and RMSE. it compares the result with other model. To predict stock market data we are using Neural Network with backpropogation. It supports numerically and graphically.

Keywords—Simple Moving average (SMA), Linear Regression Indicator (LRI), Relative Strength Index (RSI), Rate of Change (ROC), NN (Neural Network), Back Propagation (BP).

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IJATSER-Nov16-3 : Simulation & Modeling of Different level multilevel inverter for THD reduction for PV application

AUTHORS :RICHA JAIN , SHRIYANSH JAIN, AMOL BARVE

Abstract: The multilevel began with the three level inverter. Use of conventional two – level pulse width modulation (PWM) inverter provide less distorted current and voltage but at cost of higher switching losses due to high switching frequency. The rate of change of voltage dv/dt of switches is low since the switches endure reduced voltage and due to the lower voltage swing of each switching cycle Multilevel inverter are emerging as a practical alternative for high power , medium voltage application. This paper compares total harmonics alteration in five level , nine level,15 level cascade multilevel inverter. A sinusoidal PWM technique is used to control the switches of the inverter. Simulation revise confirms the reduction in harmonics distortion.

Index Terms: Multilevel inverter, Multilevel SPWM, THD

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