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Research Paper

An algorithmic formulation of solutions of solvable standard quadratic congruence of prime- power modulus

In this paper, a new generalised method of solving standard quadratic congruence of prime-power modulus is discovered. An algorithmic formula is developed. It works efficiently. It is the generalisation of author’s proposed Middle-pair solution method of solving standard quadratic congruence of prime modulus. It is very simple and time-saving.

Published by: B M Roy

Author: B M Roy

Paper ID: V4I6-1367

Paper Status: published

Published: December 15, 2018

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Research Paper

Coconut fiber reinforced polymer composite for partition wall

The increase in consumption of coconut usage every year leads to the production of the fiber of it, presently a very less quantity of coconut husk is used in domestic application mainly as a fuel and remaining as waste which is directly proportional to the quantity of coconut cultivated. The main thrust of present research work is to explore the possibility of utilizing coconut husk fibers as reinforcement for composites with an appropriate matrix material. The fiber reinforced plastic composites made of areca fibers extracted from areca were prepared with used plastics. The composite material prepared with different proportion of reinforcement and matrix material. The required dimensions of the die were prepared using mild steel. The matrix material is placed layer by layer with reinforcement in the die. The die is designed to heat the material to its semi-liquid state with the help of heater at the bottom of the die. The material is compacted by an applying a force 500 kgf and soaked in a die for 2 hours at 115C. Then the composite is allowed to cool to room temperature. The resulted composite is cut into required dimensions to carry out mechanical properties of it; they are Tensile strength, bending strength, and compression strength and impact tests. The results of the mechanical properties of composites are quite competitive with existing plywood planks. The composite is also tested for threading operation by tapping and it shows tapping is obtained successfully in the composites.

Published by: Kumar Naik M.

Author: Kumar Naik M.

Paper ID: V4I6-1362

Paper Status: published

Published: December 15, 2018

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Research Paper

Contact analysis of involute profile teeth

In this project, the purpose is to provide an in-depth understanding of tooth engagement in splined couplings based on variations in the clearance between mating teeth. It is standard practice to assume that 25-50% of the total spline teeth in a coupling are engaged due to variations from the manufacturer. Based on the assumed number of teeth engaged, the load capability of a splined coupling is determined.variations from tooth geometry from manufactured, the number of teeth actually engaged is dependent on the applied load and tooth errors

Published by: K. Mohan Kumar, B. Anbarasan

Author: K. Mohan Kumar

Paper ID: V4I6-1359

Paper Status: published

Published: December 15, 2018

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Research Paper

Multi-criteria inventory classification for retailers using Artificial Neural Network

This paper presents an artificial neural network technique which is used for classification of multi-criteria inventory for retailers. The control of large inventory items is not possible for maximum profit with an equal attention. Generally, single criteria inventory classification is followed by inventory manager such as total cost. It has been realized that for retail organizations the single criteria inventory classification is less effective, So, instead of cost, there are some other criteria which are more important, which are profit per unit, demand of the item, shelf-life, of an item and lead time to the store. So a multi-criteria approach has been used here for inventory classification of retail outlets. For this purpose, the artificial neural network technique has been used the classification of inventory has carried out by pattern recognition and classification tool in MATLAB software. For training, the network scaled conjugate gradient backpropagation is used in this work. So, a classifier model is trained for the classification of multi-criteria inventory and prediction of inventory based on an expert system which can classify any number of items in retail outlets.

Published by: Dewa Ram Kumawat, Abdul Samad

Author: Dewa Ram Kumawat

Paper ID: V4I6-1360

Paper Status: published

Published: December 15, 2018

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Research Paper

Self tuned PID based speed control of BLDC motor

Brushless DC Motors (BLDCM) have found immerse applications in automobile, automation, consumer electronics, medical and industrial applications due to their high efficiency, long operating life ratio of torque delivered to the size and fast dynamic response. In a brushless motor, the rotor incorporates the magnets, and the stator contains the windings. Commutation is implemented electronically with electronic speed controller (ESC) which uses the semiconductor switches to change the current in the windings based on the motor back EMF. PID controller is designed in MATLAB Simulink software and PID gains are tuned using an auto-tuning method. Digital PID controller is then implemented on FPGA as it provides greater flexibility and higher resources for implementing control algorithms. FPGA (PID controller) receives back EMF output from BLDC motor and generates the gate pulses which drive the switches of the electronic speed controller. The actual speed of the motor is compared with the reference speed given and the error signal is processed in a PID controller to obtain the required pulse width. As the motor rotates, feedback (back EMF) signals are produced in accordance with the rotor position. Three phase voltages are produced from ESC after they receive the decoded signals. These voltages are fed as input to the motor and it rotates at a required speed

Published by: Anuradha Muley

Author: Anuradha Muley

Paper ID: V4I6-1352

Paper Status: published

Published: December 15, 2018

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Research Paper

Emerging face of E-tailing: Online food delivery

The growth of the internet has created a significant impact on the lives of people for customers convenience is something which customers look forward to. With the internet, there are new ways of satisfying them with relative technologies and for marketers, it is about selling the products throughout the year without geographical and temporal boundaries and to understand customer’s perception on how they use online services such as food delivery and on understanding why they don’t do so. The online food delivery business has seen a rapid growth, growing at 15% every quarter in 2017. The growth has resulted in the number of orders on a daily basis clocking an average of 400,000 during the September quarter. The Fast food Industry is expected to reach to US$27.57 billion by 2020 which is set for an exponential growth as we can see the market is expected to grow at CAGR of 18% by 2020. This study attempts to take a look at the online food delivery ecosystem with a focus on its drivers and analyses the factors that are driving the growth of this business, especially in Bangalore City.

Published by: Arijit Roy, Dr. Kiran Reddy

Author: Arijit Roy

Paper ID: V4I6-1340

Paper Status: published

Published: December 15, 2018

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