College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Computer science & Sliding mode control. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Automatic dual-axis solar tracking system for parabolic dish

Abstract: In country like India demand of energy increases with increase in population so the use of renewable and natural sources of energy like wind energy, tidal energy, solar energy etc is the need of time in country. In this paper we present development and experimental study of two axis automatic control of solar tracking system using Arduino. In hardware development five light dependent resistors (LDR) has been used to sense and gather maximum solar energy. Two permanent magnet DC motors are used to move the solar dish according to the solar energy sensed by LDR. In software part we design a controller which will move the collector dish to track the sun. The controller uses LDR sensors as input and permanent magnet DC geared motors as an output. LDR are used to sense the intensity of light and generate the signals which will be further processed by ATmega328 microcontroller. Microcontroller executes the algorithm and gives control command to motor driver. This paper describes development of automatic dual axis solar tracking system for solar parabolic dish.

Dynamic response of structure with tuned mass friction damper

Abstract: The effectiveness of tuned mass friction damper (TMFD) in suppressing the dynamic response of the structure is investigated. The TMFD is a damper which consists of a tuned mass damper (TMD) with linear stiffness and pure friction damper and exhibits non-linear behavior. The response of the single-degree-of-freedom (SDOF) structure with TMFD is investigated under harmonic and seismic ground excitations. The governing equations of motion of the system are derived. The response of the system is obtained by solving the equations of motion, numerically using the state-space method. A parametric study is also conducted to investigate the effects of important parameters such as mass ratio, tuning frequency ratio and slip force on the performance of TMFD. The response of system with TMFD is compared with the response of the system without TMFD. It was found that at a given level of excitation, an optimum value of mass ratio, tuning frequency ratio and damper slip force exist at which the peak displacement of primary structure attains its minimum value. It is also observed that, if the slip force of the damper is appropriately selected, the TMFD can be a more effective and potential device to control undesirable response of the system.

To improve association rule mining using new technique: Multilevel relationship algorithm towards cooperative learning

Abstract: Mining the Data is also known as Discovery of Knowledge in Databases. It is to get correlations, trends, patterns, anomalies from the databases which can help to build exact future decisions. No one can assure that the decision will lead to good quality results. It only helps experts to understand the data and show the way to good decisions. An objective is to make rules from given multiple sources of customer database transaction. It needs increasingly deepening knowledge mining process for finding refined knowledge from data. Earlier work is on mining association rules at one level. Though mining association rules at various levels is necessary. Finding of interesting association relationship among large amount of data will helpful to decision building, marketing, & business managing. For generating frequent item set we are using Apriori Algorithm in multiple levels so called Multilevel Relationship algorithm (MRA). MRA works in first two stages. In third stage of MRA uses Bayesian probability to find out the dependency & relationship among different shops, pattern of sales & generates the rule for learning. This paper gives detail idea about concepts of association mining, mathematical model development for Multilevel Relationship Algorithm (MRA) and Implementation & Result Analysis of MRA and performance comparison of MRA and Apriori algorithm.

DDF: Diversity Dragonfly Algorithm for cost-aware test suite minimization approach for software testing

Abstract: The test suite minimization approach is a major research topic that it requires huge attention from the researchers as the traditional methods used for performing the test suite minimization is concentrated on the cost of regression testing but the requirements were not satisfied. To solve the problem of satisfying requirements, researchers proposed greedy algorithms, optimization algorithms, and so on. In this paper, a novel optimization algorithm is proposed termed as the Diversity Dragonfly Algorithm (DDF) algorithm that concentrates on the cost and quality of the test suite. The diversification included in the standard Dragonfly algorithm forms the DDF that uses three bitwise operators for diversification. The DDF algorithm determines the best suite based on the hunting mechanism of the dragonfly using a minimum objective function such that the selected test suite satisfies all the requirements. The experiment is carried out using five subject programs and the performance analysis of the proposed DDF is carried out and compared with the existing methods. It is found that the reduction capability of the DDF is better than existing methods and the cost of the proposed DDF is low ensuring a quality test suite reduction.