YMCA University of Science and Technology

About: YMCA University of Science and Technology is a education organization based out in Faridabad, India. It is known for research contribution in the topics: Web crawler & Web page. The organization has 299 authors who have published 568 publications receiving 4547 citations.

Battery operated closed loop speed control of DC Separately Excited Motor by Boost-Buck Converter

Abstract: The Boost-Buck converter, also known as Cuk converter is an alternative power conversion topology which can be used for buck and boost the battery input voltage. Hence a wide range of speed control is possible for a dc separately excited motor using such converter. In this paper, the dynamic modeling of Boost-Buck converter with motor load has been formulated using state-space averaged analysis method. Small-signal model has been derived from the state-space averaged dynamic method for linearization. The input side phenomenon, associated with passive parameters is studied using small-signal analysis to show the right-half-plane (RHP) zero in the control-to-output transfer function. Based on small-signal linearization model, the control law for speed control is derived. Speed is controlled by direct measurement of the speed and input current. The compensators for the speed loop and the current loop are designed based on the frequency responses and root locus technique. The passive parameters such as capacitor and inductors are estimated to limit the capacitor ripple voltage and inductor ripple current. Hysteresis band modulator is used for finding out the switching function of switch. Performance of control method of the compensated Boost-Buck converter is verified by simulation.

A hierarchical test case prioritization technique for object oriented software

Abstract: Software reuse is the use of existing artifacts to create new software. Inheritance is the foremost technique of reuse. But the inherent complexity due to inheritance hierarchy found in object - oriented paradigm also affect testing. Every time any change occurs in the software, new test cases are added in addition to the existing test suite. So there is need to conduct effective regression testing having less number of test cases to reduce cost and time. In this paper a hierarchical test case prioritization technique is proposed wherein various factors have been considered that affect error propagation in the inheritance. In this paper prioritization of test cases take place at two levels. In the first level the classes are prioritized and in the second level the test cases of prioritized classes are ordered. To show the effectiveness of proposed technique it was applied and analyze on a C++ program.

Sentiment Analysis and Mining of Opinions

Abstract: Now days the way of expressing opinions on certain products that people purchase and the services that they receive in the various industries has been transformed considerably because of World Wide Web. Social Networking sites fascinate people to post feedbacks and reviews online on blogs, Internet forums, review portals and much more. These opinions play a very important role for customers and product manufacturers as they tend to give better knowledge of buying and selling by setting positive and negative comments on products and other information which can improve their decision making policies. Mining of such opinions have focused the researchers to pay a keen intention in developing such a system which can not only collect useful and relevant reviews online in a ranked manner and also produce an effective summary of such reviews collected on different products according to their respective domains. However, there is little evidence that researchers have approached this issue in opinion mining with the intent of developing such a system. Our work will focus on what opinion mining is the existing works on opinion mining, the challenges in the existing techniques and the workflow of mining opinions. Consequently, the aim of this chapter is to discuss the overall novel architecture of developing an opinion system that will address the remaining challenges and provide an overview of how to mine opinions. Existing research in sentiment analysis tend to focus on finding out how to classify the opinions and produce a collaborative summary in their respective domains, despite an increase in the field of opinion mining and its research, many challenges remain in designing a more comprehensive way of building a system to mine opinions. This chapter addresses the problem of how to classify sentiments and develop the opinion system by combining theories of supervised learning.

Estimation in agile environment using resistance factors

Abstract: The estimation of cost and effort is a critical task in Agile environment because of its dynamic nature. It has been observed that the current Agile methods mostly depends on historical data of project for estimation of cost, size, effort and duration and these methods are not efficient in absence of historical data. So there is need of an algorithmic method, which can calculate cost and effort of the project. In our previous work [2] some project-related factors and people-related factors were considered on the basis of which size as well as duration of the project was calculated. However, several other resistance factors may also affects estimation in the Agile dynamic environment. In this work an Algorithmic estimation method is being proposed that calculates more accurate release date, cost, effort and duration for the project by considering various factors. The effectiveness and feasibility of the proposed algorithm has been shown by considering two cases in which different levels of factors are taken and compared.

Characterization and Microhardness Evaluation of A356/Mg Joint Produced by Vacuum-Assisted Sand Mold Compound Casting Process

Abstract: Joining of A356 alloy and magnesium was carried out by vacuum-assisted sand mold compound casting process. Experiments were performed as per central composite design method. The second-order regression model validated the accuracy and reliability of experimental results. The interfacial microstructure was assessed by using scanning electron microscope and energy-dispersive X-ray spectroscopy. Phase constitutions were identified by X-ray diffractometer. It was observed that a uniform joint interface of A356/Mg formed with three distinct layers composed of Mg2Al3, Mg17Al12 and Mg17Al12 + δ eutectic structure. Mg2Al3 revealed highest microhardness followed by Mg17Al12 and Mg17Al12 + δ eutectic structure. Brittle and partial ductile fracture morphology was observed on A356 and Mg side, respectively, whereas the middle layer indicated mixed brittle and partial ductile fracture morphology. The process parameters (pouring temperature, vacuum pressure, insert temperature and surface roughness of insert) of compound casting were optimized with respect to the microhardness of joint interface. Optimization was carried out by using response surface methodology (RSM), desirability analysis (DA) and genetic algorithm (GA). A variation of 0.30, 0.84 and 1.35% in microhardness was obtained by RSM, DA and GA, respectively.