College of Engineering, Pune

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

Decision support system for dispute resolution in construction contracts

Abstract: The construction industry has been characterized by an adversarial operating environment that generates disputes and claims due to the infinite complexities of delivering a building or infrastructure project, the multiplicity of organizations and individuals involved, and the magnitude of the funds at risk. Disputes typically start with the difference of opinion regarding claims, which can escalate to conflicts that require some form of legal action. This paper highlights the need of scientific framework for understanding and administratively resolving disputes over contract clauses. Decision Support System is one such tool. An attempt has been made to develop one such system for disputes arising out of variation and deviations clause in Indian construction contracts.

Very Fast Decision Tree (VFDT) algorithm on Hadoop

Abstract: In the era of Big Data where voluminous data is handled on a very large scale, traditional decision trees might be very time consuming and sometimes might even fail to work owing to its dataset size. Handling Big Data can also be a costly affair because of its high demand for memory and other hardware requirements. To the end of this paper, we have chosen a decision tree algorithm named Very Fast Decision Tree (VFDT) after comparing it with other decision tree algorithms like ID3 and C4.5. We have also proposed an algorithm for implementing VFDT on a Distributed Environment called Hadoop. This implementation can form a base for a large number of applications for handling Big Data. We have replaced the serial execution of VFDT algorithm by a series of Map and Reduce functions. We have also conducted an extensive analysis on various datasets which have proved our proposed algorithm to be more efficient in terms of time compared to the other existing decision tree models.

An experimental-based python programming for structural health monitoring of non-engineered RC frame

Abstract: Most of the damages were experienced on the buildings which were conventionally built without any consideration of IS codal provisions conveniently called non-engineered structures. Non-engineered structures are frequently affected by vibrations due to various natural and artificial sources. Thus, it needs special attention. It is, therefore, necessary to check the performance of non-engineered structures through various health monitoring techniques. A piezoelectric-ceramic (PZT) sensor-based technique called electromechanical impedance (EMI), in which the sensors efficiently operate at a high-frequency range and can typically detect damage at the initial level which is implemented for the purpose. In this research work, experimental tests are performed on the non-engineered reinforced concrete frame using EMI technique by utilizing a PZT sensor which is bonded to the structure using the high-strength epoxy adhesive. The experiment is carried out to identify and locate the damages using frequency variations, and the severity was checked using extracted equivalent parameter; damage index. Second, a Python programming is developed by the authors to identify and quantify the damage index and root mean square deviation index in the frame. The frequency responses obtained from the experimental tests are used in the programming. The performance of the program is compared with the experimentally calculated parameters to check the efficiency of the programming. According to the results of the comparison, it is observed that python programming can be effectively used for damage detection.

Study of sensorless control algorithms for a permanent magnet synchronous motor vector control drive

Abstract: In the recent past, the use of permanent magnet synchronous motors (PMSM) has increased considerably owing to their inherent advantages. The high performance speed and/or position control of a PMS motor requires an accurate knowledge of rotor shaft position and angular speed in order to synchronize the phase excitation pulses to the rotor position. The rotor position and speed information is specifically required for implementation of vector control scheme in a PMSM. In order to achieve the speed control various sensored methods are employed. Due to number of advantages recent trend is to implement the sensorless control drive for a PMSM. This paper presents and compares two main sensorless control algorithms viz, Sliding Mode observer(SMO) and Extended Kalman Filter (EKF) for sensorless estimation of rotor position and speed in a PMSM. The simulation results for both these methods on an identical PMSM are presented. The analysis of these results give some insights into the accuracy of estimations and subsequent working of the PMSM with them.

Automated glaucoma detection from fundus images using wavelet-based denoising and machine learning:

Abstract: Glaucoma is a domineering and irretrievable neurodegenerative eye disease produced by the optical nerve head owed to extended intra-ocular stress inside the eye. Recognition of glaucoma is an essen...