P A College of Engineering

About: P A College of Engineering is a based out in . It is known for research contribution in the topics: Dihedral angle & Ring (chemistry). The organization has 298 authors who have published 594 publications receiving 4888 citations.

Related Party Transactions and Audit Risk

Abstract: Related Party Transactions (RPTs) are perceived as genuine transactions, which fulfill the economic needs of a company. However, the controlling shareholders may use RPTs as a tool for transferring the firm’s resources for their private benefit. The dual effect of RPTs, i.e., transaction efficiency and conflict of interest between the controlling shareholders and minority shareholders, increase audit risk and as a result, increases the audit fee. The Companies Act, 2013, and Clause 49 of the SEBI listing agreement mandate arm’s length principle of pricing of RPTs. However, there are situations in which the regulations are silent about the method of pricing, and this increases the risk of auditors for auditing RPTs. This study intends to examine the relationship between RPTs and audit risk in India, based on a sample of 1,182 firms covering a period from 31 March 2011 to 31 March 2018. Panel data methodology has been applied for empirical analysis and the results show that higher audit fee is an indication of resource transferring RPTs. The results prove that instead of reducing the complexity associated with RPTs, the new RPTs regulations increase audit fee as a result of the increases in audit risk.

An evaluation of Hadoop cluster efficiency in document clustering using parallel K-means

Abstract: One of the significant data mining techniques is clustering. Due to digitalization and globalization of each work space, large datasets are being generated rapidly. Such large dataset clustering is a challenge for traditional sequential clustering algorithms as it requires large execution time to cluster such datasets. Distributed parallel architectures and algorithms are thus helpful to achieve performance and scalability requirement of clustering large datasets. In this study, we design and experiment a parallel k-means algorithm using MapReduce programming model and compared the result with sequential k-means for clustering varying size of document dataset. The result demonstrates that proposed k-means obtains higher performance and outperformed sequential k-means while clustering documents.

1-(4-Chlorophenyl)-3-(4-methoxyphenyl)- prop-2-en-1-one

Abstract: The geometrical parameters for the title compound, C16H13ClO2, are normal. Packing in a non-centrosymmetric space group, which is consistent with the non-zero second harmonic generation response, may be influenced by a C—H⋯O inter­action.