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.

Robust Feature Extraction and Recognition Model for Automatic Speech Recognition System on News Report Dataset

Abstract: Information processing has become ubiquitous. The process of deriving speech from transcription is known as automatic speech recognition systems. In recent days, most of the real-time applications such as home computer systems, mobile telephones, and various public and private telephony services have been deployed with automatic speech recognition (ASR) systems. Inspired by commercial speech recognition technologies, the study on automatic speech recognition (ASR) systems has developed an immense interest among the researchers. This paper is an enhancement of convolution neural networks (CNNs) via a robust feature extraction model and intelligent recognition systems. First, the news report dataset is collected from a public repository. The collected dataset is subjective to different noises that are preprocessed by min–max normalization. The normalization technique linearly transforms the data into an understandable form. Then, the best sequence of words, corresponding to the audio based on the acoustic and language model, undergoes feature extraction using Mel-frequency Cepstral Coefficients (MFCCs). The transformed features are then fed into convolutional neural networks. Hidden layers perform limited iterations to get robust recognition systems. Experimental results have proved better accuracy of 96.17% than existing ANN.

A Benchmarking Model for Indian Service Industries

Abstract: Benchmarking is the most important tool for improvement which is proficient over comparison through other organizations known as the best within precise extent. This study marines the service industries to focus its modest edge such as customer service, function ability, policy, adequacy and many more though conveying other processes through opposition and highlights different types of Benchmarking process used in industries, that gives effective used of factors for their implementation. Thus, an attempt is made by authors to give a model for the evaluation of Benchmarking by using MADM (ANP) approach. A benchmarking model is proposed which can be implemented in service industries of developing countries like India as the industries are showing huge interest for improving their competitiveness in global scenario.

Content-Based Social Network Aggregation

Abstract: Collecting and collating the data from different Social Network sites (SNS) at one place is a concern of today’s scenario. A social network aggregator performs this task by drawing information together from multiple SNS’s like Facebook, Twitter, and LinkedIn. It also unifies multiple social networking profiles into a single profile. The content presented by these aggregators appears in real time and there is easy switching between the multiple networks. There are many existing Social network aggregators based on the content and features. However, this paper focuses on the content-based architecture of social network aggregator that provides integrated search across multiple social networks.

A Technique for Regression Testing of Object Oriented Software

Abstract: The main challenge in testing an OOS is that there are large number of test cases which are not feasible to execute all of them within constrained time and budget. This paper proposes some factors which can be used to prioritize the test cases in order to have an effective testing. The considered factors are based on the testing history and structured analysis of the software. These factors may be nature of bug, capability of a test case, execution time, business impact, coverage of code in terms of classes(old and new classes), etc. Every factor has been assigned a positive weight which shows the criticality of the factor and ability to introduce the errors in the software. The prioritized set of test cases thus obtained is helpful to discover maximum bugs as early as possible.

Field and temperature assisted DC/AC conduction measurements of PS/ZnO nanocomposite films

Abstract: Electrical, optical and morphological properties of polymer nanocomposite materials are quite interesting to investigate due to their innovative characteristics and applications. Temperature dependent dc conductivity using different charge transport mechanisms like ionic hopping, Schottky and Poole-Frankel emissions has been investigated for pristine PS and PS/ZnO (at different wt% of ZnO) nanocomposite films in this research report. Non-ohmic conduction behaviour of these films developed an interest to carry out bulk and electrode limited conduction mechanisms. Ionic jump distance ‘a’ and conduction coefficient ‘βexp’ values for these films were calculated at various temperatures from the slopes of log I vs E and log I vs E1/2 plots respectively. The increase in dc conductivity of an order of 108 was observed by increasing the doping concentration up to 20 wt% of ZnO. The change in their ac conductivity was observed from 10−9 S/m to 10−6 S/m by varying the frequency from 1 to 300 kHz.