'Enhancing the Employability of Students’ Passing from Technical Institutions

India has the world’s second largest education system and provides one of the largest pool of skilled manpower. In the recent years, the problem of under-employment or rather unemployment among technical and professional engineering graduates & diploma pass outs is a cause of serious concern. Substandard Institutes are producing mere graduates & diploma holders instead of technically sound and competent professionals as intended. These pass outs are either under- employed or if employed, they do not fulfill or meet out the expectations of Industries or organizations. There is immediate need to take few corrective measures by the academic coordinators, policy makers and management of the institutes associated in providing technical manpower to the industries system; otherwise India will face an explosion of unemployed technical graduates/diploma holders. The world of academia will have to understand the nerve of Industries/organizations and require producing true professionals instead of mere graduates/diploma holders. The paper principally focuses on the multiple ways and means with suggested strategies for the technical teachers as well as institutions to plan, practice and administer such innovations in to their daily instructions, so as to fulfill the gap to a large exten

An Insight on Analytical Profile on Bisoprolol Fumarate – A Selective Beta-1 Adrenoreceptor Blocker

BF is Beta-adreno receptor antagonist and used as an AntiHypertensive Drug. BF gives the blocking action on β1-adrenergic receptors in the heart and vascular smooth muscle. The present review compiles the various approaches implemented for quantification of BF in bulk drug, pharmaceutical matrix and biological fluid. This review represents more than 50 analytical methods which include capillary electrophoresis, HPLC, HPTLC, UV-Spectroscopy, UPLC, impurity profiling and electrochemical methods implemented for estimation of BF as a single component as well as in multicomponent

Hardware Implementation of Speech Recognition Using MFCC and Euclidean Distance

ABSTRACT:This paper suggests Digital Signal processor (DSP) based speech recognition system with improved performance in terms of recognition accuracies and computational cost. The comprehensive surrey of various approaches of feature extraction like Mel filter banks with Mel Frequency Cepstrum Coefficients (MFCC). This paper describes an approach of isolated speech recognition by Digital Signal Processor TMS320C6713 using Mel scale Frequency Cepstral Coefficients and Euclidean distance. Several features are extracted from speech signal of spoken words. An experiments database of total five speakers, speaking 5-10 words each is collected under acoustically controlled room is taken. MFCC are extracted from speech signal of spoken words. To compare inter speaking differences Euclidean distance is used KEYWORDS:Speech Recognition, Feature Extraction MFCC, Pattern Recognition, Euclidean distance. I.INTRODUCTION Speech Recognition is the process of automatically recognizing the spoken words of person based on information in speech signal. Each spoken word is created using the phonetic combination of a set of vowel, semivowel and consonant speech sound units. The popular spectral based parameter used in recognition approach is the Mel Freqency Cepstral Coefficients called MFCC, MFCC"s are coefficients, which represents audio, based on perception of human auditory systems. The basic difference between the operation of FFT/DCT and the MFCC is that in the MFCC, the frequency bands are positioned logarithmically (on the mel scale) which approximates the human auditory system"s response more closely than the linearly spaced frequency bands of FFT or DCT. II.LITERATURE SURVEY The system consists of microphone through which input in the form of speech signal is applied. The data acquisition system of speech processor acquires the output from the microphone and then itdetects the exact word spoken If such a system is installed in a motor car, then by using several start, stop,forward,backwardetc.; we can drive a carwithout even out hands. It is widely applied to some special fields such as resource poor embedded system for its simple and effective algorithm.DTW-based application of portable value added tax calculator with speaker dependent connected word and isolated word speech recognition abilities built in. [2]Automatic speech recognition is an interesting task but it requires a lot of effort. With technical development, speech recognition system achieved excellent results, still it possess some major limitations. Especially, recognition system with hidden markov models (HMM) as major elements are suitable for many applications, but do not suffer from major restrictions that make speech recognition system unsuitable for real time applications An isolated word, speaker dependent speech recognition system capable of recognizing spoken words at sufficiently high accuracy. The system has been tested and verified on MATLAB as well as TMS320C6713 DSK wit

Hardware Implementation of Speech Recognition Using MFCC and Euclidean Distance

ABSTRACT:This paper suggests Digital Signal processor (DSP) based speech recognition system with improved performance in terms of recognition accuracies and computational cost. The comprehensive surrey of various approaches of feature extraction like Mel filter banks with Mel Frequency Cepstrum Coefficients (MFCC). This paper describes an approach of isolated speech recognition by Digital Signal Processor TMS320C6713 using Mel scale Frequency Cepstral Coefficients and Euclidean distance. Several features are extracted from speech signal of spoken words. An experiments database of total five speakers, speaking 5-10 words each is collected under acoustically controlled room is taken. MFCC are extracted from speech signal of spoken words. To compare inter speaking differences Euclidean distance is used KEYWORDS:Speech Recognition, Feature Extraction MFCC, Pattern Recognition, Euclidean distance. I.INTRODUCTION Speech Recognition is the process of automatically recognizing the spoken words of person based on information in speech signal. Each spoken word is created using the phonetic combination of a set of vowel, semivowel and consonant speech sound units. The popular spectral based parameter used in recognition approach is the Mel Freqency Cepstral Coefficients called MFCC, MFCC's are coefficients, which represents audio, based on perception of human auditory systems. The basic difference between the operation of FFT/DCT and the MFCC is that in the MFCC, the frequency bands are positioned logarithmically (on the mel scale) which approximates the human auditory system's response more closely than the linearly spaced frequency bands of FFT or DCT. II.LITERATURE SURVEY The system consists of microphone through which input in the form of speech signal is applied. The data acquisition system of speech processor acquires the output from the microphone and then itdetects the exact word spoken If such a system is installed in a motor car, then by using several start, stop,forward,backwardetc.; we can drive a carwithout even out hands. It is widely applied to some special fields such as resource poor embedded system for its simple and effective algorithm.DTW-based application of portable value added tax calculator with speaker dependent connected word and isolated word speech recognition abilities built in. [2]Automatic speech recognition is an interesting task but it requires a lot of effort. With technical development, speech recognition system achieved excellent results, still it possess some major limitations. Especially, recognition system with hidden markov models (HMM) as major elements are suitable for many applications, but do not suffer from major restrictions that make speech recognition system unsuitable for real time applications An isolated word, speaker dependent speech recognition system capable of recognizing spoken words at sufficiently high accuracy. The system has been tested and verified on MATLAB as well as TMS320C6713 DSK wit

Experimental investigations on fatigue life enhancement of composite (e-glass/epoxy) single lap joint with graphene oxide modified adhesive

With the increased use of composites in various sectors as a lightweight material exhibits high strength to weight ratio with tailor made properties. It becomes necessary to focus on various joining methods and different types of composite joints and their strength. The present study aims to improve the mechanical strength of single lap joint of composite material comprises of E-glass fibers and nano modified adhesive. Epoxy adhesive has been modified by dispersing Graphene Oxide (GO) to investigate the possibility of enhancement in the fatigue strength and fracture resistance of the single lap joint. Modified Hummer’s method has been used for synthesis of Graphene Oxide. Experimental investigations have been carried out for comparison of tensile and fatigue strength which shows significant improvement in the number of failure cycles for 0.25 wt.% and 0.75 wt.% GO concentrations respectively as compared to neat adhesive. Tension test results showed a significant increase in the fracture toughness of the joint due to addition of GO nanoparticles. There has been 33% and 19% increase in fracture toughness in 0.25 wt.% and 0.75 wt.% GO samples respectively as compared to neat adhesive. Improvement in fracture toughness, among all other nano-reinforcements has been obtained using GO, mainly because of its better capability of deviating the crack growth path to the longer path causing the final failure to retard and consequently improving mechanical properties of the adhesive for the tensile and fatigue strength parameters