Decide the Significance of Data Mining to Financial Application
Review Paper | Journal Paper
Vol.07 , Issue.02 , pp.146-149, Jan-2019
Abstract
These days with the advancement of innovation significance given to information increments progressively. Data mining empowers to shape gauges and models with respect to future by making utilization of past data. Any strategy which finds data can be utilized as a data mining technique. Endeavors increase vital upper hand by data mining strategies. Data mining is utilized in various fields. In fund field it is an uncommonly utilized in money related execution applications, speculating the endeavor insolvencies and disappointments, determining exchange control, determining monetary hazard the executives, determining client profile and profundity the executives. It tends to be exorbitant, dangerous and tedious for ventures to pick up learning. Along these lines today undertakings use data mining as a creative focused mean. The point of the examination is to decide the significance of data mining applications to capital markets.
Key-Words / Index Term
Data Mining, Financial Performance Applications, Data Transformation
References
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Citation
V. Vaishali, "Decide the Significance of Data Mining to Financial Application", International Journal of Computer Sciences and Engineering, Vol.07, Issue.02, pp.146-149, 2019.
Frequency Domain Enhancement Filters: A Survey
Survey Paper | Journal Paper
Vol.07 , Issue.02 , pp.150-153, Jan-2019
Abstract
Fingerprints are majorly used to extract the physiological characteristics of human for identification and authentication purpose. Since the fingerprint became essential factor in day today life, features of fingerprints can be tainted which includes noises. Noise is a distortion and unwanted element of an image. It affects the accuracy of the biometric system in identifying and authenticating a person. Noises are of different types such as Gaussian, Salt and Pepper, Speckle noise etc. They are generated either due to internal or external factors. Noises are removed by applying various types of filtering techniques. Usually images are filtered based on the noises. Filters are applied in either spatial or frequency domain of the image. Frequency domain transformations are functions in Fourier transformations of image. This survey aims to identify the best suitable frequency domain filtering technique which is applied to enhance fingerprint quality.
Key-Words / Index Term
Frequency – domain, FFT, fingerprints, quality, filters
References
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Citation
K. Kanagalakshmi, S. Shenbagavadivu, "Frequency Domain Enhancement Filters: A Survey", International Journal of Computer Sciences and Engineering, Vol.07, Issue.02, pp.150-153, 2019.
A Study on Impact of Workforce Diversity on Employee Performance with Reference to IT Companies
Review Paper | Journal Paper
Vol.07 , Issue.02 , pp.154-159, Jan-2019
Abstract
Workforce Diversity is one of the most prominent indicators of changing global trends and markets. In order to determine whether a varied workforce has an effect on employee performance, this research was conducted to examine the workforce diversity and its effect on employee performance in IT organisations. India`s IT sector is expanding quickly. Workforce diversity is a growing problem in the corporate world today since it presents organisations with a challenge as well as a chance that, if not effectively handled, can have an impact on employee`s performance and, ultimately, the organisation. This study focuses on Age diversity, Educational Background diversity, Religious diversity, Work Experience diversity& Attitude diversity, all of which are measured in relation to employee performance. The study`s research offers significant insight into the diversity management strategies being used by IT industry organizations. The survey unequivocally highlights the need for organizations to take action to manage diversity in order to maximize employee potential and gain a competitive edge.
Key-Words / Index Term
Age Diversity, Educational Background Diversity, Religious Diversity, Work Experience Diversity, Employee Performance.
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Citation
Shakti Singh Shekhawat, S.S. Sarangdevot, "A Study on Impact of Workforce Diversity on Employee Performance with Reference to IT Companies", International Journal of Computer Sciences and Engineering, Vol.07, Issue.02, pp.154-159, 2019.