Background
Cheiloscopy is a reliable method of personal identification which may augment the established methods like dactylography, DNA (deoxyribonucleic acid) profiling, and dental records.
Aim
This study aimed to determine the correlation of lip prints with ethnicity and gender of individuals in an attempt to bridge the gap between conventional manual methods and digital methods of cheiloscopy.
Methods
Lip prints of 300 gender-matched subjects of Indian and Malaysian-Chinese descents were collected and analyzed using the Suzuki K and Tsuchihashi Y classification system. The lip sizes were measured and lip print patterns were analyzed. The analysis was carried out using manual and computer-aided methods. A customized software for lip print analysis and validate it with the manual lip print analysis was developed.
Results
Independent sample t test showed a statistically significant difference between the width and length of the lips between males and females of the total population (p < 0.001). Pearson’s chi-square test showed no statistically significant difference between the Indian males and females in the width of the lower lip (p = 0.074). In the Malaysian-Chinese population, there was a statistically significant difference between males and females in the length of the upper lip (p = 0.032) and lower lip (p = 0.035). The type V grooves were predominant in the total study population (51.3%) followed by type III pattern (38.7%). The new customized software could not provide reliable results.
Conclusions
Lip sizes differed significantly among the Indian and Malaysian-Chinese subjects. There was no significant gender dimorphism in the distribution of lip print patterns. The results from manual and computer-aided methods were comparable.
The macroeconomic indicators play a major role in all the stock markets, and they vary from nation to nation. This paper identifies the influence of macroeconomic indicators on the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) of India. Total of forty-four macroeconomic indicators for eight years from the year 2011 to 2018 are considered in this study. The macroeconomic factors are aggregated and considered in average monthly form. The proposed method finds the correlation matrix of all considered macroeconomic indicators. The need for dimensionality reduction and the existence of multicollinearity are proven using validation techniques such as the Kaiser-Meyer-Olkin and Bartlett tests. The Principal Component Analysis (PCA) method is used to reduce the dimensionality to seven factors and then PCA with the varimax rotation method is applied to find factors with maximum variation. In addition, the influence of these seven factors on the NSE Nifty and BSE SENSEX indices are analyzed using regression. Finally, an Artificial Neural Network is used to predict stock market movement with the help of macroeconomic indicators. Accuracy of 92% and 87% are obtained on NSE NIFTY and BSE SENSEX respectively.INDEX TERMS Decision support systems, knowledge discovery, macroeconomic indicators, principal component analysis, artificial neural network, data mining.
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