Informatics Publishing Limited

K. M. Safiya ¹, S. Bhuvana ², P. Tamije Selvy ², R. Radhakrishnan ³

Affiliations
1 Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, IN
2 Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, IN
3 Sri Ramakrishna Engineering College, Coimbatore, IN

Abstract

Face verification is an important problem. The problem of designing and evaluating discriminative approaches without explicit age modelling is used. To find the gradient orientation discard magnitude information. Using hierarchical information this representation can be further improved which results in the use of gradient orientation pyramid. When combined with a structural risk minimization support vector machine with genetic algorithm, gradient orientation pyramid demonstrate excellent performance. Gradient Orientation of each color channel of human faces is robust under age progression. The feature vector which is computed as the cosines of the difference between gradient orientations at all pixels, is given as the input to the structural risk minimization support vector machine classifier. The classifier is used to divide the feature space into two classes, one for the intrapersonal pairs and the other for extrapersonal pairs. Genetic algorithm plays an important role in improving the performance of the system. The system outperformed other classifiers such as support vector machine and boosting support vector machine.

Keywords

Face Verification, Feature Space, Genetic Algorithm, Gradient Orientation Pyramid (GOP), Structural Risk Minimization, Support Vector Machine (SVM).

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C. S. Vidhya ¹, M. Loganathan ², S. Bhuvana ³, N. Baskaran ⁴, R. Meenatchi ¹

Affiliations
1 Department of Primary Processing Storage and Handling, NIFTEM - Thanjavur, (Formerly IIFPT), Thanjavur – 613005, Tamil Nadu, IN
2 Department of Academics and Human Resource Development, NIFTEM - Thanjavur, (Formerly IIFPT), Thanjavur – 613005, Tamil Nadu, IN
3 Central Instrumentation Lab, NIFTEM – Thanjavur, (formerly IIFPT), Thanjavur – 613005, Tamil Nadu, IN
4 Department of Food Processing Business Incubation Centre, NIFTEM - Thanjavur, (Formerly IIFPT), Thanjavur – 613005, Tamil Nadu, IN

Abstract

Cucurbita maxima belongs to the Cucurbitaceae family and has many traditional medicinal properties claimed that are used in food. The various parts of the Cucurbita maxima are reported to have versatile activities such as antimicrobial, antioxidant, anti-insecticidal, anti-inflammatory and anticancer properties. The current study was designed to evaluate the phytoconstituent profiles of C. maxima pulp, peel and seed extracts (aqueous and methanol) extracted at different temperatures (40 °C, 50 °C, 60 °C) and time (1 and 2 hr). For these extracts, qualitative and quantitative determination were performed, and the aqueous seed extract of C. maxima at 50 °C for 2 hours had higher phytoconstituents, which was further taken for the GCMS analysis. Furthermore, the top hit compounds from the GCMS such as Guanosine (CAS), 8,11,14-Eicosatrienoic acid, Farnesol and 13-Tetradecenal were docked against p53 Y220S mutant (6SI2), and Fibroblast growth factor receptor 1 protein (FGFR1) (4V05). The results revealed that Guanosine with p53 and 8,11,14-Eicosatrienoic acid with FGFR1 have good binding affinities of -7.2 and -6.3 kcal/mol respectively. Conclusively, the top compounds from the aqueous seed extract of C. maxima extracted at 50 °C for 2 hours have significant breast cancer activity and it has to be further taken to in vitro and in vivo studies in the future.

Keywords

Anticancer, Cucurbita maxima, FGFR1, Molecular Docking, p53.

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