scholarly journals Steganography Genetic Algorithm Hyperparameter Tuning through Response Surface Methodology

2020 ◽  
Vol 1 (1) ◽  
pp. 13-17
Author(s):  
Warley Gramacho da Silva ◽  
Rafael Lima de Carvalho ◽  
Glêndara Aparecida De Souza Martins
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Information Source ◽  
Image Steganography ◽  
Original Host

Steganography consists of hidding bits of an information source into a host source. In image processing, a common way of doing the hiding process is to break each byte from the message information and embbed into the message bytes in a way that the differences among the original host and the embedded one is minimized. A genetic algorithm can be used to find the proper combination of bits in order to minimize such differences, but some hyperparameters need to be optimized in order to get an optimized performance. This work investigates the application of Response Surface Methodology in order to find the best hyperparameters of a genetic algorithm applied to image steganography.

Optimization of Aqueous Two Phase Extraction of Proteins from Litopenaeus Vannamei Waste by Response Surface Methodology Coupled Multi-Objective Genetic Algorithm

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
P. Saravana Pandian ◽  
S. Sindhanai Selvan ◽  
A. Subathira ◽  
S. Saravanan
Keyword(s):  
Genetic Algorithm ◽  
Molecular Weight ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Litopenaeus Vannamei ◽  
Value Added ◽  
Phase System ◽  
Two Phase ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Abstract Waste generated from industrial processing of seafood is an enormous source of commercially valuable proteins. One among the underutilized seafood waste is shrimp waste, which primarily consists of head and carapace. Litopenaeus vannamei (L. vannamei) is the widely cultivated shrimp in Asia and contributes to 90 % of aggregate shrimp production in the world. This work was focused on extraction as well as purification of value-added proteins from L. vannamei waste in a single step aqueous two phase system (ATPS). Polyethylene glycol (PEG) and trisodium citrate system were chosen for the ATPS owing to their adequate partitioning and less toxic nature. Response surface methodology (RSM) was implemented for the optimization of independent process variables such as PEG molecular weight (2000 to 6000), pH (6 to 8) and temperature (25 to 45 °C). The results obtained from RSM were further validated using a Multi-objective genetic algorithm (MGA). At the optimized condition of PEG molecular weight 2000, pH 8 and temperature 35 °C, maximum partition coefficient and protein yield were found to be 2.79 and 92.37 %, respectively. Thus, L. vannamei waste was proved to be rich in proteins, which could be processed industrially through cost-effective non-polluting ATPS extraction, and RSM coupled MGA could be a potential tool for such process optimization.

scholarly journals Modelling and optimization of zinc recovery from Enyigba sphalerite in a binary solution of hydrochloric acid and hydrogen peroxide

2020 ◽  
Vol 120 (11) ◽  
Author(s):  
I.A. Nnanwube ◽  
O.D. Onukwuli
Keyword(s):  
Genetic Algorithm ◽  
Hydrogen Peroxide ◽  
Response Surface Methodology ◽  
Hydrochloric Acid ◽  
Response Surface ◽  
Binary Solution ◽  
Infrared Analysis ◽  
Zinc Recovery ◽  
X Ray ◽  
Stirring Rate

SYNOPSIS This work focused on the prediction of optimal conditions for zinc recovery from sphalerite in a binary solution of hydrochloric acid and hydrogen peroxide. The sphalerite sample was characterized with X-ray fluorescence spectrometry (XRF), X-ray diffractometry, and Fourier transform infrared analysis (FTIR). The central composite design of response surface methodology (RSM) developed in Design Expert software and the genetic algorithm (GA) tool in matlab, were deployed for the optimization exercise. The leaching temperature, acid concentration, stirring rate, leaching time, and hydrogen peroxide concentration were defined as input variables, while zinc yield was the response. An ideal zinc yield of 90.89% could be obtained with a leaching temperature of 84.17°C, HCl concentration of 3.14 M, stirring rate of 453.08 r/min, leaching time of 107.55 minutes, and hydrogen peroxide concentration of 3.93 M using RSM; while a yield of 87.73% was obtained using GA. Analysis of the post-leaching residue revealed the presence of sulphur, zircon, fluorite, gahnite, anatase, and sylvite. Keywords: sphalerite leaching, genetic algorithm, optimization, response surface methodology.

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