Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics an

Two simple methods for the determination of eugenol were developed. The first depends on the oxidative coupling of eugenol with p-amino-N,N-dimethylaniline (PADA) in the presence of K3[Fe(CN)6]. A linear regression calibration plot for eugenol was constructed at 600 nm, within a concentration range of 0.25-2.50 μg.mL–1 and a correlation coefficient (r) value of 0.9988. The limits of detection (LOD) and quantitation (LOQ) were 0.086 and 0.284 μg.mL–1, respectively. The second method is based on the dispersive liquid-liquid microextraction of the derivatized oxidative coupling product of eugenol with PADA. Under the optimized extraction procedure, the extracted colored product was determined spectrophotometrically at 618 nm. A l

In this research a local adsorbent was prepared from waste tires using two-step pyrolysis method. In the carbonization process, nitrogen gas flow rate was 0.2L/min at carbonization temperature of 500ºC for 1h. The char products were then preceded to the activation process at 850°C under carbon dioxide (CO2) activation flow rate of 0.6L/min for 3h. The activation method produced local adsorbent material with a surface area and total pore volume as high as 118.59m2 /g and 0.1467cm3/g, respectively. The produced . local adsorbent (activated carbon) was used for adsorption of lead from aqueous solution. The continuous fixed bed column experiments were conducted. The adsorption capacity performance of prepared activated carbons in this work

The development of a reversed phase high performance liquid chromatography fluorescence method for the determination of the mycotoxins fumonisin B1 and fumonisin B2 by using silica-based monolithic column is described. The samples were first extracted using acetonitrile:water (50:50, v/v) and purified by using a C18 solid phase extraction-based clean-up column. Then, pre-column derivatization for the analyte using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol was carried out. The developed method involved optimization of mobile phase composition using methanol and phosphate buffer, injection volume, temperature and flow rate. The liquid chromatographic separation was performed using a reversed phase Chromolith® RP-18e column

Simple, rapid and sensitive spectrophotometric method was proposed for the analysis of metoclopramide hydrochloride (MPH) in pure form as well as in pharmaceutical tablets. The method is based on the diazotization reaction of MPH with sodium nitrite in hydrochloric acid medium to form diazonium salt, which is coupled with 1-naphthol in sodium hydroxide medium to form azo dye, showing absorption maxima at 550 nm. Beer’s law is obeyed in the concentration range of 0.4 – 18 µg mL-1 of MPH with detection limit 0.5448 µg mL-1. The molar absorptivity and Sandell’s sensitivity are 3.4969 × 104 L mol-1 cm-1 and 0.0101 µg cm-2, respectively. The method was successfully applied to the determination of MPH in pharmaceutical tablets with

Phosphorus is usually the limiting nutrient for eutrophication in inland receiving waters; therefore, phosphorus concentrations must be controlled. In the present study, a series of jar test was conducted to evaluate the optimum pH, dosage and performance parameters for coagulants alum and calcium chloride. Phosphorus removal by alum was found to be highly pH dependent with an optimum pH of 5.7-6. At this pH an alum dosage of 80 mg/l removed 83 % of the total phosphorus. Better removal was achieved when the solution was buffered at pH = 6. Phosphorus removal was not affected by varying the slow mixing period; this is due to the fact that the reaction is relatively fast.
The dosage of calcium chloride and pH of solution play an importa