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

compound [1] was formed from the reaction of benzoin and benzaldehyde in the presence of ammonia, which was reacted with sodium hydride in DMF to obtain imidazole salt. This salt was reacted with adipoyl chloride to give compound [2]. Acid hydrazide derivative [3] was obtained from the reaction of compound [2] with hydrazine hydrate. After that Shiff bases [4-9] have been synthesized from the reaction of compound [3] with different aromatic aldehydes. These new formed compounds were diagnosed by 13C-NMR, 1H-NMR for some of them (in Ahl-Albate University in Jordan) and FT-IR spectroscopy (In Baghdad University). All of the prepared products have been studied their biological activities toward two kinds of bacteria. These products show

This study aims to know how and what is the media processing presented by the television talk shows for the religious extremism topics in terms of topics, hosted personalities, and ways to address this global phenomenon.

The study is based on descriptive research, and the researcher used the analytical-survey method, analyzing the episodes of (Awkar Al Dhalam) T.V Show which was presented on Al-Iraqiya News Channel, and (Islam Hur) T.V Show which was presented on Al-Hurra in 2019 with 25 episodes from each Show, The sample and research community was chosen with the intent to cover the research problem and its

The study reached several conclusions, including:

• The various dialogs in the episo

This article presents the simultaneous adsorption of bimetal Cu²⁺ and Zn²⁺ from an aqueous solution using activated carbon synthesized from a plum seed precursor by sulfuric acid and microwave activation: plum seeds chemically activated by 45% (w/w) sulfuric acid with 2:1 ratio for 4 h, then carbonized for 2 h at 700 °C and the product obtained activated in a microwave oven for 20 min at 700 W for final of activation. Plum seeds and activated carbon produced were characterized in terms of their physical and chemical composition using Brunauer–Emmett–Teller measurements, field emission scanning electr

The present study is to investigate the possibility of using wastes in the form of scrap iron (ZVI) and/ or aluminum ZVAI for the detention and immobilization of the chromium ions in simulated wastewater. Different batch equilibrium parameters such as contact time (0-250) min, sorbent dose (2-8 g ZVI/100 mL and 0.2-1 g ZVAI/100 mL), initial pH (3-6), initial pollutant concentration of 50 mg/L, and speed of agitation (0-250) rpm were investigated. Maximum contaminant removal efficiency corresponding to (96 %) at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed were obtained.

The best isotherm model for the batch single Cr(III) uptake by ZVI

Background: Esthetic treatment is the options of patient seeking orthodontic treatment. Therefore this study was conducted to measure the concentration of Aluminum, Nickel, Chromium and Iron ions released from combination of monocrysralline brackets with different arch wires immersed in artificial saliva at different duration, to evaluate the corrosion point on different parts of the orthodontic appliances before and after immersion in artificial saliva, and to evaluate the corrosion potential of each group of the orthodontic appliances. Material and methods: Eighty orthodontic sets prepared. Each set represents half fixed orthodontic appliance, from the central incisor to the first molar, for the maxillary arch, each set consisted of molar

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 - M ultiple mixing ratios of -transitions from levels of 56Fe populated in 56 56 Fe n n Fe ( , )  reactions are calculated by using const. S.T.M. This method has been used in other works [3,7] but with pure transition or with transitions that can be considered as pure transitions، in our work we used This method for mixed  - transitions in addition to pure  - transitions. The experimental angular distribution coefficients a2 was used from previous works [1] in order to calculet - values. It is clear from the results that the - values are in good agreement or consistent, within associated errors, with those reported previously [1]. The discrepancies that occur are due to inaccuracies existing in the expe