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alkej-882
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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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 detection is one of the results of the proposed classifier. The work demanded the collection of about 5000 color codes which in turn were subjected to algorithms for training and testing. The open-source platform TensorFlow for ML and the open-source neural network library Keras were used to construct the algorithm for the study. The results showed an acceptable efficiency of the built classifier represented by an accuracy of 90% which can be considered applicable, especially after some improvements in the future to makes it more effective as a trusted colorimeter.

 

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
The effect of creating knowledge according to the model (Nonaka & Takeuchi, 1995) on organizational ambidexterity: A study on a sample of Iraqi private banks
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Purpose - This study relies on the descriptive and analytical approach through collecting and analyzing the necessary data, as this approach focuses on polling the opinions of the research sample and its directions, and aims to develop a model that studies the relationship between knowledge creation and organizational ambidexterity in Iraqi private banks and verifying its validity experimentally.

Design / Methodology / Introduction - A survey was conducted through a questionnaire form to collect data from a sample of (113) managers in private commercial banks. In addition, this study used the AMOS program and the ready-to-use statistical program package (SPSS V.25) to test the proposed hypotheses of the t

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Application of Seed Mucilage Extracted from Lallemantia royleana as a Suspending Agent
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The mucilage from the seeds of Lallemantia royleana family Labiatae was extracted and subjected to preformulation study for evaluation of its suitability for use as suspending agent. Furosemide suspensions were prepared using (1.5% w/v) of the extracted Lallemantia royleana mucilage, (1.5% w/v) chitosan and (0.35% w/v) xanthan gum. The mucilage was white in color and the average yield of dried mucilage obtained from L.royleana nutlets was 14 % w/w of the seeds used. It is sparingly soluble in water but swells in contact with it, giving a highly viscous solution. It is slightly acidic to neutral. It was found that the extracted natural mucilage of Lallemantia royleana exhibited a higher viscosity profil

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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EXTRACTION AND CHARACTERATION OF MUCILAGE EXTRACTED FROM MUSTARD SEEDS: EXTRACTION AND CHARACTERATION OF MUCILAGE EXTRACTED FROM MUSTARD SEEDS
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The mucilage was isolated from mustard seeds and identification by some different methods like, thermo gravimetric, FTlR., X-ray powdered, proton NMR, FTIR spectra of the three gums contain different functional group in the gums, major peaks  bands noticed were belong to OH (3410.15 – 3010.88) group from hydroxyl group, CH aliphatic (2925-2343.51), C-O (1072.42-1060.85) group and C=O 1743.65, Thermo chemical parameters of mucilage was evaluated  and compared with the standard gums, Results indicated the mucilage was decomposed in 392°C and mass loss 55%, The X ray process found the mucilage had single not sharp peak

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Synthesis of Functionalized Silica from Rice Husks Containing C-I End Group
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In this paper, we have extracted Silica from rice husk ash (RHA) by sodium hydroxide to produce sodium silicate. 3-(chloropropyl)triethoxysilane (CPTES) functionalized with sodium silicate via a sol-gel method in one pot synthesis to prepare RHACCl. Chloro group in compound RHACCl replacement in iodo group to prepere RHACI. The FT-IR clearly showed absorption band of C-I at 580 cm-1. Functionalized silica RHACI has high surface area (410 m2/g) and average pore diameter (3.8 nm) within mesoporous range. X-ray diffraction pattern showed that functionalized silica RHACI has amorphous phase .Thermogravemitric analysis (TGA) showed two decomposition stages and SEM morphology of RHACI showed that the particles have irregu

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Publication Date
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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Publication Date
Mon Jan 13 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Environmental Cost Management And The Role Of Sustainable Environmental Development: بالتطبيق في مصنع اسمنت باجل
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The environmental cost management focus on continuous improvement of processes and the various activities of the organization in order to improve the environmental performance by producing an environmentally friendly products lead to a competitive advantage for the organization and supports the activities of their sustainability.

  The study was carried out in Bagel cement factory, one of the pioneer projects in Yemen in manufacturing field, The study found the need to develop a separate section for environmental management in order to put plans and environmental policies and the introduction of a special division in the Department of costs cares about Management practices cost and measure environmental costs, also give solu

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Publication Date
Wed Sep 22 2021
Journal Name
Samarra Journal Of Pure And Applied Science
Toward Constructing a Balanced Intrusion Detection Dataset
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Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

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Publication Date
Sat Jan 12 2019
Journal Name
Journal Of The College Of Education For Women
Preparation of A Measurement to the Affirmative Behavior for the Students at the University of Baghdad
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Self-Assertion is the individual ability to express any emotion well, except the anxiety. The decrease of the individuals asserting behavior makes them face many difficulties that prevent their social adjustment. Moreover it reflexes many negative behavioral and physical cases. The individual, who fails to express his or her negative feelings in required situations, feels with dissatisfaction, loneliness, depression, anxiety, social anxiety, conflict, and psychological disorder.
Accordingly, the importance of this study is represented in studying the self-assertion and studying the university students who reflect the strength of society.
The following are the two aims of the study:
1. Construct an asserting behavior scale.
2.

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
The Effects of Extracted Peptide from Skin of Iraqi Frog (Rana ridibunda) on Human Leukemic Lymphocytes
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        The purified frog skin peptides were tested on leukemic patients lymphocytes, which revealed effects of cytotoxicity. Four frogs (Rana ridibunda) were stimulated by single intra-peritoneal injection of norepinephrine-HCl . Five different peptides;1(18) A, 2(19) L, 3(20) I,4(21) E and 5(22) Y were isolated and quantified. The peptide 3(20)I had 5.87% of hemolysis, while healthy human lymphocytes cytotoxic activity was for 2(19)L with inhibition( -10.4%).All peptides were subjected to polyacrylamide gel electrophoresis. The results revealed peptides 1(18)A, 2(19)L, 3(20)I which appeared as low as 10 KDa  marker. Theoretically, the whole polypeptide had a molecular weight 7488.61 Dalt

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