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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
Mon Mar 30 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Adaptive Security Model for Data Protection Using Behavioral User Authentication
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Credential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence predi

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Sun Oct 01 2023
Journal Name
Applied Sciences
Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods
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Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Mon Feb 20 2012
Journal Name
North Africa Technical Conference And Exhibition
Comprehensive Model for Flash Calculations of Heavy Oils Using the Soave - Redlich - Kwong Equation of State
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Abstract<p>One of the main techniques to achieve phase behavior calculations of reservoir fluids is the equation of state. Soave - Redlich - Kwong equation of state can then be used to predict the phase behavior of the petroleum fluids by treating it as a multi-components system of pure and pseudo-components. The use of Soave – Redlich – Kwon equation of state is popular in the calculations of petroleum engineering therefore many researchers used it to perform phase behavior analysis for reservoir fluids (Wang and Orr (2000), Ertekin and Obut (2003), Hasan (2004) and Haghtalab (2011))</p><p>This paper presents a new flash model for reservoir fluids in gas – oil se</p> ... Show More
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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Cultivation of Microalgae Chlorella vulgaris in Airlift photobioreactor for Biomass Production using commercial NPK Nutrients
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Airlift reactors are widely used in the chemical and biochemical applications as effective contactors for mass and heat transfer. The main advantages of airlift contactor compared with simple bubble column are ease of construction, low shear rate, high capacity, good mixing and liquid circulation without mechanical agitators and circulating pumps.

In this work, growth characteristics of Chlorella vulgaris microalgae were studied in an internal loop airlift photobioreactor for biomass production. The bioreactor operated under batch and semi-continuous culture mode using commercially available 20:20:20+TE NPK fertilizer as nutrients. The experiments were conducted to evaluate the growth rate and biomass productivity of

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Studying the Possibility of using Paint to Reduce the Amount of Radon Gas Emitted from Cement
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In the present work, it had been measured the concentration of radon gas (CRn) for (10) samples of cement used in constructions before and after painting them using enamel paint, purchased from the local markets, to see the extent of its ability to reduce emissions of Rn-222 in the air. These samples were obtained from different sources available in the local markets in Baghdad and other provinces. The measurements were done by the American-made detector (RAD7). The results showed that the highest CRn in the air emitted from cement samples after coating was in the cement sample (Iranian origin) where the concentration was (58.27 Bq/m3) while the lowest CRn was found in building material samples

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Publication Date
Mon Jan 01 2024
Journal Name
Pakistan Journal Of Life And Social Sciences (pjlss)
Antibacterial and Antibiofilm Activity of Phenolic Compounds Extracted From Camellia Sinensis And Evaluate The Effect On The Gene Expression (Clfa) In Staphylococcus Aureus
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Publication Date
Sun Oct 01 2006
Journal Name
Modern Sport
The effect of using a treadmill with different incline angles in developing some functional variables among Diyala University basketball team players
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تعد لعبة كرة السلة من الألعاب الرياضية التي تحتاج متطلبات بدنية ووظيفية خاصة بها، وذلك من خلال الانتقال داخل الملعب بالكرة أو بدونها والسبل للتخلص من ملاحقة الخصم أثناء الدفاع وكيفية المناورة أثناء الهجوم مع إجادة التصويب بكافة أنواعه داخل الملعب، ومن هنا تكونت مشكلة البحث في كيفية تطوير تلك العوامل الوظيفية والتي لها الأثر في الارتقاء بمستوى أداء اللاعب أثناء اللعب، وعن طريق استخدام الباحثان لطريقة جهاز ا

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