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Illumination - Invariant Facial Components Extraction Using Adaptive Contrast Enhancement Methods
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The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material a subset consists of 1150 images belong to 91 different subjects was taken from Cohn-Kanade AU coded dataset (CK); the subjects images hold different facial expressions. The test results show the effectiveness of the proposed automated localization scheme in different illuminations conditions; it gave accuracy of about 95.7%.

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Fabrication of Copper-Graphite MMCs Using Powder Metallurgy Technique
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Copper, and its, alloys and composites (being the matrix), are broadly used in the electronic as well as bearing materials due to the excellent thermal and electrical conductivities it has.

In this study, powder metallurgy technique was used for the production of copper graphite composite with three volume perc ent of graphite.  Processing parameters selected is (900) °C sintering temperature and (90) minutes holding time for samples that were heated in an inert atmosphere (argon gas). Wear test results showed a pronounced improvement in wear resistance as the percent of graphite increased which acts as solid lubricant (where wear rate was decreased by about 88% as compared with pure Cu). Microhardness and

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Thu Apr 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Disadvantages of using Nano-particles as fertilizers in Iraq
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Abstract<p>The agriculture around the world faced many difficulties and the important was to reduce inputs of chemical fertilizers and pesticides and increase the total yield specially with the continuous grow of populations numbers at the world expected to reach more than 9 billion by 2050. In other hand there are other problems which make the challenges bigger such as wars, biotic and abiotic stress, and diseases. The scientists tried to find solutions by using Nano-fertilization which consider a modern way to quickly grow up the yield and decrease use the chemicals. The use of nanotechnology may be destructive on human and the environment due to fast accumulation in the tissues of alive bodie</p> ... Show More
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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Wed Sep 15 2021
Journal Name
2021 International Conference On Computing And Communications Applications And Technologies (i3cat)
Parallel Hybrid String Matching Algorithm Using CUDA API Function
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Publication Date
Sun Feb 25 2024
Journal Name
Tikrit Journal Of Pure Science
Optical Mark Recognition using Modify Bi-directional Associative Memory
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Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M

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Publication Date
Wed Aug 17 2022
Journal Name
Applied Sciences
Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange
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The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Carwash Wastewater Treatment by Electrocoagulation Using Aluminum Foil Electrodes
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Large quantities of contaminated carwash wastewater are produced per day from carwash places. Extensively it contains large quantities of chemicals from detergents, oil, grease, heavy metals, suspended solids, types of hydrocarbons, and biological contents. A novel electrocoagulation treatment by foil electrodes was conducted to remove COD, turbidity, Total Dissolved Solids (TDS) from contaminated carwash wastewater and decrease its Electrical Conductivity (EC). A thin layer of aluminum foil is used as an electrode in this treatment process. The effects of different voltage and treatment times were studied. The best result was found at a voltage of 30 volts and treatment time 90 minute where the removal efficiency of COD

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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Chemical Engineering
Phosphorus Removal from Wastewater Using Oven-Dried Alum Sludge
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Publication Date
Tue Jun 21 2022
Journal Name
Journal Of Planner And Development
Enviromental impact assessment of cement industry using Leopold Matrix
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The assessment of the environmental impact of the cement industry using the Leopold Matrix is ​​to determine the negative and positive impacts on the environment resulting from this industry, and what are the long-term and short-term effects, direct and indirect, and the amount of these effects and potential risks, and that this evaluation process is done through a number of methods, including Matrix method, including (Leopold).

 

The importance of the research because the cement occupies is of great importance in the world, especially in our country, Iraq, in the sector of construction and modernity, and the toxic emissions and solid waste produced by the production of this material. <

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