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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 comparative study of the algorithms in order to determine which algorithm has the highest prediction accuracy. The results showed that the value of the red color has a greater effect than the green and blue colors in predicting the sweetness of orange fruits, as there is a direct relationship between the value of the red color and the level of sweetness. In addition, the logistic regression model algorithm gave the highest degree of accuracy in predicting sweetness.

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Publication Date
Sat Sep 01 2018
Journal Name
2018 11th International Conference On Developments In Esystems Engineering (dese)
Natural Rivers Longitudinal Dispersion Coefficient Simulation Using Hybrid Soft Computing Model
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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Elimination of Congo Red Dyes From Aqueous Solution Using Eichhornia Crassipes
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   Water hyacinth (Eichhornia crassipes) is a free-floating plant, growing plentifully in the tropical water bodies. It is being speculated that the large biomass can be used in wastewater treatment, heavy steel and dye remediation, as a substrate for bioethanol and biogas production, electrical energy generation, industrial uses, human food and antioxidants, medicines, feed, agriculture, and sustainable improvement. In this work, the adsorption of Congo Red (CR) from aqueous solution onto EC biomass was investigated through a series of batch experiments. The effects of operating parameters such as pH (3-9), dosage (0.1-0.9 g. /100 ml), agitated velocity (100-300), size particle (88-353μm), temperature (10-50˚C), initial dye

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology &amp; Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Characterization Performance of Monocrystalline Silicon Photovoltaic Module Using Experimentally Measured Data
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Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for differ

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Tropical Medicine & Public Health
Assessment of Left Ventricular Function in Body builders using conventional echocardiography
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Background: Powerlifters and bodybuilders use anabolic androgenic steroids (AAS) especially – as many as 55 percent of elite powerlifters admitted using these agents. In contrast to numerous documented toxic and hormonal effects of AAS their impact on the structure and function of the left ventricular (LV) was not yet fully understood.

Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Eyewitnesses’ Visual Recollection in Suspect Identification by using Facial Appearance Model
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Facial recognition has been an active field of imaging science. With the recent progresses in computer vision development, it is extensively applied in various areas, especially in law enforcement and security. Human face is a viable biometric that could be effectively used in both identification and verification. Thus far, regardless of a facial model and relevant metrics employed, its main shortcoming is that it requires a facial image, against which comparison is made. Therefore, closed circuit televisions and a facial database are always needed in an operational system. For the last few decades, unfortunately, we have experienced an emergence of asymmetric warfare, where acts of terrorism are often committed in secluded area with no

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Publication Date
Fri Sep 08 2006
Journal Name
Journal Of Engineering
INFLUENCE OF DEFECT IN THE CONCRETE PILES USING NON-DESTRUCTIVE TESTING
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This paper presents the results of experimental investigation carried out on concrete model piles to study the behaviour of defective piles. This was achieved by employing non-destructive tests using ultrasonic waves. It was found that the reduction in pile stiffness factor is found to be about (26%) when the defect ratio increased from (5%) to (15%). The modulus of elasticity reduction factor as well as the dynamic modulus of elasticity reduction factor increase with the defect ratio

Publication Date
Sun Mar 03 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Using Information Technology for Comprehensive Analysis and Prediction in Forensic Evidence
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With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Coagulation - Flotation Process for Removing Oil from wastewater using Sawdust+ Bentonite
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In many industries especially oil companies in Iraq consumed large quantities of water which will produce oil-contaminated water which can cause major pollution in agricultural lands and rivers. The aim of the present work is to enhance the efficiency of dispersed air flotation technique by using highly effective and cost-efficient coagulant to treating gas oil emulsion. The experimental work was carried out using bubble column made of Perspex glass (5cm I.D, 120cm height). A liquid was at depth of 60cm. Different dosage of sawdust +bentonite at ratio 2:1 (0.5+ 0.25; 1+ 0.5 and 2+1) gm and alum at concentration (10,20and30mg/l) at different pH ( 4 and 7) were used to determine optimum dosages of coagulant. Jar test exper

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