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Experimental Investigation and Fuzzy Based Prediction of Titanium Alloy Performance During Drilling Process
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Publication Date
Sun Dec 27 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Phytochemical Investigation and Anti-angiogenic Examination of Iraqi Vigna radiata L. Seeds and Sprouts
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Abstract

  The objective of this study was to investigate the phytochemical constituents of two different parts of Vigna radiata (seeds and sprouts), and identify their  anti angiogenic activity .the goal was achieved by Preliminary qualitative phytochemical screening for crude ethanolic extract of two parts of plant

 ; rat aorta anti-angiogenesis assay had been conducted for both extracts .   isolation , separation and purification of some phytochemical constituents that belong to important groups (flavonoids) from  n-butanol fraction extract of Vigna radiata plant had been done in pure form by using preparative thin layer chromatography ( PTLC ) and then

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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
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Publication Date
Mon Mar 09 2020
Journal Name
Agrosystems, Geosciences & Environment
In-season potato yield prediction with active optical sensors
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Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Vertical Stress Prediction for Zubair Oil Field/ Case Study
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Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Applied Engineering Science
Rutting prediction of hot mix asphalt mixtures reinforced by ceramic fibers
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One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Medicinal And Chemical Sciences
Investigation of Biofilm Formation and Antibiotic Resistant of Bacteria Isolated from Septic Neonates
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Neonatal sepsis refers to the bacterial bloodstream infections of the newborn during the neonatal period as usually the first twenty-eight days of life. The current study was done in the laboratories of AL-Batool Teaching Hospital for Gynecology and Pediatrics in Baqubah, Diyala Governorate, including 140 blood specimens collected from the neonates admitted to the hospital with suspected sepsis, the ages of the both groups was ranged from 1 day to 28 days. Out of the total cultured samples, 32.14% (45 of 140) were positive and 67.86% (95 of 140) were negative blood culture. 45 of 140 samples were negative to the blood culture chosen as control group. The results showed highest isolates were Coagulase Negative Staphylococcus (CoNS) 19 (42.2%

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Analysis of the Effects of Aggressive Shot Peening on Fatigue Life of 7075 – T6 Aluminum Alloy
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 For many years controlled shot peening was considered as a surface treatment. It is now clear that the performance of control shot peening in terms of fatigue depends on the balance between its beneficial (compressive residual stress and work hardening) and beneficial effects (surface hardening).

The overall aim of this paper is to study the effects of aggressive shot peening on fatigue life of 7075 – T6 aluminum alloy. The fatigue life reduction factor (LRF) due to the aggressive shot peening was established and empirical relations were proposed to describe the behavior of LRF, roughness and fatigue life. The benefits of shot peering in terms of fatigue life are dependent on the shot peening time (SPT).

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