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Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Fri Jan 01 2010
Journal Name
Al-furat Journal For Agricultural Science
Effect of urea and superphosphate fertilizers on some growth characters of fenugreek plant (Trigonella foenum-graecum L.)
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Effect of Gamma Radiation on Callus Induction and Plant Regeneration of four Wheats Triticum aestivum L. Genotypes
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The effect of gamma radiation at the doses (0 , 5 , 10 or 15 ) Gray on the callus of four Triticum aestivum immature embryos genotypes (AL-Hashmiya , AL-Noor AL-Zahraa and AL-Mellad ) were studied . The fresh and dry weight for callus and shoot tips beside numbers and lengths of the shoots were used as indicators after 8 weeks . Results revealed that (AL-Noor and AL-Zahraa ) was superior by giving highest fresh and dry weight reached 274.2 and 269.2 mg and 26 and 24.3 mg respectively as compared with AL-Hashmiya and AL-Mellad. Moreover, the control treatment and the dose 10 Gray gave highest fresh weight reached 277.4 and 259.1 mg while the dry weight was highest in the control treatment and the dose 5 Gray. addition 10 Gra

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Sun Dec 15 2019
Journal Name
Al-academy
Virtual Reality Technology and its Uses in Industrial Product Design: فلاح حسن هادي -صلاح نوري محمود
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The research (Virtual Reality Technology and its Uses in Industrial Product Design) is interested in the virtual reality technology used in the industrial product design and consequently knowing the functions achieved in the industrial product according to the data of that technology which participates in activating the mental and imaginary image of the user which show the parameters of the technical transformation of that product. The terms used in the research have been defined to guide the reader. The second chapter, the theoretical framework consisted of three sections the first is concerned with technology in the industrial design. The second is concerned with the virtual environment and the virtual reality. The thirds chapter consi

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Publication Date
Thu Mar 16 2023
Journal Name
Wireless Personal Communications
Technology Applications in Tracking 2019-nCoV and Defeating Future Outbreaks: Iraqi Healthcare Industry in IoT Remote
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Publication Date
Wed Jul 27 2022
Journal Name
Journal Of Chemical Technology & Biotechnology
Broad‐ranging review: configurations, membrane types, governing equations, and influencing factors on microbial desalination cell technology
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Abstract<p>Seawater might serve as a fresh‐water supply for future generations to help meet the growing need for clean drinking water. Desalination and waste management using newer and more energy intensive processes are not viable options in the long term. Thus, an integrated and sustainable strategy is required to accomplish cost‐effective desalination via wastewater treatment. A microbial desalination cell (MDC) is a new technology that can treat wastewater, desalinate saltwater, and produce green energy simultaneously. Bio‐electrochemical oxidation of wastewater organics creates power using this method. Desalination and the creation of value‐added by‐products are expected because of this ionic mov</p> ... Show More
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Publication Date
Tue Apr 28 2026
Journal Name
Discover Artificial Intelligence
Barriers to deep learning implementation in orthodontics: data, methodological, and translational challenges—a scoping review
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Abstract Background Deep learning (DL) has attracted increasing attention in orthodontics, with many studies reporting high diagnostic and predictive accuracy. However, despite these promising results, routine clinical adoption remains limited. Objectives This scoping review aimed to explore the main barriers that restrict the translation of DL systems from research environments into everyday orthodontic practice. Methodology The review was conducted in accordance with PRISMA-ScR guidelines. Electronic searches were performed in PubMed, Scopus, Web of Science, and IEEE Xplore for English-language studies published between 2015 and June 2025. Studies reporting quantitative performance of DL-based orthodontic applications were included. Dat

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Publication Date
Mon Apr 24 2017
Journal Name
Spe Kingdom Of Saudi Arabia Annual Technical Symposium And Exhibition
Optimization of Infill Drilling in Whicher Range Field in Australia
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Abstract<p>Now that most of the conventional reservoirs are being depleted at a rapid pace, the focus is on unconventional reservoirs like tight gas reservoirs. Due to the heterogeneous nature and low permeability of unconventional reservoirs, they require a huge number of wells to hit all the isolated hydrocarbon zones. Infill drilling is one of the most common and effective methods of increasing the recovery, by reducing the well spacing and increasing the sweep efficiency. However, the problem with drilling such a large number of wells is the determination of the optimum location for each well that ensures minimum interference between wells, and accelerates the recovery from the field. Detail</p> ... Show More
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Publication Date
Tue Mar 12 2019
Journal Name
Al-khwarizmi Engineering Journal
Optimization Drilling Parameters of Aluminum Alloy Based on Taguchi Method
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This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (33) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Mechanical Engineering
Process Parameters Optimization in Single Point Incremental Forming Of Al1050
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This work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r

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