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Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Mon Feb 24 2025
Journal Name
Advances In Structural Engineering
Experimental and numerical investigation on the behavior of composite reinforced concrete columns encased by steel section and hybrid GFRP section
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GFRP was employed in constructions as an alternative to steel, which has many advantages like lightweight, large tensile strength and resist corrosion. Existing researches are insufficient in studying the influence of hybrid reinforced concrete composite columns encased by GFRP I-section (RCCCEG) and I-section steel (RCCCES). In this study twenty one (RC) specimens of a cross-section of 130 mm × 160 mm, with different length (long 1600 mm and short 750 mm) were encased by using I-section (steel and GFRP) and tested under various loading (concentric, eccentric and flexural loads). The test was focused on the influence of many parameters; load-carrying capacity, mode of failure, deformation and drawing an interaction diagram (N-

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
the role of marketing intelligence in promoting new product policies.a sample survey of workers in a number of mineral water plants in dohuk governorate
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Marketing Intelligence is one of the important methods of collecting information about competitors ' products and changes in customers ' tastes and needs that contribute to determining the policies to be followed in product development.

The problem of research, which seeks to be answered by the extent to which the companies in question have the appropriate and effective mechanisms to develop their products, and the nature of the relationship between the components of marketing intelligence and new product development policies. The importance of research is determined by the importance of obtaining important and necessary information to make the appropriate decision on the development of the new product an

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Publication Date
Wed Dec 15 2021
Journal Name
Natural Volatiles And Essential Oils
Metal complexes of the schiff base of 1H-indole_3_carbaldehyde were produced and their catecholase activities were assessed
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Publication Date
Tue Jun 01 2021
Journal Name
Iraqi Journal Of Physics
Effect of Transition Metal Dopant on the Electrical Properties of ZnO-TiO2 Films Prepared by PLD Technique
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In this article, the influence of group nano transition metal oxides such as {(MnO2), (Fe2O3) and (CuO)} thin films on the (ZnO-TiO2) electric characteristics have been analyzed. The prepared films deposited on glass substrate laser Nd-YAG with wavelength (ℷ =1064 nm) ,energy of (800mJ) and number of shots (400). The density of the film was found to be (200 nm) at room temperature (RT) and annealing temperature (573K).Using DC Conductivity and Hall Effect, we obtained the electrical properties of the films. The DC Conductivity shows that that the activation energies decrease while the σRT at annealing temperature with different elements increases the formation of mixed oxides. The Hall effect, the elec

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Publication Date
Tue Jun 15 2021
Journal Name
Al-academy
Consistency and Consistency in Contemporary Iraqi Painting - Selected Models-: حسين شاكر قاسم العيداني
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  The tagged research is concerned with observation and investigating the concepts of consistency and harmony in contemporary Iraqi painting (selected models) in order to reveal the mechanisms and rules of these two concepts in the artistic field and their mechanisms of operation. How reflected tools Consistency and harmony in contemporary Iraqi painting? What is consistency and what are its mechanisms and principles? Is consistency a unit product quality? Are there similarities between consistency and harmony? What is harmony and its principles and rules? As for the second chapter, it included two topics that dealt with the first topic - consistency and harmony between concept and significance, while the second topic meant - histor

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Wed Aug 31 2022
Journal Name
International Review On Modelling And Simulations (iremos)
Inexpensive DC to AC Inverter Device for Artificial Saline Soils Resistivity Analysis
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In aired and semiarid areas like Iraq, saline soil may be considered one of the major concerns. In addition to environmental effects, they may produce significant geotechnical hazards that could interrupt the structure stability depending on the salt type and its concentration. So, it is crucial to identify the degree of the soil salinity with a proper tool for getting a qualified assessment and consequently offering a suitable treatment. In this paper, the electrical resistivity technique has been employed to detect the degree of soil salinity by considering a new electronic system. The system used a single-phase Direct Current (DC) to Alternating Current (AC) inverter accompanied by a transformer. Natural soils became artificially saline

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Sat Jun 28 2014
Journal Name
Iraqi Postgraduate Medical Journal
Comparism Between Transvaginal Cervical Length Measurement and Digital Examination in Prediction of Imminent preterm Delivery
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BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjecte

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