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A Semi-Empirical Equation based on the Strut-and-Tie Model for the Shear Strength Prediction of Deep Beams with Multiple Large Web Openings
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be unsatisfactory for deep beams with large web openings. A simplified empirical equation to estimate the shear strength for deep T-beams with large web openings based on the strut-and-tie model was proposed and verified with numerical analysis. The numerical study considered three-dimensional finite element models, in ABAQUS software, that have been developed to simulate and predict the performance of deep beams. The results of numerical simulations were in good agreement and exhibited close correlation with the experimental data. The test results showed that the enlargement in the size of web openings substantially reduces the elements' shear capacity. The experiments revealed that increasing the width of the openings has more effect than the depth at reducing the load-carrying capacity.

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Computer Assisted Immunohistochemical Score Prediction Via Simplified Image Acquisition Technique
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Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Fri Dec 03 2021
Journal Name
Baghdad Journal Of Biochemistry And Applied Biological Sciences
A clinical-statistical study on COVID-19 infection and death status at the Alshifaa Healthcare Center/ Baghdad
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Background: COVID-19 is an ongoing disease that caused, and still causes, many challenges for humanity. In fact, COVID-19 death cases reached more than 4.5 million by the end of August 2021, although an improvement in the medical treatments and pharmaceutical protocols was obtained, and many vaccines were released. Objective: To, statistically, analyze the data of COVID-19 patients at Alshifaa Healthcare Center (Baghdad, Iraq). Methods: In this work, a statistical analysis was conducted on data included the total number, positive cases, and negative cases of people tested for COVID-19 at the Alshifaa Healthcare Center/Baghdad for the period 1 September – 31 December 2020. The number of people who got the test was 1080, where 424 w

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Publication Date
Thu May 18 2023
Journal Name
College Of Islamic Sciences
The battle of Dumat al-Jandal And its impact on the era of prophecy And the righteous caliphate
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The research in Islamic history is considered a title for the glory of the nation and a mirror for the intellectual and mental maturity of the men of the Islamic state who played an important role in saving humanity from darkness to light and from ignorance to knowledge and to show their position in building the Islamic state, and to highlight the importance of their conquests of neighboring cities and the expansion of Islam, and for this reason they appear The importance of writing on the topic (The Battle of Dumat al-Jandal and its impact on the era of the Prophethood and the Rightly Guided Caliphate). The reason for choosing this topic was to show the status of Dumat al-Jandal and its importance in the Islamic state and its great role

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Publication Date
Sun May 08 2011
Journal Name
Journal Of Planner And Development
The Effect of the Natural and Cultural Environments Factors on the Architectural and Planning Characteristics of Sulaymaniyah Mosques
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Most of the mosques in the Islamic world fall under specific and known forms and patterns to a large extent, and such patterns have grown and evolved from the few basic and uniform models, but they changed slowly due to the impact with a mixture of changing functional requirements and cultural landscapes because of the variables of time and place to form patterns known and famous in this day across parts of the Islamic world and its borders. There was no exception to these patterns, but small numbers of mosques that were probably the result of personal experiences or improvisational resolutions, or in response to specific or temporary stimuli. However, the emergence of a specific pattern which does not belong to any of these patt

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Wed Jun 20 2018
Journal Name
Al-academy
The effect of CORT educational program on creative thinking for the secondary school students in art education subject
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The current research aims to identify (the effect of CORT program on creative thinking for middle school students in the art education history of ancient art subject).

     The research society continue of the5th of scientific students in ALsadreen secondary school of excellence which related of the Directorate of Education al-sader city, for the academic year (2015/2016), The sample was (35) students for each of the two groups (experimental and control). The equivalence between the research groups was carried out in the IQ variable, the age and the level of the father and mother.

     The researcher used the experimental method of partial control and the post-test. If the course of

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Econometrics analysis of the impact of external shocks on foreign direct investment in Iraq for the period (1995-2016)
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The external shocks are one of the phenomena that the Iraqi economy is exposed to over a period of time. It is referred to as changes and events that come from outside the economic system and extends to many economic variables. However, foreign direct investment may be severely affected due to the extreme sensitivity to changes and local and international developments. This type of trauma and its characteristics to help manage and cope with external shocks, and in order to avoid the standard problems experienced by some models of simple linear regression, multi-linear regression models were used with variables Scientific and other dummy variables .

        The study foun

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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
The effect of triggering on the output performance of diode direct face pumping for disc laser in pulse mode
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The triggering effect for the face pumping of Nd:YVO4 disc medium of 4×5×0.5 mm was investigated using bulk diode laser at different resonator cavity length in pulse mode and at repetition rate of 1.3kHz. The maximum emitted peak power was found to be 100, 82, and 66 mW for resonator lengths of 10, 13.5, and 17.5 cm respectively, while the threshold pumping power was found to be 41mW. The maximum emitted peak power obtained was 300 mW when using external triggering and 10cm length, with repetition of 3Hz.

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