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Deep Bayesian for Opinion-target identification
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The use of deep learning.

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Masculine identification among secondary schoolboys
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The purposes of this study are to measure masculine's identification among secondary school students, and to examine the significant differences among secondary school students in respect of students age (16-18) year. The researcher has prepared a questionnaire comprised (25) item to measure masculine identification among students: this scale was applied on (100) student who were selected as a sample from four different school at al-rusafa side in Baghdad. The scale then modified to (23) item to be more consistent. The results revealed that there were no significant differences among students based on the variable of age, and the mean of masculine identification showed a high level than the hypothesized mean.

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of applying the target costing technique on rationalizing pricing decisions in economic units
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                The research aims to highlight the role played by the target costing technique as an administrative technique that is compatible with the rapid developments and changes in the external environment, with the information and scientific foundations it provides in the allocation of indirect costs and the accuracy in measuring the cost from the start of the project planning process up to the production process and indicating the extent of its impact on decisions Pricing in a way that contributes to the rationalization of pricing decisions in economic units in the light of intense competition and the multiplicity of alternatives.

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
A Comparative Study on the Electrical Characteristics of Generating Plasma by Using Different Target Sources
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In this research, the electrical characteristics of glow discharge plasma were studied. Glow discharge plasma generated in a home-made DC magnetron sputtering system, and a DC-power supply of high voltage as input to the discharge electrodes were both utilized. The distance between two electrodes is 4cm. The gas used to produce plasma is argon gas which flows inside the chamber at a rate of 40 sccm. The influence of work function for different target materials (gold, copper, and silver), - 5cm in diameter and around 1mm thickness - different working pressures, and different applied voltages on electrical characteristics (discharge current, discharge potential, and Paschen’s curve) were studied. The results showed that the discharge cur

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Publication Date
Tue Apr 27 2021
Journal Name
Frontiers In Pharmacology
The Endocannabinoid Anandamide Attenuates Acute Respiratory Distress Syndrome by Downregulating miRNA that Target Inflammatory Pathways
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Acute respiratory distress syndrome (ARDS) is defined as a type of respiratory failure that is caused by a variety of insults such as pneumonia, sepsis, trauma and certain viral infections. In this study, we investigated the effect of an endocannabinoid, anandamide (AEA), on ARDS induced in the mouse byStaphylococcusEnterotoxin B (SEB). Administration of a single intranasal dose of SEB in mice and treated with exogenous AEA at a dose of 40 mg/kg body weight led to the amelioration of ARDS in mice. Clinically, plethysmography results indicated that there was an improvement in lung function after AEA treatment accompanied by a decrease of inflammatory cell infiltrate. There was also a significant decrease i

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Transport Assessment Using Bayesian Method to Determine Ride-Hailing in Kula Lumpur: A Case Study
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This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai

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Publication Date
Sun Nov 20 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ISOLATION AND IDENTIFICATION OF BACTERIA THAT PRODUCE AMYLASE: ISOLATION AND IDENTIFICATION OF BACTERIA THAT PRODUCE AMYLASE
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Thirty six bacteria were isolated from various sourcesc (soil, starch, cooked rice and other foods) and subjected to a series of primary screening tests to obtain the optimal isolation to production of amylase. The volume of producing zone by logal indicator for (Seven) isolates of the secondary screening by measuring the enzymatic activity and specific enzymatic activity. The isolate A4 was found to be the most efficient for production of amylase. Then this isolate was diagnosed through microscopic, vitek 2 system technique. in addition by gentic diagnesis through gene 16s of the genes nitrogen bases by use the polymerase chain reaction (PCR) which reached 1256 bases. In comparison to the available information at the National Center for

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Publication Date
Wed Dec 01 2021
Journal Name
Computers & Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Geological Journal
Wellbore Instability Analysis to Determine the Safe Mud Weight Window for Deep Well, Halfaya Oilfield
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Wellbore instability is one of the most common issues encountered during drilling operations. This problem becomes enormous when drilling deep wells that are passing through many different formations. The purpose of this study is to evaluate wellbore failure criteria by constructing a one-dimensional mechanical earth model (1D-MEM) that will help to predict a safe mud-weight window for deep wells. An integrated log measurement has been used to compute MEM components for nine formations along the studied well. Repeated formation pressure and laboratory core testing are used to validate the calculated results. The prediction of mud weight along the nine studied formations shows that for Ahmadi, Nahr Umr, Shuaiba, and Zubair formations

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Publication Date
Thu Jan 01 2026
Journal Name
Ieee Transactions On Human-machine Systems
Deep Learning-Driven Decision Fusion: Spatio-Spectrogram Features for Inner Speech Recognition From Electroencephalogram Signals
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Publication Date
Thu Jan 01 2026
Journal Name
Ieee Transactions On Human-machine Systems
Deep Learning-Driven Decision Fusion: Spatio-Spectrogram Features for Inner Speech Recognition From Electroencephalogram Signals
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