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Enhancement of Recommendation Engine Technique for Bug System Fixes
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This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially their utility in allocating a problem to a specific developer. An analysis was conducted on two key areas: first, the development of a model to represent developer prioritizing within the bug repository, and second, the use of hybrid machine learning techniques to select bug reports. Moreover, we use our model to facilitate developer assignment responsibilities. Moreover, we considered the developers’ backgrounds and drew upon their established knowledge and experience when formulating the pertinent objectives. An examination of two individuals’ experiences with software defects and how their actions impacted their rankings as developers in a software project is presented in this study. Researchers are implementing developer categorization techniques, assessing severity, and reopening bugs. A suitable number of bug reports is used to examine the model’s output. A developer’s bug assignment employee has been established, enabling the program to successfully address software maintenance issues with the highest accuracy of 78.38%. Best engine performance was achieved by optimizing and cleansing data, using relevant attributes, and processing it using deep learning.

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Publication Date
Sat Aug 01 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Building and legalizing a test for evaluating the tactical learning of the footwork for the foil fencer in the fencing game
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AA wahid, journal mustansiriyah of sports science, 2023

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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluating the Impact of Pharmacist Counselling for Asthmatic Children at Karbala Teaching Hospital for Children: An Interventional Prospective Study (Conference Paper )#
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Asthma is one of the most common chronic, non-communicable diseases affecting children worldwide. The estimated prevalence of pediatric asthma in Iraq is 15.8%. Physiologic, inflammatory and structural factors contribute to the development of asthma. Assessment and monitoring of asthma control can be done by a validated children asthma control test (CACT). Management of asthma must address three components which are an appropriate management plan, the most appropriate medication if necessary, and the use of safe and effective medication. The management plan should consider patient counseling and education about the definition of asthma, signs, and symptoms, the pathophysiology of asthma, common triggers for asthma and how can avoid them,

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Publication Date
Mon Oct 23 2023
Journal Name
Journal Of Optics
Single mode optical fiber sensor based on surface plasmon resonance for the detection of the oil aging for the electrical transformers
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This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3

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Publication Date
Wed Apr 08 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Bayes estimators for reliability and hazard function of Rayleigh-Logarithmic (RL) distribution with application
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In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

Publication Date
Mon Sep 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Performance of Immobilized Chlorella Algae for Removing pb(II) Ions from Aqueous Solution
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This study aims to show the  effectiveness of immobilization of Chlorella green algae biomass in the form of bead for the removal of lead ions from synthetic polluted water  at various operational parameters such as pH (2–6), biosorbent dosage (0.5–20 g/L) and initial concentration (10–100 mg/L). More than 90 % removal efficiency was achieved. FTIR and SEM-EDX analysis of the biosorbent before and after sorption show differences in the functional groups on the adsorbent surface. Langmuir and Freundlich equilibrium isotherm, pseudo-first-order and pseudo-second-order kinetic models were applied to the experimental and results and show good conformity with Langmuir isotherm model and pseudo-second-order kinetic model with c

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A Novel Gravity ‎Optimization Algorithm for Extractive Arabic Text Summarization
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An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

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Publication Date
Wed Jan 01 2014
Journal Name
Iraqi Journal Of Science
Calculate the Longitude and Orbital Motion for Amaletha, Europa, Ganymede and Callisto Satellites
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The orbital motion and longitude for some Jupiter's satellites (Amaletha, Europa, Ganymede and Callisto) were calculated from two different locations Iraq and Syria. A program was designed, the input parameters were the desired year, month, day and the longitude of the location, the output parameters results were applied in form of a file, and this file includes the longitude, orbital motion, and local time of these satellites. A specific date 1-10-2013 was taken, the results of longitude was (20-336) º and orbital motion was (92-331) º for both Iraq and Syria location with observing time (05:24:14-15:18:10) for Iraq and (04:56:33-14:50:30) for Syria. The difference in time between the two locations was constant (00:45:00), these results

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Publication Date
Sun Dec 01 2024
Journal Name
Chilean Journal Of Statistics
A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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Publication Date
Tue Oct 22 2024
Journal Name
Iraqi Statisticians Journal
Inferential Methods for the Dagum Regression Model
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The Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Are flection Of Accounting for Contingent Assets, Liabilities and Provision on Faithful Representation Characteristic of Accounting Information
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Abstract                                                                     

This research aims to study the reflection of accounting for contingent assets and liabilities and provisions on Faithful Representation characteristic of accounting information, To achieve this goal has been questionnaire design has been distributed to research sample, which consists of (50) li

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