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Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
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Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling capacity and 50 models for power consumption and 25 models for refrigerant mass flow rate.

 Keywords: Performance, compressors, manufacturing, data, equations.

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
An An Accurate Estimation of Shear Wave Velocity Using Well Logging Data for Khasib Carbonate Reservoir - Amara Oil Field
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Engineering
Performance Evaluation of Pole Placement and Linear Quadratic Regulator Strategies Designed for Mass-Spring-Damper System Based on Simulated Annealing and Ant Colony Optimization
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This paper investigates the performance evaluation of two state feedback controllers, Pole Placement (PP) and Linear Quadratic Regulator (LQR). The two controllers are designed for a Mass-Spring-Damper (MSD) system found in numerous applications to stabilize the MSD system performance and minimize the position tracking error of the system output. The state space model of the MSD system is first developed. Then, two meta-heuristic optimizations, Simulated Annealing (SA) optimization and Ant Colony (AC) optimization are utilized to optimize feedback gains matrix K of the PP and the weighting matrices Q and R of the LQR to make the MSD system reach stabilization and reduce the oscillation of the response. The Matlab softwar

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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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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study the Characteristic Performance of Trickling Filter for Pharmaceutical Waste Treatment
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The impact of social audit in social performance an applied study of the views of a sample of managers and staff of Algerian business organizations
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            This research aims at clarifying the concept of social auditing, which is one of the most important reasons for its emergence is social responsibility accounting and its role in measuring the social performance of enterprises. The study also aimed to know how social auditing has an impact and its role in improving the social performance of business organizations, and the research refers to testing the hypotheses of an impact of social auditing on social performance through a commitment to social responsibility. The research sample consisted of 200 individuals from 20 Algerian business organizations and represented individuals who were researched in managers and em

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Approximate Solution of Delay Differential Equations Using the Collocation Method Based on Bernstien Polynomials???? ???????? ????????? ????????? ????????? ???????? ?????????? ???????? ??? ??????? ???? ?????????
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In this paper a modified approach have been used to find the approximate solution of ordinary delay differential equations with constant delay using the collocation method based on Bernstien polynomials.

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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Implementation of Univariate Paradigm for Streamflow Simulation Using Hybrid Data-Driven Model: Case Study in Tropical Region
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Publication Date
Sat Jan 01 2022
Journal Name
Ibero-american Journal Of Exercise And Sports psychology
THE EFFECT OF HIIT EXERCISES ON SOME PHYSIOLOGICAL AND PHYSICAL INDICATORS IN REDUCING COMPETITION ANXIETY AND PERFORMANCE OF SOME OFFENSE SKILLS FOR YOUNG BADMINTON ATHLETES
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The research aimed to use HIIT exercises, and to know the effect of HIIT exercises on some physiological and physical indicators of the young badminton players, and to identify the degree of competition anxiety and the performance of some offense skills among the young badminton players. The research community (the young badminton players), the research sample and its selection method (the research sample was chosen by the intentional method (8) badminton player from the Athwari Club), the scientific method (the experimental method with pre and post tests), measurement tools: physiological tests (high and low blood pressure) , pulse, and physical exams (explosive force of arms and legs) and the offense skills and the scale of competit

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