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An expert System for Predicting the Effects of Noise Pollution on Grass Trimming Task Using Fuzzy Modeling
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Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents a fuzzy model for predicting the effects of noise pollution on human work efficiency as a function of noise level, exposure time and age of the operators.

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Publication Date
Wed Dec 28 2022
Journal Name
Journal Of Chemical Technology And Metallurgy
THERMODYNAMIC ANALYSIS OF MOISTURE ADSORPTION ISOTHERM FOR MEFENAMIC ACID TABLETS
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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Possibility of reusing Al-Machraya River for feeding Hawizeh marsh
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Al Machraya River was considered as one of the water feeders of Hawizeh Marsh. In 1986, the outlet of this river into the marsh was blocked and the river was used as a main channel for the East Tigris Irrigation Project near Kalat Salih. This causes significant decrease in the available water supply sources, deterioration in the water quality distribution patterns and increasing the stagnation areas within the marsh. This research aims to study the possibility of reusing this river for feeding Hawizeh Marsh. A frequency analysis study was carried out to study the maximum and minimum probable water level (MMPWL) of Tigris River at the upstream of Kalat Salih Barrage. Six statistical models; Normal distribution, Log-Normal type II, Lo

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Publication Date
Fri Aug 20 2021
Journal Name
Iraqi Journal Of Laser
Fractional CO2 Laser for Treatment of Female Stress Urinary Incontinence
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Background: Urinary incontinence (UI) is a common disorder that affects women of various ages and impacts all aspects of life. This condition negatively influences quality of life. Fractional CO2 laser (10600nm) is the recent method for treatment of stress urinary incontinence in women. Objectives: The purpose of the study was to evaluate the efficacy and safety of fractional CO2 laser (10600nm) in the treatment of female stress urinary incontinence. Materials & Methods: This study was done from July 2020 to February 2021conducted at the laser institute for postgraduate studies university of Baghdad, patients collected from a private clinic and the Department of

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Publication Date
Thu Oct 01 2009
Journal Name
2009 Ieee Symposium On Industrial Electronics & Applications
Assessing combinatorial interaction strategy for reverse engineering of combinational circuits
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Publication Date
Wed Jun 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Formulation of Multi-Purpose Grease for Use under Severe Conditions
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Publication Date
Tue Nov 20 2012
Journal Name
J. Of University Of Anbar For Pure Science
Laser Processing For Nanoscale Size Quantum Wires of AlGaAs/GaAs
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In this work we investigate and calculate theoretically the variation in a number of optoelectronic properties of AlGaAs/GaAs quantum wire laser, with emphasis on the effect of wire radius on the confinement factor, density of states and gain factor have been calculated. It is found that there exist a critical wire radius (rc) under which the confinement of carriers are very weak. Whereas, above rc the confinement factor and hence the gain increase with increasing the wire radius.

Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
A Comparative Study for Estimate Fractional Parameter of ARFIMA Model
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      Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir

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Publication Date
Tue Oct 30 2018
Journal Name
Risalat Al-huquq Journal
Legal Protection for Producers of Sound Recordings under Iraqi Law
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Piracy on phonograms is now, rightly, the crime of the electronic age. Despite the protection sought by States to provide for such registrations, whether at the level of national legislation or international agreements and conventions, but piracy has been and continues to pose a significant threat to the rights of the producers of those recordings, especially as it is a profitable way for hackers to get a lot of money in a way Illegal, which is contrary to the rules of legitimate competition. Hence, this research highlights the legal protection of producers of phonograms in light of the Iraqi Copyright Protection Act No. (3) of 1971, as amended.

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Osmotically assisted reverse osmosis (OARO) for desalination of brackish water
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