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Determine Optimal Preventive Maintenance Time Using Scheduling Method
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In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and access to the optimum time for maintenance, which achieves the lowest costs. The second method depends on the reliability function, which was to determine the optimal maintenance period, which then cost less Can. We also proved through this research that the method of scheduling is better than the method of relying on the reliability function because it depends heavily on the cost of maintenance.

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Inverse Kinematics Solution for Redundant Robot Manipulator using Combination of GA and NN
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A demonstration of the inverse kinematics is a very complex problem for redundant robot manipulator. This paper presents the solution of inverse kinematics for one of redundant robots manipulator (three link robot) by combing of two intelligent algorithms GA (Genetic Algorithm) and NN (Neural Network). The inputs are position and orientation of three link robot. These inputs are entering to Back Propagation Neural Network (BPNN). The weights of BPNN are optimized using continuous GA. The (Mean Square Error) MSE is also computed between the estimated and desired outputs of joint angles. In this paper, the fitness function in GA is proposed. The sinwave and circular for three link robot end effecter and desired trajectories are simulated b

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Agricult.
FORECASTING THE EXCHANGE RATES OF THE US DOLLAR AGAINST THE IRAQI DINAR USING THE BOX-JENKINS METHODOLOGY IN TIME SERIES WITH PRACTICAL APPLICATION
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The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

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Scopus
Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
A Mathematical Model of a Thermally Activated Roof (TAR) Cooling System Using a Simplified RC-Thermal Model with Time Dependent Supply Water Temperature
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This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of antibacterial effect of irrigant solutions (titanium tetra fluoride, green tea, sodium hypochlorite, normal saline) using real-time quantitative – polymerase chain reaction
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Background: Removal of bacteria from the pulp system by instrumentation of an infected root canal, will be significantly reduced the number of bacteria, but it is well documented that instrumentation alone can-not clean and kill all bacteria found on the root canal walls. Antibacterial irrigants are needed to kill the remaining microorganisms. The aims of this study was to assess antibacterial effect of titanium tetrafluoride (TiF4) solution and brewing green tea against root canal bacteria and to compare with sodium hypochlorite and normal saline through microbiological and molecular studies. Materials and methods: Microbiological study was carried out to determine the concentration of titanium tetrafluoride and brewing green tea at which

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Publication Date
Wed Jun 20 2018
Journal Name
Bulletin Of Iraq Natural History Museum
GENOTYPE VERSUS PHENOTYPE TO DETERMINE THE DEFINITIVE IDENTIFICATION OF THE GENERA CHLORELLA BEIJERINCK, 1890 (CHLORELLACEAE) AND COELASTRELLA CHODAT, 1922 (SCENDESMACEAE)
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Publication Date
Sun Jul 01 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
GENOTYPE VERSUS PHENOTYPE TO DETERMINE THE DEFINITIVE IDENTIFICATION OF THE GENERA CHLORELLA BEIJERINCK, 1890 (CHLORELLACEAE) AND COELASTRELLA CHODAT, 1922 (SCENDESMACEAE)
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    Conventional identification of three coccoid green algae isolates was attempted to characterize the studied algae morphologically under compound microscope, which demonstrated confusional phenomenal convergence; all were classified microscopically as the green alga Chlorella vulgaris Beijerinck, 1890.

 

    Phylogenetic studies were conducted to settle the argument about the phenotype by studying the genotype. Genotype the promising field in advance classification by using 18S rRNA and compared to GenBank database using to search the related sequences. The determined sequences showed high a similarity to the strains registered in GenBank.

 

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Publication Date
Sun Oct 18 2020
Journal Name
Diagnostics
Diagnostic Accuracy of Oral Fluids Biomarker Profile to Determine the Current and Future Status of Periodontal and Peri-Implant Diseases
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Severe periodontitis is ranked as the sixth most prevalent disease affecting humankind, with an estimated 740 million people affected worldwide. The diagnosis of periodontal diseases mainly relies upon assessment of conventional clinical parameters. However, these parameters reflect past, rather than current, clinical status or future disease progression and, likely, outcome of periodontal treatment. Specific and sensitive biomarkers for periodontal diseases have been examined widely to address these issues and some biomarkers have been translated as point-of-care (PoC) tests. The aim of this review was to provide an update on PoC tests for use in the diagnosis and management of periodontal diseases. Among the PoC tests developed so

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Fabrication and Characterization of Nanofibers Membranes using Electrospinning Technology for Oil Removal
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Oily wastewater is one of the most challenging streams to deal with especially if the oil exists in emulsified form. In this study, electrospinning method was used to prepare nanofiberous polyvinylidene fluoride (PVDF) membranes and study their performance in oil removal. Graphene particles were embedded in the electrospun PVDF membrane to enhance the efficiency of the membranes. The prepared membranes were characterized using a scanning electron microscopy (SEM) to verify the graphene stabilization on the surface of the membrane homogeneously; while FTIR was used to detect the functional groups on the membrane surface. The membrane wettability was assessed by measuring the contact angle. The PVDF and PVDF / Graphene membranes efficiency

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Sun Nov 01 2020
Journal Name
Iraqi Journal Of Laser
TREATMENT OF SYMPTOMATIC CERVICAL ECTOPY USING CO2 LASER (10600 nm) – Case Study
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Background: Cervical ectopy advanced to erosion is one of the common conditions in gynecological and pathological study. It is considered as a physiologic condition resulting from columnar epithelium migration from the cervical canal into the vaginal portion of the cervix, in which no treatment for asymptomatic cervical ectropion can be given. Treatment can be accomplished via thermal cauterization (Electro cautery), Cryosurgery. CO2 laser therapy is another modality of treatment.

Objective: To study the effectiveness of CO2 laser therapy and evaluate it as a biomedical tool for the treatment of cervical ectropion. The study was done at Laser Medicine Research Clinic at the

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