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Distinguishing Gasoline Engine Oils of Different Viscosities Using Terahertz Time-Domain Spectroscopy
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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Using Bayesian method to estimate the parameters of Exponential Growth Model with Autocorrelation problem and different values of parameter of correlation-using simulation
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We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F

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Publication Date
Fri Dec 15 2023
Journal Name
Iraqi Journal Of Laser
Silver Nanoflowers as an Interfacial Liquid-State Surface Enhanced Raman Spectroscopy (SERS) Sensor for Water Pollution
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Water pollution has created a critical threat to the environment.‎‎ A lot of research has been done ‎recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na3PO4) was investigated as a pollutant using liquid SERS ‎based on colloidal Ag ‎nanoflowers. The chemical method was used to synthesize nanoflowers from silver ‎ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This ‎nanoflowers SERS action in detecting Na3PO4 was reported and analyzed

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Global Pharma Technology
Employing the Physicochemical, Spectroscopy, Antimicrobial and Antifungal Efficacy Studies of P-Hydroxy Acetophenone Based Azo Schiff Base Complexes
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The azo Schiff base [Reaction of 4-aminoanypyrine and P-hydroxy acetophenone] and O-Phenylene diamine have been prepared. One azo Schiff base chelate of Co(Il), Ni(II), Cu(II) and Zn(II)ion was also prepared. The chemical frameworks of the azo Schiff base and like elemental analyses (CHN), determinations of molar conductance, 1 H &13C NMR, IR mass and electronic spectroscopy .The elemental analyses exhibited the combination of [L: M] 1:1 ratio. Established on the values IR spectral, it is showed that the azo Schiff base compound acts as neutral hexadentate ligand bonded with the metal ion from two hydroxyl, two azomethine and two azo groups of the azo Schiff base compound in chelation was confirmed by IR , 1Hand 13CNMR spectral outco

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Publication Date
Fri Jun 30 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhanced Prosthesis Control Through Improved Shoulder Girdle Motion Recognition Using Time-Dependent Power Spectrum Descriptors and Long Short-Term Memory
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Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Using Real-Time PCR to Investigate Some of Antibiotic Resistance Genes from Streptococcus agalactiae Isolates from ewe Mastitis cases in Nineveh province
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In this study, from a total of 856 mastitis cases in lactating ewes, only 34 Streptococcus agalactiae isolates showed various types of resistance to three types of antibiotics (Penicillin, Erythromycin and Tetracycline). St. agalactiae isolates were identified according to the standard methods, including a new suggested technique called specific Chromogenic agar. It was found that antibiotic bacterial resistance was clearly identified by using MIC-microplate assay (dilution method). Also, by real-time PCR technique, it was determined that there were three antibiotics genes resistance ( pbp2b, tetO and mefA ). The high percentage of isolate carried of a single gene which was the Tetracycline (20.59%) followed by percentage Penicillin was

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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
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Optimum Time Schedule for Industrial Processes (II)
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The  present study  deals  with successive  stages  of  productive

operations happened to produce a production within each stage befo re it  moves to the next one. ll cou ld  be deduced that this study is an extension  to what bas  been mentioned  in (1 ) .ln  (I),  the  optimum distribution of  di!Terent jobs of  workers and  machines  in  the productive operations has been st ud ied whi le the study  invol ves the optimum schedule for the succession of these operations presuming that thay have already been distributed on machines and workers (2).A mathematical form has been put for this study to define the "Object.ive Function "

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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Radon concentrations assessment in tap water for different areas in Baghdad city using Rad7
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Publication Date
Sun Mar 29 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Different Methods to Predict Oil in Place in Mishrif Formation / Amara Oil Field
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The reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese

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