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Data Base for Dynamic Soil Properties of Seismic Active Zones in Iraq
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Iraq is located near the northern tip of the Arabian plate, which is advancing northwards relative to the Eurasian plate, and is predictably, a tectonically active country. Seismic activity in Iraq increased significantly during the last decade. So structural and geotechnical engineers have been giving increasing attention to the design of buildings for earthquake resistance. Dynamic properties play a vital role in the design of structures subjected to seismic load. The main objective of this study is to prepare a data base for the dynamic properties of different soils in seismic active zones in Iraq using the results of cross hole and down hole tests. From the data base collected it has been observed that the average vertical compressional wave velocities were ranged from (1125-2500) m/s in the North, (306-1544) m/s in the Middle, (805-1812) m/s in the western south, (377-1326) m/s in the eastern south and (334-1404) m/s in the South of Iraq. And the average vertical shear wave velocities were ranged from (225-476) m/s in the North, (111-408) m/s in the Middle, (268-659) m/s in the western south, (131-380)m/s in the eastern south and (102-365) m/s in the South of Iraq.

 

 

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Publication Date
Fri May 24 2024
Journal Name
Molecular Crystals And Liquid Crystals
Synthesis and liquid crystalline properties of novel series containing 5H-thiazolo[3,4-b][1, 3, 4]thiadiazole unit with schiff base and azo linkage
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating the Parameters of Exponential-Rayleigh Distribution for Progressively Censoring Data with S- Function about COVID-19
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The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
Pioneering and Growth of Plastic vision data in Modern Art
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The achievements of the art that we know today are questioned in motives that differ from what art knew before, including dramatic artistic transformations, which he called modern art.
In view of the enormity of such a topic, its ramifications and its complexity, it was necessary to confine its subject to the origin of the motives of the transformations of its first pioneers, and then to stand on what resulted from that of the data of vision in composition and drawing exclusively, and through exploration in that, we got to know the vitality of change from the art of its time.
And by examining the ruling contemporary philosophical concepts and their new standards and their epistemological role in contemporary life, since they includ

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Publication Date
Wed Dec 01 2021
Journal Name
Open Biology
Structure and in silico simulations of a cold-active esterase reveals its prime cold-adaptation mechanism
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Here we determined the structure of a cold active family IV esterase (EstN7) cloned from Bacillus cohnii strain N1. EstN7 is a dimer with a classical α/β hydrolase fold. It has an acidic surface that is thought to play a role in cold-adaption by retaining solvation under changed water solvent entropy at lower temperatures. The conformation of the functionally important cap region is significantly different to EstN7's closest relatives, forming a bridge-like structure with reduced helical content providing greater access to the active site through more than one substrate access tunnel. However, dynamics do not appear to play a major role in cold adaption. Molecular dyn

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Publication Date
Thu May 12 2016
Journal Name
Biochemistry
Probing the Role of Active Site Water in the Sesquiterpene Cyclization Reaction Catalyzed by Aristolochene Synthase
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
PHOTO DYNAMIC THERAPY (PDT) WITH BIOLOGICAL TISSUES USING ND:GLASS LASER
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A Photo Dynamic Therapy (PDT) is a technique which is used with Laser to treat many of cancer
tissues. This paper deals with the relatively new therapeutic technique (PDT) with pulsed Nd:glass Laser
which was applied to human soft tissues (Ovary and Kidney tissues), and to the hard tissues (freshly
extracted human teeth), with power density of 280 watt/mm2 and exposure time 330 usec. Different
dyes (Blue, methylene, eosin, and orange) were applied to the area before irradiation to study the effect
of the pigments on the laser interaction with biological tissues. The zone of treatment (Z-necrosis) with
aid of MATLAB was determined. The relationship of zone of treatment with exposure time,
accumulated damage and fracti

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Numerical Investigation for Simulation of Thermophysical Properties for Polypropylene 575 Polymer Melts in Single Screw Extruder
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A numerical model for Polypropylene 575 polymer melts flow along the solid conveying screw of a single screw extruder under constant heat flux using ANSYS-FLUENT 17.2 software has been conducted. The model uses the thermophysical properties such as Viscosity, thermal conductivity, Specific heat and density of polypropylene 575 that measured as a function of temperature, and residence time data for process simulation. The numerical simulation using CFD models for single screw extruder and the polymer extrusion was analysed for parameters such as (thermal conductivity, specific heat, density and viscosity) reveals a high degree of similarity to experimental data measured. The most important outcome of this study is that geometrical, parame

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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