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Improved Method to Correlate and Predict Isothermal VLE Data of Binary Mixtures
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Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equilibrium data point with very good accuracy. The developments of this method are applied on 13 binary systems at different temperatures which gives very good accuracy.

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Estimation Multivariate data points in spatial statistics with application
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This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

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Publication Date
Sun Jan 01 2017
Journal Name
Proceedings Of The Conference “recent Trends In Engineering Sciences And Sustainability”, Baghdad
GNSS positioning techniques for enhancing Google Earth data quality
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Due to the easily access to the satellite images, Google Earth (GE) images have become more popular than other online virtual globes. However, the popularity of GE is not an indication of its accuracy. A considerable amount of literature has been published on evaluating the positional accuracy of GE data; however there are few studies which have investigated the subject of improving the GE accuracy. In this paper, a practical method for enhancing the horizontal positional accuracy of GE is suggested by establishing ten reference points, in University of Baghdad main campus, using different Global Navigation Satellite System (GNSS) observation techniques: Rapid Static, Post-Processing Kinematic, and Network. Then, the GE image for the study

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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Improve Data Mining Techniques with a High-Performance Cluster
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Image data compression by using multiwavelete for color image
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There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja

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Publication Date
Wed May 02 2012
Journal Name
Journal Of Planner And Development
data about the health sector in Iraq in 2006
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The study relied on data about the health sector in Iraq in 2006 in cooperation with the Ministry of Health and the Central Bureau of Statistics and Information Technology in 2007 Included the estimates of the population distribution of the Baghdad province and the country depending on the population distribution for 1997,evaluate the health sector which included health institutions, and health staff, and other health services. The research Aimis; Measurement an amount and size of the growth of health services (increase and decrease) and the compare of verified in Iraq and Baghdad, and evaluate the effectiveness of the distribution of supplies and health services (physical and human) of the size of the population distribution and

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Data Aggregation in Wireless Sensor Networks Using Modified Voronoi Fuzzy Clustering Algorithm
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Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

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Publication Date
Tue Sep 01 2009
Journal Name
Al-nahrain Journal Of Science
Colorimetric assay of aspirin using modified method
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In this research, we did this qualitative and quantitative study in order to improve the assay of aspirin colorimetrically using visible spectrophotometer. This method depends on aqueous hydrolysis of aspirin and then treating it with the ferric chloride acidic solution to give violet colored complex with salicylic acid, as a result of aspirin hydrolysis, which has a maximum absorption at 530nm. This procedure was applied to determine the purity of aspirin powder and tablet. The results were approximately comparative so that the linearity was observed in the high value of both correlation coefficient (R= 0.998) and Determination Coefficient or Linearity (R2= 0.996) while the molar absorpitivity was 1.3× 103 mole

Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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Publication Date
Fri Jan 24 2020
Journal Name
Petroleum And Coal
Evaluation of Geomechanical Properties for Tight Reservoir Using Uniaxial Compressive Test, Ultrasonic Test, and Well Logs Data
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Tight reservoirs have attracted the interest of the oil industry in recent years according to its significant impact on the global oil product. Several challenges are present when producing from these reservoirs due to its low to extra low permeability and very narrow pore throat radius. Development strategy selection for these reservoirs such as horizontal well placement, hydraulic fracture design, well completion, and smart production program, wellbore stability all need accurate characterizations of geomechanical parameters for these reservoirs. Geomechanical properties, including uniaxial compressive strength (UCS), static Young’s modulus (Es), and Poisson’s ratio (υs), were measured experimentally using both static and dynamic met

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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