This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012), (2013), (2014).
The research aims to show the possibility of adopting the market approach to measure the fair value of biological assets in Iraq, by applying to a sample of the company listed on the Iraq Stock Exchange, where the Middle East Fish Production and Marketing Company was selected from among 7 companies representing the agricultural sector in Iraq, and according to the availability of data and for five years, the financial statements were presented of the measurement and disclosure of biological assets at fair value according to the market approach, One of the most important conclusions reached by the researcher is the The possibility of measuring and disclosing biological assets at fair value according to the market approach in the Ira
... Show MoreA band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).
This paper describes the development of a simple spectrophotometric determination of bismuth III with 4-(2-pyridylazo) resorcinol (PAR) in aqueous solution in the presence of cetypyridinium chloride surfactant at pH 5 which exhibits maximum absorption at 532 nm. Beer's law is obeyed over the range 5-200 µg/25 mL. i.e. 0.2-8 ppm with a molar absorptivity of 3×104 l.mol-1.cm-1 and Sandell's sensitivity index of 0.0069 µg.cm-2. The method has been applied successfully in the determination of Bi (III) in waters and veterinary preparation.
Background: Fibromyalgia syndrome (FMS) is the
most common rheumatic cause of diffuse pain and
multiple regional musculoskeletal pain and disability.
Objective: is to assess the contribution of serum
lipoprotein (A) in the pathogenesis of FMS patients.
Methods: One hundred twenty two FMS patients
were compared with 60 healthy control individuals
who were age and sex matched. All FMS features and
criteria are applied for patients and controls; patients
with secondary FMS were excluded. Serum
Lipoprotein (A): [Lp(A)], body mass index (BMI), &
s.lipid profile were determined for both groups.
Results: There was a statistical significant difference
between patients &controls in serum lipoprotein
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreThe goal of this work is demonstrating, through the gradient observation of a of type linear ( -systems), the possibility for reducing the effect of any disturbances (pollution, radiation, infection, etc.) asymptotically, by a suitable choice of related actuators of these systems. Thus, a class of ( -system) was developed based on finite time ( -system). Furthermore, definitions and some properties of this concept -system and asymptotically gradient controllable system ( -controllable) were stated and studied. More precisely, asymptotically gradient efficient actuators ensuring the weak asymptotically gradient compensation system ( -system) of known or unknown disturbances are examined. Consequently, under convenient hypo
... Show MoreSoil is considered one of the main factors of subsidence phenomena which
became continually happen in Baghdad (Ghazalia, Ameria, and Hay al-Amyl)
causing bad effects as shortage of drinking water, traffic jam and formation
swamps.
This thesis depends on soil study to a depth 15 meters, due to its
importance in subsidence. This done through specifying its chemical physical
properties.
Soil within Iraq climate, in case of water stopping for any reason it contract
and shrink away especially when it exposed to high pressure these factors
finally caused subsidence. In case of leakage underground water or that of
damaged water pipes this will contribute to chemical reactions which damage soil
structure and incr
A kindergarten teacher is one of the most important elements in the educational process, since she is totally relied upon in kindergartens. Therefore, she could have basic and healthy characteristics to improve the educational process by directing the child towards a perfect growing upEducating and raising up a child should be an organized process that makes desirable changes in the child’s behavior in order to improve different sides of his personality, such as his appearance side, his mental side, and his social side.
This research aims at:
1- Measuring the scientific brilliance in kindergarten teachers.
2- Investigating the statistical significant differences of the scientific brilliance among kindergarten teachers in accor