A number of nitrones have been synthesized in three different procedures, starting with N-phenyl hydroxylamine, followed by the condensation reaction with some selected aldehydes. Furthermore, these nitrones were employed in the preparation of a number of new isoxazolidines. Cycloaddition reaction of nitrones to styrene produced the desired products.
Let R be a commutative ring with unity and M be a non zero unitary left R-module. M is called a hollow module if every proper submodule N of M is small (N ≪ M), i.e. N + W ≠M for every proper submodule W in M. A δ-hollow module is a generalization of hollow module, where an R-module M is called δ-hollow module if every proper submodule N of M is δ-small (N δ  M), i.e. N + W ≠M for every proper submodule W in M with M W is singular. In this work we study this class of modules and give several fundamental properties related with this concept
In this paper we will study some of the properties of an operator by looking at the associated S-act of this operator, and conversely. We look at some operators, like one to one operators, onto operators. On the other hand, we look at some act theoretic concepts, like faithful acts, finitely generated acts, singular acts, separated acts, torsion free acts and noetherian acts. We try to determine what properties of T make the associated S-act has any of these properties.
Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling the Symmetric gray scale texture image and estimating by using
... Show MoreTwo unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
The present study deals with some morphological and anatomical characteristics of the Nonea echioides(L.) Roem. & Sehult species belonging to Boraginaceae, which is recorded to have spread recently in Kurdistan region of Iraq.
This research focused on some of the important morphological characteristics of the stems, leaves, flowers, and fruits and comparing them with other studies of neighboring countries to Iraq. These morphological characteristics were found to be important in isolating the species of the filed. The anatomical features of the epidermis, stomata, and trichomes were also investigated. The study shows that Nonea echioides belongs to C3 plants based on the anatomical featur
... Show MoreChange detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac
Thisstudy aims to determine the specifications of obese women accordingto the heightand type of obesity. It also aimstoidentify the significance of differences in choosing ready-made clothes for the research sample. Finally, the significance of differences in choosing ready-made clothes according to the variable of binaryclassification ofobesity is also identified.The study sample includes obese women: employees, non-employees and students with the age group (18-50) years.The weights and lengths of the sample have been taken to suit the group of obese women.Aquestionnaire in the form of an open question was distributed among (50) obese womenso as to extract the items of the questionnaire. After that, the questionnaire was distributed amo
... Show MoreThe vegetable cover plays an important role in the environment and Earth resource sciences. In south Iraq, the region is classified as arid or semiarid area due to the low precipitations and high temperature among the year. In this paper, the Landat-8 satellite imagery will be used to study and estimate the vegetable area in south Iraq. For this purpose many vegetation indices will be examined to estimate and extract the area of vegetation contain in and image. Also, the weathering parameters must be investigated to find the relationship between these parameters and the arability of vegetation cover crowing in the specific area. The remote sensing packages and Matlab written subroutines may be use to evaluate the results.
Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea
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