Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and geology of a Moon's surface. Therefore, it is important to study them and determine their characteristics. So, several segmentations methods were used in this study these are: K-Means, Single Feed Forward Neural Network (SFFNN), and hybrid segmentation methods. K-Means method applied with different number of clusters (k), that were used to segment Moon images and isolate lunar craters, where k=1,2,3, and 4 were used. But, all of them did not identify the boundary of craters, only K=3 gave useful results. SFFNN was also used in this work, it trained by a novel method, where weights have been replaced by masks, that create depending on the images features and targets. Thirteen lunar craters were used, ten of them utilized in training process and the last three images were used to test the performance of network. But also this method did not segment lunar images and identify the boundaries of lunar craters clearly. So, in attempt to overcome this problem, the new hybrid method was proposed, that combine the concepts of K Means and SFFNN methods. The main advantages of the proposed hybrid method is that it does not require much data in the training process as it is known in other networks, where the K-Means cluster segmentation method gave a shortcut to correlating masks with images, which led to giving perfect results in a short time. Then, results show the proposed hybrid segmentation method was succeed to segment lunar crater and identify the craters boundaries clearly.
Graphite nanoparticles were successfully synthesized using mixture of H2O2/NH4OH with three steps of oxidation. The process of oxidations were analysis by XRD and optics microscopic images which shows clear change in particle size of graphite after every steps of oxidation. The method depend on treatments the graphite with H2O2 in two steps than complete the last steps by reacting with H2O2/NH4OH with equal quantities. The process did not reduces the several sheets for graphite but dispersion the aggregates of multi-sheets carbon when removed the Van Der Waals forces through the oxidation process.
This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators
People may believe that tissue of normal brain and brain with benign tumor
have the same statistical descriptive measurements that are significantly different
from the of brain with malignant tumor. Thirty brain tumor images were collected
from thirty patients with different complains (10 normal brain images, 10 images
with benign brain tumor and 10 images with malignant brain tumor). Pixel
intensities are significantly different for all three types of images and the F-test was
measured and found equal to 25.55 with p-value less than 0.0001. The means of
standard deviations and coefficients of variation showed that pixel intensities from
normal and benign tumors images are almost have the same behavior whereas the
A preventing shield for neutrons and gamma rays was designed using alternate layers of water and iron with pre-fixed dimensions in order to study the possibility of attenuating both neutrons and gamma-rays. ANISN CODE was prepared and adapted for the shield calculation using radiation doses calculation: Two groups of cross-section were used for each of neutrons and gamma-rays that rely on the one – dimensional transport equation using discrete ordinate's method, and through transforming cross-section values to values that are independent on the number of groups. The memory size required for the applied code was reduced and the results obtained were in agreement with those of standard acceptable document samples of cross –section, this a
... Show MoreWith the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi
... Show MoreCost is the essence of any production process for it is one of the requirements for the continuity of activities so as to increase the profitability of the economic unit and to support the competitive situation in the market. Therefore, there should be an overall control to reduce the cost without compromising the product quality; to achieve this, the management should have detailed credible and reliable information about the cost to be measured, collected, understood and to analyze the causes for the spread of deviations and obstacles the management faces, and to search for the factors that trigger the emergence of these deviations and obstacles
The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
... Show MoreIn this paper a two dimensional numerical simulation have been applied using
MATLAB program for generating Fraunhofer diffraction pattern from different
apertures. This pattern is applied for three types of apertures, including, circular,
square, and rectangular functions, and it's could be generated any wavelength in the
visible light. The studying demonstrated the capability and the efficiency of optical
imaging systems to observe a point source at very long distance. The circular
aperture shows better results across the shape of Fraunhofer pattern and optical
transfer function (otf). Also, the minimum values of the normalized irradiance of
different diffracted apertures have been computed at different dimension