Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOMs). Therefore, finding a fast PET classification method that accurately classify image pattern is crucial. To this end, this paper proposes a new scheme for accurate and fast image pattern classification using an efficient DOM. To reduce the computational complexity of feature extraction, an election mechanism is proposed to reduce the number of processed block patterns. In addition, support vector machine is used to classify the extracted features for different block patterns. The proposed scheme is evaluated by comparing the accuracy of the proposed method with the accuracy achieved by state-of-the-art methods. In addition, we compare the performance of the proposed method based on different DOMs to get the robust one. The results show that the proposed method achieves the highest classification accuracy compared with the existing methods in all the scenarios considered.
The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH4) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH4) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH4VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH4 were in 2003 while the maximum values were in 2016. The vertical distribution of CH4<
... Show MoreD-mannose sugar was used to prepare [benzoic acid 6-formyl-2, 2-dimethyl-tetrahydrofuro [3, 4-d][1, 3] dioxol-4-yl ester](compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption AA,(FT-IR),(UV-Vis), TLC, ES mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol),(metal: ligand: 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2 [M2 (L)(HA) 2] where M= Co (II), Ni (II), Cu (II) and Cd (II). These complexes were characterized by eleme
... Show MoreD-mannose sugar was used to prepare [benzoic acid 6-formyl-2,2-dimethyl-tetrahydrofuro[3,4-d][1,3]dioxol-4-yl ester] (compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption A.A, (FT-I.R.), (U.V.-Vis), TLC, E.S. mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol), (metal : ligand : 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2[M2(L)(HA)2] where M= Co(II), Ni(II), Cu(II) and Cd(II). These complexes were characterized by elem
... Show MoreIn recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
... Show MoreThe density functional B3LYP is used to investigate the effect of decorating the silver (Ag) atom on the sensing capability of an AlN nanotube (AlN-NT) in detecting thiophosgene (TP). There is a weak interaction between the pristine AlN-NT and TP with the sensing response (SR) of approximately 9.4. Decoration of the Ag atom into the structure of AlN-NT causes the adsorption energy of TP to decrease from − 6.2 to − 22.5 kcal/mol. Also, the corresponding SR increases significantly to 100.5. Moreover, the recovery time when TP is desorbed from the surface of the Ag-decorated AlN-NT (Ag@AlN-NT) is short, i.e., 24.9 s. The results show that Ag@AlN-NT can selectively detect TP among other gases, such as N2, O2, CO2, CO, and H2O.
Background: Chronic periodontitis defined as “an infectious inflammatory disease within supporting tissues of the teeth, progressive attachment loss and bone loss". Aggressive periodontitis is rare which in most cases manifest themselves clinically during youth. It characterized by rapid rate of disease progression .Pro-inflammatory chemokines organized inflammatory responses. Granulocyte chemotactic protein 2 is involved in neutrophil gathering and movement. The purpose of the study is to detect serum of Granulocyte Chemotactic Protein 2 and correlate to periodontal condition in patients with chronic periodontitis, Aggressive periodontitis and Healthy Control subjects and measurement the count of neutrophils for the studied groups. S
... Show MoreMany carbonate reservoirs in the world show a tilted in originally oil-water contact (OOWC) which requires a special consideration in the selection of the capillary pressure curves and an understanding of reservoir fluids distribution while initializing the reservoir simulation models.
An analytical model for predicting the capillary pressure across the interface that separates two immiscible fluids was derived from reservoir pressure transient analysis. The model reflected the entire interaction between the reservoir-aquifer fluids and rock properties measured under downhole reservoir conditions.
This model retained the natural coupling of oil reservoirs with the aquifer zone and treated them as an explicit-region composite system
Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio