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bsj-3823
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The second level is features extraction which extracts features from the infected area based on hybrid features: grey level run length matrix and 1st order histogram based features. The attributes that extracted from second level are utilized in third level using FFNN to perform the classification process. The proposed framework is applied to database with different backgrounds, totally 120 color potato images, (80) samples used in training the network and the rest samples (40) used for testing. The proposed PDCNN framework is very effective in classifying four types of potato tubers diseases with 91.3% of efficiency.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
A Comparison between Ericson's Formulae Results and Experimental Data Using New Formulae of Single Particle Level Density
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The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
DNA Methylation Patterns of Interferon Gamma Gene Promoter and Serum Level in Pulmonary Tuberculosis: Their Role in Prognosis
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Tuberculosis (TB) still remains an important medical problem due to high levels of morbidity and mortality worldwide. A series of innate immune mechanisms that create a cytokine network control the pathogenesis of tuberculosis and this response has the capacity to modify the host genomic DNA structure through epigenetic mechanisms such as DNA methylation which could constantly alter the local gene expression pattern that can modulate the metabolism of the tissues and the immune-response. Interferon-gamma (IFN-γ) is an important pro-inflammatory cytokine regulator of the innate immune response to TB. This study aims to determine DNA methylation patterns of INF-γ gene promoter and measure serum IFN- γ level in newly diagnosed TB patient

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Publication Date
Fri Dec 15 2023
Journal Name
Iraqi Journal Of Laser
The Effect of Dual Diode Laser: (810,980) nm in Acceleration of Orthodontic Tooth Movement A Case Report
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Patients are very concerned about the lengthy nature of orthodontic treatment. It is necessary to find a non-invasive way to quicken physiologic tooth movement. This study's objective was to assess the effectiveness of low-intensity laser therapy in shortening the time and discomfort of orthodontic treatment. Experimental work: Using a split-mouth study to compare tooth movement with conventional treatment and laser-accelerated orthodontic tooth movement. A patient presenting with a class II division I malocclusion characterized by the misalignment of the upper and lower teeth as classified by Angle’s molar classification system was indicated to undergo fixed orthodontic appliance orthodontic treatment. The treatment plan involved bila

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Publication Date
Sun Oct 01 2017
Journal Name
Diyala Journal For Pure Science
Employing difference technique in some Liu estimators to semiparametric regression model
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Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With 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

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Buckling Analysis of Stiffened and Unstiffened Laminated Composite Plates
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The present study focused mainly on the analysis of stiffened and unstiffened composite laminated plates subjected to buckling load. Analytical, numerical and experimental analysis for different cases has been considered. The experimental investigation is to manufacture the laminates and to find mechanical properties of glass-polyester such as longitudinal, transverse young modulus, shear modulus. The compressive test was carried to find the critical buckling load of plate. The design parameters of the laminates such as aspect ratio, thickness ratio, boundary conditions and number of stiffeners were investigated using high order shear deformation theory (HOST) and Finite element coded by ANSYS .The main conclusion was the buckling load c

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Publication Date
Sat Dec 01 2012
Journal Name
International Journal Of Contemporary Mathematical Sciences
Approximation by Convex Polynomials in Weighted Spaces
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Here, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity

Publication Date
Wed Mar 01 2023
Journal Name
Iranian Journal Of Materials Science And Engineering
First-Principles Analysis of Cr-Doped SrTiO3 Perovskite as Optoelectronic Materials
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The influence of Cr3+ doping on the ground state properties of SrTiO3 perovskite was evaluated using GGA-PBE approximation. Computational modeling results infered an agreement with the previously published literature. The modification of electronic structure and optical properties due to Cr3+ introducing into SrTiO3 were investigated. Structural parameters assumed that Cr3+ doping alters the electronic structures of SrTiO3 by shifting the conduction band through lower energies for the Sr and Ti sites. Besides, results showed that the band gap was reduced by approximately 50% when presenting one Cr3+ atom into the SrTiO3 system and particularly positioned at Sr sites. Interestingly, substituting Ti site by Cr3+ led to eliminating the band ga

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Publication Date
Tue Jun 14 2022
Journal Name
Al-academy
Visual stimulus in the design of interior spaces
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The visual stimulus is the effective force in visual attraction that achieves visual and perceptual co-optation and is important in wooing the recipient, and many procedural processes in the design are interpreted on it as the visual stimulus achieves visual comfort and a sense of pleasure and gives (place) the interior space a transformation in its plastic structure as well as arousing attention through The kinetic rhythm and the formal diversity, which increases the possibility of breaking the routine and traditional constraints of design patterns through the coating and encapsulation of the vertical and horizontal levels . Thus, the research problem was launched based on the following question: What are the stimuli of the visual stimu

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