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Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
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Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Publication Date
Mon Oct 01 2018
Journal Name
2018 International Conference On Advanced Science And Engineering (icoase)
Performance of BCH and RS Codes in MIMO System Using MPFEC Diversity Technique
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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
Using the Nudge Theory in Improving Security Policies and Crime Prevention: Integrative Review
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The "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of  Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.

The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.

The study is bas

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Investigating the Color Distribution of Young and Old Galaxies Using Observations from SDSS
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     This research aims to investigate the color distribution of a huge sample of 613654 galaxies from the Sloan Digital Sky Survey (SDSS). Those galaxies are at a redshift of 0.001 - 0.5 and have magnitudes of g = 17 - 20. Five subsamples of galaxies at redshifts of (0.001 - 0.1), (0.1 - 0.2), (0.2 - 0.3), (0.3 - 0.4) and (0.4 - 0.5) have been extracted from the main sample. The color distributions (u-g), (g-r) and (u-r) have been produced and analysed using a Matlab code for the main sample as well as all five subsamples. Then a bimodal Gaussian fit to color distributions of data that have been carried out using minimum chi-square in Microsoft Office Excel. The results showed that the color distributions of the main sample and

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Wireless Propagation Multipaths using Spectral Clustering and Three-Constraint Affinity Matrix Spectral Clustering
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This study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Simultaneous Determination of Binary Mixture of Estradiol and Progesterone Using Different Spectrophotometric Methods
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Four rapid, accurate and very simple derivative spectrophotometric techniques were developed for the quantitative determination of binary mixtures of estradiol (E2) and progesterone (PRG) formulated as a capsule. Method I is the first derivative zero-crossing technique, derivative amplitudes were detected at the zero-crossing wavelength of 239.27 and 292.51 nm for the quantification of estradiol and 249.19 nm for Progesterone. Method II is ratio subtraction, progesterone was determined at λmax 240 nm after subtraction of interference exerted by estradiol. Method III is modified amplitude subtraction, which was established using derivative spectroscopy and mathematical manipulations. Method IIII is the absorbance ratio technique, absorba

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Publication Date
Mon Aug 12 2024
Journal Name
Applied Physics A
Fabrication and characterization of visible-enhanced CeO2/Si photodetectors using pulsed laser deposition
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Nanostructured photodetectors have garnered great attention due to their enriched electronic and optical properties. In this work, we aim to fabricate a high-performance CeO2/Si photodetector by growing a CeO2 nanostructure film on a silicon substrate using the pulsed laser deposition (PLD) technique at different laser energy densities. The impact of laser energy density and the number of pulses on the morphological, optical, and electrical properties was studied. Field emission scanning electron microscopy (FESEM) results show that the CeO2 film has a spherical grain morphology with an average grain size ranging from 33 to 54 nm, depending on the laser energy density. The film deposited at various numbers of laser pulses also has spherical

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Publication Date
Sat Oct 29 2022
Journal Name
Current Trends In Geotechnical Engineering And Construction
Simulation Design and Performance of a Residential Complex Using Liquefied Petroleum Gas Network
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The population has been trying to use clean energy instead of combustion. The choice was to use liquefied petroleum gas (LPG) for domestic use, especially for cooking due to its advantages as a light gas, a lower cost, and clean energy. Residential complexes are supplied with liquefied petroleum gas for each housing unit, transported by pipes from LPG tanks to the equipment. This research aims to simulate the design and performance design of the LPG system in the building that is applied to a residential complex in Baghdad taken as a study case with eight buildings. The building has 11 floors, and each floor has four apartments. The design in this study has been done in two parts, part one is the design of an LPG system for one building, an

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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