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Image Feature Extraction and Selection
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Features are the description of the image contents which could be corner, blob or edge. Scale-Invariant Feature Transform (SIFT) extraction and description patent algorithm used widely in computer vision, it is fragmented to four main stages. This paper introduces image feature extraction using SIFT and chooses the most descriptive features among them by blurring image using Gaussian function and implementing Otsu segmentation algorithm on image, then applying Scale-Invariant Feature Transform feature extraction algorithm on segmented portions. On the other hand the SIFT feature extraction algorithm preceded by gray image normalization and binary thresholding as another preprocessing step. SIFT is a strong algorithm and gives more accurate results but when system require increasing speed, it is better to select distinctive features and use them in description process. The experimental results show clearly reduction of features extracted using SIFT algorithm on segmented parts and the algorithm of feature extraction from normalized binary image gives better results for feature localization as shown in experimental images.

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Construction Engineering And Management
Integrating Worker Health and Safety into Sustainable Design and Construction: Designer and Constructor Perspectives
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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
Integrated Geophysical Data and GIS Technique to Forecast the Potential Groundwater Locations in Part of South Eastern Nigeria
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     The objective of this research is to select the most suitable drilling location of new groundwater exploration wells, with a decision-making tool from Geographic Information System (GIS). The optimum location will be evaluated base on the hydro-geoelectrical parameter derived from Vertical Electrical Sound (VES) including Longitudinal Conductance, the thickness of the aquifer, the apparent resistivity and Transmissivity. From the Geo-electrical method (VES) the finds shows that the aquifers in the study area have Apparent Resistivity ranging from 0.32 to 40.24 Ωm, Thickness between 0.21 m to 15.06 m, Longitudinal Conductance ranging from 0.006 to 10.246Ω-1 and Transmissivity ranging from 0.14 to

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Publication Date
Mon Dec 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
NATURE OF VARIABILITY OF CANDAHARIA LEVANDERI (SIMROTH, 1902) IN THE FERGHANA AND SURKHAN - SHERABAD VALLEYS, UZBEKISTAN
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The variability of Candaharia levanderi (Simroth, 1902)(Gastropoda, Stylommatophora, Parmacellidae) in two biotopes (southern and northern slopes, the Kampirtepa gorges, the Kugitang Tau ridge) has been investigated using polymerase chain reaction (PCR) with the implementation of primers, the 18S DNA of the region is amplified, the variability (sharply differing in color) of two populations of C. levanderi is studied .
The first population is in the suburbs of Namangan, (Namangan Region); the second population is in Kampirtepa gorges, Kugitang Tau ridge (Surkhandarya Region). It is established that, most often, the variability of morphological signs is observed on the coloration of mollusks. The development of body coloration is an ad

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Studying the Classification of Texture Images by K-Means of Co-Occurrence Matrix and Confusion Matrix
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In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

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Publication Date
Sat Feb 01 2025
Journal Name
Al–bahith Al–a'alami
Conflict and Integration between New and Traditional Media
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The new media scene reveals that the unprecedented overlap of a number of technical, economic, and political factors has made the new media a very complicated issue; and the focus of specialized and public debates about its impact on traditional means of communication and forms of social media and social relations. Then, the same scene discloses the reality of the relationship between the new and the traditional. These are the axes that will be will be discussed in this study.

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Publication Date
Fri Dec 30 2022
Journal Name
مجلة نسق
Honoring Parents and Relatives Between Christianity and Islam
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Both religions have urged (honoring parents and kin) through the texts that came in their original sources, as honoring parents means showing respect to them In word and deed, and carrying in our hearts an appreciation for their status, and God commands to honor parents; Becausee this is Important in the eyes of God that he includeincludeed it in the Ten Commandmen.

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Educational And Psychological Researches
Rivalry and bargaining between governmental and private kindergarteners
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The study aims to identify the bargaining differences between the governmental and private kindergarteners; the rivalry differences between the governmental and private kindergarteners; the rivalry and bargaining differences among private kindergarteners; and the rivalry and bargaining differences among governmental kindergarteners. The researchers had raised a question; is there any difference of rivalry and bargaining between governmental and private kindergarteners?. A total of (150) kindergarteners ranged from 5 to 6 years old, (90) student from governmental kindergarten and (60) student from private kindergarten, were selected as a sample of this study. Fifteen governmental and private kindergarten were chosen from al-rasafa directo

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Publication Date
Thu Jan 17 2019
Journal Name
Plant Archives
EFFECT OF ANTI-STRESS ON THE GROWTH AND YIELD OF SWEET AND HOT PEPPERS AND ITS CONTENT OF PEROXIDASE AND IAA
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MS Elias, RGM AL-helfy, Plant Archives, 2019

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Publication Date
Sun Apr 01 2018
Journal Name
Research Journal Of Pharmaceutical, Biological And Chemical
Synthesis and characterization of azo dyes ligands complexes with Ni (II) and Cu (II) and studies their industrial and bacterial application
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1-[4-(4-Acetyl-2-hydroxy-phenylazo)-phenyl]-ethanone (L1) and 1-[3-Hydroxy-4(4-nitro-phenylazo)-phenyl]-ethanone (L2) were readied by combination the diazonium salts of amines with 3-hydroxyacetophenone. (C.H.N) analyses, infrared spectra, UV–vis electronic absorption spectra, 1H and 13CNMR spectral mechanisms are use to identified of the ligands. Complexes of Ni+2 and Cu+2 were performed as well depicted. The formation of complexes has been identified by using atomic absorption of flame, elemental analysis, infrared spectra and UV-Vis spectral process as well conductivity and magnetic quantifications. Nature of compounds produced have been studied obeyed the mole ratio and continuous contrast methods, Beer's law followed during a concent

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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