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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 Two cases or two steps (two different angles and for the same number of classes). The agreement percentage between the classification results and the various methods was calculated.

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Wed Oct 26 2022
Journal Name
Membranes
Classification of Nanomaterials and the Effect of Graphene Oxide (GO) and Recently Developed Nanoparticles on the Ultrafiltration Membrane and Their Applications: A Review
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The emergence of mixed matrix membranes (MMMs) or nanocomposite membranes embedded with inorganic nanoparticles (NPs) has opened up a possibility for developing different polymeric membranes with improved physicochemical properties, mechanical properties and performance for resolving environmental and energy-effective water purification. This paper presents an overview of the effects of different hydrophilic nanomaterials, including mineral nanomaterials (e.g., silicon dioxide (SiO2) and zeolite), metals oxide (e.g., copper oxide (CuO), zirconium dioxide (ZrO2), zinc oxide (ZnO), antimony tin oxide (ATO), iron (III) oxide (Fe2O3) and tungsten oxide (WOX)), two-dimensional transition (e.g., MXene), metal–organic framework (MOFs), c

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Publication Date
Thu Mar 30 2023
Journal Name
Optics Continuum
Ultrafast lithium disilicate veneer debonding time assisted by a CO<sub>2</sub> laser with temperature control
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We report on using a CO2 (10.6 µm) laser to debond the lithium disilicate veneers. Sixty-four sound human premolar teeth and 64 veneer specimens were used in the study. The zigzag movement via CO2 laser handpiece along with an air-cooled jet to prevent temperature elevation above the necrosis temperature limit (5.5 C°) was applied. The optimal deboning irradiation time was super-fast, at about 5 seconds at 3 Watt CO2 laser power. It is 20 times less than any previously published work for veneers debonding. The enamel beneath the debonded veneers has been assessed by atomic force microscopy (AFM) and shear stress technique as criteria for the easiness of debonding. The

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Publication Date
Wed Aug 10 2022
Journal Name
Ibero-american Journal Of Exercise And Sports Psychology
The impact of applying the K-W-L self-scheduling technique on first-year intermediate students' learning of basic volleyball skills
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The impact of applying the K-W-L self-scheduling technique on first-year intermediate students' learning of basic volleyball skills, Ayad Ali Hussein*, Israa Fouad Salih

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Publication Date
Sun Jan 02 2022
Journal Name
Eurasian Chemical Communicaions
Modification and characterization of subs. triazole on creatinine and studying their antioxidant activity.
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Publication Date
Thu Mar 01 2018
Journal Name
2018 International Conference On Computing Sciences And Engineering (iccse)
Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler

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Publication Date
Sun Jan 01 2017
Journal Name
Rsc Advances
Investigation of the post-annealing electromagnetic response of Cu–Co oxide coatings via optical measurement and computational modelling
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The annealing temperature (200–500 °C) effects of optical frequency response on the dielectric functions of sol–gel derived CuCoOx thin film coatings: experimental and modelling.

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Publication Date
Wed Apr 05 2023
Journal Name
Journal Of Agriculture And Crops
Distribution and Classification of Medicinal Plants in Zakhikhah Area of Al-Anbar Desert
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This study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in t

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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