Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

ABSTRACT Background: One of the major problems of all ceramic restorations is their probable fracture against the occlusal forces. The objective of this in vitro study was to evaluate the effect of two gingival finishing lines (90°shoulder and deep chamfer) on the fracture resistance of full contour CAD/CAM and heat press all-ceramic crowns. Materials and Methods: Thirty two maxillary first premolars were prepared to receive full contour CAD/CAM (zolid) and heat press (Cergo Kiss) ceramic crowns using a special paralleling device (Parallel-A-Prep). The teeth were divided into four groups according to the type of finishing line prepared. Each crown was cemented to its corresponding tooth using self-etch, self-adhesive dual cure resin ceme

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Rock type identification is very important task in Reservoir characterization in order to constrict robust reservoir models. There are several approaches have been introduced to define the rock type in reservoirs and each approach should relate the geological and petrophysical properties, such that each rock type is proportional to a unique hydraulic flow unit. A hydraulic flow unit is a reservoir zone that is laterally and vertically has similar flow and bedding characteristics. According to effect of rock type in reservoir performance, many empirical and statistical approaches introduced.  In this paper Cluster Analysis technique is used to identify the rock groups in tertiary reservoir for Khabaz oil field by analyses variation o

     Cerium Oxide Nanoparticles (CeO₂ NPs) and β-carotene are natural-source products that have recently gained an increased interest as pharmaceutical additives because of their effectiveness in living systems, but the behavior of these substances varies according to factors and conditions. The above mentioned materials were evaluated in breast normal (HBL-100) and cancer cell lines (CAL-51 and MCF-7 ) by  different techniques ; MTT assay for studying cytotoxic effects, morphological changes, sqPCR, including gene expression of caspases 8 and 9, and P53. All experiments were conducted on cell lines by the use of the materials alone as well as their combination.                              

The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

Citrus fruits are one of the consumer agricultural products of the Iraqi citizen. It is rich in vitamins and usedin many food industries as well as medicines. Classifying the amount of production of citrus treesaccording to the producing governorates has been done to find a map that shows the production of citrustrees according to Iraqi governorates. A cluster analysis method was used according to the hierarchicalmethod. The results showed that Najaf and Qadisiyah are the most similar in citrus production, whileSaladin and Najaf were the two governorates with the furthest distance in proximity matrix. Diyalagovernorate was clustered in the first cluster within two, three, four or five of the clusters for classifyingIraqi governorates covere

      Iron deficiency is considered as a common problem facing the general world population. In the current research, experiments were conducted to evaluate the effects of aqueous extracts of Acacia senegal (Gum Arabic, GA), Spinacia oleracea (spinach), Zea mays (corn), and Capsicum annuum (red chili pepper) on iron and ferritin levels in rats. Vitamin C and fructose levels were first estimated in these plants by using High-Performance Liquid Chromatography (HPLC). The results showed that the GA extract contained the highest level of fructose (853 mg.L^-1), followed by red chili pepper (635 mg.L^-1), corn (521 mg.L^-1), and spinach (271 mg.L^-1