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. The extraction of features gave a high distinguishability and helped GA reach the solution more accurately and faster.
In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreCancer is one of the critical health concerns. Health authorities around the world have devoted great attention to cancer and cancer causing factors to achieve control against the increasing rate of cancer. Carcinogens are the most salient factors that are accused of causing a considerable rate of cancer cases. Scientists, in different fields of knowledge, keep warning people of the imminent attack of carcinogens which are surrounding people in the environment and may launch their attack at any moment. The present paper aims to investigate the linguistic construction of the imminent carcinogen attack in English and Arabic scientific discourse. Such an investigation contributes to enhancing the scientists’ awareness of the linguistic co
... Show MoreNew ligands, N1, N4-bis (benzo[d]thiazol-2- ylcarbamothioyl) succinamide (L1) and N1, N4- bis (benzylcarbamothioyl)succinamide (L2), derived from succinyl chloride and 2-amino benzothiazole or benzylamine, respectively, have been used to prepare a set of transition metal complexes with the general formula [M2(L)Cl4], where L=L1 or L2, M = Mn(II), Ni(II), Cu(II), Cd(II), Co(II), Zn(II) or Hg(II). The synthesized compounds were characterized using various analytical techniques including TGA, 13C NMR, mass spectroscopy, 1H and Fourier-transform infrared (FTIR) spectroscopy, magnetic measurement, molar conductivity, electronic spectrum, (%M, %C, %H, %N) and atomic absorption flame (AAF) analysis. The results showed that (L1, L2) bin
... Show MoreCleft / palate is one of the common congenital deformities in craniofacial region, associated with different types of dental anomalies like (Tooth agenesis, impaction, and supernumerary teeth) with marked changes in palatal dimensions. This study aimed to determine the prevalence of teeth agenesis and dental anomalies in cleft lip/palate patients using CBCT, and to compare the palatal dimension of cleft group with control subjects. Twenty-eight cleft cases collected during the period from 2015 to 2022, CBCT images evaluated, the study sample classified into two groups (14 bilateral and 14 unilateral cleft lip/palate) and the non-cleft control group (14 CBCT images). The presence of dental anomalies was assessed in relation to clef
... Show MoreThe performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD). In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc
... Show MoreThis study designed to prepare ultrafine apixaban (APX) o/w nanoemulsion (NE) based gel with droplet size below 50 nm as a good method for transdermal APX delivery without using permeation enhancer, alternatively, the formulation components itself act as permeation enhancer. APX, a potent oral anticoagulant drug that selectively and directly inhibit coagulation factor Xa, was selected as a good candidate for transdermal delivery as it displays poor water solubility (0.028 mg/mL) and low bioavailability (50%). APX-NE gel was prepared using triacetin, triton-x-100 and carbitol as oil phase, surfactant and cosurfactant respectively, while Carbopol 940 used as a gelling agent. Ex vivo permeation of APX-NE gel through human stratum c
... Show MoreSymmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand
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