This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

 

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

       Nanometal oxides were extracted from cement factories wastes and were employed to proliferate skin cancer cells using MTT (Methyl Thiazolyl Tetraolium) assay. MTT assay results for skin cancer cell line A375,for CaO NPs the best concentration was 200 μg/mL,The viability was reduced to 57.28% while the IC₅₀ was (69.66) g/mL for A375 and normal cell WRL68 was significantly higher (231.2 g/mL). The cytotoxicity results of CaO: MgO: Fe₂O₃ NPs, at higher concentrations (200 and 400) μg/mL showed a significant difference. The IC₅₀ was (106.4) μg/mL for A375and normal cell WRL68 was significantly higher (173.3) μg/ml CaO:MgO:Fe₂O₃ NPs. The nanometal oxides, calci

At present, the ability to promote national economy by adjusting to political, economic, and technological variables is one of the largest challenges faced by organization productivity. This challenge prompts changes in structure and line productivity, given that cash has not been invested. Thus, the management searches for investment opportunities that have achieved the optimum value of the annual increases in total output value of the production line workers in the laboratory. Therefore, the application of dynamic programming model is adopted in this study by addressing the division of investment expenditures to cope with market-dumping policy and to strive non-stop production at work.

Objective: to assess the awareness and knowledge of our medical students regarding dose levels of imaging procedures and radiation safety issues, and to conclude how the curriculum of clinical radiology in the college medical program impacts such knowledge.

Subjects and methods:  this is a cross-sectional study conducted among 150 medical students in Alkindy College of Medicine between January 2021 to July 2021, regardless of their age or gender. The study included six grades according to the year 2020-2021. A questionnaire consisting of 12 multiple-choice questions was conducted via an online survey using Google Forms. The questions were divided into two parts

This study aims to assess the suitability of the sediments present in Tigris River, Tikrit city, northern Iraq for concrete production and road building purposes. Representative samples were collected from three selected stations at the study area using the channel modeling method. According to the grain size analysis, the sediments were classified as a type of poorly graded gravels (GP) depending on the unified soil classification system. The true specific gravity of the soil ranged between 2.28 and 2.568. The chemical analysis of the study samples revealed that gypsum content ranged between 0.82 and 1.69 %. Total soluble salts ranged 2.45- 3.87%, the organic matter content ranged 0.14- 0.76%, and the pH value was between 7.73 and 7.38%