Skin cancer is the most serious health problems in the globe because of its high occurrence compared to other types of cancer. Melanoma and non-melanoma are the two most common kinds of skin cancer. One of the most difficult problems in medical image processing is the automatic detection of skin cancer. Skin melanoma is classified as either benign or malignant based on the results of this test. Impediment due to artifacts in dermoscopic images impacts the analytic activity and decreases the precision level. In this research work, an automatic technique including segmentation and classification is proposed. Initially, pre-processing technique called DullRazor tool is used for hair removal process and semi-supervised mean-shift algorithm is used for segmenting the affected areas of skin cancer images. Finally, these segmented images are given to a deep learning classifier called Deep forest for prediction of skin cancer. The experiments are carried out on two publicly available datasets called ISIC-2019 and HAM10000 datasets for the analysis of segmentation and classification. From the outcomes, it is clearly verified that the projected model achieved better performance than the existing deep learning techniques.
In this work, the switching dynamics of a Fabry-Perot etalon were analyzed in term of effective time constant, which changes dramatically near the switching points. The switch-ON and switch-OFF have been analyzed numerically using a modified Debye dynamic equation. The method used to determine the solution of the Debye relaxation equations solved numerically to predict the behavior of the etalon for modulated input power.
In this study the Fourier Transform Infrared Spectrophotometry (FTIR) provides a quick, efficient and relatively inexpensive method for identifying and quantifying gypsum concentrations in the samples taken from different sites from different localities from Alexandria district southwest Baghdad. A comprehensive spectroscopic study of gypsum-calcite system was reported to give good results for the first time by using IR for analytical grades of gypsum (CaSO4.2H2O) and calcite (CaCO3) pure crystals. The spectral results were used to create a calibration curve relates the two minerals concentrations to the intensity (peaks) of FTIR absorbance and applies this calibration to specify gypsum and calcite concentrations in Iraqi gypsiferous soi
... Show MoreAn easy, eclectic, precise high-Performance Liquid Chromatographic (HPLC) procedure was evolved and validated to estimate of Piroxicam and Codeine phosphate. Chromatographic demarcation was accomplished on a C18 column [Use BDS Hypersil C18, 5μ, 150 x 4.6 mm] using a mobile phase of methanol: phosphate buffer (60:40, v/v, pH=2.3), the flow rate was 1.1 mL/min, UV detection was at 214 nm. System Suitability tests (SSTs) are typically performed to assess the suitability and effectiveness of the entire chromatography system. The retention time for Piroxicam was found to be 3.95 minutes and 1.46 minutes for Codeine phosphate. The evolved method has been validated through precision, limit of quantitation, specificity,
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreIraqi western desert is characterized by a widespread karst phenomenon and caves. Euphrates formation (Lower Miocene) includes enormous sinkholes and cavities within carbonate rocks that usually cause severe damages to any kind of engineering facilities built over it. 3D resistivity imaging techniques were used in detecting this kind of cavities in complicated lithology. The 3D view was fulfilled by collating seven 2D imaging lines. The 2D imaging survey was carried out by Dipole-dipole array with (n) factor and electrode spacing (a) of 6 and 2m respectively. The horizontal slices of the 3D models give a good subsurface picture. There are many caves in all directions (x, y, z). They reveal many small caves near the surface. Thes
... Show MoreIn this study, a one-dimensional model represented by Butler-Volmer-Monod (BVM) model was proposed to compute the anode overpotential and current density in a mediator-less MFC system. The system was fueled with various organic loadings of real field petroleum refinery oily sludge to optimize the favorable organic loading for biomass to operate the suggested system. The increase in each organic loading showed higher resistance to electrons transport to the anode represented by ohmic loss. On the contrary, both activation and mass transfer losses exhibited a noticeable decrement upon the increased organic loadings. However, current density was improved throughout all increased loads achieving a maximum current density of 5.2 A/m3
... Show MoreKeratin is a fibrous, insoluble structural protein that is highly cross-linked with hydrophobic, hydrogen, and disulfide bonds. Keratinases are enzymes that belong to the category of serine hydrolases that are capable of breaking down keratin. The results of the determination of the better fermentation system showed that the production of keratinase from local A.terreus A13 isolate by submerged fermentation (SmF) system was the best system to give the highest specific activity (113.4 U/mg) of keratinase compared with solid-state fermentation (SSF). The optimum conditions for keratinase production by SmF, were determined via cultivation conditions, including carbon source, nitrogen source, temperature, pH of the medium,
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