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.
This paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. T
The development of better tools for diagnosis and more accurate prognosis of cancer includes the search for biomarkers; molecules whose presence, absence or change in quantity or structure is associated with a particular tumour or prognosis/therapeutic outcome. While biomarkers need not be functionally relevant, if cell survival, then they could also provide new targets for therapeutic drugs. In recent years attention has been applied to a group of proteins known as cancer testis antigens (CT antigens) [1]. These proteins are products of genes whose expression was normally confined to the testis, yet they are expressed in tumour cells. CT genes are bound to serve a wide array of roles in the testes, which have many highly differentiated cel
... Show MoreThe kinetics of removing cadmium from aqueous solutions was studied using a bio-electrochemical reactor with a packed bed rotating cylindrical cathode. The effect of applied voltage, initial concentration of cadmium, cathode rotation speed, and pH on the reaction rate constant (k) was studied. The results showed that the cathodic deposition occurred under the control of mass transfer for all applied voltage values used in this research. Accordingly, the relationship between logarithmic concentration gradient with time can be represented by a first-order kinetic rate equation. It was found that the rate constant (k) depends on the applied voltage, the initial cadmium concentration, the pH and the rotational speed of cathode. It
... Show MoreThe density-velocity relation is an important tool used to predict one of these two parameters from the other. A new empirical density –velocity equation was derived in Kf-4 well at Kifl Oil Field, south of Iraq. The density was derived from Gardner equation and the results obtained were compared with the density log (ROHB) in Kl-4 well. The petrophysical analysis was used to predict the variations in lithology of Yamama Formation depending on the well logs data, such as density, gamma, and neutron logs. The physical analysis of rocks depended on the density, Vp, and Vs values to estimate the elastic parameters, i.e. acoustic impedance (AI) and Vp/Vs ratio, to predict the lithology and hydrocarbon i
... Show MoreBackground: Thyroid cancer (TC) is an increasingly prevalent malignancy throughout the world. It has long been recognized that the incidence of TC is higher in women which increases with age. However, the association of gender disparity and age with TC aggressiveness and outcomes are still controversial. The aim of this study was focused on the association of age and gender with histopathological characteristics in TC. Methods: 153 patients who met the criteria, were selected. The included cases were divided into four age groups (≤24 years, 25-44 years, 45-64 years, and ≥65 years). Demographic, age and pathological parameters were compared among them. The association of gender and age with
... Show MoreThe present paper addresses cultivation of Chlorella vulgaris microalgae using airlift photobioreactor that sparged with 5% CO 2 /air. The experimental data were compared with that obtained from bioreactor aerated with air and unsparged bioreactor. The results showed that the concentration of biomass is 0.36 g l -1 in sparged bioreactor with CO2/air, while, the concentration of biomass reached to 0.069 g l -1 in the unsparged bioreactor. They showed also that aerated ioreactor.with CO2/air gives more biomass production even the bioreactor was aerated with air. This study proved that application of sparging system for ultivation of Chlorella vulgaris microalgae using either CO2/air mixture or air has a significant
... Show MoreCoronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models
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