Steady conjugate natural convection heat transfers in a two-dimensional enclosure filled with fluid saturated porous medium is studied numerically. The two vertical boundaries of the enclosure are kept isothermally at same temperature, the horizontal upper wall is adiabatic, and the horizontal lower wall is partially heated. The Darcy extended Brinkman Forcheimer model is used as the momentum equation and Ansys Fluent software is utilized to solve the governing equations. Rayleigh number (1.38 ≤ Ra ≤ 2.32), Darcy number (3.9 * 10-8), the ratio of conjugate wall thickness to its height (0.025 ≤ W ≤ 0.1), heater length to the bottom wall ratio (1/4 ≤  ≤ 3/4) and inclination angle (0°, 30° and 60°) are the main consid

The current study is the identification and isolation dermatophyte species in clinical isolates by both Sabouraud’s Dextrose Agar (SDA) and on Dermatophyte Test Medium (DTM). Clinical specimens of hair, nails and skin scales were collected from patients with dermatophytosis and submitted to direct microscopic examination after immersion in 20% of potassium hydroxide solution. The clinical specimens were cultured on SDA containing chloramphenicol and cycloheximide, and on DTM. Tinea corporis showed the highest prevalent dermatophyte infection among patients (26.7%), followed by Tinea pedis (23.3%), whereas Tinea manuum exhibited the lowest fungal infection (6.7 %). Rural areas revealed the highest prevalence of dermatophyte in

Digital image started to including in various fields like, physics science, computer science, engineering science, chemistry science, biology science and medication science, to get from it some important information. But any images acquired by optical or electronic means is likely to be degraded by the sensing environment. In this paper, we will study and derive Iterative Tikhonov-Miller filter and Wiener filter by using criterion function. Then use the filters to restore the degraded image and show the Iterative Tikhonov-Miller filter has better performance when increasing the number of iteration To a certain limit then, the performs will be decrease. The performance of Iterative Tikhonov-Miller filter has better performance for less de

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca