Human skin detection, which usually performed before image processing, is the method of discovering skin-colored pixels and regions that may be of human faces or limbs in videos or photos. Many computer vision approaches have been developed for skin detection. A skin detector usually transforms a given pixel into a suitable color space and then uses a skin classifier to mark the pixel as a skin or a non-skin pixel. A skin classifier explains the decision boundary of the class of a skin color in the color space based on skin-colored pixels. The purpose of this research is to build a skin detection system that will distinguish between skin and non-skin pixels in colored still pictures. This performed by introducing a metric that measu

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

Five samples of the ternary alloy Ge-S-Cd were created using the melting point method, and the effects of partially substituting cadmium for germanium were determined. and partial substitution of germanium by cadmium was used to study the change in electrical conductivity. Electrical experiments were performed on Ge_35-xS₆₅Cd_xternary alloy with x = 0, 5, 10, 15, and 20. It was discovered that the conductivity (σ_dc) rises with rising temperature in all samples under experiment. This confirms that the samples have semiconductor behavior. It has been observed that there are three regions of electrical conductivity in the electrical conductivity curve at low, moderate, and high temperatures. The pr

    In this paper we introduce a brief review about Box-Jenkins models. The acronym ARIMA stands for “autoregressive integrated moving average”. It is a good method to forecast for stationary and non stationary time series. According to the data which obtained from Baghdad Water Authority, we are modelling two series, the first one about pure water consumption and the second about the number of participants. Then we determine an optimal model by depending on choosing minimum MSE as criterion.

This study aims to develop a recommendation engine methodology to enhance the model’s effectiveness and efficiency. The proposed model is commonly used to assign or propose a limited number of developers with the required skills and expertise to address and resolve a bug report. Managing collections within bug repositories is the responsibility of software engineers in addressing specific defects. Identifying the optimal allocation of personnel to activities is challenging when dealing with software defects, which necessitates a substantial workforce of developers. Analyzing new scientific methodologies to enhance comprehension of the results is the purpose of this analysis. Additionally, developer priorities were discussed, especially th

Isradipine belong to dihydropyridine (DHP) class of calcium channel blockers (CCBs). It is  used in the treatment of hypertension, angina pectoris, in addition to Parkinson disease. It goes under the BCS class II drug (low solubility-high permeability). The drug will experience extensive first-pass metabolism in liver, therefore, oral bio-availability will be approximately15 to 24 %.

 The aim of this study was to formulate and optimize a stable  nanoparticles of a highly hydrophobic drug, isradipine by anti-solvent microprecipitation Method to achieve the higher in vitro dissolution rate, so that it will be absorbed by intestinal lymphatic transport in order to avoid hepatic first-pass metabolism&nbs

Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu