Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

Abstract

Stainless steel (AISI 304) has good electrical and thermal conductivities, good corrosion resistance at ambient temperature, apart from these it is cheap and abundantly available; but has good mechanical properties such as hardness. To improve the  hardness and corrosion resistance of stainless steel its surface can be modified by developing nanocomposite coatings applied on its surface. The main objective of this paper is to study effect of electroco-deposition method on microhardness and corrosion resistance of stainless steel, and to analyze effect of nanoparticles (Al₂O₃, ZrO₂ , and SiC)  on properties of composite coatings. I

Risperidone is an atypical antipsychotic drug that is used for treating schizophrenia, bipolar mania, and autism. Risperidone rebalances dopamine and serotonin to improve thinking, mood, and behavior by working on dopamine and serotonin α₂receptor antagonism. Risperidone has poor solubility and high permeability through the intestine, so it belongs to Biopharmaceutical Classification System (BCS) class II exhibits poor oral biopharmaceutical properties.

 The aim of the present work was to improve solubility and dissolution of Risperidone by preparing nanosuspension using different stabilizers and different solvents‎ in a method known as solvent-antisolvent precipitation method.  Twenty-eight formulas were prepared

The precipitation of calcite induced via microorganisms (MICP) is a technique that has been developed as an innovative sustainable ground improvement method utilizing ureolytic bacteria to soil strengthening and stabilization. Locally isolated Bacillus Sonorensis from Iraqi soil samples were found to have high abilities in producing urease. This study aims to use the MICP technique in improving the undrained shear strength of soft clay soil using two native urease producing bacteria that help in the precipitation of calcite to increase the cementation between soil particles. Three concentrations of each of the locally prepared Bacillus sonorensis are used in this study for cementation reagent (0.25M, 0.5M, and 1M) during

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th

The current study aimed to standardize the multi-position suicidal tendency scale MAST in the Saudi environment as well as to assess suicidal tendencies in adolescents. Moreover, the study aimed to test the psychometric characteristics of the scale among a sample of (490) high school and undergraduate students, in the adolescence who ranging in age from (16-21) years. The scale demonstrated satisfactory internal consistency in terms of validity and reliability tests. as the results showed of exploratory factor analysis to the four dimensions of suicidal tendencies loading on two factors that accommodate 74.60% of the overall variance of the scale (1) the attitude toward life,  and absorbs 43, 20% of the total variance of the scale,

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.