A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

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

Background: Selenium-73 with half- life of 7.15 hour emits β+ in nature and has six stable isotopes which are ( 74Se,76Se,77Se,78Se,80Se and 82Se ). Selenium-73 has many applications in technology and radioselenium compounds of metallic have found various applications in medicine. Objective:  To make a comparison between different reactions that produced cross sections of Se-73 radioisotopes. Subjects and methods: The feasibility of the production of Selenium -73 via various nuclear reactions was investigated. Excitation functions of 73Se production by the reactions of 75As (p,3n), 169Tm( d,x), 74Se, natSe, natBr (p,x) , 75As (d,4n), natGe (3He,x), 70Ge (α, n), and 72Ge (α, 3n) and neutron capture were calculated using the avail

Background: Selenium-73 with half- life of 7.15 hour emits β⁺ in nature and has six stable isotopes which are ( ⁷⁴Se,⁷⁶Se,⁷⁷Se,⁷⁸Se,⁸⁰Se and ⁸²Se ). Selenium-73 has many applications in technology and radioselenium compounds of metallic have found various applications in medicine.

Objective:  To make a comparison between different reactions that produced cross sections of Se-73 radioisotopes.

Subjects and methods: The feasibility of the production of Selenium -73 via various nuclear reactions was investigated. Excitation functions of ⁷³Se production by the re

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

It is often noted that disordered materials have different chemical properties to their more “ordered” cousins. Quantifying these effects in terms of thermodynamics is challenging in part because disordered materials can be difficult to characterize and are frequently relatively unstable. During the course of our experiments to understand the effects of disorder in catalysts for water oxidation we observed that many disordered manganese and cobalt oxide water oxidation catalysts directly oxidized peroxide in contrast to their more ordered analogues which catalyzed its disproportionation, that is, MnO2+2H+ +H2O2! Mn2+ +2H2O+O2(oxidation) versus H2O2!H2O+1=2 O2(disproportionation). By measuring the efficiency for one reaction over the oth