Positron annihilation lifetime has been utilized for the first time to investigate the free - volume hole properties in thermolumenscent dosimeter ( TLD ) as a function of gamma-dosc . The hole volume, free volume fraction determined form orthopsitronium lifetime are found to be ?lamatically increase to large values , and then to minimum values as a function ofgamma-dose . The free - volume holes size is found to be 0.163nm’ and to have maximum of 0.166nm^ at the gamma-dose of 0.1 and 0.8 Gy, respectively-

The effect of different doses of gamma rays that emitted from 60Co on the development of different stages of lesser grain borer Rhyzopertha dominica (Fab.) was investigated . The results showed that the eggs in both early (1-3 days) and late (7-9) old were very sensitive to gamma rays and its hatch was zero at 10 Gy for both ages in comparison with 83.3% for the control group. Furthermore, the results illustrated that the larval stage in its two old ages were different in the radiosensitivity, the percent of its death were 100% & 96.6% when they exposed to 100 & 120 Gy, respectively. Moreover, the results showed that the sensitivity of pupal stage at age of 1-3 days was increased with increasing the doses of gamma rays, the percent of no

Background: Trigeminal neuralgia (TN), or Tic Douloureux, is one of the most common neuropathic pains. Gamma knife stereotactic radiosurgery (GNSRS) has been considered one of the procedures for treating primary TN. Objective: This study evaluates the effectiveness of GNSRS in treating primary TN in patients who are unresponsive to medical treatment in a single-center experience. Subjects and Methods: This study was conducted on 180 patients from January 2018 to October 2021. The study utilized the Barrow Neurological Institute (BNI) pain intensity score to assess pain before and after GNSRS treatment. Results: A total of 180 patients with primary TN were included in this study, 108 female with a 1.5:1 female: male ratio.  Results

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

This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc