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

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

      This work is an experimental study about the effects of gas pressure and magnetic field on plasma characteristics produced in an internal hollow electrodes discharge (HED) system. The results show that the breakdown voltage values increase with increasing the working pressure (especially with the presence of a magnetic field). The breakdown voltage depends on the p.d. product, where p is the gas pressure and d is the distance between the electrodes. While the values of current discharge decrease with the increase of the working pressure. The temperature of electron and the number density of electron are calculated from the Boltzmann method and the broadening of Stark, respectively. The results showed that the electron number d

In this paper, a discrete- time ratio-dependent prey- predator model is proposed and analyzed. All possible fixed points have been obtained. The local stability conditions for these fixed points have been established. The global stability of the proposed system is investigated numerically. Bifurcation diagrams as a function of growth rate of the prey species are drawn. It is observed that the proposed system has rich dynamics including chaos.

Production sites suffer from idle in marketing of their products because of the lack in the efficient systems that analyze and track the evaluation of customers to products; therefore some products remain untargeted despite their good quality. This research aims to build a modest model intended to take two aspects into considerations. The first aspect is diagnosing dependable users on the site depending on the number of products evaluated and the user's positive impact on rating. The second aspect is diagnosing products with low weights (unknown) to be generated and recommended to users depending on logarithm equation and the number of co-rated users. Collaborative filtering is one of the most knowledge discovery techniques used positive

The article approaches the characteristics of Russian literature in the time of Khrushchev or the "thaw" period a very short period of Soviet history, characterized by the easing of the dictatorship of power and relaxation in various areas of people's lives. The interest in the research is focused on the importance of interpreting the family portrait in a short but distinct period in the development of Russian/Soviet literature. The research material is the story of Sholokhov's “The Fate of Man” 1956, the story of Panova “Serioga” 1955, and Abramov’s story “Fatherless” 1961. В статье рассматриваются особенности художественной литературы периода хруще

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This study aims to examine the main features of the new trends in agenda studies using the secondary analytic approach in analyzing the newest studies in agenda-setting issues from 2007 till 2017, in addition to the quantitative approach.
The researcher has analyzed 110 studies -75 foreign and 35 Arabic - to determine, describe and evaluate the key research trends which came in Arabic and foreign agenda-setting studies. The results confirmed that studies of the agenda theory are increasing steadily worldwide with diversity in the theoretical trends and used research tools. In addition, primary studies focus on content analysis and the survey approach (method). Also, most Arabic agenda-setting studies used the traditional methods and k

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s