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

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

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

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

Image retrieval is an active research area in image processing, pattern recognition, and
computer vision. In this proposed method, there are two techniques to extract the feature
vector, the first one is applying the transformed algorithm on the whole image and the second
is to divide the image into four blocks and then applying the transform algorithm on each part
of the image. In each technique there are three transform algorithm that have been applied
(DCT, Walsh Transform, and Kekre’s Wavelet Transform) then finding the similarity and
indexing the images, useing the correlation between feature vector of the query image and
images in database. The retrieved method depends on higher indexing number. <

The current research aims to measure the level of entrepreneurial orientation and its dimensions (creativity, independence, proactivity, risk tolerance, and achievement) in the National Security Chancellery, as its importance and role in guiding senior leaders of the chancellery to make strategic decisions with high quality in various Iraqi concerns, more specifically the security aspect. The data was collected from 94 individuals (the research sample) from the research community (120) individuals at different administrative levels and intentionally where the questionnaire was adopted as a main tool for data collection and the primary data was analyzed through descriptive and inferential statistical methods (arithmetic mean, standard dev

The current research aims to determine the intellectual security and the psychological resilience of Secondary school students and how these two variables are related to each other. The study also seeks the extent to which psychological resilience contributes to intellectual security

The research sample consisted of (420) students from the Secondary stage in the Directorate of Education of Baghdad / Rusafa III. Two scales were administered to the participants to collect the needed data. As for the analysis of data, Pearson correlation coefficient, T-test, and the Regression analysis were employed, the results revealed:

1. The members of the sample have an intellectual Security.
2. The members of the sample have

In this investigation, Rayleigh–Ritz method is used to calculate the natural frequencies of rectangular isotropic and laminated symmetric and anti-symmetric cross and angle ply composite plate with general elastic supports along its edges. Each of the admissible functions here is composed of a trigonometric function and an arbitrary continuous function that is introduced to ensure the sufficient smoothness of the so-called residual displacement function at the edges. Perhaps more importantly, this study has developed a general approach for deriving a complete set of admissible functions that can be applied to various boundary conditions. Several numerical examples are studied to demonstrate the accuracy and convergence of the current s