Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ

Water scarcity is one of the most important problems facing humanity in various fields such as economics, industry, agriculture, and tourism. This may push people to use low-quality water like industrial-wastewater. The application of some chemical compounds to get rid of heavy metals such as cadmium is an environmentally harmful approach. It is well-known that heavy metals as cadmium may induce harmful problems when present in water and invade to soil, plants and food chain of a human being. In this case, man will be forced to use the low quality water in irrigation. Application of natural materials instead of chemicals to remove cadmium from polluted water is an environmental friendly approach. Attention was drawn in this research wor

Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

With the great development in the field of the Internet, the talk about the new media and its implications began, And its interactive services have made the future of media material sometimes participating in it and manufacturing it at other times,
the public is seeking information and choosing the appropriate ones, as well as exchanging messages with the sender after what the role of the receiver is just receiving information only.
This study aims to demonstrate the effects of using digital media in various forms and types to construct the value system of Iraqi society through the identification of the following aims:
Identify the most popular digital media for the Iraqi public in their daily lives on the Internet.
Identify