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.

The contemporary business environment is witnessing increasing calls for modifications to the traditional cost system, and a trend towards adopting cost management techniques to provide appropriate financial and non-financial information for senior and executive departments, including the Resource Consumption Accounting (RCA) technique in question, which classifies costs into fixed and variable to support the decision-making process. Moreover, (RCA) combines two approaches to cost estimation, the first based on activity-based cost accounting (ABC) and the second on the German cost accounting method (GPK). The research aims to provide a conceptual vision for resource consumption accounting, after Considering it as an accounting te

Background: The aim of this study was to evaluate the shear bond strength (SBS) and adhesive remnant index (ARI) of different orthodontic adhesive systems after exposure to aging media (water storage and acid challenge). Materials and methods: Eighty human upper premolar teeth were extracted for orthodontic purposes and randomly divided into two groups (40 teeth each): the first group in which the bonded teeth were stored in distilled water for 30 days at 37°C, and the second group in which the bonded teeth were subjected to acid challenge. Each group was further subdivided into four subgroups (10 teeth each) according to the type of adhesive system that would be bonded to metal brackets: either non-fluoride releasing adhesive (NFRA),

After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph

Abstract

The open budget means everyone in the society can get information about the government budget in order to watch the governmental works. The aim of the research is to study the concepts of open budget, its advantage, limitations, role of supporting the transparency and questioning the administrative and financial corruption. Thus reflects positively on the national economy by providing governmental information to all users whether they are individuals or belong to the political class, or any other governmental or nongovernmental organizations which are interested in these information.

In order to achieve the objectives of the research aims, we make questionnaire to see aca

The purpose of this paper is to identify the statistical indicators of the searched variables and identify the relationship between the cognitive learning outcome and the performance of the two mastering skills by parallel spherical standing and equilibrium on the balance beam. And the identification of the percentage of the cognitive learning outcome contribution to the performance of the two mastering skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers used the descriptive approach in the survey method and the correlational relations, being the most appropriate to the nature of the research problem. The research community for the second stage students in the College of Physical Education and

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F