The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

the behavior of the first-order black and gray solitons propagtedin optical fiber in the presence of frequency chirp is studied analytically and numerically results show that phase profile of black solitons changes abruptly

This research aims to analyze the impact of effective manufacturing strategy on total productive maintenance. Effective manufacturing focuses on improving product quality, increasing productivity, and reducing costs, while total productive maintenance focuses on maintaining machines and equipment in good operational condition and high efficiency. The research seeks to understand how to achieve integration between these two dimensions to achieve excellent performance in manufacturing operations. The study was conducted using the General Company for Battery Manufacturing as a research community, with a sample size of 60 individuals. The research found significant results, including the fact that using an effective manufacturing strategy leads

In this research, we studied the effect of concentration carriers on the efficiency of the N749-TiO2 heterogeneous solar cell based on quantum electron transfer theory using a donor-acceptor scenario. The photoelectric properties of the N749-TiO2 interfaces in dye sensitized solar cells DSSCs are calculated using the J-V curves. For the 〖(CH_3)〗_3 COH solvent, the N749-TiO2 heterogeneous solar cell shows that the concentration carrier together with the strength coupling are the main factors affecting the current density, fill factor and efficiency. The current density and current increase as the concentration increases and the strength coupling increases as the N749-TiO2 heterogeneous in solar cell. However, the efficiency is more sens

HR Ghanim, GA Abdulhassan, International Journal of Early Childhood Special Education, 2022

The research aims at considering the reality of cognitive bias and organizational inertia as determinants of strategic change in a sample of companies listed in Amman Stock Market. To achieve objectives of the research, a model consisting of two independent variables has been designed, namely:

(1) The cognitive bias resulting from (escalating commitment, analogy, previous assumptions, representative generalization, command and control, convergent thinking), and (2) Organizational inertia due to (Icarus discrepancy, power distribution, rooted organizational culture), and a dependent variable, strategic change in (leadership patterns, strategy, the organization per se). 

From the model two main hypotheses were derived;

The Manganese doped zinc sulfide nanoparticles of the cubic zinc blende structure with the average crystallite size of about 3.56 nm were synthesized using a coprecipitation method using Thioglycolic Acid as an external capping agent for surface modification. The ZnS:Mn2+ nanoparticles of diameter 3.56 nm were manufactured through using inexpensive precursors in an efficient and eco-friendly way. X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy are used to examine the structure, morphology and chemical composition of the nanoparticles. The antimicrobial activity of (ZnS:Mn2+) nanocrystals was investigated by measuring the diameter of inhibition zone using well diffusion mechanism

In the present study, a pressure drop technique was used to identify the phase inversion point of oil-in-water to water-in-oil flows through a horizontal pipe and to study the effect of additives (nanoparticles, cationic surfactant and blend  nanoparticles-surfactant) on the critical dispersed volume fraction (phase inversion point). The measurements were carried  for mixture velocity ranges from 0.8 m/sec to 2.3 m/sec. The results showed that at low mixture velocity 0.8 and 1 m/sec there is no effect of additives and velocity on phase inversion point, while at high mixture velocities the phase inversion point for nanoparticles and blend (nanoparticles/surfactant) systems was delayed (postponed) to a higher value of the dispers