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

        In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, industry. This paper introduced the simulated model of a proposed self-balancing platform that described the self–balancing attitude in (X-axis, Y-axis, or both axis) under the influence of road disturbance. To simulate the self-balanced platform's performance during the tilt, an integration between Solidworks, Simscape, and Simulink toolboxes in MATLAB was used. The platform's dynamic model was drawn in SolidWorks and exported as a STEP file used in the Simscape Multibody environment. The system is controlled using the proportional-integral-derivative (PID) co

Leishmaniasis is one of the important parasitic diseases, affecting mainly low social class people indeveloping countries, and is more prevalent and endemic in the tropical and subtropical regions of old worldand new world. Despite ofbroad distribution in Iraq,little known about the geneticcharacteristics of thecausative agents. So this study was aimed to evaluate the genetic varietyoftwo IraqiLeishmaniatropicaisolatesbased on heat shock protein gene sequence 70 (HSP70) in comparison with universal isolates recordedsequences data. After amplification and sequencing of HSP70 gene,the obtainedresults were alignment alongwith homologous Leishmania sequences retrieved from NCBI by using BLAST. The analysis results showedpresence of particular g

Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO₂ NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil

This book presents the problem of tooth decay due to bacteria Streptococcus mutans one of methods of treatment using 3 extracts of S. persica (miswak) (aqueous, acetone and methanol) and prove its effectiveness and its impact on the gtf (B, C, and D) genes that code the glucosyltransferase (Gtf) enzymes that cause decay membrane compared to the usual means used for the prevention of tooth decay

In this study, polyester composites reinforced with pistachio shells powder (P.) with an average
diameter (150 – 200 μm) with different weight ratios (0.5%, 1%, 1.5%, 2%, and 2.5%) were
prepared to the resin. The Shore D hardness, thermal conductivity (K), and the glass transition
temperature (Tg) of the samples were examined. The results showed that the Shore D hardness
increases with the increase of the reinforcement ratio and its maximum value is (87.55) at (2.5%
P.) While the value of hardness at (0%) is (86.5). The thermal conductivity increases slightly with
the increase in the percentage of reinforcement and its maximum value is (0.213253 W/ m. K) at
(2.5% P.), while the value of K at (0% P.)