Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. To reduce the number of generated sub-graphs, overlap ratio metric is utilized for this purpose. After encoding the final selected sub-graphs, binary classification is then applied to classify the emotion of the queried input facial image using six levels of classification. Binary cat swarm intelligence is applied within each level of classification to select proper sub-graphs that give the highest accuracy in that level. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the final system accuracy was 90.00%. The results show significant accuracy improvements (about 2%) by the proposed system in comparison to current published works in SAVEE database.
The effect of electrolysis operating parameters on the removal efficiency of cadmium from a simulated wastewater was studied by adopting response surface methodology combined with Box–Behnken Design. As a new electrode design, spiral-wound woven wire mesh rotating cylinder electrode was used for cadmium removal. Current (240–400 mA), rotation speed (200–1000 rpm), initial cadmium concentration (200–600ppm), and cathode mesh number (30–60) were chosen as independent variables while the removal efficiency of cadmium was considered as a response function. The results revealed that the rotation speed has the major effect on the removal efficiency of cadmium. Regression analysis showed good fit of the experimental data to the second-or
... Show MoreIncreasing demands on producing environmentally friendly products are becoming a driving force for designing highly active catalysts. Thus, surfaces that efficiently catalyse the nitrogen reduction reactions are greatly sought in moderating air-pollutant emissions. This contribution aims to computationally investigate the hydrodenitrogenation (HDN) networks of pyridine over the γ-Mo2N(111) surface using a density functional theory (DFT) approach. Various adsorption configurations have been considered for the molecularly adsorbed pyridine. Findings indicate that pyridine can be adsorbed via side-on and end-on modes in six geometries in which one adsorption site is revealed to have the lowest adsorption energy (–45.3 kcal/mol). Over a nitr
... Show MoreA new 5‐fluorouracil–naproxen conjugate is synthesized as a mutual prodrug for targeting cancer tissues. The structure of the target compound and their intermediate are characterized by their melting point, IR, 1H NMR, 13C NMR, and elemental microanalysis. The cytotoxic activity is preliminarily evaluated using nonsmall lung cancer CRL‐2049, human breast cancer CAL‐51, and one type of normal cell line; rat embryo fibroblast cell line. The synthesized compound shows a good cytotoxic effect at the cancer cell and no significant effect at rat embryo fibroblast cell line.
It is no secret for those concerned with language concerns that the issue of figurative feminization is one of the issues that does not follow a grammatical rule governed by the fact that the subject of knowledge of this is due to hearing as indicated by linguistic references and lexicons.This research opts to find out the origin of the feminization of the word sun in the Arabic language and in light of what some language specialists have argued that the origin of figurative feminization was due to non-linguistic motives related to religious and metaphysical beliefs, and that it was memory preserved in light of the linguistic heritage.The research concluded that the feminization of the sun goes back to what settled in their minds, which
... Show MoreThe aim of t his p aper is t o const ruct t he (k,r)-caps in t he p rojective 3-sp ace PG(3,p ) over Galois field GF(4). We found t hat t he maximum comp let e (k,2)-cap which is called an ovaloid, exist s in PG(3,4) when k = 13. Moreover t he maximum (k,3)-cap s, (k,4)-cap s and (k,5)-caps.
Apium graveolens has been utilized for a multitude of purposes due to its diverse pharmacological characteristics. On the other hand, little is known about how the fatty acids (saturated and unsaturated) terpenes and steroids found in Iraqi Apium graveolens affect the human cancer cells. The purpose of this study was to examine the effects of Iraqi Apium graveolens petroleum ether extract on the human prostate cancer cell line (PC3). Subsidiary extraction and phytochemical analysis by GC/MS were performed.The dry and fresh aerial parts (leaves and stem) of Apium graveolens were extracted using a Soxhlet device with 70 % ethanol, then fractionated with petroleum ether. Then Gas Chromatography System was used to identify the bioactive
... Show MoreThis study was conducted to investigate phytoplasma causing a virescence disease on Arabic jasmine Jasminum sambac based on microscopy and molecular approaches. Samples were collected from symptomatic Arabic jasmine plants grown in nurseries in Baghdad-Iraq. Specimens from infected plants were prepared and Dienes stained for light microscopy examination. Phytoplasma were detected in infected plants by polymerase chain reaction (PCR) using P1/P7 and SecAfor1/SecArev3 Candidatus Phytoplasma specific primer sets. Light microscopy test showed symptomatic Arabic jasmine plants were phytoplasms infected when phloem tissues were stained with a dark blue color. PCR test confirmed the symptomatic plants were phytoplasms infected when SecAfor1/Sec
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.