Key-frame selection plays an important role in facial expression recognition systems. It helps in selecting the most representative frames that capture the different poses of the face. The effect of the number of selected keyframes has been studied in this paper to find its impact on the final accuracy of the emotion recognition system. Dynamic and static information is employed to select the most effective key-frames of the facial video with a short response time. Firstly, the absolute difference between the successive frames is used to reduce the number of frames and select the candidate ones which then contribute to the clustering process. The static-based information of the reduced sets of frames is then given to the fuzzy C-Means algorithm to select the best C-frames. The selected keyframes are then fed to a graph mining-based facial emotion recognition system to select the most effective sub-graphs in the given set of keyframes. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the results show that the proposed method can effectively capture the keyframes that give the best accuracy with a mean response time equals to 2.89.
Background: Levetiracetam is a member of the new antiepileptic drugs and has a broad spectrum effect, used as an adjunctive therapy in addition to monotherapy in the treatment of partial onset-seizures. The effect of levetiracetam on the development of embryo nervous system after maternal exposure during pregnancy has not been identified. Objective: to evaluate the effect of antiepileptic drug, levetiracetam (LEV) within its therapeutic dose 350mg/Kg body weight on albino female rat to clarify its effect on the developing cerebral cortex histologically. Material And Methods: Ten pregnant female rats were separated into two groups, control group and experimental group. They were obtained from the animal house of the high institute of inferti
... Show MoreAnalyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col
... Show MoreThis research studies the effect of addition of some nanoparticles
(MgO, CuO) and grain size (30,40nm) on some physical properties
(impact strength, hardness and thermal conductivity) for a matrix
blend of epoxy resin with SBR rubber. Hand –Lay up method was
used to prepare the samples. All samples were immersed in water for
9 weeks.
The Results showed decreased in the values of impact strength and
hardness but increased the coefficient of thermal conductivity.
Background: Several infectious lung diseases often develop in patients with Rheumatoid arthritis (RA), especially during immunosuppressive medication, including disease-modifying anti-rheumatic drugs (DMARDs). The present study aimed to determine the role of respiratory tract bacterial infection in RA activity. Methods: Blood and sputum samples were collected from 31 patients with RA and 12 healthy subjects as control. The bacterial isolates were isolated and identified in collected sputum by biochemical tests and Vitec 2 system. Results: In the present study, thirty-one patients with RA were compared with 12 healthy subjects. Eight patients with RA were not infected with pathogenic bacteria (RA-NIPB) (25.8%). Twenty-three RA patients wer
... Show MoreIt is through a review of conversion of vegetable oils into glycidyl ethers focusing on their roles in achieving sustainability and improved epoxy resin performance. It involves functionalization of triglycerides in the form of epoxidation followed by glycidylation and yields bio-based monomers having improved mechanical as well as thermal properties. The review covers the underlying chemistry, production drivers, industrial applications, and future issues, supported by quantitative data and comparative studies. In addition, it integrates recent data on catalyst choice, feedstock flexibility, and environmental performance factors of bio-based resins, indicating their suitability for replacing traditional petroleum-based components.<
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