Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In addition, a bi-modal system for recognising emotions from facial expressions and speech signals is presented. This is important since one modality may not provide sufficient information or may not be available for any reason beyond operator control. To perform this, decision-level fusion is performed using a novel way for weighting according to the proportions of facial and speech impressions. The results show an average accuracy of 93.22 %.
Electrospun nanofiber membranes are employed in a variety of applications due to its unique features. the nanofibers' characterizations are effected by the polymer solution. The used solvent for dissolving the polymer powder is critical in preparing the precursor solution. In this paper, the Polyacrylonitrile (PAN)-based nanofibers were prepared in a concentration of 10 wt.% using various solvents (NMP, DMF, and DMSO). The surface morphology, porosity, and the mechanical strength of the three prepared 10 wt.% PAN-based nanofibers membranes (PAN/NMP, PAN/DMF, and PAN/DMSO) were characterized using the Scanning Electron Microscopy (SEM), Dry-wet Weights method, and Dynamic Mechanical Analyzer (DMA). Using DMF as a solvent resulted in a lon
... Show MoreThis article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
Background: The marginal adaptation has a key role in the success and longevity of the fixed dental restoration, which is affected by the impression and the fabrication techniques .The objective of this in vitro study was to evaluate and compare the marginal fitness of lithium disilicate crowns using two different digital impression techniques (direct and indirect techniques) and two different fabrication techniques (CAD/CAM and Press techniques). Materials and Methods: Thirty two sound upper first premolar teeth of comparable size extracted for orthodontic reason were selected in this study .Standardized preparation of all teeth samples were carried out with modified dental surveyor to receive all ceramic crown restoration with 1 mm deep
... Show MoreMM Abdulwahhab, kufa Journal for Nursing sciences, 2017 - Cited by 1
Background: In the Thermafil as a root canal obturation, system little is known about the effect that varying rates of insertion have on the adaptability of thermoplasticized GP and the amount of apical extrusion. Materials and methods: thirty simulated root canals were obturated with thermafil obturators and Apexit Plus sealer at three different insertion rates. The obturated canals were sectioned at three different levels, the sealer average film thickness for each section was calculated and the amount of apical extrusion for each canal was conducted. Results: the higher adaptability was seen with the faster insertion rate while the slower insertion rate showed fewer tendencies to cause apical extrusion. Conclusions: the intermediate i
... Show MoreBackground: Ceramic veneers represent the treatment of choice in minimally invasive esthetic dentistry; one of the critical factors in their long term success is marginal adaptation. The aim of the present study is to evaluate the marginal gap of ceramic veneers by using two different fabrication techniques and two different designs of preparation. Material and methods: A typodont maxillary central incisor used in the preparation from which metal dies were fabricated, which were in turn used to make forty stone dies. The dies divided into four experimental groups, each group had ten samples: A1: prepared with butt-joint incisal reduction and restored with IPS e.max CAD, A2: prepared with overlapped incisal reduction and restored with IPS e.
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