Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.
The involvement of maxillofacial tissues in SARS‐CoV‐2 infections ranges from mild dysgeusia to life‐threatening tissue necrosis, as seen in SARS‐CoV‐2‐associated mucormycosis. Angiotensin‐converting enzyme 2 (ACE2) which functions as a receptor for SARS‐CoV‐2 was reported in the epithelial surfaces of the oral and nasal cavities; however, a complete understanding of the expression patterns in deep oral and maxillofacial tissues is still lacking.
The immunohistochemical expression of ACE2 was analyzed in 95 specimens from maxillofacial tissues and 10 specimens o
The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
... Show MoreModeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t
... Show MoreEstimation of trip attraction and analyzing its main influencing factors are powerful for offering different classifications for business districts and presenting recommendations for improving attractiveness in long term. This is beneficial for designing transportation facilities and infrastructures. The paper presents the prediction of trip attraction using an artificial intelligence technology due to the profits that the technology can possess in shortening time, lowering expenses and saving effort. The new model has utilized six input parameters that have not been considered previously within the area of Nasiriyah city including; age and educational level of the passengers, mode of transport that the passengers use, purpose of the trip,
... Show MoreThe aim of the research is to:. Preparation and implementation of special educational units using multimedia to learn the skill of scrolling from below. 2 to recognize the impact of the use of multimedia in learning the skill of scrolling from below. 3 to identify the differences between the tests after the two groups research in learning the skill of passing from the bottom volleyball. The research represented the students of the first stage and the sample of the research was drawn randomly and the number of (50) students were divided into two experimental and control groups and each group (25) students were used standardized tests and conducting pre-tests and the implementation of the main exp
... Show MoreThis article reviews the technical applicability of nanofiltration membrane process for the removal of nickel, lead, and copper ions from industrial wastewater.
Synthetic industrial wastewater samples containing Ni(II), Pb(II), and Cu(II) ions at various concentrations (50, 100, 150 and 200 ppm), under different pressures (1, 2, 3 and 4 bar), temperatures (10, 20, 30 and 40 oC), pH (2, 3, 4, 5 and 5.5), and flow rates (1, 2, 3 and 4 L/hr), were prepared and subjected treated by NF systems in the laboratory. Suitable NF membrane was chosen after testing a number of NF membranes (University of Technology-Baghdad), in terms of production and removal. NF system was capable of removing more than (85%, 78%, and 66% for Ni(II
... Show MoreThe kinetic of atropine pertraction from seeds of Datura Metel Linn plant was studied. Diisopropyl ether, n-hexane and n-heptane were used as membranes for atropine recovery. The effect of speed of agitation and time in the range of 200-300 rpm and 0-3.5h, respectively were studied using the proposed membranes. The pertraction experiments were carried outs in a batch laboratory unit. The liquid-liquid pertraction was found to be very suitable for atropine recovery from its liquid extracts of Datura Metel seeds. A high purity (94-96%) can be obtained in the receiver phase. The pertraction process was found to be very selective for atropine recovery with diisopropyl ether membrane. As the speed of agitation increases the efficiency of pertrac
... Show MoreThe electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)
... Show MoreIn the present research the flame retardancy to buildings and industrial foundations which are manufacturing from advanced polymeric composite material was increased by coating it with surface layer included flame retardant material. A(3mm) thick antimony tetroxide was used as a coated layer to retard and prevent the flame spread to the coating surface of polyester resin (SIROPOL 8340-PI) reinforced with hybrid fibers as a woven roving (°45-°0) consist of carbon and kevlar (49) fibers, and exposed it to direct flame generated from gas torch at temperature of (2000ºC), at different exposed distance (10,15,20mm)and study the rang of resistance for this layer and its ability to protec
... Show MoreEvaporation is one of the major components of the hydrological cycle in the nature, thus its accurate estimation is so important in the planning and management of the irrigation practices and to assess water availability and requirements. The aim of this study is to investigate the ability of fuzzy inference system for estimating monthly pan evaporation form meteorological data. The study has been carried out depending on 261 monthly measurements of each of temperature (T), relative humidity (RH), and wind speed (W) which have been available in Emara meteorological station, southern Iraq. Three different fuzzy models comprising various combinations of monthly climatic variables (temperature, wind speed, and relative humidity) were developed
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