Vol. 6, Issue 1 (2025)

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

In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o

Background: This in vitro study measure and compare the effect of light curing tip distance on the depth of cure by measuring vickers microhardness value on two recently launched bulk fill resin based composites Tetric EvoCeram Bulk Fill and Surefil SDR Flow with 4 mm thickness in comparison to Filtek Z250 Universal Restorative with 2 mm thickness. In addition, measure and compare the bottom to top microhardness ratio with different light curing tip distances. Materials and Method: One hundred fifty composite specimens were obtained from two cylindrical plastic molds the first one for bulk fill composites (Tetric EvoCeram Bulk Fill and Surefil SDR Flow) with 4 mm diameter and 4 mm depth, the second one for Filtek Z250 Universal Restorative

Unmanned aerial vehicles (UAVs) can provide valuable spatial information products for many projects across a wide range of applications. One of the major challenges in this discipline is the quality of positioning accuracy of the resulting mapping products in professional photogrammetric projects. This is especially true when using low-cost UAV systems equipped with GNSS receivers for navigation. In this study, the influence of UAV flight direction and camera orientation on positioning accuracy in an urban area on the west bank of the Euphrates river in Iraq was investigated. Positioning accuracy was tested in this study with different flight directions and camera orientation settings using a UAV autopilot app (Pix4Dcapture software