The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wireless temperature sensor, which utilizes proton resonance frequency of carbon-13 isotope material. In addition to that, this study also addresses the energy distribution of the particles by selecting an updated appropriate approach that has interesting points of limitation in the number of degree of freedom: (1) thermodynamically limits and (2) theoretical statistical thermodynamics observations. Lastly, the main idea of this paper is to visualize the analysis of temperate in the nanoscale system via statistical thermodynamics approach along with the material characterization of carbon-13 isotope.
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
... Show MoreSkull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MorePhosphorus‐based Schiff base were synthesized by treating bis{3‐[2‐(4‐amino‐1.5‐dimethyl‐2‐phenyl‐pyrazol‐3‐ylideneamino)ethyl]‐indol‐1‐ylmethyl}‐phosphinic acid with paraformaldehyde and characterized as a novel antioxidant. Its corresponding complexes [(VO)2L(SO4)2], [Ni2LCl4], [Co2LCl4], [Cu2LCl4], [Zn2LCl4], [Cd2LCl4], [Hg2LCl4], [Pd2LCl4], and [PtL
... Show MoreIn this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg
... Show MoreThe corrosion inhibition of low carbon steel in1N HCl solution in the presence of peach juice at temperature (30,40,50,and 60)°C at concentration ( 5, 10, 20, 30, 40and 50 cm3/L)were studied using weight loss and polarization techniques. Results show that the inhibition efficiency was increased with the increase of inhibitor concentration and increased with the increase of temperature up to 50ºC ,above 50ºC (i.e. at 60 ºC) the values of efficiency decreases. Activation parameters of the corrosion process such as activation energies, Ea, activation enthalpies, ΔH, and activation entropies, ΔS, were calculated. The adsorption of inhibitor follows Langmuir isotherm. Maximum inhibition efficiency obtained was a bout 91% at 50ºC in the
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This study offers the elastic response of the variable thickness functionally graded (FG) by single walled carbon nanotubes reinforced composite (CNTRC) moderately thick cylindrical panels under rotating and transverse mechanical loadings. It’s considered that, three kinds of distributions of carbon nanotubes which are uniaxial aligned in the longitudinal direction and two functionally graded in the transverse direction of the cylindrical panels. Depending on first order shear deformation theory (FSDT), the governing equations can be derived. The partial differential equations are solved by utilizing the technique of finite element method (FEM) with a program has been built by using FORTRAN 95. The results are calculat
... Show MoreATTAPULGITE clay was modified in this study by the graphene oxide sheets and the clay was diagnosed before and after modification using several techniques (Fourier-transform infrared spectroscopy FT-IR, X-ray powder diffraction XRD, Scanning electron microscope SEM , energy dispersive spectroscopy EDX ) ,The surface of the attapulgite clay (before (Ata) after modification by graphene oxide (Ata-GO) ) was applied to adsorption of the Alizarin dye from its water solutions through the application of several kinetic models (pseudo first-order model , pseudo second -order model , intraparticle diffusion model ),It was found that the practical results follow pseudo second -order model. The process of modification on the surface of the mud has imp
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