scholarly journals INFORMATION TECHNOLOGY FOR DETERMINATION OF CHARACTERISTICS ON THE FACE FOR EMOTIONAL RECOGNITION

2020 ◽  
Vol 2 (2) ◽  
pp. 47-53
Author(s):  
S. IVASCHENKO ◽  
◽  
O. KALYTA ◽  
O. BARMAK ◽  
T. SKRYPNYK ◽  
...  
Keyword(s):  
Input Data ◽  
Emotional State ◽  
Face Image ◽  
Network Module ◽  
Computing Power ◽  
Proposed Model ◽  
The Face ◽  
Last Stage ◽  
Characteristic Features

One of the ways to process an image presented in the form of a set of pixels, in order to further identify, classify the objects present on it is to display the specified set in the form of sets of certain features. Such features are not universal in nature, but rather significantly depend on the tasks under consideration. For certain classes of problems, such features (model) are selected that best allow the application of appropriate methods to solve the problem. The paper considers a class of problems for recognizing the emotional state on a person's face. In, a convolutional neural network (CNN) is used to detect emotions. CNN differs from multilayer perceptron (MLP) in that they have hidden layers called convolutional layers. The proposed method is based on a two-tier CNN system. At the first level, the background of the image is removed to better reflect emotions. A standard CNN network module is used to obtain the primary expression vector (EV). EV is formed by tracking the relevant important points of the face. EV is directly related to changes in facial expression. EV is obtained using a basic perceptron unit plotted on a face image with the background removed. In the proposed model at the last stage, there is a non-evolutionary perceptron layer. Each of the convoluted layers receives input data (images), converts them, and then takes them to the next level. After detecting a face, the CNN filter of the second part captures parts of the face, such as eyes, ears, lips, nose, and cheeks. The authors agree that the method has some limitations, and especially requires high computing power when setting up CNN. The technology of determination of characteristic features on the face for recognition of emotional manifestations is presented and experimentally investigated.

Modification of an Involute Gearing and Its Effect on a Loading Capacity

2007 ◽  
Author(s):  
Zdenek Dejl ◽  
Vladimir Moravec
Keyword(s):  
Contact Stress ◽  
Input Data ◽  
Experimental Methods ◽  
Loading Capacity ◽  
Separate Part ◽  
Face Width ◽  
Lifetime Test ◽  
The Face ◽  
Involute Gears

A modification of an involute gearing is presented by a modification of an involute and a longitudinal modification along the face width. In the contribution both of the modifications are presented and theoretical and practical methods for determination of their parameters are shown. Experimental methods of setting up of input data for design of modifications are brought in then. These data are prepared on the basis of measuring of deformations of gearwheels bodies, shafts and shafts supports. An attention is given to the influence on a size and position of a zone of contact of meshing teeth. A separate part deals with the appreciation of an influence of modification on a size of a noise and vibrations of involute gears. As far as a loading capacity of modified involute gearings, the attention is first given to the loading capacity in a contact stress between teeth faces. The comparison is made between loading capacity of an involute gearing with no modification and a gearing modified by various types of modifications. This comparison is made both by using a FEM and by experiment. Experiment is based on lifetime test of these gearing.

scholarly journals Otimização do método dos molinetes com ajuste do perfil hidrodinâmico para a estimação da descarga líquida em corpos hídricos usando recursos de interpolação e integração numérica

2018 ◽  
Vol 1 (38) ◽  
pp. 61
Author(s):  
John Williams Ferreira de Souza ◽  
Monaliza Araújo Parnaíba ◽  
Patrício Luiz de Andrade ◽  
Bruno De Medeiros Souza
Keyword(s):  
River Basin ◽  
Flow Measurement ◽  
Input Data ◽  
Flow Rates ◽  
Traditional Form ◽  
Numerical Integrations ◽  
Proposed Model ◽  
Measuring Campaign ◽  
Computational Analyses

In the last years, there has been an increase in computational analyses in the study of hydrodynamic profiles for the determination of flows in watercourses as an attempt to reduce inaccuracies in traditional calculations. This article aims to develop an algorithm for the determination of flow rates in open channels using numerical procedures to optimize the hydrometric windlasses method in order to reduce the time in data analyzes and to provide a detailed treatment of velocities as a function of depth. In this article, the input data used in the computational project result from the measuring campaign present in Literature,which was carried out in the Braço do Norte river, in the Tubarão river basin, at the point where the São Ludgero Hydrometeorological Station, of National Waters Aggency (ANA), is located, in SC. Regarding the method of the windlasses in their traditional form,the model presented in this work presents small percentage differences of estimates This allows the validation of the proposed model and means that the use of numerical integrations and interpolations, especially the cubic splines, for the modeling of the flow measurement in watercourses is satisfactory and it can be used in the practice of instrumentation and measurement.

The quantitative comparison of experimental and simulated diffraction contrast images

1995 ◽  
Vol 53 ◽  
pp. 102-103
Author(s):  
Stuart McKernan
Keyword(s):  
Image Processing ◽  
Personal Computer ◽  
Close Agreement ◽  
Quantitative Comparison ◽  
Image Simulation ◽  
Computing Power ◽  
Diffraction Contrast ◽  
Simulated Images ◽  
Made In

For many years the concept of quantitative diffraction contrast experiments might have consisted of the determination of dislocation Burgers vectors using a g.b = 0 criterion from several different 2-beam images. Since the advent of the personal computer revolution, the available computing power for performing image-processing and image-simulation calculations is enormous and ubiquitous. Several programs now exist to perform simulations of diffraction contrast images using various approximations. The most common approximations are the use of only 2-beams or a single systematic row to calculate the image contrast, or calculating the image using a column approximation. The increasing amount of literature showing comparisons of experimental and simulated images shows that it is possible to obtain very close agreement between the two images; although the choice of parameters used, and the assumptions made, in performing the calculation must be properly dealt with. The simulation of the images of defects in materials has, in many cases, therefore become a tractable problem.

Modeling of Dynamic Loads on the Polished Rod of Pumping Unit in Case of Mulfunction of Rod Pump Operating

2014 ◽  
Vol 10 ◽  
pp. 95-101
Author(s):  
A.S. Topolnikov
Keyword(s):  
Multiphase Flow ◽  
Satisfactory Agreement ◽  
Model Simulation ◽  
Theoretical Modeling ◽  
Dynamic Loads ◽  
Plunger Pump ◽  
Proposed Model ◽  
Pumping Unit ◽  
Polished Rod

The paper presents the results of theoretical modeling of joined movement of pump rods and plunger pump and multiphase flow in a well for determination of dynamic loads on the polished rod of pumping unit. The specificity of the proposed model is the possibility of taking into account for complications in rod pump operating, such as leakage in valve steam, presence of gas and emulsion, incorrect fitting of plunger inside the cylinder pump. The satisfactory agreement of results of the model simulation with filed measurements are obtained.

Research on Improved Gamma Transform Face Image Preprocessing Fusion Algorithm under Complex Lighting Conditions

2020 ◽  
Vol 13 ◽  
Author(s):  
Xiaolin Tang ◽  
Xiaogang Wang ◽  
Jin Hou ◽  
Huafeng Wu ◽  
Ping He
Keyword(s):  
Edge Detection ◽  
Face Image ◽  
Light Sources ◽  
Fusion Algorithm ◽  
Edge Information ◽  
Image Preprocessing ◽  
Lighting Conditions ◽  
Weighted Fusion ◽  
The Face ◽  
Sobel Edge Detection

Introduction: Under complex illumination conditions such as poor light sources and light changes rapidly, there are two disadvantages of current gamma transform in preprocessing face image: one is that the parameters of transformation need to be set based on experience; the other is the details of the transformed image are not obvious enough. Objective: Improve the current gamma transform. Methods: This paper proposes a weighted fusion algorithm of adaptive gamma transform and edge feature extraction. First, this paper proposes an adaptive gamma transform algorithm for face image preprocessing, that is, the parameter of transformation generated by calculation according to the specific gray value of the input face image. Secondly, this paper uses Sobel edge detection operator to extract the edge information of the transformed image to get the edge detection image. Finally, this paper uses the adaptively transformed image and the edge detection image to obtain the final processing result through a weighted fusion algorithm. Results: The contrast of the face image after preprocessing is appropriate, and the details of the image are obvious. Conclusion: The method proposed in this paper can enhance the face image while retaining more face details, without human-computer interaction, and has lower computational complexity degree.

scholarly journals Determination of the Vertical Dimension and the Position of the Occlusal Plane in a Removable Prosthesis Using Cephalometric Analysis and Golden Proportion

2021 ◽  
Vol 11 (15) ◽  
pp. 6948
Author(s):  
Gabriele Cervino ◽  
Sergio Sambataro ◽  
Chiara Stumpo ◽  
Salvatore Bocchieri ◽  
Fausto Murabito ◽  
...  
Keyword(s):  
Vertical Dimension ◽  
Occlusal Plane ◽  
X Rays ◽  
Common Procedure ◽  
Lower Incisor ◽  
Golden Proportion ◽  
The Face ◽  
Removable Prosthesis ◽  
Edentulous Patients

The aim of this study is to demonstrate the use and the effectiveness of cephalometry and golden proportions analysis of the face in planning prosthetic treatments in totally edentulous patients. In order to apply this method, latero-lateral and posterior-anterior X-rays must be performed in addition to the common procedure. Two main concerns for totally edentulous patients are the establishment of the vertical dimension and the new position of the occlusal plane. The divine proportion analysis was carried out by the use of a golden divider. The prosthetic protocol was divided into three steps and a case was selected for better understanding. Referring to the golden relations, if the distance from the chin to the wing of the nose is 1.0, the distance from the nose to eye is 0.618. This proportion is useful and effective in determining the correct prosthetic vertical dimension. The incisal margin of the lower incisor must be positioned between Point A (A) and protuberance menti (Pm) according to the gold ratio 0.618 of the total height A-Pm. Posteriorly the occlusal plane must be placed 2 mm below the divine occlusal plane (traced from the incisal margin of lower incisors to Xi point). A prosthesis made in accordance with cephalometric parameters and divine proportions of the face helps to improve the patient’s aesthetics, function and social personality.

scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

scholarly journals Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 930
Author(s):  
Fahimeh Hadavimoghaddam ◽  
Mehdi Ostadhassan ◽  
Ehsan Heidaryan ◽  
Mohammad Ali Sadri ◽  
Inna Chapanova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Viscosity Data ◽  
Oil Viscosity ◽  
Pvt Data ◽  
Proposed Model ◽  
Wide Range ◽  
Engineering Problems ◽  
Functional Forms ◽  
Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

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