Effect of medial surface shape on voice production in a MRI-based three-dimensional phonation model

2019 ◽  
Vol 146 (4) ◽  
pp. 3086-3086
Author(s):  
Liang Wu ◽  
Zhaoyan Zhang
Keyword(s):  
Three Dimensional ◽  
Surface Shape ◽  
Voice Production ◽  
Medial Surface

scholarly journals The Numerical Analysis of the Flow on the Smooth and Nonsmooth Boundaries by IBEM/DBIEM

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Gang Xu ◽  
Guangwei Zhao ◽  
Jing Chen ◽  
Shuqi Wang ◽  
Weichao Shi
Keyword(s):  
Boundary Value ◽  
Three Dimensional ◽  
Boundary Surface ◽  
Tangential Velocity ◽  
Integral Equation Method ◽  
Boundary Integral ◽  
Surface Shape ◽  
Normal Vector ◽  
Computational Domain ◽  
Nonsmooth Boundary

The value of the tangential velocity on the Boundary Value Problem (BVP) is inaccurate when comparing the results with analytical solutions by Indirect Boundary Element Method (IBEM), especially at the intersection region where the normal vector is changing rapidly (named nonsmooth boundary). In this study, the singularity of the BVP, which is directly arranged in the center of the surface of the fluid computing domain, is moved outside the computational domain by using the Desingularized Boundary Integral Equation Method (DBIEM). In order to analyze the accuracy of the IBEM/DBIEM and validate the above-mentioned problem, three-dimensional uniform flow over a sphere has been presented. The convergent study of the presented model has been investigated, including desingularized distance in the DBIEM. Then, the numerical results were compared with the analytical solution. It was found that the accuracy of velocity distribution in the flow field has been greatly improved at the intersection region, which has suddenly changed the boundary surface shape of the fluid domain. The conclusions can guide the study on the flow over nonsmooth boundaries by using boundary value method.

scholarly journals Quantitative Evaluation of the In Vivo Vocal Fold Medial Surface Shape

2017 ◽  
Vol 31 (4) ◽  
pp. 513.e15-513.e23 ◽  
Author(s):  
Andrew M. Vahabzadeh-Hagh ◽  
Zhaoyan Zhang ◽  
Dinesh K. Chhetri
Keyword(s):  
Quantitative Evaluation ◽  
Vocal Fold ◽  
Surface Shape ◽  
Medial Surface

Gradient-Augmented Level Set Two-Phase Flow Method With Pretreated Reinitialization for Three-Dimensional Violent Sloshing

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Jianjian Xin ◽  
Fulong Shi ◽  
Qiu Jin ◽  
Lin Ma
Keyword(s):  
Free Surface ◽  
Level Set ◽  
Two Phase Flow ◽  
Three Dimensional ◽  
Surface Shape ◽  
Phase Flow ◽  
Two Phase ◽  
Correction Technique ◽  
Highly Nonlinear ◽  
Violent Sloshing

Abstract A three-dimensional (3D) gradient-augmented level set (GALS) two-phase flow model with a pretreated reinitialization procedure is developed to simulate violent sloshing in a cuboid tank. Based on a two-dimensional (2D) GALS method, 3D Hermite, and 3D Lagrange polynomial schemes are derived to interpolate the level set function and the velocity field at arbitrary positions over a cell, respectively. A reinitialization procedure is performed on a 3D narrow band to treat the strongly distorted interface and improve computational efficiency. In addition, an identification-correction technique is proposed and incorporated into the reinitialization procedure to treat the tiny droplet which can distort the free surface shape, even lead to computation failure. To validate the accuracy of the present GALS method and the effectiveness of the proposed identification-correction technique, a 3D velocity advection case is first simulated. The present method is validated to have better mass conservation property than the classical level set and original GALS methods. Also, distorted and thin interfaces are well captured on all grid resolutions by the present GALS method. Then, sloshing under coupled surge and sway excitation, sloshing under rotational excitation are simulated. Good agreements are obtained when the present wave and pressure results are compared with the experimental and numerical results. In addition, the highly nonlinear free surface is observed, and the relationship between the excitation frequency and the impulsive pressure is investigated.

scholarly journals A Methodology for Multi-Camera Surface-Shape Estimation of Deformable Unknown Objects

Robotics ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 69 ◽  
Author(s):  
Evgeny Nuger ◽  
Beno Benhabib
Keyword(s):  
Particle Filtering ◽  
Surface Deformation ◽  
Vision System ◽  
Three Dimensional ◽  
Target Object ◽  
Surface Shape ◽  
Shape Estimation ◽  
Formal Approach ◽  
Camera System ◽  
Unknown Objects

A novel methodology is proposed herein to estimate the three-dimensional (3D) surface shape of unknown, markerless deforming objects through a modular multi-camera vision system. The methodology is a generalized formal approach to shape estimation for a priori unknown objects. Accurate shape estimation is accomplished through a robust, adaptive particle filtering process. The estimation process yields a set of surface meshes representing the expected deformation of the target object. The methodology is based on the use of a multi-camera system, with a variable number of cameras, and range of object motions. The numerous simulations and experiments presented herein demonstrate the proposed methodology’s ability to accurately estimate the surface deformation of unknown objects, as well as its robustness to object loss under self-occlusion, and varying motion dynamics.

scholarly journals A Fast Semiautomatic Algorithm for Centerline-Based Vocal Tract Segmentation

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Anton A. Poznyakovskiy ◽  
Alexander Mainka ◽  
Ivan Platzek ◽  
Dirk Mürbe
Keyword(s):  
Major Part ◽  
Vocal Tract ◽  
Active Contours ◽  
Three Dimensional ◽  
Voice Therapy ◽  
Segmentation Method ◽  
Voice Production ◽  
Medical Issues ◽  
Dimensional Measurements ◽  
Spatial Geometry

Vocal tract morphology is an important factor in voice production. Its analysis has potential implications for educational matters as well as medical issues like voice therapy. The knowledge of the complex adjustments in the spatial geometry of the vocal tract during phonation is still limited. For a major part, this is due to difficulties in acquiring geometry data of the vocal tract in the process of voice production. In this study, a centerline-based segmentation method using active contours was introduced to extract the geometry data of the vocal tract obtained with MRI during sustained vowel phonation. The applied semiautomatic algorithm was found to be time- and interaction-efficient and allowed performing various three-dimensional measurements on the resulting model. The method is suitable for an improved detailed analysis of the vocal tract morphology during speech or singing which might give some insights into the underlying mechanical processes.

scholarly journals Body Dimension Measurements of Qinchuan Cattle with Transfer Learning from LiDAR Sensing

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5046 ◽  
Author(s):  
Lvwen Huang ◽  
Han Guo ◽  
Qinqin Rao ◽  
Zixia Hou ◽  
Shuqin Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Transfer Learning ◽  
Three Dimensional ◽  
Automatic Measurement ◽  
The Body ◽  
Surface Shape ◽  
Body Dimension ◽  
Qinchuan Cattle ◽  
Body Dimensions ◽  
Deep Model

For the time-consuming and stressful body measuring task of Qinchuan cattle and farmers, the demand for the automatic measurement of body dimensions has become more and more urgent. It is necessary to explore automatic measurements with deep learning to improve breeding efficiency and promote the development of industry. In this paper, a novel approach to measuring the body dimensions of live Qinchuan cattle with on transfer learning is proposed. Deep learning of the Kd-network was trained with classical three-dimensional (3D) point cloud datasets (PCD) of the ShapeNet datasets. After a series of processes of PCD sensed by the light detection and ranging (LiDAR) sensor, the cattle silhouettes could be extracted, which after augmentation could be applied as an input layer to the Kd-network. With the output of a convolutional layer of the trained deep model, the output layer of the deep model could be applied to pre-train the full connection network. The TrAdaBoost algorithm was employed to transfer the pre-trained convolutional layer and full connection of the deep model. To classify and recognize the PCD of the cattle silhouette, the average accuracy rate after training with transfer learning could reach up to 93.6%. On the basis of silhouette extraction, the candidate region of the feature surface shape could be extracted with mean curvature and Gaussian curvature. After the computation of the FPFH (fast point feature histogram) of the surface shape, the center of the feature surface could be recognized and the body dimensions of the cattle could finally be calculated. The experimental results showed that the comprehensive error of body dimensions was close to 2%, which could provide a feasible approach to the non-contact observations of the bodies of large physique livestock without any human intervention.

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