Tao Li¹, Lingyun Wang¹, Yin Chen^1,*, Yongjun Ren¹, Lei Wang¹, Jinyue Xia²

Journal on Artificial Intelligence, Vol.1, No.2, pp. 59-68, 2019, DOI:10.32604/jai.2019.06346

Abstract In order to solve the problem that real-time face recognition is susceptible to illumination changes, this paper proposes a face recognition method that combines Local Binary Patterns (LBP) and Embedded Hidden Markov Model (EHMM). Face recognition method. The method firstly performs LBP preprocessing on the input face image, then extracts the feature vector, and finally sends the extracted feature observation vector to the EHMM for training or recognition. Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate. More >

Cheng Zhang^{1, *}, Mingge Wu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 459-469, 2019, DOI:10.32604/fdmp.2019.08477

Abstract A computational study of the stretching mechanism of a liquid bridge and the effect of the liquid properties on the DPN (dip-pen nanolithography) process is presented. The results show that the viscosity and contact angle can have an appreciable influence on these processes. The greater the viscosity, the harder the liquid bridge is to break, which allows more molecular transfer during the DPN spotting process. Besides, when the contact angle between the liquid and substrate is less than 60 degrees, the time required to stretch the bridge and break it grows with the contact More >

Jianjun Liang¹, Zhe Song², Peili Zhang^{1, *}

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 445-458, 2019, DOI:10.32604/fdmp.2019.07951

Abstract In order to investigate the burning characteristics of a 0# diesel and 3# jet fuel, a small-scale experimental bench mainly composed of a cone calorimeter was arranged. The heat release and burning rates were investigated changing the external irradiance in order to clarify the triadic relationship among these quantities. The effective heat of combustion of 0# diesel and 3# jet fuel were 38.89 MJ/kg and 43.15 MJ/kg, respectively, with the corresponding combustion efficiencies being 96.78% and 99.60% (the effective peak heat of combustion being 1.665 times the mean value for both types of fuel). According… More >

Mingge Wu¹, Lei Wang¹, Yixiang Wang¹, Cheng Zhang¹, Cheng Qiu^{1, 2, *}

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 431-444, 2019, DOI:10.32604/fdmp.2019.08209

Abstract Water management in proton exchange membrane fuel cells (PEMFC) is a topic of great importance for the optimization of these systems. Effective proton conductivity calls for moderate moisture content in the membrane, while uneven water distribution can lead to instability of the whole flow field, thereby decreasing the performance of the fuel cell. In the present study, a simplified two-tier hybrid structure is used to investigate the impact of the dynamic behavior of liquid water on the current density of the PEMFC. Simulation results show that water droplets attached to wall sides tend to increase More >

N. Kins Burk Sunil^{1, *}, R. Ganesan², B. Sankaragomathi³

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 351-375, 2019, DOI:10.31614/cmes.2018.04484

Abstract Obstructive Sleep Apnea (OSA) is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation. The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea (SA) activity. In the proposed method, the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted. These features are applied to the Classification and Regression Tree (CART)-Particle Swarm Optimization (PSO) classifier which classifies the More >

Han Li¹, Tianding Chen^{2, *}, Hualiang Teng³, Yingtao Jiang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 253-274, 2019, DOI:10.31614/cmes.2019.05807

Abstract In any classical value-based reinforcement learning method, an agent, despite of its continuous interactions with the environment, is yet unable to quickly generate a complete and independent description of the entire environment, leaving the learning method to struggle with a difficult dilemma of choosing between the two tasks, namely exploration and exploitation. This problem becomes more pronounced when the agent has to deal with a dynamic environment, of which the configuration and/or parameters are constantly changing. In this paper, this problem is approached by first mapping a reinforcement learning scheme to a directed graph, and… More >

Dugang Guo^{1, *}

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 419-430, 2019, DOI:10.32604/fdmp.2019.07831

Abstract The role of different grid search computer algorithms for the determination of the thermodynamic properties of water and steam in the p-T and P-S planes has been investigated via experimental and analytical methods. The results show that the spline interpolation grid search algorithm and the power grid search algorithm are more efficient, stable and clear than other algorithms. More >

Donghong He¹, Hang Ma^{2, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.1, pp. 15-40, 2019, DOI:10.31614/cmes.2019.04327

Abstract To deal with the problems encountered in the large scale numerical simulation of three dimensional (3D) elastic solids with fluid-filled pores, a novel computational model with the corresponding iterative solution procedure is developed, by introducing Eshelby’s idea of eigenstrain and equivalent inclusion into the boundary integral equations (BIE). Moreover, by partitioning all the fluid-filled pores in the computing domain into the near- and the far-field groups according to the distances to the current pore and constructing the local Eshelby matrix over the near-field group, the convergence of iterative procedure is guaranteed so that the problem… More >

Haojie Pan^{1, *}, Xiaojun Zhou¹

FDMP-Fluid Dynamics & Materials Processing, Vol.15, No.4, pp. 403-417, 2019, DOI:10.32604/fdmp.2019.07808

Abstract Traditional mathematical models cannot predict and explain the phenomenon by which the drag torque (DT) in wet clutches rises in the high-speed zone. In order to evaluate the DT in such conditions, a two-phase air-fluid mathematical model for a DT with grooves was elaborated. The mathematical model was based on the theory of viscous fluid flow. A two-phase volume of fluid model was also used to investigate the distribution and volume fraction of air and fluid. Experiments on three friction plates with different grooves were conducted to validate the resulting mathematical model. It was found More >

Kazuhiko Kakuda^1,*, Tomoyuki Enomoto¹, Shinichiro Miura²

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.1, pp. 1-14, 2019, DOI:10.31614/cmes.2019.04676

Abstract The nonlinear activation functions in the deep CNN (Convolutional Neural Network) based on fluid dynamics are presented. We propose two types of activation functions by applying the so-called parametric softsign to the negative region. We use significantly the well-known TensorFlow as the deep learning framework. The CNN architecture consists of three convolutional layers with the max-pooling and one fully-connected softmax layer. The CNN approaches are applied to three benchmark datasets, namely, MNIST, CIFAR-10, and CIFAR-100. Numerical results demonstrate the workability and the validity of the present approach through comparison with other numerical performances. More >