Browsing by Author "Huang, Yi-Cheng"

Now showing 1 - 5 of 5

A FINITE-VOLUME-BASED APPROACH FOR DYNAMIC FLUID-STRUCTURE INTERACTION
(2013)
Tsui, Yeng-Yung
;
Huang, Yi-Cheng
;
Huang, Chun-Lung
;
Lin, Shi-Wen
;
機械工程學系
It is common to adopt finite-element methods to solve solid mechanics problems and finite-volume methods for fluid dynamics computations. The use of different methods causes complication of the solution procedure for problems involving both fluids and solids. In this study, a partitioned approach based on the finite-volume method for dynamic fluid-structure interaction is presented. The method is formulated in a way suitable for an unstructured mesh with arbitrary grid geometry. The variables for the fluid are stored at the centroids of grid cells, whereas those for the solid at the grid nodes. The latter arrangement makes it more suitable for large structure deformation. After spatial discretization for the solid using the finite-volume approach, the resulting system of ordinary differential equations is solved implicitly using the dual-time-stepping scheme. As for the fluid calculation, a pressure-based algorithm is employed and the time step is advanced in a prediction-correction manner. The finite-volume method for the solid is assessed by calculating the deformation and dynamics of a cantilever under various loads. Good agreement with analytical solutions is obtained. Then, the solution procedure is applied to two cases with coupled fluid flow and structure dynamics. One is the flow over a vertical plate with one end fixed on the floor in a channel. The other is the flow over a cylinder with a plate attached to it on the lee side.
A PITCH BASED VAD ADOPTING QUASI-ANSI 1/3 OCTAVE FILTER BANK WITH 11.3 ms LATENCY FOR MONOSYLLABLE HEARING AIDS
(2013)
Huang, Yi-Cheng
;
Yi FanChiang
;
Jou, Shyh-Jye
;
電子工程學系及電子研究所
;
Department of Electronics Engineering and Institute of Electronics
This paper presents a pitch based voice activity detection (PBVAD) algorithm adopting a quasi-ANSI 1/3 octave filter bank which has low group delay for realistic implementation in hearing aids systems. For compensating the drawback of low resolution resulted from quasi-ASNI filter bank, this pitch based VAD algorithm integrals the features of monosyllable speech such as pitch and corresponding harmonics, onset and time of word length. Simulation results reveal that with more harmonics detection, the accuracy of the proposed PBVAD algorithm improves from 78.9% to 87.7%. Additionally, the proposed VAD algorithm is implemented in ANSI filter bank for comparisons. With the integration of features, the result shows the proposed algorithm can achieve similar VAD accuracy, less than 2.5%, in quasi-ANSI filter bank and ANSI filter bank. Thus, the proposed algorithm can tackle the drawback of quasi-ANSI filter bank and is also suitable for ANSI filter bank. Moreover, the latency incurred by quasi-ANSI filter bank and the proposed VAD algorithm is 11.3ms and this satisfies the requirement of HA systems for practical implementation.
Enhanced mixing via alternating injection in radial Hele-Shaw flows
(2015-10-07)
Chen, Ching-Yao
;
Huang, Yi-Cheng
;
Huang, Yu-Sheng
;
Miranda, Jose A.
;
機械工程學系
Mixing at low Reynolds numbers, especially in the framework of confined flows occurring in Hele-Shaw cells, porous media, and microfluidic devices, has attracted considerable attention lately. Under such circumstances, enhanced mixing is limited due to the lack of turbulence, and absence of sizable inertial effects. Recent studies, performed in rectangular Hele-Shaw cells, have demonstrated that the combined action of viscous fluid fingering and alternating injection can dramatically improve mixing efficiency. In this work, we revisit this important fluid mechanical problem, and analyze it in the context of radial Hele-Shaw flows. The development of radial fingering instabilities under alternating injection conditions is investigated by intensive numerical simulations. We focus on the impact of the relevant physical parameters of the problem (Peclet number Pe, viscosity contrast A, and injection time interval Delta t) on fluid mixing performance.
Forecasting Interaction of Exchange Rates Between Fiat Currencies and Cryptocurrencies Based on Deep Relation Networks
(2019-01-01)
Chen, Chiao-Ting
;
Chiang, Lin-Kuan
;
Huang, Yi-Cheng
;
Huang, Szu-Hao
;
資訊管理與財務金融系註：原資管所+財金所
Forecasting exchange rates is difficult because financial time-series data is too complicated to analyze. In traditional financial studies, economic models and statistic approaches were widely used for predicting exchange rates. Recently, machine learning and deep learning techniques have played increasingly important roles in financial technology studies. This study adopts a deep learning technique called relation networks (RNs) to predict the exchange rates of fiat currencies and cryptocurrencies. To discover the relationship among different currencies, the concept of visual question answering (VQA) is applied in RNs. We also propose a specially designed architecture for the feature extraction stage to consider both spatial and temporal relationships simultaneously. The experimental results show that the proposed approach can achieve higher prediction performance for cryptocurrencies with approximately 65% accuracy rate. We aim to improve traditional approaches and construct a model using the concept of VQA based on RNs to optimize the prediction performance between fiat currencies and cryptocurrencies.
Neuromorphic Pitch Based Noise Reduction for Monosyllable Hearing Aid System Application
(2014-02-01)
Chen, Yu-Jui
;
Wei, Cheng-Wen
;
Yi FanChiang
;
Meng, Yi-Le
;
Huang, Yi-Cheng
This paper presents a low computational complexity hardware-oriented neuromorphic pitch based noise reduction (NR) algorithm and hardware implementation for monosyllable hearing aid system applications. The proposed NR design consists of a pitch-based voice activity detector (pitch-based VAD) for speech detection and a neuromorphic noise attenuator for speech enhancement. The pitch-based VAD is developed on ANSI S1.11 based filter bank architecture and employs the characteristics of monosyllable and nonlinear energy operator (NEO) to improve the accuracy of VAD. The neuromorphic noise attenuator reduces the background noise by using the characteristics of human hearing system and the clues of speech. Simulation results show that the proposed algorithm has better SNR and PESQ performance than other non-pitch based NR algorithms in non-stationary background noise environments. Compared with multiband (mband) spectral subtraction and minimum mean square error (mmse) algorithms, the computational complexity of the proposed algorithm can save 90% computational complexity. The hardware implementation consumes 47.74 mu W at 0.5 V operation with 65 nm HVT standard cell library.