The reliability of amorphous-InGaZnO4 thin film transistor influence by self-heating stress at high temperature under compressive strain

Flexible thin-film transistors (TFTs) play an important role in flexible technology applications, including wearable devices and high-resolution foldable displays and as curved displays. A reliability test was performed in this work, including mechanism and electrical stress at high temperature. An abnormal hump can be found in flexible a-InGaZnO4 TFTs after a self-heating stress at 90°C under compressive bending. COMSOL simulation confirmed that the etching stop layer absorbs more mechanism stress than the gate insulator. Accordingly, during the reliability stress, holes induced by the impact ionization tend to inject into the defect in the etching stop layer near the source side rather than the gate insulator, which is induced by compressive bending. Single side C-V measurement and forward/reverse-operation mode are utilized to analyze the hole trapping distribution. Please click Additional Files below to see the full abstract

InQSS: a speech intelligibility and quality assessment model using a multi-task learning network

Speech intelligibility and quality assessment models are essential tools for researchers to evaluate and improve speech processing models. However, only a few studies have investigated multi-task models for intelligibility and quality assessment due to the limitations of available data. In this study, we released TMHINT-QI, the first Chinese speech dataset that records the quality and intelligibility scores of clean, noisy, and enhanced utterances. Then, we propose InQSS, a non-intrusive multi-task learning framework for intelligibility and quality assessment. We evaluated the InQSS on both the training-from-scratch and the pretrained models. The experimental results confirm the effectiveness of the InQSS framework. In addition, the resulting model can predict not only the intelligibility scores but also the quality scores of a speech signal.Comment: accepted by Insterspeech 202

Stability of filled cylindrical shell columns

This experimental investigation was conducted to study the stability of filled cylindrical shell columns. Two kinds of filler materials, flower clay (florist clay) and silica sand, were investigated. The cylindrical shells were made of 2024-T3 Reynolds aluminum tubing. Uniaxial compressive loading was applied directly to the filler materials through two loading rams, one at each end of the cylinder, (no loading was applied directly to the shell). Tests for investigating the load transmitting characteristics of the filler materials were performed, and the states of the stresses existing in the cylindrical shells were then obtained. The buckling formula for thin-walled cylindrical shells under internal hydrostatic pressure was compared with the experimental results of the cylinders filled with clay. The theory for thin-walled cylinders subjected to direct uniaxial compressive loading on the shells was compared with the results for the sand filled cylinders. It was necessary to introduce a reduction factor for effective length when sand was used the filler material. The tangent modulus formula was chosen to predict the buckling load of the filled cylinders beyond the elastic range of the material. The experimental results were found to be in good agreement with the theoretically predicted curves. Comparisons of the theoretical and experimental buckling loads are given graphically as functions of the length and the reciprocal of the square of the length --Abstract, pages ii-iii

Voice Conversion Based on Cross-Domain Features Using Variational Auto Encoders

An effective approach to non-parallel voice conversion (VC) is to utilize deep neural networks (DNNs), specifically variational auto encoders (VAEs), to model the latent structure of speech in an unsupervised manner. A previous study has confirmed the ef- fectiveness of VAE using the STRAIGHT spectra for VC. How- ever, VAE using other types of spectral features such as mel- cepstral coefficients (MCCs), which are related to human per- ception and have been widely used in VC, have not been prop- erly investigated. Instead of using one specific type of spectral feature, it is expected that VAE may benefit from using multi- ple types of spectral features simultaneously, thereby improving the capability of VAE for VC. To this end, we propose a novel VAE framework (called cross-domain VAE, CDVAE) for VC. Specifically, the proposed framework utilizes both STRAIGHT spectra and MCCs by explicitly regularizing multiple objectives in order to constrain the behavior of the learned encoder and de- coder. Experimental results demonstrate that the proposed CD- VAE framework outperforms the conventional VAE framework in terms of subjective tests.Comment: Accepted to ISCSLP 201

Air resistance of cylinder combinations

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautical Engineering, 1916.by Tsao Yu, Tsoo Wong.M.S