http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Le Vu Truong Son (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
Relaxor characteristics of PSLZT-BMT-based ferroelectric material ceramics
Nguyen Van Thinh,Le Dai Vuong,Do Viet On,Truong Van Chuong,Le Vu Truong Son,Trinh Ngoc Dat,Le Van Thanh Son,Vo Thanh Tung 한양대학교 청정에너지연구소 2023 Journal of Ceramic Processing Research Vol.24 No.3
(1-x)[(Pb0.94Sr0.05La0.01)(Zr0.54Ti0.46)0.9975O3]-x[Bi(Mn1/2Ti1/2)O3] (PSLZT-BMT) ferroelectric material ceramics with x in therange of 0-0.05 mol were successfully synthesized following the conventional solid-phase route. The materials were thoroughlyinvestigated to study their structural phase, microstructure, ferro-piezoelectric characteristics, and dielectric behavior. Theexperimental results show that the density of the samples decreased from 7.75 to 7.58 g/cm3, and the relative density decreasedin the range of 98.48%-96.28%. However, with increasing contents of BMT, the dielectric and ferroelectric properties ofPSLZT-BMT ceramics tend to decrease, specifically the maximum dielectric constant (εmax) of PSLZT-BMT decreased in therange of 23579-9991 and the residual polarization (Pr) decreases in the range of 22.54-7.87 μC/cm2 when the doping contentincreased in the range of 0.0-0.05 mol. The diffusivity values (γ) of the PSLZT-BMT material are 1.74, 1.78, 1.82, 1.84, 1.79,and 1.77 when the doping content x varies as 0.0, 0.01, 0.02, 0.03, 0.04, and 0.05 mol, respectively, which is characteristic ofrelaxor ferroelectric materials. Besides, the Tm, TB, TC-W, and C values depend on BMT concentration, and the trend decreases.
-
A Low-Cost Speech to Sign Language Converter
Le, Minh,Le, Thanh Minh,Bui, Vu Duc,Truong, Son Ngoc International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.3
This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
