21,719 research outputs found
A Review of silicon carbide development in MEMS applications
No full textDue to its desirable material properties, Silicon Carbide (SiC) hasbecome an alternative material to replace Si for MicroelectromechanicalSystems (MEMS) applications in harsh environments. To promote SiC MEMSdevelopment towards future cost-effective products, main technology areas inmaterial deposition and processes have attracted significant interest. Thedevelopments in these areas have contributed to the rapid emergence of SiCMEMS prototypes. In this paper, we give an overview of the importantdevelopments in SiC material formation and fabrication processes in recentyears. Some of the most interesting state-of-the-art SiC MEMS devices arereviewed. This highlights the major progresses in SiC MEMS developed thusfar. This paper also looks into the prospect of SiC MEMS drawing attention topotential issues
manymome: An R package for Computing the Indirect Effects, Conditional Effects, and Conditional Indirect Effects, Standardized or Unstandardized, and Their Bootstrap Confidence Intervals, in Many (Though Not All) Models
No full textCheung, S. F., & Cheung, S.-H. (2024). manymome: An R package for computing the indirect effects, conditional effects, and conditional indirect effects, standardized or unstandardized, and their bootstrap confidence intervals, in many (though not all) models. Behavior Research Methods, 56(5), 4862–4882. https://doi.org/10.3758/s13428-023-02224-
manymome: An R package for Computing the Indirect Effects, Conditional Effects, and Conditional Indirect Effects, Standardized or Unstandardized, and Their Bootstrap Confidence Intervals, in Many (Though Not All) Models
No full textCheung, S. F., & Cheung, S.-H. (2024). manymome: An R package for computing the indirect effects, conditional effects, and conditional indirect effects, standardized or unstandardized, and their bootstrap confidence intervals, in many (though not all) models. Behavior Research Methods, 56(5), 4862–4882. https://doi.org/10.3758/s13428-023-02224-
A wireless multimedia system
No full textThe complexity, robustness, image and speech quality as well as packet multiplexing issues of a reconfigurable multi-media mobile communicator are addressed. The proposed moderate complexity motion-compensated Discrete Cosine Transform (DCT) based image communicator provides an image peak signal-to-noise ratio (PSNR) of 38 dB at an average bit rate of about 25 kbits/s. The speech codec used is a low-complexity 32 kbit/s CCITT G721 standard scheme. Bandwidth efficient 16 or 64level quadrature amplitude modulation (QAM) combined with embedded low-complexity binary Bose-Chaudhuri-Hocquenghem (BCH) forward error correction coding is deployed. The 20-slot packet reservation multiple access (PRMA) scheme used supports an extra 2.4 kbit/s low-rate data channel for each speech user, in addition to providing 5-6 video-phone channels. The ADPCM/DCT/BCH/16-QAM as well as 64QAM schemes provide nearly unimpaired speech and image quality for channel SNRs in excess of 30 dB and 38 dB, respectively
Some Weighted Hardy-type Inequalities of Vector-Valued Functions
No full textBy adopting the C-technique of Cheung and Pečrić, we establish some interesting weighted Hardy-type inequalities of vector-valued functions. These generalize and improve some existing results of Cheung, Cheung-Hanjš-Pēcarić, Hanjš-Love-Pečarić, Levinson, and Pachpatte. [ABSTRACT FROM AUTHOR
R script for selection of the top ancestry-informative markers based on population differentiation potential
No full textSupplementary File S2. R script for selecting the top ancestry-informative markers based on the calculation of population differentiation potential using various metrics
betaDelta and betaSandwich: Confidence Intervals for Standardized Regression Coefficients in R
No full textResearch compendium for the manuscript Pesigan, I. J. A., Sun, R. W., & Cheung, S. F. (2023). betaDelta and betaSandwich: Confidence intervals for standardized regression coefficients in R. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2023.220127
semfindr: An R Package for Identifying Influential Cases in Structural Equation Modeling
No full textCheung, S. F., & Lai, M. H. C. (2026). semfindr: An R package for identifying influential cases in structural equation modeling. Multivariate Behavioral Research, 1–9. https://doi.org/10.1080/00273171.2026.2634293 (https://www.tandfonline.com/doi/abs/10.1080/00273171.2026.2634293
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