Predictively encoded graph convolutional network for noise-robust skeleton-based action recognition

Applied Intelligence - In skeleton-based action recognition, graph convolutional networks (GCNs), which model human body skeletons using graphical components such as nodes and connections, have...     

Frictional properties of VA‐mode alignment‐film surfaces studied by frictional force microscopy

Abstract— The surface‐friction characteristics of the post‐bake temperature were compared to that of the rubbing condition on VA‐mode alignment films (AFs) using frictional force microscopy (FFM). The surface roughness and the surface frictional force increased when the temperature was elevated. However, the frictional asymmetry could not be detected by the frictional loop due to the instability of the side‐chain molecular arrangement. For the inter‐influences of the total friction and surface roughness, the density of the side chain was changed and it was intentionally rubbed for evaluation. The results showed that the total friction was higher when the rubbing was stronger and side‐chain density lower, and the surface roughness also increased in the same manner. This can be explained by the potential interaction due to the curved structure of the side‐chain surface that establishes the probe that is scanned and the top surface layer. In order to confirm the influence of the pre‐tilt angle on the tilt of the side chain, a test cell was produced under the same conditions and evaluated. The results showed that the pre‐tilt‐angle decreased according to the difference in density of the side chain and strength of rubbing after injecting liquid‐crystal (LC).     

Study of polymer‐network structure on polymer‐stabilized blue phase

Abstract— To understand the mechanism of the disclination defect of the liquid‐crystal (LC) phase, this study was conducted to directly analyze the polymer‐network (PN) structure of polymer‐stabilized blue phase (PSBP), which is minutely formed on all LC layers. The PN was examined after first removing the glass decap and then the LC. Important to note is that the removal of the glass decap did not affect or damage the PN structure. The PN was determined to be a stable structure without any change to the thickness of the layer. When removing the LC, both hexane and acetone solutions were used. Moreover, there was no structural deformation to the PN when using the hexane solution. The results of the study show that the actual size of the polymer chain is in fact 50–60 nm, five times larger than previous theories which estimated the size to be only 10 nm. In addition, this study confirmed that the pores between the PN are 100–200 nm. The PN structure was shown to be susceptible to change based on different heating temperatures. In summation, now that defect lines of a LC display (LCD) could be directly measured, further progress and development in the theoretical interpretations of the Kerr effect on PSBP can be realized.     

Individual,social, and organizational contexts for active knowledge sharing in communities of practice

Firms that have implemented knowledge management initiatives are now interested in nurturing voluntary knowledge sharing organizations, called communities of practice (CoPs). Adopting the Triandis model on attitude formation, we identified and validated a set of organizational factors that was anticipated to have effects on knowledge sharing by CoP members such as perceived consequences, affect, social factors and facilitating conditions. One hundred and seventy-nine members from 70 CoPs of a large multinational electronics firm participated in this survey. Based on the PLS analysis, perceived consequences, affect, social factors, and facilitating conditions were found to significantly affect knowledge sharing in CoPs.     

An index of applicability for the decomposition method ofmultivariable fuzzy systems

Research on the application of fuzzy set theory to the design of control systems has led to interest in decomposition of multivariable fuzzy systems. Decomposition of multivariable control rules is preferable since it alleviates the complexity of the problem, but the inference error is inevitable because of its approximate nature. In this paper we show that a large inference error is generated when the Gupta's decomposition method (1986) is applied to Exclusive-nor (ENOR) gate model which is used as a counter example. We define an index of applicability which can classify whether the decomposition method can be applied to a multivariable fuzzy system or not     

Leakage current in a Si-based nanopore structure and its influence on noise characteristics

We have measured leakage current in a silicon substrate-based nanopore membrane device immersed in an aqueous environment which typically shows the current level of few nA. This current level is compared with the measured current density (400 nA/cm² at 1 V) from the pristine Si wafer (p-type, 10¹⁶/cm³ boron doping) indicating that the exposed Si surface in a nanopore membrane device acts as an electrochemical reaction site. The leakage current is drastically reduced from >10 nA to <100 pA at 1 V by the deposition of a dielectric layer to the Si-based nanopore membrane device. We also noted that the root-mean-square noise of the ionic current is also reduced from 38 to 28 pA in correlation with the reduction of leakage current, indicating that electrochemical reaction provides one of the major sources of noise.     

Influence of wall charge distribution on time lag of address discharge in AC plasma display panels

The influence of wall charge distribution on the time lag of address discharge in an AC plasma display panel is investigated using two different reset waveforms: one (typical reset) induces both face and surface discharges and the other (TR reset) induces face discharges only. The measured formative time lag and statistical time lag of address discharge for TR were 21–31 ns and 31–74 ns shorter than the one for the typical reset, respectively. The TR reset resulted in much less increase of statistical time lag than the typical reset when the reset-to-address time interval was increased, and 70 ns smaller deviation of the statistical time lag among different color cells. Calculations show that the TR reset forms a much smoother wall charge profile, which is less susceptible to cell parameter variations, than the typical reset. The observed differences in the time lags of address discharge between different scan lines and color cells are strongly correlated to the differences of the wall charge profile, indicating that a smooth wall charge profile formed by the reset using face discharges only reduces the time lag of address discharge and minimizes the susceptibility of address discharge to cell parameter variation.     

Analog piezoelectric-driven tunable gratings with nanometer resolution

This work presents the design, fabrication, and characterization of a piezoelectrically actuated MEMS diffractive optical grating, whose spatial periodicity can be tuned in analog fashion to within a fraction of a nanometer. The fine control of the diffracted beams permits applications in dense wavelength-division multiplexing (DWDM) optical telecommunications and high-resolution miniaturized spectrometers. The design concept consists of a diffractive grating defined on a deformable membrane, strained in the direction perpendicular to the gratings grooves via thin-film piezoelectric actuators. The tunable angular range for the first diffracted order is up to 400 /spl mu/rad with 0.2% strain (/spl sim/8 nm change in grating periodicity) at 10 V actuation, as predicted by device modeling. The actuators demonstrate a piezoelectric d/sub 31/ coefficient of -100 pC/N and dielectric constant /spl epsiv//sub r/ of 1200. Uniformity across the tunable grating and the out-of-plane deflections are also characterized and discussed.     

Estimating plot volume using lidar height and intensity distributional parameters

This study explored the feasibility of height distributional metrics and intensity values extracted from low-density airborne light detection and ranging (lidar) data to estimate plot volumes in dense Korean pine (Pinus koraiensis) plots. Multiple linear regression analyses were performed using lidar height and intensity distributional metrics. The candidate variables for predicting plot volume were evaluated using three data sets: total, canopy, and integrated lidar height and intensity metrics. All intensities of lidar returns used were corrected by the reference distance. Regression models were developed using each data set, and the first criterion used to select the best models was the corrected Akaike Information Criterion (AIC_c). The use of three data sets was statistically significant at R² = 0.75 (RMSE = 52.17 m³ ha^?1), R² = 0.84 (RMSE = 45.24 m³ ha^?1), and R² = 0.91 (RMSE = 31.48 m³ ha^?1) for total, canopy, and integrated lidar distributional metrics, respectively. Among the three data sets, the integrated lidar metrics-derived model showed the best performance for estimating plot volumes, improving errors up to 42% when compared to the other two data sets. This is attributed to supplementing variables weighted and biased to upper limits in dense plots with more statistical variables that explain the lower limits. In all data sets, intensity metrics such as skewness, kurtosis, standard deviation, minimum, and standard error were employed as explanatory variables. The use of intensity variables improved the accuracy of volume estimation in dense forests compared to prior research. Correction of the intensity values contributed up to a maximum of 58% improvement in volume estimation when compared to the use of uncorrected intensity values (R² = 0.78, R² = 0.53, and R² = 0.63 for total, canopy, and integrated lidar distributional metrics, respectively). It is clear that the correction of intensity values is an essential step for the estimation of forest volume.