Generalized Eigenvalue Decomposition Applied to Estimation of Spatial rPPG Distribution of Skin

Journal of Mathematical Imaging and Vision - Remote photoplethysmography (rPPG) has been at the forefront recently, thanks to its capacity in estimating non-contact physiological parameters such as...     

Single mask fabrication process for movable MEMS devices

The current work reports on the realization of movable micromachining devices using self-aligned single-mask fabrication process. Only dry etching process utilizing inductively coupled plasma reactive ion etching was used to release 3D micro structures from single crystal silicon substrate. No wet etching process is required to release the structures as is the case with silicon on insulator (SOI) wafers. Also the developed process does not require an SOI substrate and accordingly dispensing with the application of a wet etching step, thus yielding uniform structures without stiction. The optimized process was applied to realize thermally actuated microgrippers. The article presents the development of the fabrication process and demonstrates the operation of the fabricated device. The optimized process provides an avenue for low cost fabrication of movable micromachining devices without the use of complicated wet etching steps typically associated with SOI substrates.     

Representation and estimation of spectral reflectances using projection on PCA and wavelet bases

In this article, we deal with the problem of spectral reflectance function representation and estimation in the context of multispectral imaging. Because the reconstruction of such functions is an inverse problem, slight variations in input data completely skew the expected results. Therefore, stabilizing the reconstruction process is necessary. To do this, we propose to use wavelets as basis functions, and we compare those with Fourier and PCA bases. We present the idea and compare these three methods, which belong to the class of linear models. The PCA method is training‐set dependent and confirms its robustness when applied to reflectance estimation of the training sets. Fourier and wavelet bases allow good generalization; an advantage of wavelets is that they avoid boundary artifacts. The results are evaluated with the commonly used goodness‐of‐fit coefficient (GFC), and the reliability of the use of wavelets is proved. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 485–493, 2008     

Modeling the performance of a micromachined piezoelectric energy harvester

Piezoelectric energy microgenerators are devices that generate continuously electricity when they are subjected to varying mechanical strain due to e.g. ambient vibrations. This paper presents the mathematical analysis, modelling and validation of a miniaturized piezoelectric energy harvester based on ambient random vibrations. Aluminium nitride as piezoelectric material is arranged between two electrodes. The device design includes a silicon cantilever on which AlN film is deposited and which features a seismic mass at the end of the cantilever. Euler–Bernoulli energy approach and Hamilton’s principle are applied for device modeling and analysis of the operation of the device at various acceleration values. The model shows good agreement with the experimental findings, thus giving confidence into model. Both mechanical and electrical characteristics are considered and compared with the experimental data, and good agreement is obtained. The developed analytical model can be applied for the design of piezoelectric microgenerators with enhanced performance.     

Polycarbonate/silica nanocomposite membranes: Fabrication,characterization, and performance evaluation

Polycarbonate/silica nanocomposite membranes at low silica loading were fabricated by solution blending and solvent evaporation technique. The functionalized silica nanoparticles used were synthesized by co‐condensing hydrolyzed tetraethylorthosilicate with 3‐aminopropyl trimethoxysilane in the sol–gel process. The membranes morphology, composition, surface, structure, thermal and mechanical properties were analyzed by the standard characterization techniques. The gas permeation tests were conducted in four‐channel permeation cells. Field emission scanning electron microscopy results reveal that membranes above 3 wt % silica content formed distinguishable voids and agglomerates. Fair distribution of silica nanoparticles and absence of residual solvents were observed by energy dispersive X‐ray and thermogravimetric analysis. Fourier transform infrared spectroscopy spectra confirmed the presence of new functional groups (N? H) and (O? H) bonds. The X‐ray diffraction pattern revealed the polymer‐particle interactions, the formation of rigidified polymer chain, and nanostructured silicon crystals. Further, the thermogravimetric analysis results revealed thermal stability enhancement while differential scanning calorimetry results of increased glass transition temperatures confirmed the presence of rigidified polymer chain. Furthermore, enhancements in mechanical strength of the membranes were observed. Moreover, at all feed pressures, increased CO₂, N₂, and CH₄ gas permeation was observed. At 6 bar feed pressure, the CO₂/N₂ and CO₂/CH₄ ideal selectivities of PC membranes with 3 wt % silica loading have increased from 19.2 to 38.0 and 29.2, respectively. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 45310.     

Design,fabrication and testing of a piezoelectric energy microgenerator

This article presents the design, fabrication and characterization of a micromachined energy harvester utilizing aluminium nitride (AlN) as a piezoelectric thin film material for energy conversion of random vibrational excitations. The harvester was designed and fabricated using silicon micromachining technology where AlN is sandwiched between two electrodes on top of a silicon cantilever beam which is terminated by a silicon seismic mass. The harvester generates electric power when subjected to mechanical vibrations. The generated electrical response of the device was experimentally evaluated at various acceleration levels. A maximum power of 34.78 μW was obtained for the device with a seismic mass of 5.6 × 5.6 mm² at an acceleration value of 2 g. Various fabricated devices were tested and evaluated in terms of the generated electrical power as well as the resonant frequency.     

Improved process monitoring using the CUSUM and EWMA-based multiscale PCA fault detection framework

Process monitoring techniques are of paramount importance in the chemical industry to improve both the product quality and plant safety. Small or incipient irregularities may lead to severe degradation in complex chemical processes, and the conventional process monitoring techniques cannot detect these irregularities. In this study to improve the performance of monitoring, an online multiscale fault detection approach is proposed by integrating multiscale principal component analysis (MSPCA) with cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts. The new Hotelling's T² and square prediction error (SPE) based fault detection indices are proposed to detect the incipient irregularities in the process data. The performance of the proposed fault detection methods was tested for simulated data obtained from the CSTR system and compared to that of conventional PCA and MSPCA based methods. The results demonstrate that the proposed EWMA based MSPCA fault detection method was successful in detecting the faults. Moreover, a comparative study shows that the SPE-EWMA monitoring index exhibits a better performance with lower values of missed detections ranging from 0% to 0.80% and false alarms ranging from 0% to 21.20%.