Influence of Temperature on Shockley Stacking Fault Expansion and Contraction in SiC PiN Diodes

While Shockley stacking fault (SSF) creation and expansion within 4H-SiC bipolar devices is well known, only recently was it observed that this expansion and the associated increase in the forward voltage drop (V _f) could be completely reversed via low-temperature annealing. Here we report the temperature dependence of the recovery rate of the V _f drift via annealing, reporting an activation energy of 1.3 ± 0.3 eV. The V _f drift was observed to saturate following extended electrical stressing, and it was observed that the value of V _f at this saturation was inversely proportional to the stressing temperature. We also observed that SSF and V _f drift recovery could occur in highly stressed diodes at elevated temperatures even under high current injection conditions (14 A/cm²).     

晶圆边缘的检测

随着特征尺寸的缩小,晶圆表面任何一部分都不允许闲置不用,器件越发地靠近边缘,因此对于晶圆的检查不能再忽视边缘。现有的检查平台必须升级以面对这种挑战。     

Suspended channel MEMS fabrication process for advanced device design and bio-analytical functionalization

This paper reports a simple and novel process that allows the fabrication of suspended channel MEMS devices. Two basic types of suspended structures were fabricated using the new process, and a possible functionalization mechanism for bio-analytical detection and sensing using spotting and capillary action was successfully tested.Possible uses of the fabricated structures are described, as specific existing types of biochemical MEMS sensors.     

Computation of diffusion function measures in q-space using magnetic resonance hybrid diffusion imaging

The distribution of water diffusion in biological tissues may be estimated by a 3-D Fourier transform (FT) of diffusion-weighted measurements in q-space. In this study, methods for estimating diffusion spectrum measures (the zero-displacement probability, the mean-squared displacement, and the orientation distribution function) directly from the q-space signals are described. These methods were evaluated using both computer simulations and hybrid diffusion imaging (HYDI) measurements on a human brain. The HYDI method obtains diffusion-weighted measurements on concentric spheres in q-space. Monte Carlo computer simulations were performed to investigate effects of noise, q-space truncation, and sampling interval on the measures. This new direct computation approach reduces HYDI data processing time and image artifacts arising from 3-D FT and regridding interpolation. In addition, it is less sensitive to the noise and q-space truncation effects than conventional approach. Although this study focused on data using the HYDI scheme, this computation approach may be applied to other diffusion sampling schemes including Cartesian diffusion spectrum imaging.     

Optical determination of the junction temperature of OLEDs

This paper describes a novel optical measurement technique for the in situ determination of the spatial temperature distribution at the organic layer level in large-area organic light-emitting diodes (OLEDs). The local junction temperature of OLEDs is a very important factor with respect to the luminance uniformity. Moreover the variation of local temperatures leads to a non-uniform depreciation of its light output, which in turn increases the luminance non-uniformity over time and affects the lifetime expectancy of the OLED.     

Short- and long-term joint symbolic dynamics of heart rate and blood pressure in dilated cardiomyopathy

Autonomic cardiovascular control involves complex interactions of heart rate and blood pressure. In patients with dilated cardiomyopathy (DCM), this control is impaired and parameters for its quantification might be of prognostic importance. In this paper, we introduce methods based on joint symbolic dynamics (JSD) for the enhanced analysis of heart rate and blood pressure interactions. To assess the coarse-grained dynamics beat-to-beat changes of heart rate and blood pressure are encoded in symbol strings. Subsequently, the distribution properties of short symbol sequences (words) as well as the scaling properties of the whole symbol string are assessed. The comparison of joint symbolic heart rate and blood pressure dynamics in DCM (n = 75) with those in healthy controls (n = 75) showed significant changes. Both, the distribution of words and the scaling properties indicate a loss in heart rate dynamics associated with blood pressure regulation in DCM. In conclusion, the analyses of short- and long-term JSDs provide insights into complex physiological heart rate and blood pressure interactions and furthermore reveal patho-physiological cardiovascular control in DCM.     

Primary User Emulation Detection Algorithm Based on Distributed Sensor Networks

In this paper, we propose a novel primary user emulation (PUE) detection approach which employs a distributed sensor network, where each sensor node operates as an independent PUE detector. Distributed nodes collaborate in order to obtain the final detection results for the whole network. A voting algorithm is used to improve the performance of energy detection, while the classification is conducted by the nearest node in order to improve the efficiency of the detector. As a result of voting, if a potential primary user exists, then the features of the unknown user is compared with entries from the database in order to obtain a solid detection match. An artificial neural network (ANN) is used for the classification of an unknown user. To assess the accuracy of the detection result, we implement a reliability check at the output of ANN. The proposed algorithm is validated via computer simulations as well as by experimental hardware implementations using the Universal Software Radio Peripheral (USRP) software-defined radio (SDR) platform. The experiment results show that the distributed network detector detects the PUE 180–200%, depending on the number of primary users, faster than single node detector.     

Application of kernel principal component analysis for single-lead-ECG-derived respiration

Recent studies show that principal component analysis (PCA) of heartbeats is a well-performing method to derive a respiratory signal from ECGs. In this study, an improved ECG-derived respiration (EDR) algorithm based on kernel PCA (kPCA) is presented. KPCA can be seen as a generalization of PCA where nonlinearities in the data are taken into account by nonlinear mapping of the data, using a kernel function, into a higher dimensional space in which PCA is carried out. The comparison of several kernels suggests that a radial basis function (RBF) kernel performs the best when deriving EDR signals. Further improvement is carried out by tuning the parameter σ(2) that represents the variance of the RBF kernel. The performance of kPCA is assessed by comparing the EDR signals to a reference respiratory signal, using the correlation and the magnitude squared coherence coefficients. When comparing the coefficients of the tuned EDR signals using kPCA to EDR signals obtained using PCA and the algorithm based on the R peak amplitude, statistically significant differences are found in the correlation and coherence coefficients (both p<0.0001), showing that kPCA outperforms PCA and R peak amplitude in the extraction of a respiratory signal from single-lead ECGs.     

Physiological parameter monitoring from optical recordings with a mobile phone

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal. We note that this technology can also be used with recently developed algorithms for detection of atrial fibrillation or blood loss.