Adhesion, friction, and wear of plasma-deposited thin silicon nitride films at temperatures to 700 C

The adhesion, friction, and wear behavior of silicon nitride films deposited by low- and high-frequency plasmas (30 kHz and 13.56 MHz) at various temperatures to 700 C in vacuum were examined. The results of the investigation indicated that the Si/N ratios were much greater for the films deposited at 13.56 MHz than for those deposited at 30 kHz. Amorphous silicon was present in both low- and high-frequency plasma-deposited silicon nitride films. However, more amorphous silicon occurred in the films deposited at 13.56 MHz than in those deposited at 30 kHz. Temperature significantly influenced adhesion, friction, and wear of the silicon nitride films. Wear occurred in the contact area at high temperature. The wear correlated with the increase in adhesion and friction for the low- and high-frequency plasma-deposited films above 600 and 500 C, respectively. The low- and high-frequency plasma-deposited thin silicon nitride films exhibited a capability for lubrication (low adhesion and friction) in vacuum at temperatures to 500 and 400 C, respectively

Visual-only recognition of normal, whispered and silent speech

Silent speech interfaces have been recently proposed as a way to enable communication when the acoustic signal is not available. This introduces the need to build visual speech recognition systems for silent and whispered speech. However, almost all the recently proposed systems have been trained on vocalised data only. This is in contrast with evidence in the literature which suggests that lip movements change depending on the speech mode. In this work, we introduce a new audiovisual database which is publicly available and contains normal, whispered and silent speech. To the best of our knowledge, this is the first study which investigates the differences between the three speech modes using the visual modality only. We show that an absolute decrease in classification rate of up to 3.7% is observed when training and testing on normal and whispered, respectively, and vice versa. An even higher decrease of up to 8.5% is reported when the models are tested on silent speech. This reveals that there are indeed visual differences between the 3 speech modes and the common assumption that vocalized training data can be used directly to train a silent speech recognition system may not be true

Time-dependent reduction of structural complexity of the buccal epithelial cell nuclei after treatment with silver nanoparticles

Recent studies have suggested that silver nanoparticles (AgNPs) may affect cell DNA structure in in vitro conditions. In this paper, we present the results indicating that AgNPs change nuclear complexity properties in isolated human epithelial buccal cells in a time-dependent manner. Epithelial buccal cells were plated in special tissue culture chamber / slides and were kept at 37°C in an RPMI 1640 cell culture medium supplemented with L-glutamine. The cells were treated with colloidal silver nanoparticles suspended in RPMI 1640 medium at the concentration 15 mg L−1. Digital micrographs of the cell nuclei in a sample of 30 cells were created at five different time steps: before the treatment (controls), immediately after the treatment, as well as 15 , 30 and 60 min after the treatment with AgNPs. For each nuclear structure, values of fractal dimension, lacunarity, circularity, as well as parameters of grey level co-occurrence matrix (GLCM) texture, were determined. The results indicate time-dependent reduction of structural complexity in the cell nuclei after the contact with AgNPs. These findings further suggest that AgNPs, at concentrations present in today's over-the-counter drug products, might have significant effects on the cell genetic material

Electron beam induced damage in PECVD Si3N4 and SiO2 films on InP

Phosphorus rich plasma enhanced chemical vapor deposition (PECVD) of silicon nitride and silicon dioxide films on n-type indium phosphide (InP) substrates were exposed to electron beam irradiation in the 5 to 40 keV range for the purpose of characterizing the damage induced in the dielectic. The electron beam exposure was on the range of 10(exp -7) to 10(exp -3) C/sq cm. The damage to the devices was characterized by capacitance-voltage (C-V) measurements of the metal insulator semiconductor (MIS) capacitors. These results were compared to results obtained for radiation damage of thermal silicon dioxide on silicon (Si) MOS capacitors with similar exposures. The radiation induced damage in the PECVD silicon nitride films on InP was successfully annealed out in an hydrogen/nitrogen (H2/N2) ambient at 400 C for 15 min. The PECVD silicon dioxide films on InP had the least radiation damage, while the thermal silicon dioxide films on Si had the most radiation damage

Influence of synaptic depression on memory storage capacity

Synaptic efficacy between neurons is known to change within a short time scale dynamically. Neurophysiological experiments show that high-frequency presynaptic inputs decrease synaptic efficacy between neurons. This phenomenon is called synaptic depression, a short term synaptic plasticity. Many researchers have investigated how the synaptic depression affects the memory storage capacity. However, the noise has not been taken into consideration in their analysis. By introducing "temperature", which controls the level of the noise, into an update rule of neurons, we investigate the effects of synaptic depression on the memory storage capacity in the presence of the noise. We analytically compute the storage capacity by using a statistical mechanics technique called Self Consistent Signal to Noise Analysis (SCSNA). We find that the synaptic depression decreases the storage capacity in the case of finite temperature in contrast to the case of the low temperature limit, where the storage capacity does not change

ELECTRO-ACOUSTIC ANALOGIES BETWEEN THERMOELASTIC COMPONENT OF THE PHOTOACOUSTIC SIGNAL AND LOW-PASS RC FILTER

This paper presents a new approach to the thermal characterization of aluminum, based on the electro-acoustic analogy between the thermoelastic component of the photoacoustic signal and the passive RC low-pass filter. The analogies were used to calculate the characteristic thermoelastic cut-off frequencies of the photoacoustic component and obtain their relationship with the thickness of the aluminum samples. Detailed numerical analysis showed that the required relationship is linear in the log-log scale and can serve as a reference curve for the given material. The results of the numerical analysis were also confirmed experimentally

Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema

In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011

Improvement of the realisation of the mass scale

The project 19RPT02“Improvement of the realisation of the mass scale”(EMPIR [1] Call 2019 –Energy, Environment, Normative and Research Potential)has just started.Its aim is to improve the quality of one of the most important tasksin mass metrology,the realisation of the mass scale. After the new definition of the kilogram this technique is getting more important

Recognition of Facial Expressions by Cortical Multi-scale Line and Edge Coding

Face-to-face communications between humans involve emotions, which often are unconsciously conveyed by facial expressions and body gestures. Intelligent human-machine interfaces, for example in cognitive robotics, need to recognize emotions. This paper addresses facial expressions and their neural correlates on the basis of a model of the visual cortex: the multi-scale line and edge coding. The recognition model links the cortical representation with Paul Ekman's Action Units which are related to the different facial muscles. The model applies a top-down categorization with trends and magnitudes of displacements of the mouth and eyebrows based on expected displacements relative to a neutral expression. The happy vs. not-happy categorization yielded a. correct recognition rate of 91%, whereas final recognition of the six expressions happy, anger, disgust, fear, sadness and surprise resulted in a. rate of 78%