Comprehensive nanostructural study of SSRM nanocontact on silicon

Scanning Spreading Resistance Microscopy electro-mechanical nanocontacts are nowadays well understood and numerous influent parameters have been identified (bias, load, surface state sample, radius of curvature of the tip). Despite several simulation and modelization possibilities, calibration curves are required to ensure reliable electrical characterizations. In this paper, we bring, through nanostructural studies (Scanning Transmission Electron Microscopy) of surface state of both SSRM tips and doped silicon surface a new understanding of tip-sample interaction during SSRM measurements. As a result of load, a nanometric residual amorphous silicon layer was observed which thickness depends on applied force and might be due to as well to the plastic transformation (Si to β-tin phase) as to plough-effect residues resulting from the tip indentation into the sample. It appears thus important in a failure analysis process to find the best compromise between stable electrical SSRM response and sample/tip surface degradation.     

Cadmium sulfide thin films growth by chemical bath deposition

Cadmium sulfide (CdS) thin films have been prepared by a simple technique such as chemical bath deposition (CBD).A set of samples CdS were deposited on glass substrates by varying the bath temperature from 55 to 75 ℃ at fixed deposition time (25 min) in order to investigate the effect of deposition temperature on CdS films physical properties.The determination of growth activation energy suggests that at low temperature CdS film growth is governed by the release of Cd2+ ions in the solution.The structural characterization indicated that the CdS films structure is cubic or hexagonal with preferential orientation along the direction (111) or (002),respectively.The optical characterization indicated that the films have a fairly high transparency,which varies between 55％ and 80％ in the visible range of the optical spectrum,the refractive index varies from 1.85 to 2.5 and the optical gap value of which can reach 2.2 eV.It can be suggested that these properties make these films perfectly suitable for their use as window film in thin films based solar cells.     

Geometric MMSE for one-sided and two-sided vector linear predictors: From the finite-length case to the infinite-length case

In the present paper we derive a formula for the geometric minimum mean square error (GMMSE) for one-sided and two-sided finite-length vector linear predictors. This formula is written only in terms of the autocorrelation matrix of the vector process being predicted. We also obtain a formula for the GMMSE for one-sided and two-sided infinite-length vector linear predictors of any wide sense stationary (WSS) vector process. This GMMSE expression for the infinite-length case is derived from the GMMSE expression obtained for the finite-length case.     

A Behavioral Model of MEMS Convective Accelerometers for the Evaluation of Design and Calibration Strategies at System Level

This paper presents a behavioral model that can be used to improve the manufacturability of systems based on MEMS convective sensors. This model permits to handle faults related to process scattering, taking into account not only the electrical and lateral geometrical parameters but also the influence of the cavity depth. Moreover correlations between conductive and convective phenomena are included. The model is validated with respect to FEM simulations and a very good agreement is obtained between the behavioral model and FEM results. The proposed model can then be used in system-level simulations, for instance to evaluate the impact of process scattering on the performances of the sensing part and/or to investigate different design and calibration strategies with respect to the system robustness.     

Gettering by heat thermal processing: application in crystalline silicon solar cells

The aim of this work is to getter unwanted impurities from solar grade crystalline silicon (Si) wafers and then to enhance their electronic properties. This was done by forming a sacrificial porous silicon (PS) layer on both sides of the Si wafers and by performing infrared (IR) thermal annealing treatments (at around 950 °C) in a SiCl₄/N₂ controlled atmosphere. The process allows concentrating unwanted impurities in the PS layer and near the PS/silicon interface. These treatments reduce the resistivity by about two orders of magnitude at a depth of about 40 μm and improve the minority carrier diffusion length from 75 to 210 μm. This gettering method was also tested on silicon wafers where grooved fingers and back contacts were achieved using a chemical vapor etching (CVE) method. Front buried metallic contacts and small holes for local back surface field were then achieved after the gettering stage in order to realize silicon solar cells. It was shown that the photovoltaic parameters of gettered silicon solar cells were improved as regard to ungettered ones.     

Bandwidth Aspects in Second Generation Current Conveyors

This paper discusses bandwidth problems associated with second-generation current conveyors (CCII). In particular, our work is centered in high-capacitance applications, and has been oriented for wireless optical links and applied physics. We discuss techniques for improving bandwidth in these CCIIs, and develop a new CCII structure with larger bandwidth than traditional circuits. These circuits are then compared in terms of their noise and dynamic range characteristics. A test circuit was developed to verify these different bandwidth behaviors.     

Anti-aliasing weighting functions for single-slice helical CT

Spatially variant longitudinal aliasing plagues most volumes reconstructed from single-slice helical computed tomography data, and its presence can degrade resolution and distort image structures. We have recently developed a Fourier-based approach to longitudinal interpolation in helical computed tomography that can, for scans performed at pitch 1 or lower, essentially eliminate this longitudinal aliasing by exploiting a generalization of the Whittaker-Shannon sampling theorem whose conditions are satisfied by the interlaced pairs of direct and complementary longitudinal samples. However, the algorithm is computationally intensive and cannot be pipelined. In this paper, we address this shortcoming by deriving two spatial-domain, projection-data weighting functions that approximate the application of the Fourier-based approach, and preserve its aliasing suppression properties to some degree, while allowing for a pipelined implementation. The first approach, which we call simply 180AA, for anti-aliasing, is a direct spatial-domain approximation of the 180FT approach. The second approach, which we call 180BSP, is based on an approximate generalized interpolation approach making use of B-splines. Studies of aliasing and resolution properties in reconstructions from simulated data indicate that while the 180AA and 180BSP approaches do not perfectly replicate the favorable aliasing suppression and resolution properties of the 180FT approach, they do represent an improvement over the clinically standard 180LI approach on these fronts.     

Automatic detection of pathological voices using complexity measures, noise parameters, and mel-cepstral coefficients

This paper proposes a new approach to improve the amount of information extracted from the speech aiming to increase the accuracy of a system developed for the automatic detection of pathological voices. The paper addresses the discrimination capabilities of 11 features extracted using nonlinear analysis of time series. Two of these features are based on conventional nonlinear statistics (largest Lyapunov exponent and correlation dimension), two are based on recurrence and fractal-scaling analysis, and the remaining are based on different estimations of the entropy. Moreover, this paper uses a strategy based on combining classifiers for fusing the nonlinear analysis with the information provided by classic parameterization approaches found in the literature (noise parameters and mel-frequency cepstral coefficients). The classification was carried out in two steps using, first, a generative and, later, a discriminative approach. Combining both classifiers, the best accuracy obtained is 98.23% ± 0.001.     

Evaluating Bluetooth Low Energy Suitability for Time-Critical Industrial IoT Applications

In recent years, integration of wireless sensor networks in industrial environments has greatly increased. With this trend, new fields such as industrial IoT have arisen, which in turn have opened the doors to new possibilities that are shaping the future of industrial automation. In contrast to regular wireless networks, however, industrial applications of WSN are characterized for being time-critical systems with highly stringent requirements that challenge all available technologies. Because of its ultra-low energy properties, compatibility with most mobile units, reduced production costs, robustness and high throughput, Bluetooth low energy (BLE) is a potential candidate for these settings. This article explores the potential of BLE of meeting the real-time demands found in the domain of industrial process automation and industrial IoT. In order to evaluate the suitability of the protocol for these scenarios, the effect of adaptations in the retransmission scheme on the reliability and timeliness performance are thoroughly studied. Three retransmission schemes are evaluated and simulation results proved that by optimally modifying the BLE retransmission model, a maximum delay below 46 ms and a packet loss rate in the order of \(10^{-5}\) can be obtained, enabling BLE to fulfill the requirements of even the most demanding cases within the considered range of applications.     

Automatic identification of the pectoral muscle in mammograms

The pectoral muscle represents a predominant density region in most medio-lateral oblique (MLO) views of mammograms; its inclusion can affect the results of intensity-based image processing methods or bias procedures in the detection of breast cancer. Local analysis of the pectoral muscle may be used to identify the presence of abnormal axillary lymph nodes, which may be the only manifestation of occult breast carcinoma. We propose a new method for the identification of the pectoral muscle in MLO mammograms based upon a multiresolution technique using Gabor wavelets. This new method overcomes the limitation of the straight-line representation considered in our initial investigation using the Hough transform. The method starts by convolving a group of Gabor filters, specially designed for enhancing the pectoral muscle edge, with the region of interest containing the pectoral muscle. After computing the magnitude and phase images using a vector-summation procedure, the magnitude value of each pixel is propagated in the direction of the phase. The resulting image is then used to detect the relevant edges. Finally, a post-processing stage is used to find the true pectoral muscle edge. The method was applied to 84 MLO mammograms from the Mini-MIAS (Mammographic Image Analysis Society, London, U.K.) database. Evaluation of the pectoral muscle edge detected in the mammograms was performed based upon the percentage of false-positive (FP) and false-negative (FN) pixels determined by comparison between the numbers of pixels enclosed in the regions delimited by the edges identified by a radiologist and by the proposed method. The average FP and FN rates were, respectively, 0.58% and 5.77%. Furthermore, the results of the Gabor-filter-based method indicated low Hausdorff distances with respect to the hand-drawn pectoral muscle edges, with the mean and standard deviation being 3.84 +/- 1.73 mm over 84 images.