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.     

Passivation of the facets of 980 nm GaAs pump lasers by a pulsed UV laser-assisted technique

It is reported on the passivation of the mirror facets, opened in the air, of ridge waveguide InGaAs/GaAs/AlGaAs single quantum well (λ=980 nm) laser diodes. The passivation concept consists of two steps, namely, oxide removal by irradiation of the mirror facets with a pulsed KrF laser, immediately followed by the deposition of a thin silicon layer. The experimental arrangement (the process operation and the aging behavior-resistance to catastrophic optical damage) of the lasers thus treated are described. The structural modification of the laser facets, as probed by micro-Raman spectroscopy and Rutherford backscattering spectroscopy, and the calibration technique used to assess the rate of oxide removal are also presented.     

Power consumption reduction through elastic data rate adaptation in survivable multi-layer optical networks

Network survivability requires the provisioning of backup resources in order to protect active traffic against any failure scenario. Backup resources, however, can remain unused most of the time while the network is not in failure condition, inducing high power consumption wastage, if fully powered on. In this paper, we highlight the power consumption wastage of the additional resources for survivability in IP/multi-protocol label switching (MPLS) over dense wavelength division multiplexing multi-layer optical networks. We assume MPLS protection switching as the failure recovery mechanism in the network, a solution interesting for current network operators to ensure fast recovery as well as fine-grained recovery treatment per label switched path. Next, we quantitatively show how elastic optical technologies can effectively reduce such a power consumption by dynamically adjusting the data rate of the transponders to the carried amount of traffic.     

On the Complexity of Distributed Self-Configuration in Wireless Networks

We consider three distributed configuration tasks that arise in the setup and operation of multi-hop wireless networks: partition into coordinating cliques, Hamiltonian cycle formation and conflict-free channel allocation. We show that the probabilities of accomplishing these tasks undergo zero-one phase transitions with respect to the transmission range of individual nodes. We model these tasks as distributed constraint satisfaction problems (DCSPs) and show that, even though they are NP-hard in general, these problems can be solved efficiently on average when the network is operated sufficiently far from the transition region. Phase transition analysis is shown to be a useful mechanism for quantifying the critical range of energy and bandwidth resources needed for the scalable performance of self-configuring wireless networks.     

An energy efficient middleware for an ad-hoc AAL wireless sensor network

DIA (Dispositivo Inteligente de Alarma, in Spanish) is an AAL (Ambient Assisted Living) system that allows to infer a potential dangerous action of an elderly person living alone at home. This inference is obtained by a specific sensorisation with sensor nodes (portables and fixes) and a reasoning layer embedded in a PC that learns of the users behaviour patterns and advices when actual one differs significantly of the normal patterns. In AAL systems, energy is a limited resource therefore sensor devices need to be properly managed to conserve energy. In this paper, we introduce the design and implementation of innovative and specific mechanisms at the sensory layer middleware which is capable of, first to discriminate spurious motion detections assuming that these signals do not resemble the patterns of real motion detections and, second to reduce the dynamics of messages by a sensor signal processing in order to compress the whole information in one single event. The middleware achieves power saving by modifying the raw information from sensors and adapting it to the predefined semantic of the reasoning layer. It manages the important task of data processing from sensors (raw information), and transfers the pre-processed information into the top layer of reasoning in a more energy efficient way. We also address the trade-off between reducing power consumption and reducing delay for incoming data. We present results from experiments using our implementation of these mechanisms at the middleware that comprises from node firmware to the PC driver. The number of messages of the proposed method with respect to the raw data is reduced by approximately 98.5%. The resources used in the PIR signal processing is reduced by approximately 85%. The resulting delay introduced is small (10–19 s) but system dynamics is slow enough to avoid contextualisation errors or reduction of system performance. We consider these results as very satisfactory.     

Self‐Defensive Biomaterial Coating Against Bacteria and Yeasts: Polysaccharide Multilayer Film with Embedded Antimicrobial Peptide

Prevention of pathogen colonization of medical implants is a major medical and financial issue since infection by microorganisms constitutes one of the most serious complications after surgery or critical care. Immobilization of antimicrobial molecules on biomaterials surfaces is an efficient approach to prevent biofilm formation. Herein, the first self‐defensive coating against both bacteria and yeasts is reported, where the release of the antimicrobial peptide is triggered by enzymatic degradation of the film due to the pathogens themselves. Biocompatible and biodegradable polysaccharide multilayer films based on functionalized hyaluronic acid by cateslytin (CTL), an endogenous host‐defensive antimicrobial peptide, and chitosan (HA‐CTL‐C/CHI) are deposited on a planar surface with the aim of designing both antibacterial and antifungal coating. After 24 h of incubation, HA‐CTL‐C/CHI films fully inhibit the development of Gram‐positive Staphylococcus aureus bacteria and Candida albicans yeasts, which are common and virulent pathogens agents encountered in care‐associated diseases. Hyaluronidase, secreted by the pathogens, leads to the film degradation and the antimicrobial action of the peptide. Furthermore, the limited fibroblasts adhesion, without cytotoxicity, on HA‐CTL‐C/CHI films highlights a medically relevant application to prevent infections on catheters or tracheal tubes where fibrous tissue encapsulation is undesirable.     

RCS reduction of a conducting cone-cylinder using an active method

This paper presents an active method for reducing the radar cross section (rcs) of a perfectly conducting cone-cylinder. The active elements are four microstrip patch antennas located symmetrically along the conecylinder axis. These elements radiate a field which permit the total scattered field in the direction of the receiver to be close to zero. In each time step, the hoarded system should determine some parameters of the incident wave: the incident direction, its frequency, amplitude, and phase. Then when antennas are fed with currents of suitable amplitude and phase, they radiate an electromagnetic field in the direction of the receiver that has the same amplitude but is opposite in phase compared to the scattered field, without feeding patches. Then the total field vanishes in the direction of the receiver.     

Using Stochastic Differential Equation for Verification of Noise in Analog/RF Circuits

Today’s analog/RF design and verification face significant challenges due to circuit complexity, process variations and short market windows. In particular, the influence of technology parameters on circuits, and the issues related to noise modeling and verification still remain a priority for many applications. Noise could be due to unwanted interaction between the circuit elements or it could be inherited from the circuit elements. In addition, manufacturing disparity influence the characteristic behavior of the manufactured circuits. In this paper, we propose a methodology for modeling and verification of analog/RF designs in the presence of noise and process variations. Our approach is based on modeling the designs using stochastic differential equations (SDE) that will allow us to incorporate the statistical nature of noise. We also integrate the device variation due to 0.18μ m fabrication process in an SDE based simulation framework for monitoring properties of interest in order to quickly detect errors. Our approach is illustrated on nonlinear Tunnel-Diode and a Colpitts oscillator circuits.     

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.