Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.     

Measurement of fractional order model parameters of respiratory mechanical impedance in total liquid ventilation

This study presents a methodology for applying the forced-oscillation technique in total liquid ventilation. It mainly consists of applying sinusoidal volumetric excitation to the respiratory system, and determining the transfer function between the delivered flow rate and resulting airway pressure. The investigated frequency range was f ∈ [0.05, 4] Hz at a constant flow amplitude of 7.5 mL/s. The five parameters of a fractional order lung model, the existing "5-parameter constant-phase model," were identified based on measured impedance spectra. The identification method was validated in silico on computer-generated datasets and the overall process was validated in vitro on a simplified single-compartment mechanical lung model. In vivo data on ten newborn lambs suggested the appropriateness of a fractional-order compliance term to the mechanical impedance to describe the low-frequency behavior of the lung, but did not demonstrate the relevance of a fractional-order inertance term. Typical respiratory system frequency response is presented together with statistical data of the measured in vivo impedance model parameters. This information will be useful for both the design of a robust pressure controller for total liquid ventilators and the monitoring of the patient's respiratory parameters during total liquid ventilation treatment.     

Physical investigation of the impact of electrolessly deposited self-aligned caps on insulation of copper interconnects

With the miniaturization of ULSI circuits and the associated increase of current density up to several MA/cm², copper interconnects are facing electromigration issues at the top interface with the dielectric capping layer SiC(N). A promising solution is to insert selectively on top of copper lines a CoWP metallic self-aligned encapsulation layer, deposited using a wet electroless process. We study the impact of this process on electrical line insulation as a function of cap thickness at the 65 nm technology node and we investigate the physical origin of leakage currents. Below a critical thickness, only a slight leakage current increase of less than one decade is observed, remaining within the specification for self-aligned capping layer processes. Above this critical thickness, large leakage currents are generated due to the combined effect of lateral growth and the presence of parasitic redeposited nodules. We show that a simple phenomenological model allows to reproduce the experimental data, to assess quantitatively the contribution of parasitic defects, and to predict that the self-aligned barrier technology should be extendible up to the 32 nm node, provided that a thin cap layer of less than 8 nm is used.     

Machine learning to design full-reference image quality assessment algorithm

A crucial step in image compression is the evaluation of its performance, and more precisely, available ways to measure the quality of compressed images. In this paper, a machine learning expert, providing a quality score is proposed. This quality measure is based on a learned classification process in order to respect human observers. The proposed method namely Machine Learning-based Image Quality Measure (MLIQM) first classifies the quality using multi-Support Vector Machine (SVM) classification according to the quality scale recommended by the ITU. This quality scale contains 5 ranks ordered from 1 (the worst quality) to 5 (the best quality). To evaluate the quality of images, a feature vector containing visual attributes describing images content is constructed. Then, a classification process is performed to provide the final quality class of the considered image. Finally, once a quality class is associated to the considered image, a specific SVM regression is performed to score its quality. Obtained results are compared to the one obtained applying classical Full-Reference Image Quality Assessment (FR-IQA) algorithms to judge the efficiency of the proposed method.     

Tuning Memristivity by Varying the Oxygen Content in a Mixed Ionic–Electronic Conductor

The rising interest shown for adaptable electronics and brain‐inspired neuromorphic hardware increases the need for new device architectures and functional materials to build such devices. The rational design of these memory components also benefits the comprehension and thus the control over the microscopic mechanisms at the origin of memristivity. In oxide‐based valence‐change memories, the control of the oxygen drift and diffusion kinetics is a key aspect in obtaining the gradual analog‐type change in resistance required for artificial synapse applications. However, only a few devices are designed with this in mind, as they are commonly built around ionic insulating active materials. This shortcoming is addressed by using a mixed ionic–electronic conductor as functional memristive material. This work demonstrates how the oxygen content in La₂NiO_4+δ (L2NO4), tuned through post‐annealing treatments, has a critical influence on the memory characteristics of L2NO4‐based memristive devices. The presence of interstitial oxygen point defects in L2NO4 affects both its structure and electrical properties. High oxygen stoichiometry in the pristine state leads to an increased electrical conductivity, ultimately resulting in an improved memory window with highly multilevel, analog‐type memory programing capabilities, desirable for analog computing and synaptic applications in particular.     

Efficient Photomodulation of Visible Eu(III) and Invisible Yb(III) Luminescences using DTE Photochromic Ligands for Optical Encryption

This work describes a class of complex combining three dithienylethene units and a lanthanide ion used as an optical system displaying a double encryption method: i) a colorful code, drawn and erased under UV and visible irradiations respectively, due to coloration and discoloration of the photochromic entities, and ii) a concomitant gradual disappearance and progressive restoration of the associated lanthanide ion luminescence triggered with the same stimuli. The innovation of the system stems from the emission color tunability, i.e., with either a lanthanide ion emitting only in the visible range (Eu³⁺) or with another lanthanide ion emitting only in the near infrared (NIR) range (Yb³⁺), therefore observable, or not, to the naked eye. This system is the very first one to achieve efficient repeatable modulation of pure NIR luminescence on photochemical command. Furthermore, it is proven to be highly efficient when embedded in a PDMS polymer opening real opportunities for practical applications as anti‐counterfeiting.     

Al0.3Ga0.7As-GaAs microwave resonant tunneling oscillator

We describe the design of a microwave oscillator using resonant tunneling diodes. The devices are fabricated from Al_0.3Ga_0.7As-GaAs double barrier hetero-structures grown by molecular beam epitaxy. Design criteria improving current drivability are established from a theoretical study of tunneling transmission probabilities. Very high peak current densities up to 3.10⁴ A/cm², favorable for high frequency operation as an oscillator, have been achieved experimentally. The devices exhibit stable oscillations at liquid nitrogen temperature and at room temperature when the tunnel diode oscillator is constructed with a stabilizing network.     

Modelling of through silicon via and devices electromagnetic coupling

This paper is essentially composed of two parts for future synthesis. We developed 2D and 3D simulations, starting from a 0.35 μm standard CMOS technology, focusing on through silicon via or redistribution layer induced coupling; nMOSFET, pMOSFET, and the sensitive regions of the CMOS inverter are investigated. We also study stacked devices in 3D circuits, in the radiofrequency range, and propagation of electromagnetic waves along some interconnections with discontinuities. This study is performed in the time domain—a finite-difference time-domain method is applied to the analysis of some vias flanked by two striplines, all embedded in silicon. Electric and magnetic field distributions, transmission and reflexion parameters, and pulse propagations along a transverse via are presented.     

Architecture of a Memory Manager for an MPEG-2 Video Decoding Circuit

A study of the MPEG-2 video decoding standard in Main Profile @ Main Level has been performed, comparing the different solutions existing for the VLSI implementation of the basic functions (Huffman decoding, IDCT...) included in the standard. Afterwards, a new dynamically configurable architecture is proposed for the memory manager, which is necessary to deal with the large data flow inside the decoder. It is aimed at interfacing the external memory, arbitrating the access requests coming from the different decoding units and allowing generic memory requests through the definition of virtual addresses. It is shown that, by means of a particular data organization, the circuit requires an external memory, which is a 2-MB DRAM in fast page or EDO mode, accessible via a 64-bit bus. The memory manager works at 27 MHz and allows a real-time decoding for MP @ ML bitstreams. It has been synthesized in a 0.8-m two-metal CMOS technology and presents a total area of 5.4 mm2 for 6500 gates.     

Analytic investigation of frequency sensitivity in microwave oscillators: Application to the computation of phase noise in a dielectric resonator oscillator

The conversion of low frequency noise into phase noise in microwave oscillators is studied through an analytical calculation of the pushing factor. This calculation is based on a simplified equivalent circuit for two types of active devices : field effect transistors (Fet) and heterojunction bipolar transistors (hbt). The preeminence in the conversion process of the gate- source capacitance in theFet and the base- emitter junction in thehbt is pointed out. Practical methods are proposed to reduce the phase noise in these circuits.