An Integrated CAD Methodology for Yield Enhancement of VLSI CMOS Circuits Including Statistical Device Variations

In this paper a novel CAD methodology for yield enhancement of VLSI CMOS circuits including random device variations is presented. The methodology is based on a preliminary characterization of the technological process by means of specific test chips for accurate mismatch modeling. To this purpose, a very accurate position-dependent parameter mismatch model has been formulated and extracted. Finally a CAD tool implementing this model has been developed. The tool is fully integrated in an environment of existing commercial tools and it has been experimented in the STMicroelectronics Flash Memory CAD Group.As an example of application, a bandgap reference circuit has been considered and the results obtained from simulations have been compared with experimental data. Furthermore, the methodology has been applied to the read path of a complex Flash Memory produced by STMicroelectronics, consisting of about 16,000 MOSFETs. Measurements of electrical performances have confirmed the validity of the methodology, and the accuracy of both the mismatch model and the simulation flow.     

A High Speed VLSI Architecture for Handwriting Recognition

This article presents PAPRICA-3, a VLSI-oriented architecture for real-time processing of images and its implementation on HACRE, a high-speed, cascadable, 32-processors VLSI slice. The architecture is based on an array of programmable processing elements with the instruction set tailored to image processing, mathematical morphology, and neural networks emulation. Dedicated hardware features allow simultaneous image acquisition, processing, neural network emulation, and a straightforward interface with a hosting PC.HACRE has been fabricated and successfully tested at a clock frequency of 50 MHz. A board hosting up to four chips and providing a 33 MHz PCI interface has been manufactured and used to build BEATR IX, a system for the recognition of handwritten check amounts, by integrating image processing and neural network algorithms (on the board) with context analysis techniques (on the hosting PC).     

Role of adenine nucleotides in the activation of microsomal cholesterol ester hydrolase by fructose or adenosine in rat hepatocytes

The significance of the demonstration of a clonal B-cell population in gastric lymphoid infiltrates was investigated by analysis of immunoglobulin heavy chain (IgH) gene rearrangements using sensitive polymerase chain reactions, employing fluorescently labelled primers to target the FR3 and FR1 regions. Tissue blocks were studied showing different histological features (high-grade lymphoma, low-grade lymphoma, and chronic gastritis) from 12 gastrectomies for primary gastric lymphoma, together with blocks showing chronic gastritis from 13 cases of gastric adenocarcinoma and biopsies from 33 patients with active Helicobacter-associated chronic gastritis. Clonal IgH gene rearrangements were detected in lymphoma samples from eight of the gastrectomies for lymphoma (67 per cent). In four of these eight specimens, clonal rearrangements were also detectable in the samples showing only chronic gastritis. Three of 28 (11 per cent) informative biopsies showing active Helicobacter-associated chronic gastritis had detectable clonal populations. Clonal rearrangements were also demonstrated in two of eight (25 per cent) informative blocks showing chronic gastritis from eight gastrectomies for adenocarcinoma. It is concluded that the detection of a clonal population in a suspicious lymphoid infiltrate does not confirm the diagnosis of lymphoma, nor does the absence of such a population imply benignity.     

Nonlinear Creep Damage Model for Concrete under Uniaxial Compression

An isotropic model for creep damage of concrete under uniaxial compression is proposed, where the combined effect of nonlinear viscous strain evolution and crack nucleation and propagation at high stress levels is considered. Strain splitting assumption is used for creep and damage contributions. Creep is modeled by a modified version of solidification theory. As usual in the modeling of damage of concrete, a damage index based on positive strains is introduced. As particular cases, the proposed model reduces to linear viscoelasticity for long time low stress levels whereas, for very high stresses, tertiary creep causing failure at a finite time can be described. The effect of strength variation with time is also included. The model is numerically implemented to perform time integration of nonlinear equations by means of a modified version of exponential algorithm. The model is validated through comparison with experimental results. Some numerical examples are also presented, where the roles of concrete ageing and strength variation with time are investigated.     

Kinetic study on the metallothermic reduction of chromite ore using magnesium scrap

A study on the metallothermic reduction of chromite ore is presented and discussed, using magnesium scrap as reducing agent. Microstructural analysis corroborated the distribution of phases inside the particles, where Fe and Cr were located at the centre surrounded by layers of reaction products, mainly MgO. The maximum conversion efficiency of Fe and Cr was 38% at 1050°C, after a reaction time of 3 hours, using 75% excess of magnesium scrap. A kinetic study was performed fitting the experimental data to available kinetic models, where the data adjusted to the chemical reaction model, especially at the beginning of reaction. A second reaction stage was confirmed once the experimental data was adjusted to the Jander diffusion model. For the chemical reaction model, the constant rate and the activation energy were 0.32?h^?1 and 60.12?kJ?mol^?1, respectively. For the diffusion model, the rate constant was 0.20?h^?1 and the activation energy 47.04?kJ?mol^?1.     

Intrusion Detection System for Wireless Sensor Networks Using Danger Theory Immune-Inspired Techniques

An IDS framework inspired in the Human Immune System to be applied in the wireless sensor network context is proposed. It uses an improved decentralized and customized version of the Dendritic Cell Algorithm, which allows nodes to monitor their neighborhood and collaborate to identify an intruder. The work was implemented and tested both in simulation and in real sensor platform scenarios, comparing them to each other and was also compared to a Negative Selection Theory implementation in order to demonstrate its efficiency in detecting a denial-of-sleep attack and in energy consumption. Results demonstrated the success of the proposal.     

A glucose-specific metric to assess predictors and identify models

In diabetes, the mean square error (MSE) metric is extensively used for assessing glucose prediction methods and identifying glucose models. One limitation of this metric is that, by equally treating errors in hypo-, eu-, and hyperglycemia, it is not able to weight the different clinical impact of errors in these three situations. In this paper, we propose a new cost function, which overcomes this limitation and can be used in place of MSE for several scopes, in particular for assessing the quality of glucose predictors and identifying glucose models. The new metric called glucose-specific MSE (gMSE) modifies MSE with a Clark error grid inspired penalty function, which penalizes overestimation in hypoglycemia and underestimation in hyperglycemia, i.e., the most harmful conditions on a clinical perspective. From a mathematical point of view, gMSE retains sensitivity of MSE and inherits some of its important mathematical features, in particular it has no local minima, simplifying the optimization. This makes it suitable for model identification purposes also. First, the goodness of it is demonstrated by means of three experiments, designed ad hoc to evidence its sensitivity to accuracy, precision, and distortion in glucose predictions. Second, a prediction assessment problem is presented, in which two real prediction profiles are compared. Results show that the MSE chooses the worst clinical situation, while gMSE correctly selects the situation with less clinical risk. Finally, we also demonstrate that models identified minimizing gMSE are more accurate in potentially harmful situations (hypo- and hyperglycemia) than those obtained by MSE.     

Wavelength Conversion Technologies

This paper reports a review of the different technologies used for wavelength conversion in wavelength-division multiplexed networks. The strengths and the weaknesses of the competing technologies, including optoelectronic wavelength conversion, four-wave mixing, difference frequency generation, cross-gain and cross-phase modulation in semiconductor optical amplifiers, are stressed with regard to conversion speed, transparency and regeneration of the converted signal.