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.     

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.     

Narrow-FSK optical packet labeling scheme for optical ethernet networks

In this work, an intensity modulation/frequency-shift keying (IM/FSK) orthogonal modulation scheme is achieved by direct modulation of a distributed feedback laser source using its adiabatic chirp characteristics. Optical frequencies for "1" and "0" bits are separated only 0.7 GHz, obtaining a narrow-FSK modulation and, accordingly, a low residual intensity modulation. Ethernet frames at 1.25 Gb/s (GbE) are transmitted with a label inserted using coded mark inversion codification at a 155-Mb/s rate. Error rates for the Ethernet payload and for the label have been measured for different payload extinction ratios, showing the viability of this scheme for distances up to 25 km.     

A cross validation study of deep brain stimulation targeting: from experts to atlas-based, segmentation-based and automatic registration algorithms

Validation of image registration algorithms is a difficult task and open-ended problem, usually application-dependent. In this paper, we focus on deep brain stimulation (DBS) targeting for the treatment of movement disorders like Parkinson's disease and essential tremor. DBS involves implantation of an electrode deep inside the brain to electrically stimulate specific areas shutting down the disease's symptoms. The subthalamic nucleus (STN) has turned out to be the optimal target for this kind of surgery. Unfortunately, the STN is in general not clearly distinguishable in common medical imaging modalities. Usual techniques to infer its location are the use of anatomical atlases and visible surrounding landmarks. Surgeons have to adjust the electrode intraoperatively using electrophysiological recordings and macrostimulation tests. We constructed a ground truth derived from specific patients whose STNs are clearly visible on magnetic resonance (MR) T2-weighted images. A patient is chosen as atlas both for the right and left sides. Then, by registering each patient with the atlas using different methods, several estimations of the STN location are obtained. Two studies are driven using our proposed validation scheme. First, a comparison between different atlas-based and nonrigid registration algorithms with a evaluation of their performance and usability to locate the STN automatically. Second, a study of which visible surrounding structures influence the STN location. The two studies are cross validated between them and against expert's variability. Using this scheme, we evaluated the expert's ability against the estimation error provided by the tested algorithms and we demonstrated that automatic STN targeting is possible and as accurate as the expert-driven techniques currently used. We also show which structures have to be taken into account to accurately estimate the STN location.     

Quantitative Auger Electron Spectroscopic Analysis of Hg1−x Cd x Te

Auger electron spectroscopy of Hg_1?x Cd _x Te has been investigated for quantitative analysis. HgCdTe is known to be a very sensitive material which easily suffers from ion beam and electron beam interactions. Two methods were compared for accurate and reproducible quantification of the chemical composition. The first strategy was to reduce as much as possible the damage caused by surface preparation and the effect of the incident electron beam on the material. Quantification was then achieved by use of relative sensitivity factors estimated by use of calibration reference samples. This method was rejected because of unavoidable beam damage which resulted in different chemical changes for the reference CdTe and the HgCdTe sample of interest. The second strategy was to precisely control the experimental conditions to ensure reproducible degradation. Quantification was achieved by analysis of reference HgCdTe samples with different Cd composition. Successful quantification was achieved on stoichiometric material of composition of 0.2 < X _Cd < 0.3 with a X _Cd discrimination limit of ΔX _Cd = 0.02 and an analysis step of 10 nm.     

Influence of Bulky Organo‐Ammonium Halide Additive Choice on the Flexibility and Efficiency of Perovskite Light‐Emitting Devices

Perovskite light‐emitting diodes (LEDs) require small grain sizes to spatially confine charge carriers for efficient radiative recombination. As grain size decreases, passivation of surface defects becomes increasingly important. Additionally, polycrystalline perovskite films are highly brittle and mechanically fragile, limiting their practical applications in flexible electronics. In this work, the introduction of properly chosen bulky organo‐ammonium halide additives is shown to be able to improve both optoelectronic and mechanical properties of perovskites, yielding highly efficient, robust, and flexible perovskite LEDs with external quantum efficiency of up to 13% and no degradation after bending for 10 000 cycles at a radius of 2 mm. Furthermore, insight of the improvements regarding molecular structure, size, and polarity at the atomic level is obtained with first‐principles calculations, and design principles are provided to overcome trade‐offs between optoelectronic and mechanical properties, thus increasing the scope for future highly efficient, robust, and flexible perovskite electronic device development.     

Photovoltaic Devices: High‐Performance Organic Solar Cells with Spray Coated Hole‐Transport and Active Layers (Adv. Funct. Mater. 1/2011)

In this study, we report high performance organic solar cells with spray coated hole‐transport and active layers. With optimized ink formulations we are able to deposit films with controlled thickness and very low surface roughness (<10 nm). Specifically we deposit smooth and uniform 40 nm thick films of poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) as well as films composed of a mixture of poly(3‐hexyl thiophene) (P3HT) and the C₆₀‐derivative (6,6)‐phenyl C61‐butyric acid methyl ester (PCBM) with thicknesses in the range 200–250 nm. To control film morphology, formation and thickness, the optimized inks incorporate two solvent systems in order to take advantage of surface tension gradients to create Marangoni flows that enhance the coverage of the substrate and reduce the roughness of the film. Notably, we achieve fill factors above 70% and attribute the improvement to an enhanced P3HT crystallization, which upon optimized post‐drying thermal annealing results in a favorable morphology. As a result, we could extend the thickness of the layer to several hundreds of nanometers without noticing a substantial decrease of the transport properties of the layer. By proper understanding of the spreading and drying dynamics of the inks we achieve spray coated devices with power conversion efficiency of 3.75%, with fill factor, short circuit current and open circuit voltage of 70%, 9.8 mA cm^?2 and 550 mV, respectively.     

A quantitative and comparative analysis of endmember extraction algorithms from hyperspectral data

Linear spectral unmixing is a commonly accepted approach to mixed-pixel classification in hyperspectral imagery. This approach involves two steps. First, to find spectrally unique signatures of pure ground components, usually known as endmembers, and, second, to express mixed pixels as linear combinations of endmember materials. Over the past years, several algorithms have been developed for autonomous and supervised endmember extraction from hyperspectral data. Due to a lack of commonly accepted data and quantitative approaches to substantiate new algorithms, available methods have not been rigorously compared by using a unified scheme. In this paper, we present a comparative study of standard endmember extraction algorithms using a custom-designed quantitative and comparative framework that involves both the spectral and spatial information. The algorithms considered in this study represent substantially different design choices. A database formed by simulated and real hyperspectral data collected by the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) is used to investigate the impact of noise, mixture complexity, and use of radiance/reflectance data on algorithm performance. The results obtained indicate that endmember selection and subsequent mixed-pixel interpretation by a linear mixture model are more successful when methods combining spatial and spectral information are applied.     

An integrated content and metadata based retrieval system for art

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.