ESD–RF co-design methodology for the state of the art RF-CMOS blocks

This paper describes an approach to design ESD protection for integrated low noise amplifier (LNA) circuits used in narrowband transceiver front-ends. The RF constraints on the implementation of ESD protection devices are relaxed by co-designing the RF and the ESD blocks, considering them as one single circuit to optimise. The method is applied for the design of 0.25 μm CMOS LNA. Circuit protection levels higher than 3 kV HBM stress are achieved using conventional highly capacitive ggNMOS snapback devices. The methodology can be extended to other RF-CMOS circuits requiring ESD protection by merging the ESD devices in the functionality of the corresponding matching blocks.     

Self-ignition and mechanisms of interaction of coal with oxygen at low temperatures. 1. Changes in the composition of coal heated at constant rate to 250 °C in air

The changes in weight, in elementary composition, in content of oxygen functional groups and in spin concentration of lignite, brown and black coal samples heated in a stream of humid air at a rate of 1 °C/min to various temperatures have been determined I.r. spectra of oxidized and non-oxidized brown coal are recorded and the yields of CO, CO₂ and H₂O were measured. The mixtures of low-molecular-weight hydrocarbons evolved before self-ignition were analysed by gas chromatography, and the temperatures of self-ignition were determined in an oxygen stream using a Leitz microscope. A region of coal oxidation was identified where the hydrogen content remained invariable or increased, indicating an interaction of coal with water in the presence of oxygen. For the next region the atomic ratio H/C of the overall gaseous product was found to be high (6 to 10). Self-ignition was found to occur in this region. The results permit coal oxidation to be considered as a redox process. The aromatic part of coal is believed to act as an oxidizing agent in the region where hydrogen is less affected by molecular oxygen.     

Adaptive neighborhood selection in peer-to-peer networks based on content similarity and reputation

To address the two most critical issues in P2P file-sharing systems: efficient information discovery and authentic data acquisition, we propose a Gnutella-like file-sharing protocol termed Adaptive Gnutella Protocol (AGP) that not only improves the querying efficiency in a P2P network but also enhances the quality of search results at the same time. The reputation scheme in the proposed AGP evaluates the credibility of peers based on their contributions to P2P services and subsequently clusters nodes together according to their reputation and shared content, essentially transforming the P2P overlay network into a topology with collaborative and reputed nodes as its core. By detecting malicious peers as well as free-riders and eventually pushing them to the edge of the overlay network, our AGP propagates search queries mainly within the core of the topology, accelerating the information discovery process. Furthermore, the clustering of nodes based on authentic and similar content in our AGP also improves the quality of search results. We have implemented the AGP with the PeerSim simulation engine and conducted thorough experiments on diverse network topologies and various mixtures of honest/dishonest nodes to demonstrate improvements in topology transformation, query efficiency, and search quality by our AGP.

Managing cohort movement of mobile sensors via GPS-free and compass-free node localization

A critical problem in mobile ad hoc wireless sensor networks is each node’s awareness of its position relative to the network. This problem is known as localization. In this paper, we introduce a variant of this problem, directional localization, where each node must be aware of both its position and orientation relative to its neighbors. Directional localization is relevant for applications that require uniform area coverage and coherent movement. Using global positioning systems for localization in large scale sensor networks may be impractical in enclosed spaces, and might not be cost effective. In addition, a set of pre-existing anchors with globally known positions may not always be available. In this context, we propose two distributed algorithms based on directional localization that facilitate the collaborative movement of nodes in a sensor network without the need for global positioning systems, seed nodes or a pre-existing infrastructure such as anchors with known positions. Our first algorithm, GPS-free Directed Localization (GDL) assumes the availability of a simple digital compass on each sensor node. We relax this requirement in our second algorithm termed GPS- and Compass-free Directed Localization (GCDL). Through experimentation, we demonstrate that our algorithms scale well for large numbers of nodes and provide convergent localization over time, despite errors introduced by motion actuators and distance measurements. In addition, we introduce mechanisms to preserve swarm formation during directed sensor network mobility. Our simulations confirm that, in a number of realistic scenarios, our algorithms provide for a mobile sensor network that preserves its formation over time, irrespective of speed and distance traveled. We also present our method to organize the sensor nodes in a polygonal geometric shape of our choice even in noisy environments, and investigate the possible uses of this approach in search-and-rescue type of missions.     

Fast Cloth Animation on Walking Avatars

This paper describes a fast technique for animating clothing on walking humans. It exploits a mass-spring cloth model but applies a new velocity directional modification approach to overcome its super-elasticity. The algorithm for cloth-body collision detection and response is based on image-space interference tests, unlike the existing ones that use object-space checks. The modern workstations' graphics hardware is used not only to compute the depth maps of the body but also to interpolate the body normal vectors and velocities of each vertex. As a result the approach is very fast and makes it possible to produce animation at a rate of three to four frames per second.     

Information characteristics and the structure of landscapes

Various techniques for statistical analysis of the structure of fitness landscapes have been proposed. An important feature of these techniques is that they study the ruggedness of landscapes by measuring their correlation characteristics. This paper proposes a new information analysis of fitness landscapes. The underlying idea is to consider a fitness landscape as an ensemble of objects that are related to the fitness of neighboring points. Three information characteristics of the ensemble are defined and studied. They are termed: information content, partial information content, and information stability. The information characteristics of a range of landscapes with known correlation features are analyzed in an attempt to reveal the advantages of the information analysis. We show that the proposed analysis is an appropriate tool for investigating the structure of fitness landscapes.     

Validation of LAI and assessment of winter wheat status using spectral data and vegetation indices from SPOT VEGETATION and simulated PROBA-V images

Due to the information gap between the VEGETATION sensors and Sentinel-3 mission, the Belgian state decided to build a small satellite, Project for Onboard Autonomy-Vegetation (PROBA-V), to ensure the continuity of the data record for vegetation studies. In this study, simulated PROBA-V data generated by the Landsat Thematic Mapper (TM) were used to evaluate the potential of this mission to assess winter wheat status. The root mean square error (RMSE) of PROBA-V's leaf area index (LAI), which was generated using the exponential method and the interpolation method, is 0.33 and 0.96 for March 2011 and 1.40 and 3.33 for May 2011, respectively. Système Pour l'Observation de la Terre (SPOT) VEGETATION's LAI does not show a significant relationship with the reference LAI values except for the LAI values during the stem elongation 100% phenological stage generated using the exponential method (correlation coefficient, r = 0.91; p = 0.01). For the tillering and stem elongation 100% phenological stages, linear regression models for the fraction of absorbed photosynthetically active radiation (FAPAR) with PROBA-V's normalized difference vegetation index (NDVI) were developed (coefficient of determination, R ², of 0.94 and 0.88). Exponential models for LAI (R ² of 0.91 and 0.93) and fresh weight of above-ground biomass (AGBf) (R ² of 0.90 and 0.93) with PROBA-V's near-infrared (NIR) and visible and near-infrared bands (VNIR B2) were developed accordingly. The assessment of winter wheat status showed that the highest and the lowest values of PROBA-V's simulated data (SD), i.e. NDVI, normalized difference water index (NDWI), and LAI of Field 2 and Field 4, correspond to the ground-measured biometric parameters.