Electrochemically-induced TCNQ/Mn TCNQ 2 (H2O) 2 (TCNQ= 7, 7, 8, 8-Tetracyanoquinodimethane) solid-solid interconversion : two voltammetrically distinct processes that allow selective generation of nanofiber or nanorod network morphologies

Unlike the case with other divalent transition metal M\[TCNQ](2)(H(2)O)(2) (M = Fe, Co, Ni) analogues, the electrochemically induced solid-solid phase interconversion of TCNQ microcrystals (TCNQ = 7,7,8,8-tetracyanoquinodimethane) to Mn\[TCNQ](2)(H(2)O)(2) occurs via two voltammetrically distinct, time dependent processes that generate the coordination polymer in nanofiber or rod-like morphologies. Careful manipulation of the voltammetric scan rate, electrolysis time, Mn(2+)((aq)) concentration, and the method of electrode modification with solid TCNQ allows selective generation of either morphology. Detailed ex situ spectroscopic (IR, Raman), scanning electron microscopy (SEM), and X-ray powder diffraction (XRD) characterization clearly establish that differences in the electrochemically synthesized Mn-TCNQ material are confined to morphology. Generation of the nanofiber form is proposed to take place rapidly via formation and reduction of a Mn-stabilized anionic dimer intermediate, \[(Mn(2+))(TCNQ-TCNQ)(2)(*-)], formed as a result of radical-substrate coupling between TCNQ(*-) and neutral TCNQ, accompanied by ingress of Mn(2+) ions from the aqueous solution at the triple phase TCNQ/electrode/electrolyte boundary. In contrast, formation of the nanorod form is much slower and is postulated to arise from disproportionation of the \[(Mn(2+))(TCNQ-TCNQ)(*-)(2)] intermediate. Thus, identification of the time dependent pathways via the solid-solid state electrochemical approach allows the crystal size of the Mn\[TCNQ](2)(H(2)O)(2) material to be tuned and provides new mechanistic insights into the formation of different morphologies.

SWIRLnet : portable anemometer network for wind speed measurements of land-falling tropical cyclones

Wind speed measurement systems are sparse in the tropical regions of Australia. Tropical cyclone wind speeds impacting communities are often ‘guestimated’ from analyzing damaged structures. A re-locatable anemometer system is required to enable measurements of wind speeds. This paper discusses design criteria of the tripods and tie down system, proposed deployment of the anemometers, instrumentation, and data logging. Preliminary assessment of the anemometer response indicates a reliable system for 1 second response, however, it is noted that the Australian building code and wind loading standard uses a moving average time of approximately 0.2 seconds for its wind speed design criteria.

Wind speed measurements of land-falling tropical cyclones using SWIRLnet, a portable anemometer network

Wind speed measurement systems are sparse in the tropical regions of Australia. Given this, tropical cyclone wind speeds impacting communities are seldom measured and often only ‘guestimated’ by analysing the extent of damage to structures. In an attempt to overcome this dearth of data, a re-locatable network of anemometers to be deployed prior to tropical cyclone landfall is currently being developed. This paper discusses design criteria of the network’s tripods and tie down system, proposed deployment of the anemometers, instrumentation and data logging. Preliminary assessment of the anemometer response indicates a reliable system for measuring the spectral component of wind with frequencies of approximately 1 Hz. This system limitation highlights an important difference between the capabilities of modern instrumentation and that of the Dines anemometer (around 0.2 seconds) that was used to develop much of the design criteria within the Australian building code and wind loading standard.

A new load distribution strategy for linear network with communication delays

In this paper, we propose a new load distribution strategy called `send-and-receive' for scheduling divisible loads, in a linear network of processors with communication delay. This strategy is designed to optimally utilize the network resources and thereby minimizes the processing time of entire processing load. A closed-form expression for optimal size of load fractions and processing time are derived when the processing load originates at processor located in boundary and interior of the network. A condition on processor and link speed is also derived to ensure that the processors are continuously engaged in load distributions. This paper also presents a parallel implementation of `digital watermarking problem' on a personal computer-based Pentium Linear Network (PLN) topology. Experiments are carried out to study the performance of the proposed strategy and results are compared with other strategies found in literature.

A Network Model of Static Foam Drainage

On the basis of a more realistic tetrakaidecahedral structure of foam bubbles, a network model of static foam drainage has been developed. The model considers the foam to be made up of films and Plateau borders. The films drain into the adjacent Plateau borders, which in turn form a network through which the liquid moves from the foam to the liquid pool. From the structure, a unit flow cell was found, which constitutes the foam when stacked together both horizontally and vertically. Symmetry in the unit flow cell indicates that the flow analysis of a part of it can be employed to obtain the drainage for the whole foam. Material balance equations have been written for each segment of this subsection, ensuring connectivity, and solved with the appropriate boundary and initial conditions. The calculated rates of drainage, when compared with the available experimental results, indicate that the model predicts the experimental results well.

An Efficient Load Distribution Strategy for a Distributed Linear Network of Processors with Communication Delays

In this paper, we present an improved load distribution strategy, for arbitrarily divisible processing loads, to minimize the processing time in a distributed linear network of communicating processors by an efficient utilization of their front-ends. Closed-form solutions are derived, with the processing load originating at the boundary and at the interior of the network, under some important conditions on the arrangement of processors and links in the network. Asymptotic analysis is carried out to explore the ultimate performance limits of such networks. Two important theorems are stated regarding the optimal load sequence and the optimal load origination point. Comparative study of this new strategy with an earlier strategy is also presented.

Generic Routing Rules and a Scalable Access Enhancement for the Network-on-Chip RECONNECT

RECONNECT is a Network-on-Chip using a honeycomb topology. In this paper we focus on properties of general rules applicable to a variety of routing algorithms for the NoC which take into account the missing links of the honeycomb topology when compared to a mesh. We also extend the original proposal [5] and show a method to insert and extract data to and from the network. Access Routers at the boundary of the execution fabric establish connections to multiple periphery modules and create a torus to decrease the node distances. Our approach is scalable and ensures homogeneity among the compute elements in the NoC. We synthesized and evaluated the proposed enhancement in terms of power dissipation and area. Our results indicate that the impact of necessary alterations to the fabric is negligible and effects the data transfer between the fabric and the periphery only marginally.

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

Analysis of transients in a canal network

A generalised formulation of the mathematical model developed for the analysis of transients in a canal network, under subcritical flow, with any realistic combination of control structures and their multiple operations, has been presented. The model accounts for a large variety of control structures such as weirs, gates, notches etc. discharging under different conditions, namely submerged and unsubmerged. A numerical scheme to compute and approximate steady state flow condition as the initial condition has also been presented. The model can handle complex situations that may arise from multiple gate operations. This has been demonstrated with a problem wherein the boundary conditions change from a gate discharge equation to an energy equation and back to a gate discharge equation. In such a situation the wave strikes a fixed gate and leads to large and rapid fluctuations in both discharge and depth.

Transitional intermittency detection by neural network

A neural network has been used to predict the flow intermittency from velocity signals in the transition zone in a boundary layer. Unlike many of the available intermittency detection methods requiring a proper threshold choice in order to distinguish between the turbulent and non-turbulent parts of a signal, a trained neural network does not involve any threshold decision. The intermittency prediction based on the neural network has been found to be very satisfactory.

Simultaneous source localization and boundary mapping for contaminants

This paper addresses the problem of localizing the sources of contaminants spread in the environment, and mapping the boundary of the affected region using an innovative swarm intelligence based technique. Unlike most work in this area the algorithm is capable of localizing multiple sources simultaneously while also mapping the boundary of the contaminant spread. At the same time the algorithm is suitable for implementation using a mobile robotic sensor network. Two types of agents, called the source localization agents (or S-agents) and boundary mapping agents (or B-agents) are used for this purpose. The paper uses the basic glowworm swarm optimization (GSO) algorithm, which has been used only for multiple signal source localization, and modifies it considerably to make it suitable for both these tasks. This requires the definition of new behaviour patterns for the agents based on their terminal performance as well as interactions between them that helps the swarm to split into subgroups easily and identify contaminant sources as well as spread along the boundary to map its full length. Simulations results are given to demonstrate the efficacy of the algorithm.

Finite element analysis of compressor disc heat transfer using the transient conduction method with sparse boundary collocation points

Surface temperature measurements from two discs of a gas turbine compressor rig are used as boundary conditions for the transient conduction solution (inverse heat transfer analysis). The disc geometry is complex, and so the finite element method is used. There are often large radial temperature gradients on the discs, and the equations are therefore solved taking into account the dependence of thermal conductivity on temperature. The solution technique also makes use of a multigrid algorithm to reduce the solution time. This is particularly important since a large amount of data must be analyzed to obtain correlations of the heat transfer. The finite element grid is also used for a network analysis to calculate the radiant heat transfer in the cavity formed between the two compressor discs. The work discussed here proved particularly challenging as the disc temperatures were only measured at four different radial locations. Four methods of surface temperature interpolation are examined, together with their effect on the local heat fluxes. It is found that the choice of interpolation method depends on the available number of data points. Bessel interpolation gives the best results for four data points, whereas cubic splines are preferred when there are considerably more data points. The results from the analysis of the compressor rig data show that the heat transfer near the disc inner radius appears to be influenced by the central throughflow. However, for larger radii, the heat transfer from the discs and peripheral shroud is found to be consistent with that of a buoyancy-induced flow.

Processing of Synthetic Aperture Radar Images by a Multiscale Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. The segmentation is performed by three "copies" of the BCS and FCS, of small, medium, and large scales, wherein the "short-range" and "long-range" interactions within each scale occur over smaller or larger distances, corresponding to the size of the early filters of each scale. A diffusive filling-in operation within the segmented regions at each scale produces coherent surface representations. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.