Spatial Color Indexing and Applications

We define a new image feature called the color correlogram and use it for image indexing and comparison. This feature distills the spatial correlation of colors and when computed efficiently, turns out to be both effective and inexpensive for content-based image retrieval. The correlogram is robust in tolerating large changes in appearance and shape caused by changes in viewing position, camera zoom, etc. Experimental evidence shows that this new feature outperforms not only the traditional color histogram method but also the recently proposed histogram refinement methods for image indexing/retrieval. We also provide a technique to cut down the storage requirement of the correlogram so that it is the same as that of histograms, with only negligible performance penalty compared to the original correlogram.We also suggest the use of color correlogram as a generic indexing tool to tackle various problems arising from image retrieval and video browsing. We adapt the correlogram to handle the problems of image subregion querying, object localization, object tracking, and cut detection. Experimental results again suggest that the color correlogram is more effective than the histogram for these applications, with insignificant additional storage or processing cost.     

The boundary node method for three‐dimensional problems in potential theory

The boundary node method (BNM) is developed in this paper for solving potential problems in three dimensions. The BNM represents a coupling between boundary integral equations (BIE) and moving least‐squares (MLS) interpolants. The main idea here is to retain the dimensionality advantage of the former and the meshless attribute of the later. This results in decoupling of the ‘mesh’ and the interpolation procedure for the field variables. A general BNM computer code for 3‐D potential problems has been developed. Several parameters involved in the BNM need to be chosen carefully for a successful implementation of the method. An in‐depth and systematic study has been carried out in this paper in order to better understand the effects of various parameters on the performance of the method. Numerical results for spheres and cubes, subjected to different types of boundary conditions, are extremely encouraging. Copyright © 2000 John Wiley & Sons, Ltd.     

Susceptor-assisted microwave annealing for activation of arsenic dopants in silicon

Microwave annealing of arsenic-doped silicon was employed to achieve nearly complete dopant activation and repair of damage caused by ion implantation. Analysis of Rutherford backscattering spectra suggested that volumetric heating from microwaves can repair ion-implantation damage. Secondary ion mass spectroscopy depth profiling revealed that even with high damage due to implanted arsenic, microwave annealing achieves repair of lattice damage, and electrical activation of dopants without allowing any significant dopant diffusion into the silicon substrate. Surface temperatures greater than 700 °C were achieved within ~ 100 s with assisted microwave heating, marking this as a quick annealing technique when compared to un-assisted annealing. This temperature was sufficient for solid phase epitaxial growth in Si. The temperature profile recorded by a thermocouple-calibarated IR pyrometer was explained based upon the type of losses the sample undergoes while heating. The mechanism for susceptor-assisted microwave heating was dominated by dipole polarization losses in the initial stages of anneal and by Ohmic conduction losses at higher temperatures. Cross-section transmission electron microscopy, along with ion channeling spectra indicated that the silicon lattice regained nearly all of its crystallinity during the microwave anneal. Hall measurement and sheet resistance characterization were used to assess the extent of dopant activation.     

Low‐Cost versus Innovation: Contrasting Outsourcing and Integration Strategies in Manufacturing

This paper analyses how two different outsourcing manufacturing strategies relate to plant performance and innovation capability when taking into account the organizational integration of design and manufacturing as well as product complexity. The study discriminates between low‐cost‐oriented outsourcing and innovation‐oriented outsourcing. The empirical data used is based on a survey of 267 engineering firms, of which half have outsourced manufacturing. We found that the two outsourcing strategies do have different effects, which illustrates that outsourcing represents a trade‐off between improving innovation capability and lowering costs. The study furthermore shows that manufacturing and supplier integration in product design processes is mainly beneficial when applying innovation‐oriented outsourcing, and in particular when products and manufacturing processes are complex.     

A hybridized snapshot proper orthogonal decomposition-discrete wavelet transform technique for the analysis of flow structures and their time evolution

A novel hybrid technique has been proposed in order to reveal in a greater detail the turbulent flow structures and their time evolution, and to address the issues and limitations related to the application of snapshot proper orthogonal decomposition (POD) and wavelet transform technique. The proposed hybrid technique combines the inherent abilities of the snapshot proper orthogonal decomposition and the two-dimensional discrete wavelet transform technique. The POD gives us the overall view of the most energetic flow pattern in an ensemble by decomposing the flow field into spatial and temporal modes, while two-dimensional wavelet transform gives us the localized spatial information through scale wise decomposition of the flow field. In this work, we apply the wavelet transform on the POD spatial modes. This enables us to understand the space scale structure of the flow events captured by the spatial POD modes, and the scale wise selectivity of these spatial POD modes. Thus, we are able to relate the most energetic flow events over a period of time (as obtained in spatial modes of snapshot POD) with the localized dominant scales that are contributing to it. Further, this information is utilized in the selection of those pod spatial modes that can effectively reconstruct a flow structure and its time evolution. The proposed technique has also been able to address the issues in the literature concerning the application of POD when the flow is less deterministic, as then a single POD mode may not reveal the flow structure and combination of modes is required to reconstruct it. In the present work, this hybrid methodology has been used to reveal the near wall intermittent events in channel flow: the ascending streaks and the bursts and their time evolution, the vortex tube and leading edge vortices in jet and the Taylor-Couette and irregular small chaotic vortices in Taylor-Couette flow. The planar dataset used for such an analysis has been obtained from particle image velocimetry and large eddy simulation studies.     

Development of conductive cotton fabrics for heating devices

Recent developments in the area of textiles to make fabrics more functional have led to synthesizing “intelligent fabrics.” This can be achieved by making the fabrics electrically conducting. In the present study it is reported that the cotton fabrics, when impregnated with polypyrrole, achieve enhanced level of conduction. The method of diffusion of pyrrole, followed by polymerization using iron chloride as oxidant, was used. The different levels of conduction were achieved by varying the contents of monomer in the bath from 0.01 to 0.1M during the synthesis. The conductivity could be enhanced from the initial value of 10^?12 to 10¹ S/cm. It is shown that when a fixed voltage is applied to such a modified piece of cloth, the heat generated is up to 1000 W/m² depending on the percentage of pyrrole present. Such fabrics can be used as heating pads and integrated into the apparel to keep the wearer warm enough using a portable 9.0‐V battery. Being flexible and breathable, such fabrics have better comfort properties (compared with conventional heating pads). It can find applications in dresses for army personnel and old‐age patients. Such conductive fabrics can also find applications in many areas such as electromagnetic interference shielding, gas sensors, and temperature indicators. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 4690–4695, 2006     

Comparative Investigation of Dynamic Foam Behavior of Air–Water and CO2–Water Systems

The purpose of this study was to understand and compare the dynamic foam behavior of the surfactant Tween‐20 in air–water and CO₂–water systems. The foam height in the CO₂–water system was less than that in the air–water system, but the foam stability was better in the CO₂–water system. The effect of temperature on axial dye displacement and foam bubble size was studied, where the foam generation ability of the surfactant was directly proportional to the temperature, while the foaminess was inversely proportional. The observed highest foam volume for the air–water system was 3922 ± 181 cm³ and for the CO₂–water system 3195 ± 181 cm³ at 5.0 g L^–1 of surfactant at air flow rate of 1 liter per minute (LPM) at 52 °C. The half‐life for the air–water and the CO₂–water system was 110 and 40 s, respectively, at 5.0 g L^–1 of surfactant at the air flow rate of 1 LPM and 28 °C. In wet foam, the liquid holdup range for the air–water system was 0.38–0.52% and for the CO₂–water system 0.51–0.72% in the concentration range 1.0–5.0 g L^–1 at 1 LPM gas flow rate.     

A blind detection-guided approach for normalised multi-modulus crosstalk estimator in sparse multi-user DSL channels

In high-speed digital subscriber lines (DSL), far-end crosstalk is the main limiting factor on data rates. However, most of the crosstalk is due to the neighbouring twisted pairs in the binder. Therefore, the crosstalk channel matrix is sparse. Using Level 3 of Dynamic Spectrum Management, users are co-ordinated at the central office to cancel the crosstalk. Means for estimating the crosstalk canceller matrix are of critical importance for the cancellation to prove effective. Preferably, the estimation procedure should have low overhead both in computation and bandwidth. Normalised least mean squares (NLMS) based adaptive crosstalk cancellers (Gujrathi et al. (2009) [1]) have a low computational overhead but use a training sequence to ensure they converge adequately. However, using a training sequence consumes some amount of bandwidth which can be avoided if an unsupervised or blind algorithm like a normalised multi-modulus algorithm (NMMA) is used instead. A limitation of NMMA is that its convergence time is often longer than that of the NLMS algorithm. Furthermore, this is made worse as the number of canceller coefficients is made larger. In application to adaptive crosstalk cancellation within the multi-user DSL binder-channel, we argue that the convergence time can be significantly decreased by using an activity detector to exclude canceller coefficients below an appropriate minimum. In this paper, we present an activity detector design using a thresholding criterion based on the least squares technique, Akaike's information criterion (Homer et al. (1998) [2]) and Donoho's universal thresholding principle (Donoho (1995) [3]). This enables us to identify the significant crosstalkers within a DSL binder for each user. We further incorporate this strategy within the blind estimation NMMA and propose an enhanced crosstalk canceller. Our simulations indicate this multi-modulus detection-guided crosstalk canceller demonstrates improved convergence speed and has a steady state error close to that of the standard (non-detection-guided) canceller.     

Quantifying streambank movement and topography using unmanned aircraft system photogrammetry with comparison to terrestrial laser scanning

Streambank movement is an integral part of geomorphic changes along river corridors and affects a range of physical, ecological, and socio‐economic systems including aquatic habitat, water quality, and infrastructure. Various methods have been used to quantify streambank erosion, including bank pins, ground surveys, lidar, and analytical models, however, due to high‐cost or labour intensive fieldwork these are typically feasible or appropriate only for site‐specific studies. Advancements in unmanned aircraft systems (UAS) and photogrammetry provide opportunities for more rapid and economical quantification of streambank erosion and deposition at variable scales. This work assesses the performance of UAS‐based photogrammetry for capturing topography of streambank surfaces and quantifying bank movement. UAS data are compared to terrestrial laser scanner (TLS) and GPS surveying from streambank sites located in Vermont that featured a variety of bank conditions and vegetation. Cross‐sectional analysis of data from UAS and TLS revealed that the UAS reliably captured the bank surface within 0.2 m of TLS and GPS surveys across all sites during leaf‐off conditions. Mean error between UAS and TLS was only 0.11 m in early spring conditions. Dense summer vegetation resulted in decreased accuracy and was a limiting factor in the ability of the UAS to capture the ground surface. At areas with observed bank movement, the change in cross‐sectional area estimated using UAS data compared reliably to TLS survey for net cross‐sectional changes greater than 3.5 m², given a 10% error tolerance. At locations with smaller changes, error increased due to the effect of vegetation, georeferencing, and overhanging bank profiles. UAS‐based photogrammetry shows significant promise for capturing bank topography and movement at fine resolutions in a flexible and efficient manner.