Spectral derivative feature coding for hyperspectral signature analysis

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC.     

POLYELECTROLYTE MULTILAYER STAMPING IN AQUEOUS PHASE AND NON-CONTACT MODE

Polyelectrolyte multilayer (PEM) transfer printing has been previously achieved by stamping under dry conditions. Here, we show for the first time, that PEM can be transferred from a stamp to the base substrate under aqueous conditions whereby the two surfaces are in a non-contact mode. Degradable multilayers of (PAA/PEG)(10.5) followed by non-degradable multilayers of (PDAC/SPS)(80.5) were fabricated under acidic pH conditions on either PDMS or glass (stamp), and subsequently transferred over top of another multilayer prepared on a different substrate (base substrate), with a spacing of ~ 200 μm between the stamping surface and the base substrate. This multilayer transfer was performed under physiological pH conditions. This process is referred to herein as non-contact, aqueous-phase multilayer (NAM) transfer. NAM transfer can be useful for applications such as fabricating three-dimensional (3-D) cellular scaffolds. We attempted to create a 3-D cellular scaffold using NAM transfer, and characterized the scaffolds with conventional and fluorescence microscopy.     

Automatic content-based retrieval and semantic classification of video content

The problem of video classification can be viewed as discovering the signature patterns in the elemental features of a video class. In order to solve this problem, a large and diverse set of video features is proposed in this paper. The contributions of the paper further lie in dealing with high-dimensionality induced by the feature space and in presenting an algorithm based on two-phase grid searching for automatic parameter selection for support vector machine (SVM). The framework thus is directed to bridge the gap between low-level features and semantic video classes. The experimental results and comparison with state-of-the-art learning tools on more than 5000 video segments show the effectiveness of our approach.     

The Role of Modeling and Asynchronous Distributed Simulation in Analyzing Complex Systems of the Future

The word simulate implies to imitate or to mimic while the word modeling refers to a small object, usually built to scale, that represents some existing object. Although the art of mimicking and modeling may be traced back to the beginning of civilization, with the emergence of computers, a few decades ago, the art of modeling and simulation experienced a remarkable transformation. The computational intelligence of the computer imparted the ability to encapsulate and simulate specific characteristics of not only living and inanimate objects but abstract concepts. While the human brain is equally capable of simulating abstract concepts, the precision and speed of the computers are unparalleled and they impart computer modeling and simulation a qualitative jump in its capability and fidelity. Also, while intimately connected to each other, modeling refers to the notion of representing the desired behavior of the target object or idea in the host computer and simulation refers to the execution of the model on a host computer. Today, towards the end of the twentieth century, the nature of modeling and simulation is undergoing another radical transformation. The emergence of economical and powerful computers coupled with the ability to network a large number of computers, promises the ability to model and simulate complex, real-world systems, that are rapidly becoming commonplace in the society, successfully and with a high degree of fidelity. Already, today's real-world systems including complex banking, credit-card transaction, transportation, ground-based communication, and space-based tele-communication systems defy the analytical modeling that had characterized the efforts over the past three decades. Virtually all analytical studies are severely restricted in the number of variables and the number of interacting units that may be modeled. Tomorrow's systems are expected to be far more complex, implying that modeling and large-scale simulation may be the most logical and, often, the only vehicle to study them objectively. This paper presents a fundamental analysis of the nature of complex physical and natural processes that will increasingly constitute the challenging problems of the future. It then develops a set of principles for modeling complex systems. Finally, it examines the role of asynchronous, distributed simulation in the study of a number of real-world systems. In general, modeling and simulation enables one to detect design errors, prior to developing a prototype, in a cost effective manner, identify potential problems during system operation, detect rare and elusive errors, and investigate hypothetical concepts that do not exist in nature. Upon execution, the simulation provides greater quantitative and qualitative insight into the behavior of the actual system. In addition, an asynchronous, distributed simulation, executing on a loosely-coupled parallel processor, closely resembles the actual, operational system, yielding results that potentially reflect reality, as close as possible. Furthermore, elements of the simulation code that emulate the system behavior may be transferred directly onto the operational system with minimal modifications. The knowledge encapsulated in this paper, has been derived from a number of actual case studies involving the modeling and simulation of a number of real-world problems.     

Tracking set-expression cardinalities over continuous update streams

There is growing interest in algorithms for processing and querying continuous data streams (i.e., data seen only once in a fixed order) with limited memory resources. In its most general form, a data stream is actually an update stream, i.e., comprising data-item deletions as well as insertions. Such massive update streams arise naturally in several application domains (e.g., monitoring of large IP network installations or processing of retail-chain transactions). Estimating the cardinality of set expressions defined over several (possibly distributed) update streams is perhaps one of the most fundamental query classes of interest; as an example, such a query may ask what is the number of distinct IP source addresses seen in passing packets from both router R ₁ and R ₂ but not router R ₃?. Earlier work only addressed very restricted forms of this problem, focusing solely on the special case of insert-only streams and specific operators (e.g., union). In this paper, we propose the first space-efficient algorithmic solution for estimating the cardinality of full-fledged set expressions over general update streams. Our estimation algorithms are probabilistic in nature and rely on a novel, hash-based synopsis data structure, termed 2-level hash sketch. We demonstrate how our 2-level hash sketch synopses can be used to provide low-error, high-confidence estimates for the cardinality of set expressions (including operators such as set union, intersection, and difference) over continuous update streams, using only space that is significantly sublinear in the sizes of the streaming input (multi-)sets. Furthermore, our estimators never require rescanning or resampling of past stream items, regardless of the number of deletions in the stream. We also present lower bounds for the problem, demonstrating that the space usage of our estimation algorithms is within small factors of the optimal. Finally, we propose an optimized, time-efficient stream synopsis (based on 2-level hash sketches) that provides similar, strong accuracy-space guarantees while requiring only guaranteed logarithmic maintenance time per update, thus making our methods applicable for truly rapid-rate data streams. Our results from an empirical study of our synopsis and estimation techniques verify the effectiveness of our approach.Received: 20 October 2003, Accepted: 16 April 2004, Published online: 14 September 2004Edited by: J. Gehrke and J. Hellerstein.Sumit Ganguly: sganguly@cse.iitk.ac.in Current affiliation: Department of Computer Science and Engineering, Indian Institute of Technology, Kanpur, India     

Evaluation of the suitability of data base management systems: a case study at the US Forest Service

A methodology for assessing the feasibility of a data base management system is described, and its use demonstrated in a specific situation: the U.S. Forest service. A series of questions to be answered at the test organization is formulated, aimed at quantifying the benefits of a DBMS. Results of attempting to answer these questions at two test sites are provided. Implications of these results are given for both forest and higher level management.     

Comparison of soluble and immobilized acetate for removing Pb from contaminated soil

Five lead (Pb) contaminated soils were used in a laboratory and modeling study to examine the effects of soluble and immobilized acetate on Pb removal from a contaminated soil as a function of pH. Soluble acetate was added as sodium acetate; immobilized acetate was added in the form of a cation exchange resin. For comparative purposes, Pb adsorption with no acetate also was measured as a function of pH. A surface complexation modeling framework was used to interpret experimental data. Experimental results showed the cation exchange resin was much more effective than soluble acetate in removing Pb from soils due to a strong affinity of the resin for Pb. In addition, concentrations of soluble Pb in resin/soil slurry were very low, minimizing the pollution threat if discharged. As deduced from modeling studies, soluble acetate performed poorly compared to the resin, in part, due to adsorption of the soluble PbAc(+) complex. The effectiveness of both soluble and immobilized acetate was diminished below pH 4 as a result of competition by H(+) for acetate. Modeling results based on resin affinity for Pb compare well with experimental data for resin/soil mixtures, suggesting that Pb partitioning in resin/soil mixtures may be predicted reasonably well if soil/Pb and resin/Pb partitioning are known. Thus, the modeling approach may be used as a screening tool to determine the performance of alternative resins.     

Fermi-Level Pinning in Nanocrystal Memories

The nanocrystal (NC) work-function engineering, which plays an important role on the NC memory characteristics such as memory window and retention time, were long regarded as a matter of choice on NC materials. In this letter, we report opposite polarities of charge storage in Au NC memories with different control oxides. The effective NC work function is found to be not only a bulk property of the NC, but also governed by the interface with surrounding dielectric, as a result of the Fermi-level pinning. By replacing Au NCs with C₆₀ molecules, we also show the pinning effect generally exists at quantum-dot-based devices with high density of interface states. This fundamental interface property should be taken into account in the selection of NC and dielectric materials for the NC memory optimization     

MWCNT reinforced Polyamide-6,6 films: preparation,characterization and properties

Composite films of Polyamide-6,6 (PA66) and multi-walled carbon nanotubes (MWCNTs) were prepared by a combination of solution casting followed by compression molding techniques. Both unfunctionalized (u-MWCNTs) and functionalized nanotubes (f-MWCNTs) were used in this study. The functionalization involved direct solvent-free amination of MWCNTs with hexamethylenediamine. Thermogravimetric analysis was used to observe the changes in the nanotubes upon functionalization and morphological features of the resulting composite films were studied using scanning electron microscopy, transmission electron microscopy, and atomic force microscopy. The crystallinity changes by incorporation of the u-MWCNTs and f-MWCNTs in the PA66 matrix were studied by wide angle X-ray scattering and differential scanning calorimetry. The f-MWCNT/PA66 film showed an improvement of ∼43% in maximum tensile stress (MTS) and ∼32% in Young’s modulus over pristine PA66 film, while at a similar loading of 0.5 wt%, the f-MWCNT/PA66 film showed ∼15% increase in MTS and ∼16% increase in modulus over the u-MWCNT/PA66 film. Dynamic mechanical analysis indicated significant difference in the small-strain mechanical properties between the MWCNT-filled and unfilled PA66 at the very low MWNT loadings that were tested and supported the tensile results. The water absorption trend of the composite films showed dramatic improvement over the neat film.