Characterization of polymer‐layered silicate (clay) nanocomposites by transmission electron microscopy and X‐ray diffraction: A comparative study

Several polymer‐layered silicate (clay) nanocomposites (PLSNs) were analyzed by transmission electron microscopy (TEM) and wide‐angle X‐ray diffraction (XRD) in an effort to characterize the nanoscale dispersion of the layered silicate. The PLSNs investigated included thermoset (cyanate esters) and thermoplastic polymers (polystyrene, nylon 6, and polypropylene‐g‐maleic anhydride). The results of this study reveal that the overall nanoscale dispersion of the clay in the polymer is best described by TEM, especially when mixed morphologies are present. XRD is useful for the measurement of d‐spacings in intercalated systems but cannot always observe low clay loadings (<5%) or be used as a method to identify an exfoliated nanocomposite where no XRD peaks are present (constituting a negative result). Most importantly, the study showed that XRD is not a stand‐alone technique, and it should be used in conjunction with TEM. Our studies suggest that new definitions, or a clarification of existing definitions, are needed to properly describe the diversity of PLSN nanostructures seen in various materials. Published 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 1329–1338, 2003     

A model for studying LCAT reaction: In vitro cholesterol esterification in pig ovarian follicular fluid

Phosphatidylcholine acyltransferase (lecithin:cholesterol acyltransferase or LCAT; EC 2.3.1.43) activity was found to be present in pig ovarian follicular fluid (POFF), in addition to pig serum (PS). The cholesterol esterification rate in both POFF and PS is linear with incubation time up to 2 hr. The mean absolute rate of POFF-cholesterol esterification was 8.1±0.4 nmoles per ml per hr approximately one-fourth of that in PS. However, the fractional rate (percent of labeled cholesterol esterified per hr) of POFF-cholesterol esterification was similar to that observed in PS. There was little variation of absolute rate of cholesterol esterification in the fluid obtained from different sizes of follicles. Fatty acid or triacylglycerol did not participate in the reaction of cholesterol esterification in POFF. No appreciable change in enzymatic activity was found from storing POFF at 4 C for periods of time up to 24 hr or at −70 C up to 2 months, but activity was lost thereafter. On the other hand, PS showed a much longer period of stability (5 days at 4 C and 9 months at −70 C). A discrepancy between the fatty acid composition of cholesteryl esters formed by the LCAT reaction and the fatty acid composition at the C-2 position of phosphatidylcholine led us to propose a two-step mechanism for the LCAT reaction. It is concluded that the LCAT of POFF, as well as that of plasma, is specific for individual fatty acids rather than for the fatty acid composition of phosphatidylcholine. The fatty acid concentration of lysophosphatidylcholine decreased during prolonged incubation times (6 to 21 hr) suggesting that the increased lysophosphatidylcholine formed as a product of the LCAT reaction may be reused as substrate for the LCAT reaction or for hydrolysis by lysophosphatidylcholine hydrolase. Presented at the AOCS Meeting, New York, May 1977.     

Ranking protective coatings: Laboratory vs. field experience

Environmentally protective coatings are used on a wide range of gas turbine components for survival in the harsh operating conditions of engines. A host of coatings are commercially available to protect hot-section components, ranging from simple aluminides to designer metallic overlays and ceramic thermal barrier coatings. A variety of coating-application processes are available, and they range from simple pack cementation processing to complex physical vapor deposition, which requires multimillion dollar facilities. Detailed databases are available for most coatings and coating/process combinations for a range of laboratory tests. Still, the analysis of components actually used in engines often yields surprises when compared against predicted coating behavior from laboratory testing. This paper highlights recent work to develop new laboratory tests that better simulate engine environments. Comparison of in-flight coating performance as well as industrial and factory engine testing on a range of hardware is presented along with laboratory predictions from standard testing and from recently developed cyclic burner-rig testing.     

A high temperature apparatus for measurement of the Seebeck coefficient

A high temperature Seebeck coefficient measurement apparatus with various features to minimize typical sources of error is designed and built. Common sources of temperature and voltage measurement error are described and principles to overcome these are proposed. With these guiding principles, a high temperature Seebeck measurement apparatus with a uniaxial 4-point contact geometry is designed to operate from room temperature to over 1200 K. This instrument design is simple to operate, and suitable for bulk samples with a broad range of physical types and shapes.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

Gossip-based aggregation of trust in decentralized reputation systems

Decentralized Reputation Systems have recently emerged as a prominent method of establishing trust among self-interested agents in online environments. A key issue is the efficient aggregation of data in the system; several approaches have been proposed, but they are plagued by major shortcomings. We put forward a novel, decentralized data management scheme grounded in gossip-based algorithms. Rumor mongering is known to possess algorithmic advantages, and indeed, our framework inherits many of their salient features: scalability, robustness, a global perspective, and simplicity. We demonstrate that our scheme motivates agents to maintain a very high reputation, by showing that the higher an agent’s reputation is above the threshold set by its peers, the more transactions it would be able to complete within a certain time unit. We analyze the relation between the amount by which an agent’s average reputation exceeds the threshold and the time required to close a deal. This analysis is carried out both theoretically, and empirically through a simulation system called GossipTrustSim. Finally, we show that our approach is inherently impervious to certain kinds of attacks. A preliminary version of this article appeared in the proceedings of IJCAI 2007.     

Graphical histories for visualization: supporting analysis, communication, and evaluation

Interactive history tools, ranging from basic undo and redo to branching timelines of user actions, facilitate iterative forms of interaction. In this paper, we investigate the design of history mechanisms for information visualization. We present a design space analysis of both architectural and interface issues, identifying design decisions and associated trade-offs. Based on this analysis, we contribute a design study of graphical history tools for Tableau, a database visualization system. These tools record and visualize interaction histories, support data analysis and communication of findings, and contribute novel mechanisms for presenting, managing, and exporting histories. Furthermore, we have analyzed aggregated collections of history sessions to evaluate Tableau usage. We describe additional tools for analyzing users’ history logs and how they have been applied to study usage patterns in Tableau.     

Optimizing multiple dimensional queries simultaneously in multidimensional databases

Some significant progress related to multidimensional data analysis has been achieved in the past few years, including the design of fast algorithms for computing datacubes, selecting some precomputed group-bys to materialize, and designing efficient storage structures for multidimensional data. However, little work has been carried out on multidimensional query optimization issues. Particularly the response time (or evaluation cost) for answering several related dimensional queries simultaneously is crucial to the OLAP applications. Recently, Zhao et al. first exploited this problem by presenting three heuristic algorithms. In this paper we first consider in detail two cases of the problem in which all the queries are either hash-based star joins or index-based star joins only. In the case of the hash-based star join, we devise a polynomial approximation algorithm which delivers a plan whose evaluation cost is $ O(n^{\epsilon }$) times the optimal, where n is the number of queries and is a fixed constant with . We also present an exponential algorithm which delivers a plan with the optimal evaluation cost. In the case of the index-based star join, we present a heuristic algorithm which delivers a plan whose evaluation cost is n times the optimal, and an exponential algorithm which delivers a plan with the optimal evaluation cost. We then consider a general case in which both hash-based star-join and index-based star-join queries are included. For this case, we give a possible improvement on the work of Zhao et al., based on an analysis of their solutions. We also develop another heuristic and an exact algorithm for the problem. We finally conduct a performance study by implementing our algorithms. The experimental results demonstrate that the solutions delivered for the restricted cases are always within two times of the optimal, which confirms our theoretical upper bounds. Actually these experiments produce much better results than our theoretical estimates. To the best of our knowledge, this is the only development of polynomial algorithms for the first two cases which are able to deliver plans with deterministic performance guarantees in terms of the qualities of the plans generated. The previous approaches including that of [ZDNS98] may generate a feasible plan for the problem in these two cases, but they do not provide any performance guarantee, i.e., the plans generated by their algorithms can be arbitrarily far from the optimal one. Received: July 21, 1998 / Accepted: August 26, 1999     

Tracking mobile users in wireless networks via semi-supervised colocalization

Recent years have witnessed the growing popularity of sensor and sensor-network technologies, supporting important practical applications. One of the fundamental issues is how to accurately locate a user with few labeled data in a wireless sensor network, where a major difficulty arises from the need to label large quantities of user location data, which in turn requires knowledge about the locations of signal transmitters or access points. To solve this problem, we have developed a novel machine learning-based approach that combines collaborative filtering with graph-based semi-supervised learning to learn both mobile users' locations and the locations of access points. Our framework exploits both labeled and unlabeled data from mobile devices and access points. In our two-phase solution, we first build a manifold-based model from a batch of labeled and unlabeled data in an offline training phase and then use a weighted k-nearest-neighbor method to localize a mobile client in an online localization phase. We extend the two-phase colocalization to an online and incremental model that can deal with labeled and unlabeled data that come sequentially and adapt to environmental changes. Finally, we embed an action model to the framework such that additional kinds of sensor signals can be utilized to further boost the performance of mobile tracking. Compared to other state-of-the-art systems, our framework has been shown to be more accurate while requiring less calibration effort in our experiments performed on three different testbeds.