Measurement Function Design for Visual Tracking Applications

Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Frequency stabilised grating feedback laser diode for atom cooling applications

The free running linewidth of an external cavity grating feedback diode laser is on the order of a few megahertz and is limited by the mechanical and acoustic vibrations of the external cavity. Such frequency fluctuations can be removed by electronic feedback. We present a hybrid stabilisation technique that uses both a Fabry-Perot confocal cavity and an atomic resonance to achieve excellent short and long term frequency stability. The system has been shown to reduce the laser linewidth of an external cavity diode laser by an order of magnitude to 140 kHz, while limiting frequency excursions to 60 kHz relative to an absolute reference over periods of several hours. The scheme also presents a simple way to frequency offset two lasers many gigahertz apart which should find a use in atom cooling experiments, where hyperfine ground-state frequency separations are often required.

Applications of NMR in drug design: Sructure-activity relationships in disulfide-rich peptides

NMR is a powerful technique for determining structures of biologically active molecules in solution. In recent years. our laboratory has focussed on the structure determination of small disulfide-rich proteins from both plants and animals which are valuable targets in drug design applications. This article will review these structural studies and their implications in drug design.

Programming internet based DAI applications in Qu-Prolog

This paper presents the unique collection of additional features of Qu-Prolog, a variant of the Al programming language Prolog, and illustrates how they can be used for implementing DAI applications. By this we mean applications comprising communicating information servers, expert systems, or agents, with sophisticated reasoning capabilities and internal concurrency. Such an application exploits the key features of Qu-Prolog: support for the programming of sound non-clausal inference systems, multi-threading, and high level inter-thread message communication between Qu-Prolog query threads anywhere on the internet. The inter-thread communication uses email style symbolic names for threads, allowing easy construction of distributed applications using public names for threads. How threads react to received messages is specified by a disjunction of reaction rules which the thread periodically executes. A communications API allows smooth integration of components written in C, which to Qu-Prolog, look like remote query threads.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

Porous clays and pillared clays-based catalysts. Part 2: A review of the catalytic and molecular sieve applications

Metal oxide pillared clay (PILC) possesses several interesting properties, such as large surface area, high pore volume and tunable pore size (from micropore to mesopore), high thermal stability, strong surface acidity and catalytic active substrates/metal oxide pillars. These unique characteristics make PILC an attractive material in catalytic reactions. It can be made either as catalyst support or directly used as catalyst. This paper is a continuous work from Kloprogge's review (J.T. Kloprogge, J. Porous Mater. 5, 5 1998) on the synthesis and properties of smectites and related PILCs and will focus on the diverse applications of clay pillared with different types of metal oxides in the heterogeneous catalysis area and adsorption area. The relation between the performance of the PILC and its physico-chemical features will be addressed.

Multiresolution spatial databases: Making web-based spatial applications faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

On S-asymptotically omega-periodic functions on Banach spaces and applications

This paper is devoted to the study of the class of continuous and bounded functions f : [0, infinity] -> X for which exists omega > 0 such that lim(t ->infinity) (f (t + omega) - f (t)) = 0 (in the sequel called S-asymptotically omega-periodic functions). We discuss qualitative properties and establish some relationships between this type of functions and the class of asymptotically omega-periodic functions. We also study the existence of S-asymptotically omega-periodic mild solutions of the first-order abstract Cauchy problem in Banach spaces. (C) 2008 Elsevier Inc. All rights reserved.

Tissue-specific expression of head-to-tail cyclized miniproteins in Violaceae and structure determination of the root cyclotide Viola hederacea root cyclotide1

The plant cyclotides are a family of 28 to 37 amino acid miniproteins characterized by their head-to-tail cyclized peptide backbone and six absolutely conserved Cys residues arranged in a cystine knot motif: two disulfide bonds and the connecting backbone segments form a loop that is penetrated by the third disulfide bond. This knotted disulfide arrangement, together with the cyclic peptide backbone, renders the cyclotides extremely stable against enzymatic digest as well as thermal degradation, making them interesting targets for both pharmaceutical and agrochemical applications. We have examined the expression patterns of these fascinating peptides in various Viola species (Violaceae). All tissue types examined contained complex mixtures of cyclotides, with individual profiles differing significantly. We provide evidence for at least 57 novel cyclotides present in a single Viola species (Viola hederacea). Furthermore, we have isolated one cyclotide expressed only in underground parts of V, hederacea and characterized its primary and three-dimensional structure. We propose that cyclotides constitute a new family of plant defense peptides, which might constitute an even larger and, in their biological function, more diverse family than the well-known plant defensins.

Pt-RuO(2) electrodes prepared by thermal decomposition of polymeric precursors as catalysts for direct methanol fuel cell applications

The electrocatalytic activity of Pt and RuO(2) mixed electrodes of different compositions towards methanol oxidation was investigated. The catalysts were prepared by thermal decomposition of polymeric precursors and characterized by energy dispersive X-ray, scanning electronic microscopy, X-ray diffraction and cyclic voltammetry. This preparation method allowed obtaining uniform films with controlled stoichiometry and high surface area. Cyclic voltammetry experiments in the presence of methanol showed that mixed electrodes decreased the potential peak of methanol oxidation by approximately 100 mV (RHE) when compared to the electrode containing only Pt. In addition, voltammetric experiments indicated that the Pt(0.6)Ru(0.4)O(y) electrode led to higher oxidation current densities at lower potentials. Chronoamperometry experiments confirmed the contribution of RuO(2) to the catalytic activity as well as the better performance of the Pt(0.6)Ru(0.4)O(y) electrode composition. Formic acid and CO(2) were identified as being the reaction products formed in the electrolysis performed at 400 and 600 mV. The relative formation of CO(2) was favored in the electrolysis performed at 400 mV (RHE) with the Pt(0.6)Ru(0.4)O(y) electrode. The presence of RuO(2) in Pt-Ru-based electrodes is important for improving the catalytic activity towards methanol electrooxidation. Moreover, the thermal decomposition of polymeric precursors seems to be a promising route for the production of catalysts applicable to DMFC. (C) 2009 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.