Multiple object tracking using evolutionary MCMC-based particle algorithms

Algorithms are presented for detection and tracking of multiple clusters of co-ordinated targets. Based on a Markov chain Monte Carlo sampling mechanization, the new algorithms maintain a discrete approximation of the filtering density of the clusters' state. The filters' tracking efficiency is enhanced by incorporating various sampling improvement strategies into the basic Metropolis-Hastings scheme. Thus, an evolutionary stage consisting of two primary steps is introduced: 1) producing a population of different chain realizations, and 2) exchanging genetic material between samples in this population. The performance of the resulting evolutionary filtering algorithms is demonstrated in two different settings. In the first, both group and target properties are estimated whereas in the second, which consists of a very large number of targets, only the clustering structure is maintained. © 2009 IFAC.

Molecular characterization of a weak fibrinogen-clotting enzyme from Trimeresurus jerdonii venom

A fibrinogen-clotting enzyme designed as jerdonobin-II was isolated from the venom of Trimeresurus jerdonii. It differed in molecular weight and N-terminal sequence with the previously isolated jerdonobin, a thrombin-like enzyme from the same venom. The enzyme consists of a single polypeptide chain with molecular weights of 30,000 and 32,000 under non-reducing and reducing conditions, respectively. Jerdonobin-II showed weak fibrinogen clotting activity and its activity unit on fibrinogen was calculated to be less than one unit using human thrombin as standard. The precursor protein sequence of jerodonobin-II was deduced from cloned cDNA sequence. The sequence shows high similarity (identity = 89%) to TSV-PA, a specific plasminogen activator from venom of T stejnegeri. Despite of the sequence similarity, jerdonobin-II was found devoid of plasminogen activating effect. Sequence alignment analysis suggested that the replacement of Lys(239) in TSV-PA to Gln(239) in jerdonobin-II might play an important role on their plasminogen activating activity difference. (C) 2005 Elsevier Ltd. All rights reserved.

Indole and carbazole alkaloids from Glycosmis montana with weak anti-HIV and cytotoxic activities

A diprenylated indole, (E)-3-(3-hydroxymethyl-2-butenyl)-7-(3-methyl-2-butenyl)-1H-indole (1), and six known carbazole alkaloids were isolated from the twigs and leaves of Glycosmis montana Pierre (Rutaceae). Their structures were determined on the basis of analysis of spectral evidence including 1D and 2D NMR and MS. The alkaloids (1-3) exhibited weak to moderate take in vitro inhibitory activity against HIV replication in C8166 cells, and they (as well as carbalexine A and B) had cytotoxic activity against the human leukaemia cell line CCRF-CEM. (c) 2005 Elsevier Ltd. All rights reserved.

Performance optimization of adaptive loading algorithms for SMF-based optical OFDM transceivers

Detailed investigations of the effectiveness of three widely adopted optical orthogonal frequency division multiplexing (OOFDM) adaptive loading algorithms, including power loading (PL), bit loading (BL), and bit-and-power loading (BPL), are undertaken, over < 100km single-mode fibre (SMF) system without incorporating inline optical amplification and chromatic dispersion (CD) compensation. It is shown that the BPL (PL) algorithm always offers the best (worst) transmission performance. The absolute transmission capacity differences between these algorithms are independent of transmission distance and launched optical power. Moreover, it is shown that in comparison with the most sophisticated BPL algorithm, the simplest PL algorithm is effective in escalating the OOFDM SMF links performance to its maximum potential. On the other hand, when employing a large number of subcarriers and a high digital-to-analogue DAC)/analogue-to-digital (ADC) sampling rate, the sophisticated BPL algorithm has to be adopted. © 2011 IEEE.

Network structure preserving model reduction with weak a priori structural information

This paper extends a state projection method for structure preserving model reduction to situations where only a weaker notion of system structure is available. This weaker notion of structure, identifying the causal relationship between manifest variables of the system, is especially relevant is settings such as systems biology, where a clear partition of state variables into distinct subsystems may be unknown, or not even exist. The resulting technique, like similar approaches, does not provide theoretical performance guarantees, so an extensive computational study is conducted, and it is observed to work fairly well in practice. Moreover, conditions characterizing structurally minimal realizations and sufficient conditions characterizing edge loss resulting from the reduction process, are presented. ©2009 IEEE.

Adjoint algorithms for the Navier-Stokes equations in the low Mach number limit

This paper describes a derivation of the adjoint low Mach number equations and their implementation and validation within a global mode solver. The advantage of using the low Mach number equations and their adjoints is that they are appropriate for flows with variable density, such as flames, but do not require resolution of acoustic waves. Two versions of the adjoint are implemented and assessed: a discrete-adjoint and a continuous-adjoint. The most unstable global mode calculated with the discrete-adjoint has exactly the same eigenvalue as the corresponding direct global mode but contains numerical artifacts near the inlet. The most unstable global mode calculated with the continuous-adjoint has no numerical artifacts but a slightly different eigenvalue. The eigenvalues converge, however, as the timestep reduces. Apart from the numerical artifacts, the mode shapes are very similar, which supports the expectation that they are otherwise equivalent. The continuous-adjoint requires less resolution and usually converges more quickly than the discrete-adjoint but is more challenging to implement. Finally, the direct and adjoint global modes are combined in order to calculate the wavemaker region of a low density jet. © 2011 Elsevier Inc.

SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases

The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of structured knowledge and answer complex queries. However, the efficient alignment of large-scale knowledge bases still poses a considerable challenge. Here, we present Simple Greedy Matching (SiGMa), a simple algorithm for aligning knowledge bases with millions of entities and facts. SiGMa is an iterative propagation algorithm which leverages both the structural information from the relationship graph as well as flexible similarity measures between entity properties in a greedy local search, thus making it scalable. Despite its greedy nature, our experiments indicate that SiGMa can efficiently match some of the world's largest knowledge bases with high precision. We provide additional experiments on benchmark datasets which demonstrate that SiGMa can outperform state-of-the-art approaches both in accuracy and efficiency.

Information theory, inference, and learning algorithms

Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.