Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Relationships between EEA1 binding partners and their role in endosome fusion

Homotypic fusion between early endosomes requires the phosphatidylinositol 3-phosphate (PI3P)-binding protein, Early Endosomal Autoantigen 1 (EEA1). We have investigated the role of other proteins that interact with EEA1 in the fusion of early endosomes derived from Baby Hamster Kidney (BHK) cells. We confirm a requirement for syntaxin 13, but additionally show that the assay is equally sensitive to reagents specifically targeted against syntaxin 6. Binding of EEA1 to immobilised GST-syntaxin 6 and 13 was directly compared; only syntaxin 6 formed a stable complex with EEA1. Early endosome fusion requires the release of intravesicular calcium, and calmodulin plays a vital role in the fusion pathway, as judged by sensitivity to antagonists. We demonstrate that both EEA1 and syntaxin 13 interact with calmodulin. In the case of EEA1, binding to calmodulin requires an IQ domain, which is adjacent to a C-terminal FYVE domain that specifically binds to PI3P. We have assessed the influence of protein binding partners on EEA1 interaction with PI3P and find that both calmodulin and rab5-GTP are antagonistic to PI3P binding, whilst syntaxins 6 and 13 have no effect. These studies reveal a complex network of interactions between the proteins required for endosome fusion.

Regulation of endosome fusion

Homotypic fusion between early endosomes can be reconstituted in vitro. By using wortmannin and LY294002, inhibitors of phosphatidylinositol (Pl) 3-kinase, a requirement for this activity has been established in order for fusion to proceed efficiently. It has been shown that Pl 3-kinase activity is required downstream of rab5 activation, although a large excess of activated rab5 can overcome wortmannin inhibition. A series of experiments have also been performed which indicate a role for early endosomal autoantigen 1 (EEA1) in determining fusion efficiency. EEA1 dissociates from membranes following wortmannin treatment. It is proposed that the requirement of endosome fusion for Pl 3-kinase activity is to promote the association of EEA1 with endosomes.

Involvement of the endosomal autoantigen EEA1 in homotypic fusion of early endosomes

In mammalian cells, fusion between early endocytic vesicles has been shown to require the ubiquitous intracellular fusion factors N-ethylmaleimide-sensitive factor (NSF) and alpha-SNAP, as well as a factor specific for early endosomes, the small GTPase Rab5 [1-3]. We have previously demonstrated an additional requirement for phosphatidylinositol 3-kinase (PI 3-kinase) activity [4]. The membrane association of early endosomal antigen 1 (EEA1), a specific marker of early endosomes [5,6], has recently been shown to be similarly dependent on PI 3-kinase activity [7], and we therefore postulated that it might be involved in endosome fusion. Here, we present evidence that EEA1 has an important role in determining the efficiency of endosome fusion in vitro. Both the carboxy-terminal domain of EEA1 (residues 1098-1411) and specific antibodies against EEA1 inhibited endosome fusion when included in an in vitro assay. Furthermore, depletion of EEA1, both from the membrane fraction used in the assay by washing with salt and from the cytosol using an EEA1-specific antibody, resulted in inhibition of endosome fusion. The involvement of EEA1 in endosome fusion accounts for the sensitivity of the endosome fusion assay to inhibitors of PI 3-kinase.

Inhibition of endosome fusion by wortmannin persists in the presence of activated Rab5

Rab5-dependent endosome fusion is sensitive to the phosphoinositide 3-kinase inhibitor, wortmannin. It has been proposed that phosphoinositide 3-kinase activity may be required for activation of rab5 by influencing its nucleotide cycle such as to promote its active GTP state. In this report we demonstrate that endosome fusion remains sensitive to wortmannin despite preloading of endosomes with stimulatory levels of a GTPase-defective mutant rab5(Q79L) or of a xanthosine triphosphate-binding mutant, rab5(D136N), in the presence of the nonhydrolysable analogue XTPgammaS. These results suggest that activation of rab5 cannot be the principal function of the wortmannin-sensitive factor on the endosome fusion pathway. This result is extrapolated to all GTPases by demonstrating that endosome fusion remains wortmannin sensitive despite prior incubation with the nonhydrolysable nucleotide analogue GTPgammaS. Consistent with these results, direct measurement of clathrin-coated vesicle-stimulated nucleotide dissociation from exogenous rab5 was insensitive to the presence of wortmannin. A large excess of rab5(Q79L), beyond levels required for maximal stimulation of the fusion assay, afforded protection against wortmannin inhibition, and partial protection was also observed with an excess of wild-type rab5 independent of GTPgammaS.

An evidential fusion approach for gender profiling

CCTV (Closed-Circuit TeleVision) systems are broadly deployed in the present world. To ensure in-time reaction for intelligent surveillance, it is a fundamental task for real-world applications to determine the gender of people of interest. However, normal video algorithms for gender profiling (usually face profiling) have three drawbacks. First, the profiling result is always uncertain. Second, the profiling result is not stable. The degree of certainty usually varies over time, sometimes even to the extent that a male is classified as a female, and vice versa. Third, for a robust profiling result in cases that a person’s face is not visible, other features, such as body shape, are required. These algorithms may provide different recognition results - at the very least, they will provide different degrees of certainties. To overcome these problems, in this paper, we introduce an Dempster-Shafer (DS) evidential approach that makes use of profiling results from multiple algorithms over a period of time, in particular, Denoeux’s cautious rule is applied for fusing mass functions through time lines. Experiments show that this approach does provide better results than single profiling results and classic fusion results. Furthermore, it is found that if severe mis-classification has occurred at the beginning of the time line, the combination can yield undesirable results. To remedy this weakness, we further propose three extensions to the evidential approach proposed above incorporating notions of time-window, time-attenuation, and time-discounting, respectively. These extensions also applies Denoeux’s rule along with time lines and take the DS approach as a special case. Experiments show that these three extensions do provide better results than their predecessor when mis-classifications occur.

The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages

We study the computational complexity of finding maximum a posteriori configurations in Bayesian networks whose probabilities are specified by logical formulas. This approach leads to a fine grained study in which local information such as context-sensitive independence and determinism can be considered. It also allows us to characterize more precisely the jump from tractability to NP-hardness and beyond, and to consider the complexity introduced by evidence alone.

Learning Bayesian Networks with Thousands of Variables

We present a method for learning Bayesian networks from data sets containing thousands of variables without the need for structure constraints. Our approach is made of two parts. The first is a novel algorithm that effectively explores the space of possible parent sets of a node. It guides the exploration towards the most promising parent sets on the basis of an approximated score function that is computed in constant time. The second part is an improvement of an existing ordering-based algorithm for structure optimization. The new algorithm provably achieves a higher score compared to its original formulation. Our novel approach consistently outperforms the state of the art on very large data sets.

Learning Bounded Tree-Width Bayesian Networks via Sampling

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods [12, 14] tackle the problem by using k-trees to learn the optimal Bayesian network with tree-width up to k. In this paper, we propose a sampling method to efficiently find representative k-trees by introducing an Informative score function to characterize the quality of a k-tree. The proposed algorithm can efficiently learn a Bayesian network with tree-width at most k. Experiment results indicate that our approach is comparable with exact methods, but is much more computationally efficient.

Electron-impact excitation and ionization of W 3+ for the determination of tungsten influx in a fusion plasma

Tungsten will be employed as a plasma facing material in the ITER fusion reactor under construction in Cadarache, France; therefore, there is a significant need for accurate electron-impact excitation and ionization data for the ions of tungsten. We report on the results of extensive calculations of ionization and excitation for W 3+ that are intended to provide the atomic data needed for the determination of impurity influx diagnostics of tungsten in several existing tokamak reactors. The electron-impact excitation rate coefficients for this study were determined using the relativistic R -matrix method. The contribution to direct electron-impact ionization was determined using the distorted-wave approximation, the accuracy of which was verified by an R -matrix with pseudo states calculation. Contributions to total ionization from excitation autoionization were also generated from the relativistic R -matrix method. These results were then employed to calculate values of ionization per emitted photon, or SXB ratios, for four carefully selected spectral lines; these data will allow the determination of impurity influx from tungsten facing surfaces. For the range of densities of importance in the edge region of a tokamak reactor, these SXB ratios are found to be nearly independent of electron density but vary significantly with electron temperature.

The application of atomic physics within impurity diagnostics for fusion plasmas

With the focus of ITER on the transport and emission properties of tungsten, generating atomic data for complex species has received much interest. Focusing on impurity influx diagnostics, we discuss recent work on heavy species. Perturbative approaches do not work well for near neutral systems so non-perturbative data are required, presenting a particular challenge for these influx diagnostics. Recent results on Mo+ are given as an illustration of how the diagnostic applications can guide the theoretical calculations for such systems.

A radiation-damped R -matrix approach to the electron-impact excitation of helium-like ions for diagnostic application to fusion and astrophysical plasmas

Electron-impact excitation collision strengths for transitions between all singly excited levels up to the n = 4 shell of helium-Eke argon and the n = 4 and 5 shells of helium-like iron have been calculated using a radiation-damped R-matrix approach. The theoretical collision strengths have been examined and associated with their infinite-energy limit values to allow the preparation of Maxwell-averaged effective collision strengths. These are conservatively considered to be accurate to within 20% at all temperatures, 3 x 10(5)-3 x 10(8) K forAr(16+) and 10(6)-10(9) K for Fe24+. They have been compared with the results of previous studies, where possible, and we find a broad accord. The corresponding rate coefficients are required for use in the calculation of derived, collisional-radiative, effective emission coefficients for helium-like lines for diagnostic application to fusion and astrophysical plasmas. The uncertainties in the fundamental collision data have been used to provide a critical assessment of the expected resultant uncertainties in such derived data, including redistributive and cascade collisional-radiative effects. The consequential uncertainties in the parts of the effective emission coefficients driven by excitation from the ground levels for the key w, x, y and z lines vary between 5% and 10%. Our results remove an uncertainty in the reaction rates of a key class of atomic processes governing the spectral emission of helium-like ions in plasmas.