Multiresolution semantic activity characterisation and abnormality discovery in videos

This paper addresses the issue of activity understanding from video and its semantics-rich description. A novel approach is presented where activities are characterised and analysed at different resolutions. Semantic information is delivered according to the resolution at which the activity is observed. Furthermore, the multiresolution activity characterisation is exploited to detect abnormal activity. To achieve these system capabilities, the focus is given on context modelling by employing a soft computing-based algorithm which automatically enables the determination of the main activity zones of the observed scene by taking as input the trajectories of detected mobiles. Such areas are learnt at different resolutions (or granularities). In a second stage, learned zones are employed to extract people activities by relating mobile trajectories to the learned zones. In this way, the activity of a person can be summarised as the series of zones that the person has visited. Employing the inherent soft relation properties, the reported activities can be labelled with meaningful semantics. Depending on the granularity at which activity zones and mobile trajectories are considered, the semantic meaning of the activity shifts from broad interpretation to detailed description.Activity information at different resolutions is also employed to perform abnormal activity detection.

Hierarchical clustering based web service discovery

This paper presents a hierarchical clustering method for semantic Web service discovery. This method aims to improve the accuracy and efficiency of the traditional service discovery using vector space model. The Web service is converted into a standard vector format through the Web service description document. With the help of WordNet, a semantic analysis is conducted to reduce the dimension of the term vector and to make semantic expansion to meet the user’s service request. The process and algorithm of hierarchical clustering based semantic Web service discovery is discussed. Validation is carried out on the dataset.

Semantic-level Visual Content Descriptor combining visual and textual cues as collaterals

In this paper, we introduce a novel high-level visual content descriptor which is devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt to bridge the so called “semantic gap”. The proposed image feature vector model is fundamentally underpinned by the image labelling framework, called Collaterally Confirmed Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts of the images with the state-of-the-art low-level image processing and visual feature extraction techniques for automatically assigning linguistic keywords to image regions. Two different high-level image feature vector models are developed based on the CCL labelling of results for the purposes of image data clustering and retrieval respectively. A subset of the Corel image collection has been used for evaluating our proposed method. The experimental results to-date already indicates that our proposed semantic-based visual content descriptors outperform both traditional visual and textual image feature models.

Automatically constructing the semantic web

The storage and processing capacity realised by computing has lead to an explosion of data retention. We now reach the point of information overload and must begin to use computers to process more complex information. In particular, the proposition of the Semantic Web has given structure to this problem, but has yet realised practically. The largest of its problems is that of ontology construction; without a suitable automatic method most will have to be encoded by hand. In this paper we discus the current methods for semi and fully automatic construction and their current shortcomings. In particular we pay attention the application of ontologies to products and the particle application of the ontologies.

Networks of contextualised ontologies for the Semantic Web

Currently many ontologies are available for addressing different domains. However, it is not always possible to deploy such ontologies to support collaborative working, so that their full potential can be exploited to implement intelligent cooperative applications capable of reasoning over a network of context-specific ontologies. The main problem arises from the fact that presently ontologies are created in an isolated way to address specific needs. However we foresee the need for a network of ontologies which will support the next generation of intelligent applications/devices, and, the vision of Ambient Intelligence. The main objective of this paper is to motivate the design of a networked ontology (Meta) model which formalises ways of connecting available ontologies so that they are easy to search, to characterise and to maintain. The aim is to make explicit the virtual and implicit network of ontologies serving the Semantic Web.

xhRank: ranking entities on the Semantic Web

In general, ranking entities (resources) on the Semantic Web (SW) is subject to importance, relevance, and query length. Few existing SW search systems cover all of these aspects. Moreover, many existing efforts simply reuse the technologies from conventional Information Retrieval (IR), which are not designed for SW data. This paper proposes a ranking mechanism, which includes all three categories of rankings and are tailored to SW data.

Action following the discovery of a global association between the whole genome and adverse event risk in a clinical drug-development programme

Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non-sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to? determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright (C) 2008 John Wiley & Sons, Ltd.

Mapping antimalarial pharmacophores as a useful tool for the rapid discovery of drugs effective in vivo: design, construction, characterization, and pharmacology of metaquine

Resistant strains of Plasmodium falciparum and the unavailability of useful antimalarial vaccines reinforce the need to develop new efficacious antimalarials. This study details a pharmacophore model that has been used to identify a potent, soluble, orally bioavailable antimalarial bisquinoline, metaquine (N,N'-bis(7-chloroquinolin-4-yl)benzene-1,3-diamine) (dihydrochloride), which is active against Plasmodium berghei in vivo (oral ID50 of 25 mu mol/kg) and multidrug-resistant Plasmodium falciparum K1 in vitro (0.17 mu M). Metaquine shows strong affinity for the putative antimalarial receptor, heme at pH 7.4 in aqueous DMSO. Both crystallographic analyses and quantum mechanical calculations (HF/6-31+G*) reveal important regions of protonation and bonding thought to persist at parasitic vacuolar pH concordant with our receptor model. Formation of drug-heme adduct in solution was confirmed using high-resolution positive ion electrospray mass spectrometry. Metaquine showed strong binding with the receptor in a 1: 1 ratio (log K = 5.7 +/- 0.1) that was predicted by molecular mechanics calculations. This study illustrates a rational multidisciplinary approach for the development of new 4-aminoquinoline antimalarials, with efficacy superior to chloroquine, based on the use of a pharmacophore model.

Discovery of three polymorphs of 7-fluoroisatin reveals challenges in using computational crystal structure prediction as a complement to experimental screening

A combined computational and experimental polymorph search was undertaken to establish the crystal forms of 7-fluoroisatin, a simple molecule with no reported crystal structures, to evaluate the value of crystal structure prediction studies as an aid to solid form discovery. Three polymorphs were found in a manual crystallisation screen, as well as two solvates. Form I ( P2(1)/c, Z0 1), found from the majority of solvent evaporation experiments, corresponded to the most stable form in the computational search of Z0 1 structures. Form III ( P21/ a, Z0 2) is probably a metastable form, which was only found concomitantly with form I, and has the same dimeric R2 2( 8) hydrogen bonding motif as form I and the majority of the computed low energy structures. However, the most thermodynamically stable polymorph, form II ( P1 , Z0 2), has an expanded four molecule R 4 4( 18) hydrogen bonding motif, which could not have been found within the routine computational study. The computed relative energies of the three forms are not in accord with experimental results. Thus, the experimental finding of three crystalline polymorphs of 7- fluoroisatin illustrates the many challenges for computational screening to be a tool for the experimental crystal engineer, in contrast to the results for an analogous investigation of 5- fluoroisatin.