Scalable real-time crisis mapping and analytics of social media streams for disaster management and breaking news

Real-time geoparsing of social media streams (e.g. Twitter, YouTube, Instagram, Flickr, FourSquare) is providing a new 'virtual sensor' capability to end users such as emergency response agencies (e.g. Tsunami early warning centres, Civil protection authorities) and news agencies (e.g. Deutsche Welle, BBC News). Challenges in this area include scaling up natural language processing (NLP) and information retrieval (IR) approaches to handle real-time traffic volumes, reducing false positives, creating real-time infographic displays useful for effective decision support and providing support for trust and credibility analysis using geosemantics. I will present in this seminar on-going work by the IT Innovation Centre over the last 4 years (TRIDEC and REVEAL FP7 projects) in building such systems, and highlights our research towards improving trustworthy and credible of crisis map displays and real-time analytics for trending topics and influential social networks during major news worthy events.

Integration of knowledge-based, qualitative and numeric tools for real time dynamic systems supervision

The proposal presented in this thesis is to provide designers of knowledge based supervisory systems of dynamic systems with a framework to facilitate their tasks avoiding interface problems among tools, data flow and management. The approach is thought to be useful to both control and process engineers in assisting their tasks. The use of AI technologies to diagnose and perform control loops and, of course, assist process supervisory tasks such as fault detection and diagnose, are in the scope of this work. Special effort has been put in integration of tools for assisting expert supervisory systems design. With this aim the experience of Computer Aided Control Systems Design (CACSD) frameworks have been analysed and used to design a Computer Aided Supervisory Systems (CASSD) framework. In this sense, some basic facilities are required to be available in this proposed framework: ·

Biologically motivated model for object detection and identification in real-world scenes

The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.

Sequentially testing for a gene-drug interaction in a genomewide analysis

Assaying a large number of genetic markers from patients in clinical trials is now possible in order to tailor drugs with respect to efficacy. The statistical methodology for analysing such massive data sets is challenging. The most popular type of statistical analysis is to use a univariate test for each genetic marker, once all the data from a clinical study have been collected. This paper presents a sequential method for conducting an omnibus test for detecting gene-drug interactions across the genome, thus allowing informed decisions at the earliest opportunity and overcoming the multiple testing problems from conducting many univariate tests. We first propose an omnibus test for a fixed sample size. This test is based on combining F-statistics that test for an interaction between treatment and the individual single nucleotide polymorphism (SNP). As SNPs tend to be correlated, we use permutations to calculate a global p-value. We extend our omnibus test to the sequential case. In order to control the type I error rate, we propose a sequential method that uses permutations to obtain the stopping boundaries. The results of a simulation study show that the sequential permutation method is more powerful than alternative sequential methods that control the type I error rate, such as the inverse-normal method. The proposed method is flexible as we do not need to assume a mode of inheritance and can also adjust for confounding factors. An application to real clinical data illustrates that the method is computationally feasible for a large number of SNPs. Copyright (c) 2007 John Wiley & Sons, Ltd.

A qualitative host-pathogen interaction in the Theobroma cacao-Moniliophthora perniciosa pathosystem

The aim of this study was to test whether resistance of clones of Theobroma cacao ( cocoa) varied between isolates of Moniliophthora (formerly Crinipellis) perniciosa, the cause of witches' broom disease. Developing buds of vegetatively propagated T. cacao grown in greenhouses in the UK were inoculated with 16 000 spores of M. perniciosa per meristem in water, under conditions where water condensed on the inoculated shoot for at least 12 h after inoculation. The proportion of successful inoculations varied between clones and was inversely correlated with time to symptom production or broom formation. A specific interaction was demonstrated among three single-spore isolates of M. perniciosa and the clone Scavina 6 (SCA 6) and a variety of susceptible clones. Isolates Castenhal-I and APC3 were equally likely to infect SCA 6 and the other clones, but isolate Gran Couva A9 never infected SCA 6, although it was as virulent on the other clones. The interaction was maintained when the wetness period was extended to 70 h. Offspring of SCA 6 x Amelonado matings were all susceptible to both Castenhal-I and GC-A5, with no evidence of greater variability in susceptibility to GC-A5 than Castanhal-I. This suggests recessive inheritance of a single homozygous factor conferring resistance to GC-A5, from SCA 6. The progenies were slightly more susceptible to Castanhal-I than GC-A5. The implications for managing the disease are discussed.

Direct detection of chlorosilylene and time resolved study of some of its reactions in the gas-phase using a new photochemical precursor

Chlorosilylene, ClSiH, was prepared by 193 nm laser flash photolysis of 1-chloro-1-silacyclopent-3-ene in the gas phase. ClSiH was monitored in real time at 457.9 nm using a CW argon ion laser. The kinetics of reactions of ClSiH with C2H4, CH2 = CHCMe3, C2H2, Me2O, SO2, HCl, MeSiH3, Me2SiH2, Me3SiH, MeGeH3, MeGeH3 and precursor have been studied at ambient temperatures for the first time. Addition reactions of ClSiH and reactions with lone pair donors are faster than insertion reactions. Surprisingly ClSiH inserts faster into Si-H than Ge-H bonds. ClSiH is intermediate in reactivity between SiH2 and SiCI2. Relative reactivities of CISiH and SiH2 vary considerably. (c) 2005 Elsevier B.V. All rights reserved.

Engineering Pt in ceria for a maximum metal-support interaction in catalysis

Conventional supported metal catalysts are metal nanoparticles deposited on high surface area oxide supports with a poorly defined metal−support interface. Typically, the traditionally prepared Pt/ceria catalyzes both methanation (H2/CO to CH4) and water−gas shift (CO/H2O to CO2/H2) reactions. By using simple nanochemistry techniques, we show for the first time that Pt or PtAu metal can be created inside each CeO2 particle with tailored dimensions. The encapsulated metal is shown to interact with the thin CeO2 overlayer in each single particle in an optimum geometry to create a unique interface, giving high activity and excellent selectivity for the water−gas shift reaction, but is totally inert for methanation. Thus, this work clearly demonstrates the significance of nanoengineering of a single catalyst particle by a bottom-up construction approach in modern catalyst design which could enable exploitation of catalyst site differentiation, leading to new catalytic properties.

Solvent influences on metastable polymorph lifetimes: real-time interconversions using energy dispersive X-ray diffractometry

Solvent influences on the crystallization of polymorph and hydrate forms of the nootropic drug piracetam (2-oxo-pyrrolidineacetamide) were investigated from water, methanol, 2-propanol, isobutanol, and nitromethane. Crystal growth profiles of piracetam polymorphs were constructed using time-resolved diffraction snapshots collected for each solvent system. Measurements were performed by in situ energy dispersive X-ray diffraction recorded in Station 16.4 at the synchrotron radiation source (SRS) at Daresbury Laboratory, CCLRC UK. Crystallizations from methanol, 2-propanol, isobutanol, and nitromethane progressed in a similar fashion with the initial formation of form I which then converted relatively quickly to form II with form III being generated upon further cooling. However, considerable differences were observed for the polymorphs lifetime and both the rate and temperature of conversion using the different solvents. The thermodynamically unstable form I was kinetically favored in isobutanol and nitromethane where traces of this polymorph were observed below 10 degrees C. In contrast, the transformation of form II and subsequent growth of form III were inhibited in 2-propanol and nitromethane solutions. Aqueous solutions produced hydrate forms of piracetam which are different from the reported monohydrate; this crystallization evolved through successive generation of transient structures which transformed upon exchange of intramolecular water between the liquid and crystalline phases. (c) 2007 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 96:1069-1078, 2007.

Preliminary results from a real time control system using optical information

Successful results from training an adaptive controller to use optical information to balance an inverted pendulum are presented in comparison to the training requirements using traditional controller inputs. Results from research into the psychology of the sense of balance in humans are presented as the motivation for the investigation of this new type of controller. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training time for the adaptive controller and reduced performance (measured as the time the pendulum remains upright).

Investigation into the performance of an algorithm for deriving concise descriptions of optic flow fields for real-time control

This paper describes a region-based algorithm for deriving a concise description of a first order optical flow field. The algorithm described achieves performance improvements over existing algorithms without compromising the accuracy of the flow field values calculated. These improvements are brought about by not computing the entire flow field between two consecutive images, but by considering only the flow vectors of a selected subset of the images. The algorithm is presented in the context of a project to balance a bipedal robot using visual information.

Real-time context-aware network security policy enforcement system (RC-NSPES)

The major technical objectives of the RC-NSPES are to provide a framework for the concurrent operation of reactive and pro-active security functions to deliver efficient and optimised intrusion detection schemes as well as enhanced and highly correlated rule sets for more effective alerts management and root-cause analysis. The design and implementation of the RC-NSPES solution includes a number of innovative features in terms of real-time programmable embedded hardware (FPGA) deployment as well as in the integrated management station. These have been devised so as to deliver enhanced detection of attacks and contextualised alerts against threats that can arise from both the network layer and the application layer protocols. The resulting architecture represents an efficient and effective framework for the future deployment of network security systems.

Robust real-time tracking for visual surveillance

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.