Distributed intelligent management of active networks

This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distributed across the whole network. We adopt the Situation Calculus to define a network model and the Reactive Golog language to implement the logical reasoner. An active network management architecture is used by the reasoner to inject and execute operational tasks in the network. The integrated system collects the advantages coming from logical reasoning and network programmability, and provides a powerful system capable of performing high-level management tasks in order to deal with network fault.

Distributed mining of molecular fragments

In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

Use of remote sensing to measure change in the extent of habitat for the critically endangered Jerdon's Courser Rhinoptilus bitorquatus in India

Jerdon's Courser Rhinoptilus bitorquatus is one of the most endangered and least understood birds in the world. It is endemic to scrub habitats in southeast India which have been lost and degraded because of human land use. We used satellite images from 1991 and 2000 and two methods for classifying land cover to quantify loss of Jerdon's Courser habitat. The scrub habitats on which this species depends decreased in area by 11-15% during this short period (9.6 years), predominantly as a result of scrub clearance and conversion to agriculture. The remaining scrub patches were smaller and further from human settlements in 2000 than in 1991, implying that much of the scrub loss had occurred close to human population centres. We discuss the implications of our results for the conservation of Jerdon's Courser and the use of remote sensing methods in conservation.

Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modeling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

Pyrene-functionalised, alternating copolyimide for sensing nitroaromatic compounds

A novel, pyrene-functionalised copolymer has been synthesised in a single step via imidisation of poly(maleic anhydride-alt-1-octadecene) with 1-pyrenemethylamine, and its potential for the detection of volatile nitro aromatic compounds (NACs) evaluated. The new copolymer forms complexes in solution with NACs such as 2,5-dinitrobenzonitrile, as shown by H-1 NMR, UV-vis and fluorescence spectroscopy. Moreover, thin films of this copolymer, cast from THF solution, undergo almost instantaneous fluorescence quenching when exposed to the vapour of 2,5-dinitrobenzonitrile (a model for TNT) at ambient temperatures and pressures.

Carboxylate anions binding and sensing by a novel tetraazamacrocycle containing ferrocene as receptor

A tetraazamacrocycle containing ferrocene moieties has been synthesized and characterized. The tetraprotonated form of this compound was evaluated as a receptor (R) for anion recognition of several substrates (S), Cl-, PF6-, HSO4-, H2PO4- and carboxylates, such as p-nitrobenzoate (p-nbz(-)), phthalate (ph(2-)), isophthalate (iph(2-)) and dipicolinate (dipic(2-)). H-1 NMR titrations in CD3OD indicated that this receptor is not suitable for recognizing HSO4- and H2PO4-, but weakly binds p-nbz(-), and strongly interacts with ph(2-), dipic(2-), and iph(2-) anions forming 1 : 2 assembled species. The largest beta(2) binding constant was determined for ph(2-), followed by dipic(2-) and finally iph(2-). The effect of the anionic substrates on the electron-transfer process of the ferrocene units of R was evaluated using cyclic voltammetry (CV) and square wave voltammetry (SWV) in methanol solution and 0.1 mol dm(-3) (CH3)(4)NCl as the supporting electrolyte. Titrations of the receptor were undertaken by addition of anion solutions in their tetrabutylammonium or tetramethylammonium forms. The protonated ligand exhibits a reversible voltammogram, which shifts cathodically in the presence of the substrates. The data revealed kinetic constraints in the formation of the receptor/substrate entity for dipic(2-), ph(2-) and iph(2-) anions, but not for p-nbz(-). In spite of the slow kinetics of assembled species formation with the ph(2-) substrate, this anion provides the largest redox-response when the supramolecular entity is formed, followed by dipic(2-), iph(2-) and finally p-nbz(-) anions. This trend is in agreement with the H-1 NMR results and the values of the binding constants. Single crystal X-ray structures of the receptor with PF6-, ph(2-), iph(2-) and p-nbz(-) were carried out and showed that supermolecules with a RS2 stoichiometry are formed with the first three anions, but RS4 with p-nbz(-). In all cases the binding occurs outside the macrocyclic cavity via N-H center dot center dot center dot O=C hydrogen bonds for carboxylate anions and N - H center dot center dot center dot F hydrogen bonds for the PF6- anion, which is in agreement with the solution results. The macrocyclic framework adopts different conformations in order to interact with each substrate having Fe center dot center dot center dot Fe intramolecular distances ranging from 10.125(14) to 12.783(15) angstrom.

Electrochemical deposition of praseodymium oxide on tin-doped indium oxide as a thin sensing film

Fabrication of a thin praseodymium oxide film is of great technological interest in sensor, semiconducting, and ceramic industries. It is shown for the first time that an ultrathin layer of praseodymium oxide can be deposited on tin-doped indium oxide surface (ITO) by applying a negative sweeping voltage (cathodic electrodeposition) to the aqueous solution containing Pr(NO3)(3) and H2O2 using cyclic voltammetry, followed by annealing the film at 500 S C for 1 h. X-ray diffraction suggested that the predominant phase of the film is Pr6O11 and atomic force microscopy and scanning electron microscopy characterizations indicated that this film is assembled with a monolayer coverage of spherical praseodymium oxide nanoparticles packed closely on the ITO surface. AC impedance measurements of the thin Pr6O11 film on ITO also revealed that the composite material displays a much higher electrical conductivity compared to the pure ITO. As a result, the material could suitably be used as a new chemical sensor. (c) 2006 The Electrochemical Society.

Quantitative thermal imaging analysis of aircraft materials: through skin sensing (Invited Paper)

Thermal non-destructive testing (NDT) is commonly used for assessing aircraft structures. This research work evaluates the potential of pulsed -- transient thermography for locating fixtures beneath aircraft skins in order to facilitate accurate automated assembly operations. Representative aluminium and carbon fibre aircraft skin-fixture assemblies were modelled using thermal modelling software. The assemblies were also experimentally investigated with an integrated pulsed thermographic evaluation system, as well as using a custom built system incorporating a miniature un-cooled camera. Modelling showed that the presence of an air gap between skin and fixture significantly reduced the thermal contrast developed, especially in aluminium. Experimental results show that fixtures can be located to accuracies of 0.5 mm.

Recent advances in biomimetic sensing technologies

The importance of biological materials has long been recognized from the molecular level to higher levels of organization. Whereas, in traditional engineering, hardness and stiffness are considered desirable properties in a material, biology makes considerable and advantageous use of softer, more pliable resources. The development, structure and mechanics of these materials are well documented and will not be covered here. The purpose of this paper is, however, to demonstrate the importance of such materials and, in particular, the functional structures they form. Using only a few simple building blocks, nature is able to develop a plethora of diverse materials, each with a very different set of mechanical properties and from which a seemingly impossibly large number of assorted structures are formed. There is little doubt that this is made possible by the fact that the majority of biological ‘materials’ or ‘structures’ are based on fibres and that these fibres provide opportunities for functional hierarchies. We show how these structures have inspired a new generation of innovative technologies in the science and engineering community. Particular attention is given to the use of insects as models for biomimetically inspired innovations.

Economic models and algorithms for distributed systems

Distributed computing paradigms for sharing resources such as Clouds, Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. While there are some success stories such as PlanetLab, OneLab, BOINC, BitTorrent, and SETI@home, a widespread use of these technologies for business applications has not yet been achieved. In a business environment, mechanisms are needed to provide incentives to potential users for participating in such networks. These mechanisms may range from simple non-monetary access rights, monetary payments to specific policies for sharing. Although a few models for a framework have been discussed (in the general area of a "Grid Economy"), none of these models has yet been realised in practice. This book attempts to fill this gap by discussing the reasons for such limited take-up and exploring incentive mechanisms for resource sharing in distributed systems. The purpose of this book is to identify research challenges in successfully using and deploying resource sharing strategies in open-source and commercial distributed systems.

Parallel and distributed computing with Java

The Java language first came to public attention in 1995. Within a year, it was being speculated that Java may be a good language for parallel and distributed computing. Its core features, including being objected oriented and platform independence, as well as having built-in network support and threads, has encouraged this view. Today, Java is being used in almost every type of computer-based system, ranging from sensor networks to high performance computing platforms, and from enterprise applications through to complex research-based.simulations. In this paper the key features that make Java a good language for parallel and distributed computing are first discussed. Two Java-based middleware systems, namely MPJ Express, an MPI-like Java messaging system, and Tycho, a wide-area asynchronous messaging framework with an integrated virtual registry are then discussed. The paper concludes by highlighting the advantages of using Java as middleware to support distributed applications.

Semantic organization to enhance active learning based on distributed multimedia educational resources

In order to organize distributed educational resources efficiently, to provide active learners an integrated, extendible and cohesive interface to share the dynamically growing multimedia learning materials on the Internet, this paper proposes a generic resource organization model with semantic structures to improve expressiveness, scalability and cohesiveness. We developed an active learning system with semantic support for learners to access and navigate through efficient and flexible manner. We learning resources in an efficient and flexible manner. We provide facilities for instructors to manipulate the structured educational resources via a convenient visual interface. We also developed a resource discovering and gathering engine based on complex semantic associations for several specific topics.

A flexible monitoring and notification system for distributed resources

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware, a faulty, system or application software. Desirable characteristics for monitoring systems are the ability to connect to any number of different types of monitoring agents and to provide different views of the system, based on a client's particular preferences. This paper outlines and discusses the ongoing activities within the GridRM wide-area resource-monitoring project.

Linear hashtable motion estimation algorithm for distributed video processing

This paper presents a parallel Linear Hashtable Motion Estimation Algorithm (LHMEA). Most parallel video compression algorithms focus on Group of Picture (GOP). Based on LHMEA we proposed earlier [1][2], we developed a parallel motion estimation algorithm focus inside of frame. We divide each reference frames into equally sized regions. These regions are going to be processed in parallel to increase the encoding speed significantly. The theory and practice speed up of parallel LHMEA according to the number of PCs in the cluster are compared and discussed. Motion Vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass Hexagonal Search (HEXBS) motion estimation, which only searches a small number of Macroblocks (MBs). We evaluated distributed parallel implementation of LHMEA of TPA for real time video compression.