12,301 research outputs found

    Software service adaptation based on interface localisation

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    The aim of Web services is the provision of software services to a range of different users in different locations. Service localisation in this context can facilitate the internationalisation and localisation of services by allowing their adaption to different locales. The authors investigate three dimensions: (i) lingual localisation by providing service-level language translation techniques to adopt services to different languages, (ii) regulatory localisation by providing standards-based mappings to achieve regulatory compliance with regionally varying laws, standards and regulations, and (iii) social localisation by taking into account preferences and customs for individuals and the groups or communities in which they participate. The objective is to support and implement an explicit modelling of aspects that are relevant to localisation and runtime support consisting of tools and middleware services to automating the deployment based on models of locales, driven by the two localisation dimensions. The authors focus here on an ontology-based conceptual information model that integrates locale specification into service architectures in a coherent way

    Cloud service localisation

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    The essence of cloud computing is the provision of software and hardware services to a range of users in dierent locations. The aim of cloud service localisation is to facilitate the internationalisation and localisation of cloud services by allowing their adaption to dierent locales. We address the lingual localisation by providing service-level language translation techniques to adopt services to dierent languages and regulatory localisation by providing standards-based mappings to achieve regulatory compliance with regionally varying laws, standards and regulations. The aim is to support and enforce the explicit modelling of aspects particularly relevant to localisation and runtime support consisting of tools and middleware services to automating the deployment based on models of locales, driven by the two localisation dimensions. We focus here on an ontology-based conceptual information model that integrates locale specication in a coherent way

    AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

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    This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

    Genetic Programming for Smart Phone Personalisation

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    Personalisation in smart phones requires adaptability to dynamic context based on user mobility, application usage and sensor inputs. Current personalisation approaches, which rely on static logic that is developed a priori, do not provide sufficient adaptability to dynamic and unexpected context. This paper proposes genetic programming (GP), which can evolve program logic in realtime, as an online learning method to deal with the highly dynamic context in smart phone personalisation. We introduce the concept of collaborative smart phone personalisation through the GP Island Model, in order to exploit shared context among co-located phone users and reduce convergence time. We implement these concepts on real smartphones to demonstrate the capability of personalisation through GP and to explore the benefits of the Island Model. Our empirical evaluations on two example applications confirm that the Island Model can reduce convergence time by up to two-thirds over standalone GP personalisation.Comment: 43 pages, 11 figure

    A Software Suite for the Control and the Monitoring of Adaptive Robotic Ecologies

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    Adaptive robotic ecologies are networks of heterogeneous robotic devices (sensors, actuators, automated appliances) pervasively embedded in everyday environments, where they learn to cooperate towards the achievement of complex tasks. While their flexibility makes them an increasingly popular way to improve a system’s reliability, scalability, robustness and autonomy, their effective realisation demands integrated control and software solutions for the specification, integration and management of their highly heterogeneous and computational constrained components. In this extended abstract we briefly illustrate the characteristic requirements dictated by robotic ecologies, discuss our experience in developing adaptive robotic ecologies, and provide an overview of the specific solutions developed as part of the EU FP7 RUBICON Project

    A robust client-driven distributed service localisation architecture

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    The fundamental purpose of service-oriented computing is the ability to quickly provide software resources to global users. The main aim of service localisation is to provide a method for facilitating the internationalisation and localisation of software services by allowing them to be adapted to different locales. We address lingual localisation by providing a service interface translation using the latest web services technology to adapt services to different languages and currency conversion as an example of regulatory localisation by using real-time data provided by the European Central Bank. Units and Regulatory Localisations are performed by a conversion mapping, which we have generated for a subset of locales. The aim is to investigate a standardised view on the localisation of services by using runtime and middleware services to deploy a localisation implementation. We apply traditional software localisation ideas to service interfaces. Our contribution is a localisation platform consisting of a conceptual model classifying localisation concerns and the definition of a number of specific platform services. The architecture in which this localisation technique is client-centric in a way that it allows the localisation to be controlled and managed by the client, ultimately providing more personalisation and trust. It also addresses robustness concerns by enabling a fault-tolerant architecture for third-party service localisation in a distributed setting

    A service localisation platform

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    The fundamental purpose of service-oriented computing is the ability to quickly provide software and hardware resources to global users. The main aim of service localisation is to provide a method for facilitating the internationalisation and localisation of software services by allowing them to be adapted to different locales. We address lingual localisation by providing a service translation using the latest web services technology to adapt services to different languages and currency conversion by using real-time data provided by the European Central Bank. Units and Regulatory Localisations are performed by a conversion mapping, which we have generated for a subset of locales. The aim is to investigate a standardised view on the localisation of services by using runtime and middleware services to deploy a localisation implementation. Our contribution is a localisation platform consisting of a conceptual model classifying localisation concerns and the definition of a number of specific platform services

    Applying Cross-cultural theory to understand users’ preferences on interactive information retrieval platform design

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    Presented at EuroHCIR 2014, the 4th European Symposium on Human-Computer Interaction and Information Retrieval, 13th September 2014, at BCS London Office, Covent Garden, London.In this paper we look at using culture to group users and model the users’ preference on cross cultural information retrieval, in order to investigate the relationship between the user search preferences and the user’s cultural background. Initially we review and discuss briefly website localisation. We continue by examining culture and Hofstede’s cultural dimensions. We identified a link between Hofstede’s five dimensions and user experience. We did an analogy for each of the five dimensions and developed six hypotheses from the analogies. These hypotheses were then tested by means of a user study. Whilst the key findings from the study suggest cross cultural theory can be used to model user’s preferences for information retrieval, further work still needs to be done on how cultural dimensions can be applied to inform the search interface design

    A robot swarm assisting a human fire-fighter

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    Emergencies in industrial warehouses are a major concern for fire-fighters. The large dimensions, together with the development of dense smoke that drastically reduces visibility, represent major challenges. The GUARDIANS robot swarm is designed to assist fire-fighters in searching a large warehouse. In this paper we discuss the technology developed for a swarm of robots assisting fire-fighters. We explain the swarming algorithms that provide the functionality by which the robots react to and follow humans while no communication is required. Next we discuss the wireless communication system, which is a so-called mobile ad-hoc network. The communication network provides also the means to locate the robots and humans. Thus, the robot swarm is able to provide guidance information to the humans. Together with the fire-fighters we explored how the robot swarm should feed information back to the human fire-fighter. We have designed and experimented with interfaces for presenting swarm-based information to human beings
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