Accurate fitting of a lower-limb prosthetic socket is the most important factor affecting amputee satisfaction and rehabilitation. The technology is now available to allow real-time monitoring of in-service pressure d...
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Information systems exist in every aspect of our life and our society depends on them enormously. Despite this reliance, these systems are often unreliable, prone to errors, and pose vulnerabilities for potential secu...
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Information systems exist in every aspect of our life and our society depends on them enormously. Despite this reliance, these systems are often unreliable, prone to errors, and pose vulnerabilities for potential security attacks. We are often faced with a choice between using a valuable (or even an essential) system, which is not fully trustworthy, or else forgoing the services it provides. Developing a trustworthy software system is a challenging task. The system's overall trustworthiness depends on trust relationships that are usually assumed and not properly analysed during the analysis and design of the system. The lack of appropriate analysis of such trust relationships, or the lack of appropriate justification of relevant trust assumptions, usually results in systems that can potentially fail to fully achieve those functionalities that depend on such trust relationships. In this paper, we present a meta-model for a modelling language that allows developers to capture possible trust relationships and to reason about them. The meta-model includes a set of trust based concepts, which support the development of trustworthy systems. A case study from the UK health care sector is used to illustrate the usefulness of the meta-model.
This paper presents a novel image processing algorithm to measure the length and depth of an epidural needle during insertion. A wireless camera is used which transmits video during insertion to a host computer. The c...
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ISBN:
(纸本)9781849196321
This paper presents a novel image processing algorithm to measure the length and depth of an epidural needle during insertion. A wireless camera is used which transmits video during insertion to a host computer. The computer contains the image processing algorithm to detect the visible needle in the image and measures the length. The measurement is done by HSV background removal, colour comparison and using RGB histograms to locate 10mm markings on the Tuohy needle shaft. The visible length is then subtracted from the known length of the needle to calculate the depth of the needle tip. The camera can be placed in the operating theatre up to one meter away from the needle insertion site. The purpose of measuring needle depth in real time is to precisely place the needle in the epidural space.
Determining event ordering has always been a crucial issue in distributed computing. A well known model for describing event ordering is the happened-before relation. However, the traditional happened-before relation ...
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ISBN:
(纸本)9781457715846
Determining event ordering has always been a crucial issue in distributed computing. A well known model for describing event ordering is the happened-before relation. However, the traditional happened-before relation model is inadequate to faithfully characterize event ordering in recent emerging mobile ad hoc networks (MANETs), which usually have no fixed supporting infrastructure and may experience dynamic network topology changes. In this paper, we first propose a new relation, called the extended-happened-before relation, to model the ordering of events for a MANET. Then we present an algorithm to assign logical time to events such that the extended-happened-before relation between events can be decided by comparing their timestamps. We finally show how to construct consistent global snapshots in a MANET when the ordering of events can be determined.
Developing service discovery, information retrieval and context-aware to adapt to user everywhere/anytime and attain the ambient intelligence arise the issue of handling misclassification, imperfect reasoning and esti...
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Developing service discovery, information retrieval and context-aware to adapt to user everywhere/anytime and attain the ambient intelligence arise the issue of handling misclassification, imperfect reasoning and estimation with respect to the current context. To deal with this issue, we propose the use of Fuzzy set theory with the purpose of inferring and reasoning that adopt fuzzy lattice classifier for decision making. It is applied on top of SOIM framework to increase the accuracy of the classification process with clearer decisions.
Current methods of evaluating the performance of a runner using Energy Storing and Returning (ESR) prosthesis rely heavily on metabolic and biological factors. This makes it difficult to differentiate between the cont...
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Combination of classifiers leads to a substantial reduction of classification errors in a wide range of applications. Among them SVM ensembles with bagging have shown better performance in classification than a single...
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Combination of classifiers leads to a substantial reduction of classification errors in a wide range of applications. Among them SVM ensembles with bagging have shown better performance in classification than a single SVM. However, the training process of SVM ensembles is notably computationally intensive especially when the number of replicated training datasets is large. This paper presents MRESVM, a MapReduce based distributed SVM ensemble algorithm for image annotation which re-samples the training dataset based on bootstrapping and trains SVM on each dataset in parallel using a cluster of computers. MRESVM is evaluated in a experimental environment and the results show that the MRESVM algorithm reduces the training time significantly while achieves high level of accuracy in classifications.
This article presents an evolution-based model for the US airport network. The topological properties and the volume of people travelling are both studied in detail, revealing high heterogeneity in space and time. A r...
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Modeling and analyzing software architectures are useful for helping to understand the system structures and facilitate proper implementation of user requirements. Despite its importance in the software engineering pr...
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Modeling and analyzing software architectures are useful for helping to understand the system structures and facilitate proper implementation of user requirements. Despite its importance in the software engineering practice, the lack of formal description and verification support hinders the development of quality architectural models. In this work, we develop an approach for modeling and verifying software architectures specified using Monterey Phoenix (MP) architecture description language. Firstly, we formalize the syntax and operational semantics for MP. This language is capable of modeling system and environment behaviors based on event traces, as well as supporting different architecture composition operations and views. Secondly, a dedicated model checker for MP is developed based on PAT verification framework. Finally, several case studies are presented to evaluate the usability and effectiveness of our approach.
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