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2969 items found
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Displaying Results 351 - 375 of 2969 on page 15 of 119
Marked
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Model-Based, Multimodal Interaction in Document Browsing.
(2006)
Eslambolchilar, Parisa; Murray-Smith, Roderick
Model-Based, Multimodal Interaction in Document Browsing.
(2006)
Eslambolchilar, Parisa; Murray-Smith, Roderick
Abstract:
In this paper we introduce a dynamic system approach to the design of multimodal interactive systems. We use an example where we support human behavior in browsing a document, by adapting the dynamics of navigation and the visual feedback (using a focus-in-context (F+C) method) to support the current inferred task. We also demonstrate non-speech audio feedback, based on a language model. We argue that to design interaction we need models of key aspects of the process, here for example, we need models for the dynamic system, language model and sonification. We show how the user's intention is coupled to the visualization technique via the dynamic model, and how the focus-in-context method couples details in context to audio samples via the language identifcation system. We present probabilistic audio feedback as an example of a multimodal approach to sensing different languages in a multilingual text. This general approach is well suited to mobile and wearable applications, and ...
http://eprints.maynoothuniversity.ie/1774/
Marked
Mark
Software supported modelling in pharmacokinetics.
(2006)
Telgmann, Regina ; von Kleist, Max; Huisinga, Wilhelm
Software supported modelling in pharmacokinetics.
(2006)
Telgmann, Regina ; von Kleist, Max; Huisinga, Wilhelm
Abstract:
A powerful new software concept to physiologically based pharmacokinetic (PBPK) modelling of drug disposition is presented. It links the inherent modular understanding in pharmacology with orthogonal design principles from software engineering. This concept allows for flexible and user-friendly design of pharmacokinetic whole body models, data analysis, hypotheses testing or extrapolation. The typical structure of physiologically-based pharmacokinetic models is introduced. The resulting requirements from a modelling and software engineering point of view and its realizations in the software tool MEDICI-PK are described. Finally, an example in the context of drug-drug interaction studies is given, that demonstrates the advantage of defining a whole-body pharmacokinetic model in terms of the underlying physiological processes quite impressively: A system of 162 ODEs is automatically compiled based on the specification of 7 local physiological processes only.
http://eprints.maynoothuniversity.ie/1770/
Marked
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How expensive is link utilization?
(2007)
Stanojević, Rade; Shorten, Robert N.
How expensive is link utilization?
(2007)
Stanojević, Rade; Shorten, Robert N.
Abstract:
Understanding the relationship between queueing delays and link utilization for general traffic conditions is an important open problem in networking research. Difficulties in understanding this relationship stem from the fact that it depends on the complex nature of arriving traffic and the problems associated with modelling such traffic. Existing AQM schemes achieve a "low delay" and "high utilization" by responding early to congestion without considering the exact relationship between delay and utilization. However, in the context of exploiting the delay/utilization tradeoff, the optimal choice of a queueing scheme's control parameter depends on the cost associated with the relative importance of queueing delay and utilization. The optimal choice of control parameter is the one that maximizes a benefit that can be defined as the difference between utilization and cost associated with queuing delay. We present a generic algorithm Optimal Delay-Utilization...
http://eprints.maynoothuniversity.ie/1759/
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An Application of Gaussian mixtures: colour segmenting for the four legged league using HSI colour space.
(2008)
Henderson, Naomi; King, Robert; Middleton, Richard H.
An Application of Gaussian mixtures: colour segmenting for the four legged league using HSI colour space.
(2008)
Henderson, Naomi; King, Robert; Middleton, Richard H.
Abstract:
In the colour coded environment of the RoboCup 4 Legged League it is crucial to extract as much colour information as possible from an image without error. To do this requires hours of manual YUV pixel mapping and testing to ensure robustness under all possible lighting conditions. The YUV colour space is a very convenient standard for transmission of video data, but for colour classification and segmentation it suffers from being non-intuitive and sensitive to changes in lighting. Alternatively, colour classification principles can be applied in an HSI colour space; one of the convenient characteristics of the HSI colour space is that the hue value, H, represents the colour wavelength information. From this concept it is easier to separate and label colour regions in an automated process as the theoretical hue and colour wavelength relationship is known. By fitting a Gaussian model using mixtures to HSI histograms we can generate boundaries of colour classes in HSI colour space.
http://eprints.maynoothuniversity.ie/1712/
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Channel dependent interference and decentralized colouring
(2007)
Clifford, P.; Leith, D. J.
Channel dependent interference and decentralized colouring
(2007)
Clifford, P.; Leith, D. J.
Abstract:
We consider channel allocation to mitigate interference be- tween wireless LANs. The channel allocation task is often formulated in the literature as finding a proper colouring of a single graph. We show that the interference between WLANs can be channel dependent in which case a different conflict graph is associated with each channel. Channel allocation then corresponds to a multi-graph colouring problem. This potentially has profound implications as the behaviour of many proposed colouring-based algorithms for channel allocation is unclear in a multi-graph context. We prove that a recently proposed decentralized colouring algorithm performs correctly in the multi-graph setting. We also present a new, extended version of this algorithm suited to a wide range of multi-radio architectures.
http://eprints.maynoothuniversity.ie/1710/
Marked
Mark
Inferring Queue State by Measuring Delay in a WiFi Network
(2009)
Malone, David; Leith, Douglas J. ; Dangerfield, Ian
Inferring Queue State by Measuring Delay in a WiFi Network
(2009)
Malone, David; Leith, Douglas J. ; Dangerfield, Ian
Abstract:
Packet round trip time is a quantity that is easy to measure for end hosts and applications. In many wired networks, the round trip has been exploited for purposes such as congestion control and bandwidth measurement because of relatively simple relationships between buffer occupancy and drain time. In 802.11 networks, the buffer drain times show considerable variability due to the random nature of the MAC service. We examine some of the problems faced when using round-trip-time-based queue estimates in these networks, particularly in relation to congestion control.
http://eprints.maynoothuniversity.ie/1500/
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Specification de services dans une logique temporelle compositionnelle
(1996)
Gibson, Paul; Mermet, B; Mokhtari, Y
Specification de services dans une logique temporelle compositionnelle
(1996)
Gibson, Paul; Mermet, B; Mokhtari, Y
Abstract:
Rapport de fin du lot1 du march© no96 1B CNET-CNRS-CRIN, Centre de Recherche en Informatique de Nancy.
http://eprints.maynoothuniversity.ie/17/
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An optical model of computation
(2005)
Woods, Damien; Naughton, Thomas J.
An optical model of computation
(2005)
Woods, Damien; Naughton, Thomas J.
Abstract:
We prove computability and complexity results for an original model of computation called the continuous space machine. Our model is inspired by the theory of Fourier optics. We prove our model can simulate analog recurrent neural networks, thus establishing a lower bound on its computational power. We also dene a (log2 n) unordered search algorithm with our model.
http://eprints.maynoothuniversity.ie/571/
Marked
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Collaboration-Preserving Authenticated Encryption for Operational Transformation Systems
(2012)
TEWARI, HITESH; HUGHES, ARTHUR
Collaboration-Preserving Authenticated Encryption for Operational Transformation Systems
(2012)
TEWARI, HITESH; HUGHES, ARTHUR
http://hdl.handle.net/2262/68179
Marked
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On the Application of Software Metrics to UML Models
(2007)
McQuillan, Jacqueline A.; Power, James F.
On the Application of Software Metrics to UML Models
(2007)
McQuillan, Jacqueline A.; Power, James F.
Abstract:
In this position paper we discuss a number of issues relating to model metrics, with particular emphasis on metrics for UML models. Our discussion is presented as a series of nine observations where we examine some of the existing work on applying metrics to UML models, present some of our own work in this area, and specify some topics for future research that we regard as important. Furthermore, we identify three categories of challeges for model metrics and describe how our nine observations can be partitioned into these categories.
http://eprints.maynoothuniversity.ie/6400/
Marked
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Platform Independent Timing of Java Virtual Machine Bytecode Instructions
(2008)
Lambert, Jonathan M.; Power, James F.
Platform Independent Timing of Java Virtual Machine Bytecode Instructions
(2008)
Lambert, Jonathan M.; Power, James F.
Abstract:
The accurate measurement of the execution time of Java bytecode is one factor that is important in order to estimate the total execution time of a Java application running on a Java Virtual Machine. In this paper we document the difficulties and solutions for the accurate timing of Java bytecode. We also identify trends across the execution times recorded for all imperative Java bytecodes. These trends would suggest that knowing the execution times of a small subset of the Java bytecode instructions would be sufficient to model the execution times of the remainder. We first review a statistical approach for achieving high precision timing results for Java bytecode using low precision timers and then present a more suitable technique using homogeneous bytecode sequences for recording such information. We finally compare instruction execution times acquired using this platform independent technique against execution times recorded using the read time stamp counter assembly instruction...
http://eprints.maynoothuniversity.ie/6382/
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An early completion algorithm: Thue's 1914 paper on the transformation of symbol sequences
(2014)
Power, James F.
An early completion algorithm: Thue's 1914 paper on the transformation of symbol sequences
(2014)
Power, James F.
Abstract:
References to Thue's 1914 paper on string transformation systems are based mainly on a small section of that work defining Thue systems. A closer study of the remaining parts of that paper highlight a number of important themes in the history of computing: the transition from algebra to formal language theory, the analysis of the "computational power" (in a pre-1936 sense) of rules, and the development of algorithms to generate rule-sets.
http://eprints.maynoothuniversity.ie/6372/
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Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous : Computer Science and Artificial Intelligence Laboratory Technical Report MIT-CSAIL-TR-2012-031
(2012)
Whelan, Thomas; Johannsson, Hordur; Kaess, Michael; Leonard, John J.; McDonald, John
Robust Tracking for Real-Time Dense RGB-D Mapping with Kintinuous : Computer Science and Artificial Intelligence Laboratory Technical Report MIT-CSAIL-TR-2012-031
(2012)
Whelan, Thomas; Johannsson, Hordur; Kaess, Michael; Leonard, John J.; McDonald, John
Abstract:
This paper describes extensions to the Kintinuous [1] algorithm for spatially extended KinectFusion, incorporating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust tracking; (ii) a novel GPU-based implementation of an existing dense RGB-D visual odometry algorithm; (iii) advanced fused realtime surface coloring. These extensions are validated with extensive experimental results, both quantitative and qualitative, demonstrating the ability to build dense fully colored models of spatially extended environments for robotics and virtual reality applications while remaining robust against scenes with challenging sets of geometric and visual features.
http://eprints.maynoothuniversity.ie/6501/
Marked
Mark
Applying natural language processing to clinical information retrieval
(2014)
Cogley, James
Applying natural language processing to clinical information retrieval
(2014)
Cogley, James
Abstract:
Medical literature, such as medical health records are increasingly digitised.As with any large growth of digital data, methods must be developed to managedata as well as to extract any important information. Information Retrieval(IR) techniques, for instance search engines, provide an intuitive medium inlocating important information among large volumes of data. With more andmore patient records being digitised, the use of search engines in a healthcaresetting provides a highly promising method for efficiently overcomingthe problem of information overload.Traditional IR approaches often perform retrieval based solely using term frequencycounts, known as a `bag-of-words' approach. While these approachesare effective in certain settings they fail to account for more complex semanticrelationships that are often more prevalent in medical literature such as negation(e.g. `absence of palpitations'), temporality (e.g. `previous admissionfor fracture') or attribution (e.g. `...
http://hdl.handle.net/10197/6803
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L_ Inference for shape parameter estimation
(2014)
Arellano Vidal, Claudia L.
L_ Inference for shape parameter estimation
(2014)
Arellano Vidal, Claudia L.
Abstract:
THESIS 10384
In this thesis, we propose a method to robustly estimate the parameters that controls the mapping of a shape (model shape) onto another (target shape). The shapes of interest are contours in the 2D space, surfaces in the 3D space and point clouds (either in 2D and 3D spaces). We propose to model the shapes using Gaussian Mixture Models (GMMs) and estimate the transformation parameters by minimising a cost function based on the Euclidean (L2) distance between the target and model GMMs. This strategy allows us to avoid the need for the computation of one to one point correspondences that are required by state of the art approaches making them sensitive to both outliers and the choice of the starting guess in the algorithm used for optimisation. Shapes are well represented by GMMs when careful consideration is given to the design of the covariance matrices. Compared to isotropic covariance matrices, we show how shape matching with L2 can be made more robust and accurat...
http://hdl.handle.net/2262/77592
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Reliability updating in linear opinion pooling for multiple decision makers
(2016)
Bolger, Donnacha
Reliability updating in linear opinion pooling for multiple decision makers
(2016)
Bolger, Donnacha
Abstract:
Accurate information sources are vital prerequisites for good decision making. In this thesis we consider a multiple participant setting, where all decision makers (DMs) have a collection of neighbours with whom they share their beliefs about some common relevant uncertain quantity. When determining which course of action to follow a DM takes into account all the information received from her neighbours. Over time, in light of the returns observed from choices made, DMs update their own beliefs over the uncertain event, and also adjust the degree of consideration that they afford to the opinions of each neighbour based on the level of reliability that the information they provide is ascertained to have. Much of this thesis is concerned with constructing a method that incorporates both of these learning facets in a dynamic fashion. This technique, termed the Plug-in approach, is motivated and derived, and attempts are made to justify its use by consideration of some attractive proper...
http://hdl.handle.net/2262/77598
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A new method to implement Bayesian inference on stochastic differential equation models
(2011)
Joshi, Chaitanya
A new method to implement Bayesian inference on stochastic differential equation models
(2011)
Joshi, Chaitanya
Abstract:
THESIS 9176
Stochastic differential equations (SDEs) are widely used to model numerous real-life phenomena. However, transition densities of most of the SDE models used in practice are not known, making both likelihood based and Bayesian inference difficult. Methods for Bayesian inference have mainly relied on MCMC based methods which are computationally expensive. There is a need to develop a computationally efficient method which will provide accurate inference. This thesis introduces a new approach to approximate Bayesian inference for SDE models. This approach is not MCMC based and aims to provide a more efficient option for Bayesian inference on SDE models. This research problem was motivated by a civil engineering problem of modeling the force exerted by vehicles on the road surface as they traverse it. Proposed here two new methods to implement this approach. These methods have been named as the Gaussian Modified Bridge Approximation (GaMBA) and its extension GaMBA- Impor...
http://hdl.handle.net/2262/77625
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Bayesian inference for short term traffic forecasting
(2013)
Mai, Tiep K.
Bayesian inference for short term traffic forecasting
(2013)
Mai, Tiep K.
Abstract:
THESIS 10292
In intelligent transport systems, short term traffic forecasting is one of the most important problems, reflecting the network state in the near future and feeding information to other application modules. Even though there have been quite a lot of works in this area, most of them are univariate models which may not be able to exploit the spatial relationship of traffic variables. So, this thesis explores the domain of two renowned modelling classes, the auto regressive moving average model and the dynamic model, taking into account the spatial dependency. The sparse-form vector autoregressive moving average model is applied to the short term traffic forecasting problem with different preprocessing methods. Network information is used to constrain the matrix parameters of the model, reducing the number of parameters. For the estimation problem, an improved MCMC method is proposed to tackle the variable correlation problem, using the marginalisation and the correlati...
http://hdl.handle.net/2262/77634
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Mark
Tracking the distribution of bugs across software release versions
(2015)
? R?ord?in, Se?n
Tracking the distribution of bugs across software release versions
(2015)
? R?ord?in, Se?n
Abstract:
Real software systems always contain bugs and the question on every release manager?s mind coming up to a release centres around how many undiscovered bugs there still remain. This work looks at one model, (Goel and Okumoto, 1979), which tries to answer this question and extends previous work to try to borrow strength from previous release versions to help answer this question in a more rational manner.
http://hdl.handle.net/2262/77644
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Bayesian approaches to content-based image retrieval
(2006)
Stefanou, Georgios Andrea
Bayesian approaches to content-based image retrieval
(2006)
Stefanou, Georgios Andrea
Abstract:
THESIS 7902
This thesis addresses some issues in the relatively new field of Content-Based Image Retrieval. Content-based image retrieval is a technique that uses the visual content of images to aid searches from large scale image databases. The field of content-based image retrieval is growing in importance as image archives grow in size in many fields, and a means to search for visual content on the Web. In this thesis we investigate Bayesian approaches to content-based image retrieval. Starting from the work of Cox et al. (1996) and Cox et al. (2000), we propose a retrieval system that attempts to capture properties of the visual content of images and how a user conducts a search. Decision theory is applied to the problem of selecting images to retrieve. The system is evaluated using a variety of tests with users.
http://hdl.handle.net/2262/77665
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Baran: an interaction-centred user monitoring framework
(2015)
Hashemi, Mohammad; Herbert, John
Baran: an interaction-centred user monitoring framework
(2015)
Hashemi, Mohammad; Herbert, John
Abstract:
User Quality of Experience (QoE) is a subjective entity and difficult to measure. One important aspect of it, User Experience (UX), corresponds to the sensory and emotional state of a user. For a user interacting through a User Interface (UI), precise information on how they are using the UI can contribute to understanding their UX, and thereby understanding their QoE. As well as a user’s use of the UI such as clicking, scrolling, touching, or selecting, other real-time digital information about the user such as from smart phone sensors (e.g. accelerometer, light level) and physiological sensors (e.g. heart rate, ECG, EEG) could contribute to understanding UX. Baran is a framework that is designed to capture, record, manage and analyse the User Digital Imprint (UDI) which, is the data structure containing all user context information. Baran simplifies the process of collecting experimental information in Human and Computer Interaction (HCI) studies, by recording comprehensive real-t...
http://hdl.handle.net/10468/3360
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Bayesian kernel classification for high dimensional data with variable selection
(2009)
Domijan, Katarina
Bayesian kernel classification for high dimensional data with variable selection
(2009)
Domijan, Katarina
Abstract:
THESIS 8829
High dimensional data sets, where the dimension of the measurements exceeds the number of samples, arise in many application domains. In particular, the development of genomic and proteomic technologies in the last decade has seen a rapid emergence of such ?high-throughput? data and has generated much interest in the statistical community, as analysis of such data requires novel statistical techniques. One area where this has arisen is classification of high dimensional data. This challenging problem is the central focus of this thesis. Models for classification are developed based on reproducing kernel Hilbert spaces theory and are set in the fully Bayesian framework. MCMC techniques are employed in order to sample from the posterior distributions of the model parameters. The proposed classification approaches are applied to microarray, image processing and near-infrared spectroscopy data sets. However, the methods are general and can be used for a variety of classi...
http://hdl.handle.net/2262/78348
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Utilisation of electronic fare collection data of urban bus operators with regard to transfer journeys and origin / destination estimation
(2008)
Hofmann, Markus
Utilisation of electronic fare collection data of urban bus operators with regard to transfer journeys and origin / destination estimation
(2008)
Hofmann, Markus
Abstract:
THESIS 8635
The understanding of an urban public transport network from an operational point of view and the understanding of passenger?s travel patterns become increasingly important due to the growing complexity of most networks. Large cities heavily depend on their public transport networks as urbanisation vastly increases. One way of obtaining more factual knowledge of network?s performance measures and passenger travel patterns is to analyse Electronic Fare Collection (EFC) data which are recorded when buying or validating tickets. Dublin?s main urban bus operator, Dublin Bus, records trip level data from passengers that use a ticket that is valid for a period of time. Such tickets have a unique identifier for the validity period which allows to analyse travel paths of individual passengers. Over 45 million individual passenger boardings were recorded over a two year period.
http://hdl.handle.net/2262/78422
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Fast approximate inverse Bayesian inference in non-parametric multivariate regression with application to palaeoclimate reconstruction
(2009)
Salter-Townshend, Michael
Fast approximate inverse Bayesian inference in non-parametric multivariate regression with application to palaeoclimate reconstruction
(2009)
Salter-Townshend, Michael
Abstract:
THESIS 8747
Bayesian statistical methods often inyolye computationally intensive inference procedures. Sampling algorithms represent the current standard for fitting and testing models. Such methods, while flexible, are computationally intensive and suffer from long run times and high potential sampling error. New methods for fitting non-parametric approximations offer a fast and accurate alternative. Essentially, a multivariate Gaussian distribution is used to approximate the posterior of the model parameters.
http://hdl.handle.net/2262/78617
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Advances in Bayesian model development and inversion in multivariate inverse inference problems : with application to palaeoclimate reconstruction
(2012)
Sweeney, James
Advances in Bayesian model development and inversion in multivariate inverse inference problems : with application to palaeoclimate reconstruction
(2012)
Sweeney, James
Abstract:
THESIS 10049
An extremely challenging example of a multivariate inverse inference problem is the statistical reconstruction of palaeoclimate from fossil pollen data, which represents the motivating research problem considered in this thesis. The model training dataset, consisting of highly multivariate, zero-inflated compositional counts for vegetation, as well as measurements on several climate covariates, presents numerous challenges of model choice and inference. The addressing of these challenges provides the focus for the research contributions presented herein.
http://hdl.handle.net/2262/79366
Displaying Results 351 - 375 of 2969 on page 15 of 119
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