11 resultados para abstract user interfaces

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Models and software products have been developed for modelling, simulation and prediction of different correlations in materials science, including 1. the correlation between processing parameters and properties in titanium alloys and ?-titanium aluminides; 2. time–temperature–transformation (TTT) diagrams for titanium alloys; 3. corrosion resistance of titanium alloys; 4. surface hardness and microhardness profile of nitrocarburised layers; 5. fatigue stress life (S–N) diagrams for Ti–6Al–4V alloys. The programs are based on trained artificial neural networks. For each particular case appropriate combination of inputs and outputs is chosen. Very good performances of the models are achieved. Graphical user interfaces (GUI) are created for easy use of the models. In addition interactive text versions are developed. The models designed are combined and integrated in software package that is built up on a modular fashion. The software products are available in versions for different platforms including Windows 95/98/2000/NT, UNIX and Apple Macintosh. Description of the software products is given, to demonstrate that they are convenient and powerful tools for practical applications in solving various problems in materials science. Examples for optimisation of the alloy compositions, processing parameters and working conditions are illustrated. An option for use of the software in materials selection procedure is described.

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For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.

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Managing gait disturbances in people with Parkinson’s disease is a pressing challenge, as symptoms can contribute to injury and morbidity through an increased risk of falls. While drug-based interventions have limited efficacy in alleviating gait impairments, certain non-pharmacological methods, such as cueing, can also induce transient improvements to gait. The approach adopted here is to use computationally-generated sounds to help guide and improve walking actions. The first method described uses recordings of force data taken from the steps of a healthy adult which in turn were used to synthesize realistic gravel-footstep sounds that represented different spatio-temporal parameters of gait, such as step duration and step length. The second method described involves a novel method of sonifying, in real time, the swing phase of gait using real-time motion-capture data to control a sound synthesis engine. Both approaches explore how simple but rich auditory representations of action based events can be used by people with Parkinson’s to guide and improve the quality of their walking, reducing the risk of falls and injury. Studies with Parkinson’s disease patients are reported which show positive results for both techniques in reducing step length variability. Potential future directions for how these sound approaches can be used to manage gait disturbances in Parkinson’s are also discussed.

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Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users’ need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “dengue fever headache.” In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.

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In this paper a model of grid computation that supports both heterogeneity and dynamicity is presented. The model presupposes that user sites contain software components awaiting execution on the grid. User sites and grid sites interact by means of managers which control dynamic behaviour. The orchestration language ORC [9,10] offers an abstract means of specifying operations for resource acquisition and execution monitoring while allowing for the possibility of non-responsive hardware. It is demonstrated that ORC is sufficiently expressive to model typical kinds of grid interactions.

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In this paper we continue our investigation into the development of computational-science software based on the identification and formal specification of Abstract Data Types (ADTs) and their implementation in Fortran 90. In particular, we consider the consequences of using pointers when implementing a formally specified ADT in Fortran 90. Our aim is to highlight the resulting conflict between the goal of information hiding, which is central to the ADT methodology, and the space efficiency of the implementation. We show that the issue of storage recovery cannot be avoided by the ADT user, and present a range of implementations of a simple ADT to illustrate various approaches towards satisfactory storage management. Finally, we propose a set of guidelines for implementing ADTs using pointers in Fortran 90. These guidelines offer a way gracefully to provide disposal operations in Fortran 90. Such an approach is desirable since Fortran 90 does not provide automatic garbage collection which is offered by many object-oriented languages including Eiffel, Java, Smalltalk, and Simula.

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This paper describes an end-user model for a domestic pervasive computing platform formed by regular home objects. The platform does not rely on pre-planned infrastructure; instead, it exploits objects that are already available in the home and exposes their joint sensing, actuating and computing capabilities to home automation applications. We advocate an incremental process of the platform formation and introduce tangible, object-like artifacts for representing important platform functions. One of those artifacts, the application pill, is a tiny object with a minimal user interface, used to carry the application, as well as to start and stop its execution and provide hints about its operational status. We also emphasize streamlining the user's interaction with the platform. The user engages any UI-capable object of his choice to configure applications, while applications issue notifications and alerts exploiting whichever available objects can be used for that purpose. Finally, the paper briefly describes an actual implementation of the presented end-user model. © (2010) by International Academy, Research, and Industry Association (IARIA).

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This paper describes a substantial effort to build a real-time interactive multimodal dialogue system with a focus on emotional and non-verbal interaction capabilities. The work is motivated by the aim to provide technology with competences in perceiving and producing the emotional and non-verbal behaviours required to sustain a conversational dialogue. We present the Sensitive Artificial Listener (SAL) scenario as a setting which seems particularly suited for the study of emotional and non-verbal behaviour, since it requires only very limited verbal understanding on the part of the machine. This scenario allows us to concentrate on non-verbal capabilities without having to address at the same time the challenges of spoken language understanding, task modeling etc. We first summarise three prototype versions of the SAL scenario, in which the behaviour of the Sensitive Artificial Listener characters was determined by a human operator. These prototypes served the purpose of verifying the effectiveness of the SAL scenario and allowed us to collect data required for building system components for analysing and synthesising the respective behaviours. We then describe the fully autonomous integrated real-time system we created, which combines incremental analysis of user behaviour, dialogue management, and synthesis of speaker and listener behaviour of a SAL character displayed as a virtual agent. We discuss principles that should underlie the evaluation of SAL-type systems. Since the system is designed for modularity and reuse, and since it is publicly available, the SAL system has potential as a joint research tool in the affective computing research community.