887 resultados para Harp with instrumental ensemble


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Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

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The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

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Relationships between self-reported retrospective falls and cognitive measures (executive function, reaction time, processing speed, working memory, visual attention) were examined in a population based sample of older adults (n = 658). Two of the choice reaction time tests involved inhibiting responses to either targets of a specific color or location with hand and foot responses. Potentially confounding demographic variables, medical conditions and postural sway were controlled for in logistic regression models, excluding participants with possible cognitive impairment. A factor analysis of cognitive measures extracted factors measuring reaction time, accuracy and inhibition, and visual search. Single fallers did not differ from non-fallers in terms of health, sway or cognitive function, except that they performed worse on accuracy and inhibition. In contrast, recurrent fallers performed worse than non-fallers on all measures. Results suggest that occasional falls in late life may be associated with subtle age-related changes in the pre-frontal cortex leading to failures of executive control, whereas recurrent falling may result from more advanced brain ageing that is associated with generalized cognitive decline.

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Occupational stress has been a concern for human resource managers in light of research investigating the work stressor-employee adjustment relationship. This research has consistently demonstrated many negative effects between stressors in the workplace and employee adjustment. A considerable amount of literature also describes potential moderators of this relationship. Subjective fit with organizational culture has been established as a significant predictor of employee job-related attitudes; however, research has neglected investigation of the potential moderating effect of subjective fit in the work stressor-employee adjustment process. It was predicted that perceptions of subjective fit with the organization’s values and goals would mitigate the negative effect of work stressors on employee adjustment in an employee sample from three organizations (N ¼ 256). Hierarchical multiple regression analyses revealed support for the stress-buffering effects of high subjective fit in the prediction of physical symptoms, job satisfaction, and intentions to leave. The theoretical and practical implications of the results are discussed.

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Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

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This paper describes protection and control of a microgrid with converter interfaced micro sources. The proposed protection and control scheme consider both grid connected and autonomous operation of the microgrid. A protection scheme, capable of detecting faults effectively in both grid connected and islanded operations is proposed. The main challenge of the protection, due to current limiting state of the converters is overcome by using admittance relays. The relays operate according to the inverse time characteristic based on measured admittance of the line. The proposed scheme isolates the fault from both sides, while downstream side of the microgrid operates in islanding condition. Moreover faults can be detected in autonomous operation. In grid connected mode distributed generators (DG) supply the rated power while in absence of the grid, DGs share the entire power requirement proportional to rating based on output voltage angle droop control. The protection scheme ensures minimum load shedding with isolating the faulted network and DG control provides a smooth islanding and resynchronization operation. The efficacy of coordinated control and protection scheme has been validated through simulation for various operating conditions.

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This paper proposes a method of enhancing system stability with a distribution static compensator (DSTATCOM) in an autonomous microgrid with multiple distributed generators (DG). It is assumed that there are both inertial and non-inertial DGs connected to the microgrid. The inertial DG can be a synchronous machine of smaller rating while inertia less DGs (solar) are assumed as DC sources. The inertia less DGs are connected through Voltage Source Converter (VSC) to the microgrid. The VSCs are controlled by either state feedback or current feedback mode to achieve desired voltage-current or power outputs respectively. The power sharing among the DGs is achieved by drooping voltage angle. Once the reference for the output voltage magnitude and angle is calculated from the droop, state feedback controllers are used to track the reference. The angle reference for the synchronous machine is compared with the output voltage angle of the machine and the error is fed to a PI controller. The controller output is used to set the power reference of the synchronous machine. The rate of change in the angle in a synchronous machine is restricted by the machine inertia and to mimic this nature, the rate of change in the VSCs angles are restricted by a derivative feedback in the droop control. The connected distribution static compensator (DSTATCOM) provides ride through capability during power imbalance in the microgrid, especially when the stored energy of the inertial DG is not sufficient to maintain stability. The inclusion of the DSATCOM in such cases ensures the system stability. The efficacies of the controllers are established through extensive simulation studies using PSCAD.

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Our students come from diverse backgrounds. They need flexibility in their learning. First year students tend to worry when they miss lectures or part of lectures. Having the lecture as an on line resource allows students to miss a lecture without stressing about it and to be more relaxed in the lecture, knowing that anything they may miss will be available later. The resource: The Windows based program from Blueberry Software (not Blackberry!) - BB Flashback - allows the simultaneous recording of the computer screen together with the audio, as well as Webcam recording. Editing capabilities include adding pause buttons, graphics and text to the file before exporting it in a flash file. Any diagrams drawn on the board or shown via visualiser can be photographed and easily incorporated. The audio from the file can be extracted if required to be posted as podcast. Exporting modes other than Flash are also available, allowing vodcasting if you wish. What you will need: - the recording software: it can be installed on the lecture hall computer just prior to lecture if needed - a computer: either the ones in lecture halls, especially if fitted with audio recording, or a laptop (I have used audio recording via Bluetooth for mobility). Feedback from students has been positive and will be presented on the poster.

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PERWAPI is a component for reading and writing .NET PE-files. The name is a compound acronym for Program Executable – Reader/Writer – Application Programming Interface. The code was written by one of us (Diane Corney) with some contributions from some of the early users of the tool. PERWAPI is a managed component, written entirely in safe C#. The design of the writer part of the component is loosely based on Diane Corney’s previous PEAPI component. It is open source software, and is released under a “FreeBSD-like” license. The source may be downloaded from “http://plas.fit.qut.edu.au/perwapi/” As of the date of this document the code has facilities for reading and writing PEfiles compatible with the latest (beta-2) release of the ”Whidbey” version of .NET, that is, the Visual Studio 2005 framework. An invocation option allows earlier versions of the framework to be targeted.

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Functional communication training was used to replace multiply determined problem behaviour in two boys with autism. Experiment 1 involved a functional analysis of several topographies of problem behaviour using a variation of the procedures described by Iwata, Dorsey, Slifer, Bauman, and Richman. Results suggested that aggression, self-injury, and disruption were multiply determined (i.e., maintained by both attention and access to preferred objects). Experiment 2 involved a multiple-baseline design across subjects. The focus of intervention was to replace aggression, self-injury, and disruption with functionally equivalent communicative alternatives. Both boys were taught alternative “mands” to recruit attention and request preferred objects. Acquisition of these alternative communication skills was associated with concurrent decreases in aggression, self-injury, and disruption. Results suggest that multiply determined challenging behaviour can be decreased by teaching an alternative communication skill to replace each assessed function of the problem behaviour.

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Intervention to reduce challenging behaviour may be enhanced when based on a prior functional analysis. The present study describes a discrete-trial approach for the functional analysis of aggressive behaviour in two boys with autism. Twenty brief assessment trials were conducted in the classroom by the teacher under each of three conditions (i.e., attention, task and tangible). The results showed a clear pattern to each child's aggressive behaviour and suggested logical intervention strategies, although the study is limited because it involved only two children. The discrete-trial approach would appear to represent a practical and ecologically valid technique for conducting a functional analysis of challenging behaviour in applied settings

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3D Motion capture is a medium that plots motion, typically human motion, converting it into a form that can be represented digitally. It is a fast evolving field and recent inertial technology may provide new artistic possibilities for its use in live performance. Although not often used in this context, motion capture has a combination of attributes that can provide unique forms of collaboration with performance arts. The inertial motion capture suit used for this study has orientation sensors placed at strategic points on the body to map body motion. Its portability, real-time performance, ease of use, and its immunity from line-of-sight problems inherent in optical systems suggest it would work well as a live performance technology. Many animation techniques can be used in real-time. This research examines a broad cross-section of these techniques using four practice-led cases to assess the suitability of inertial motion capture to live performance. Although each case explores different visual possibilities, all make use of the performativity of the medium, using either an improvisational format or interactivity among stage, audience and screen that would be difficult to emulate any other way. A real-time environment is not capable of reproducing the depth and sophistication of animation people have come to expect through media. These environments take many hours to render. In time the combination of what can be produced in real-time and the tools available in a 3D environment will no doubt create their own tree of aesthetic directions in live performance. The case study looks at the potential of interactivity that this technology offers.

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This paper reports on a six month longitudinal study exploring people’s personal and social emotional experience with Portable Interactive Devices (PIDs). The study is concerned with the experience design approach and based on the theoretical framework of Activity Theory. The focus is on emotional experiences and how artefacts mediate and potentially enhance this experience. The outcomes of the study identified interesting aspects of PID interaction. Findings revealed people interact with PIDs emotionally both at a personal and a social level, supporting previous studies. Further, the social level impacts significantly on the emotional experience attained. If negative social experiences exceeded negative personal experiences the emotional experience was constant over six months. If negative personal experiences surpassed negative social experiences the emotional experience was varied over six months. The findings are discussed in regards to their significance to the field of design, their implication for future PID design and future research directions.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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This paper is aimed at investigating the effect of web openings on the plastic bending behaviour and section moment capacity of a new cold-formed steel beam known as LiteSteel beam (LSB) using numerical modelling. Different LSB sections with varying circular hole diameter and spacing were considered. A simplified but appropriate numerical modelling technique was developed for the modelling of monosymmetric sections such as LSBs subject to bending, and was used to simulate a series of section moment capacity tests of LSB flexural members with web openings. The buckling and ultimate strength behaviour was investigated in detail and the modeling technique was further improved through a comparison of numerical and experimental results. This paper describes the simplified finite element modeling technique used in this study that includes all the significant behavioural effects affecting the plastic bending behaviour and section moment capacity of LSB sections with web holes. Numerical and test results and associated findings are also presented.