529 resultados para FINITE-STATE MACHINES


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Parliamentary questions are the most popular and visible tool for making the executive accountable to the legislature. However, their use, purpose and effectiveness vary in different countries. In this study, 4023 parliamentary questions asked in the Uttar Pradesh State Legislative Assembly were analysed. The results show that half of the total members of the Assembly used this device. Contrary to findings in the Australian parliamentary system, there was no evidence of ‘Dorothy Dix’ and party influence on parliamentary questions. Furthermore, 30% of the questions were aimed at seeking information and 70% pressed for action. The government provided the required information in 95% of the questions in the former category but only took action in 37% in the latter category. The study concludes that parliamentary questions serve as an effective legislative tool in the Uttar Pradesh Legislature

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Industrial applications of the simulated-moving-bed (SMB) chromatographic technology have brought an emergent demand to improve the SMB process operation for higher efficiency and better robustness. Improved process modelling and more-efficient model computation will pave a path to meet this demand. However, the SMB unit operation exhibits complex dynamics, leading to challenges in SMB process modelling and model computation. One of the significant problems is how to quickly obtain the steady state of an SMB process model, as process metrics at the steady state are critical for process design and real-time control. The conventional computation method, which solves the process model cycle by cycle and takes the solution only when a cyclic steady state is reached after a certain number of switching, is computationally expensive. Adopting the concept of quasi-envelope (QE), this work treats the SMB operation as a pseudo-oscillatory process because of its large number of continuous switching. Then, an innovative QE computation scheme is developed to quickly obtain the steady state solution of an SMB model for any arbitrary initial condition. The QE computation scheme allows larger steps to be taken for predicting the slow change of the starting state within each switching. Incorporating with the wavelet-based technique, this scheme is demonstrated to be effective and efficient for an SMB sugar separation process. Moreover, investigations are also carried out on when the computation scheme should be activated and how the convergence of the scheme is affected by a variable stepsize.

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Fire design is an essential element of the overall design procedure of structural steel members and systems. Conventionally the fire rating of load-bearing stud wall systems made of light gauge steel frames (LSF) is based on approximate prescriptive methods developed on the basis of limited fire tests. This design is limited to standard wall configurations used by the industry. Increased fire rating is provided simply by adding more plasterboards to the stud walls. This is not an acceptable situation as it not only inhibits innovation and structural and cost efficiencies but also casts doubt over the fire safety of these light gauge steel stud wall systems. Hence a detailed fire research study into the performance and effectiveness of a recently developed innovative composite panel wall system was undertaken at Queensland University of Technology using both full scale fire tests and numerical studies. Experimental results of LSF walls using the new composite panels under axial compression load have shown the improvement in fire performance and fire resistance rating. Numerical analyses are currently being undertaken using the finite element program ABAQUS. Measured temperature profiles of the studs are used in the numerical models and the results are used to calibrate against full scale test results. The validated model will be used in a detailed parametric study with an aim to develop suitable design rules within the current cold-formed steel structures and fire design standards. This paper will present the results of experimental and numerical investigations into the structural and fire behaviour of light gauge steel stud walls protected by the new composite panel. It will demonstrate the improvements provided by the new composite panel system in comparison to traditional wall systems.

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Assessing the structural health state of urban infrastructure is crucial in terms of infrastructure sustainability. This chapter uses dynamic computer simulation techniques to apply a procedure using vibration-based methods for damage assessment in multiple-girder composite bridges. In addition to changes in natural frequencies, this multi-criteria procedure incorporates two methods, namely, the modal flexibility and the modal strain energy method. Using the numerically simulated modal data obtained through finite element analysis software, algorithms based on modal flexibility and modal strain energy change, before and after damage, are obtained and used as the indices for the assessment of structural health state. The feasibility and capability of the approach is demonstrated through numerical studies of a proposed structure with six damage scenarios. It is concluded that the modal strain energy method is capable of application to multiple-girder composite bridges, as evidenced through the example treated in this chapter.

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This paper examines accountability in the context of New Zealand's state-owned enterprises (SOEs), and considers an accountability framework which extends beyond traditional (upward and outward) dimensions. While traditional accountability dimensions are clearly detailed in the legislation, less clear are the dilemmas and contradictions faced by SOEs, balancing multiple interests, and at times, conflicting objectives. These issues are explored through interviews conducted in two phases over a two year period with senior executives from 12 of the then 17 SOEs operating in New Zealand. Findings reveal a number of dimensions of accountability that extend beyond current conceptualisations of accountability in the public sector, often including multiple directions of accountability. Implications suggest the need for a more explicit framework of accountability relevant to the SOE context, which may serve useful in identifying potential pathways to conflict mitigation.

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Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the application of Gaussian mixture model (GMM) techniques to speaker verification systems providing state-of-the-art performance. GMM's are a type of generative classifier trained to model the probability distribution of the features used to represent a speaker. Recently introduced to the field of ASV research is the support vector machine (SVM). An SVM is a discriminative classifier requiring examples from both positive and negative classes to train a speaker model. The SVM is based on margin maximisation whereby a hyperplane attempts to separate classes in a high dimensional space. SVMs applied to the task of speaker verification have shown high potential, particularly when used to complement current GMM-based techniques in hybrid systems. This work aims to improve the performance of ASV systems using novel and innovative SVM-based techniques. Research was divided into three main themes: session variability compensation for SVMs; unsupervised model adaptation; and impostor dataset selection. The first theme investigated the differences between the GMM and SVM domains for the modelling of session variability | an aspect crucial for robust speaker verification. Techniques developed to improve the robustness of GMMbased classification were shown to bring about similar benefits to discriminative SVM classification through their integration in the hybrid GMM mean supervector SVM classifier. Further, the domains for the modelling of session variation were contrasted to find a number of common factors, however, the SVM-domain consistently provided marginally better session variation compensation. Minimal complementary information was found between the techniques due to the similarities in how they achieved their objectives. The second theme saw the proposal of a novel model for the purpose of session variation compensation in ASV systems. Continuous progressive model adaptation attempts to improve speaker models by retraining them after exploiting all encountered test utterances during normal use of the system. The introduction of the weight-based factor analysis model provided significant performance improvements of over 60% in an unsupervised scenario. SVM-based classification was then integrated into the progressive system providing further benefits in performance over the GMM counterpart. Analysis demonstrated that SVMs also hold several beneficial characteristics to the task of unsupervised model adaptation prompting further research in the area. In pursuing the final theme, an innovative background dataset selection technique was developed. This technique selects the most appropriate subset of examples from a large and diverse set of candidate impostor observations for use as the SVM background by exploiting the SVM training process. This selection was performed on a per-observation basis so as to overcome the shortcoming of the traditional heuristic-based approach to dataset selection. Results demonstrate the approach to provide performance improvements over both the use of the complete candidate dataset and the best heuristically-selected dataset whilst being only a fraction of the size. The refined dataset was also shown to generalise well to unseen corpora and be highly applicable to the selection of impostor cohorts required in alternate techniques for speaker verification.

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Examines the political and ideological influences on China's economic reforms since the early 1980s. Discusses the influence of the Chinese Communist Party and Confucianism on economic progress and assesses the effect of reforms. Outlines the requirement for new corporate governance laws to meet the needs of expanding private businesses and considers China's use and adaptation of some Western models of corporate governance. Comments on whether these fit easily with China's business culture. Criticises the shortcomings of China's corporate laws. Looks in particular at the telecommunications industry and at the Company Law 2006.

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On the surface the subjects of Corporate Social Responsibility (CSR) and Critical Management Studies (CMS) seem to be closely related. Both are concerned with reflecting on the impact of management and organisation on employees, the wider community and the environment. Both suggest that there may be a need for organisations to take responsibility for and account of people other than shareholders and both have used the concept of accountability to suggest that organisations may need to do more than just comply with the legal framework.

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This article examines the relationship between the arts and national innovation policy in Australia, pivoting around the Venturous Australia report released in September 2008 as part of the Review of the National Innovation System (RNIS). This came at a time of optimism that the arts sector would be included in Australia’s federal innovation policy. However, despite the report’s broad vision for innovation and specific commentary on the arts, the more ambitious hopes of arts sector advocates remained unfulfilled. This article examines the entwining discourses of creativity and innovation which emerged globally and in Australia prior to the RNIS, before analysing Venturous Australia in terms of the arts and the ongoing science-and-technology bias to innovation policy. It ends by considering why sector-led policy research and lobbying has to date proved unsuccessful and then suggests what public policy development is now needed.

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US state-based data breach notification laws have unveiled serious corporate and government failures regarding the security of personal information. These laws require organisations to notify persons who may be affected by an unauthorized acquisition of their personal information. Safe harbours to notification exist if personal information is encrypted. Three types of safe harbour have been identified in the literature: exemptions, rebuttable presumptions and factors. The underlying assumption of exemptions is that encrypted personal information is secure and therefore unauthorized access does not pose a risk. However, the viability of this assumption is questionable when examined against data breaches involving encrypted information and the demanding practical requirements of effective encryption management. Recent recommendations by the Australian Law Reform Commission (ALRC) would amend the Privacy Act 1988 (Cth) to implement a data breach scheme that includes a different type of safe harbour, factor based analysis. The authors examine the potential capability of the ALRC’s proposed encryption safe harbour in relation to the US experience at the state legislature level.

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In a recent decision by Mr Justice Laddie, a patent was held anticipated by, inter alia, prior use of a device which fell within the claims of the patent in suit, even though its circuitry was enclosed in resin. The anticipating invention had been "made available to the public" within the terms of section 2 (2) of the Patents Act 1977 because its essential integers would have been revealed by an interesting character, the "skilled forensic engineer".

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When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.

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VMSCRIPT is a scripting language designed to allow small programs to be compiled for a range of generated tiny virtual machines, suitable for sensor network devices. The VMSCRIPT compiler is an optimising compiler designed to allow quick re-targeting, based on a template, code rewriting model. A compiler backend can be specified at the same time as a virtual machine, with the compiler reading the specification and using it as a code generator.

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Introduction Ovine models are widely used in orthopaedic research. To better understand the impact of orthopaedic procedures computer simulations are necessary. 3D finite element (FE) models of bones allow implant designs to be investigated mechanically, thereby reducing mechanical testing. Hypothesis We present the development and validation of an ovine tibia FE model for use in the analysis of tibia fracture fixation plates. Material & Methods Mechanical testing of the tibia consisted of an offset 3-pt bend test with three repetitions of loading to 350N and return to 50N. Tri-axial stacked strain gauges were applied to the anterior and posterior surfaces of the bone and two rigid bodies – consisting of eight infrared active markers, were attached to the ends of the tibia. Positional measurements were taken with a FARO arm 3D digitiser. The FE model was constructed with both geometry and material properties derived from CT images of the bone. The elasticity-density relationship used for material property determination was validated separately using mechanical testing. This model was then transformed to the same coordinate system as the in vitro mechanical test and loads applied. Results Comparison between the mechanical testing and the FE model showed good correlation in surface strains (difference: anterior 2.3%, posterior 3.2%). Discussion & Conclusion This method of model creation provides a simple method for generating subject specific FE models from CT scans. The use of the CT data set for both the geometry and the material properties ensures a more accurate representation of the specific bone. This is reflected in the similarity of the surface strain results.

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The paper compares three different methods of inclusion of current phasor measurements by phasor measurement units (PMUs) in the conventional power system state estimator. For each of the three methods, comprehensive formulation of the hybrid state estimator in the presence of conventional and PMU measurements is presented. The performance of the state estimator in the presence of conventional measurements and optimally placed PMUs is evaluated in terms of convergence characteristics and estimator accuracy. Test results on the IEEE 14-bus and IEEE 300-bus systems are analyzed to determine the best possible method of inclusion of PMU current phasor measurements.