956 resultados para Convergence conditionnelle


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Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

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This paper examines the dynamic behaviour of relative prices across seven Australian cities by applying panel unit root test procedures with structural breaks to quarterly consumer price index data for 1972 Q1–2011 Q4. We find overwhelming evidence of convergence in city relative prices. Three common structural breaks are endogenously determined at 1985, 1995, and 2007. Further, correcting for two potential biases, namely Nickell bias and time aggregation bias, we obtain half-life estimates of 2.3–3.8 quarters that are much shorter than those reported by previous research. Thus, we conclude that both structural breaks and bias corrections are important to obtain shorter half-life estimates.

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It is of course recognised that technology can be gendered and implicated in gender relations. However, it continues to be the case that men’s experiences with technology are underexplored and the situation is even more problematic where digital media is concerned. Over the past 30 years we have witnessed a dramatic rise in the pervasiveness of digital media across many parts of the world and as associated with wide ranging aspects of our lives. This rise has been fuelled over the last decade by the emergence of Web 2.0 and particularly Social Networking Sites (SNS). Given this context, I believe it is necessary for us to undertake more work to understand men’s engagements with digital media, the implications this might have for masculinities and the analysis of gender relations more generally. To begin to unpack this area, I engage theorizations of the properties of digital media networks and integrate this with the masculinity studies field. Using this framework, I suggest we need to consider the rise in what I call networked masculinities – those masculinities (co)produced and reproduced with digitally networked publics. Through this analysis I discuss themes related to digital mediators, relationships, play and leisure, work and commerce, and ethics. I conclude that as masculinities can be, and are being, complicated and given agency by advancing notions and practices of connectivity, mobility, classification and convergence, those engaged with masculinity studies and digital media have much to contribute.

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In this paper, we propose a novel online hidden Markov model (HMM) parameter estimator based on Kerridge inaccuracy rate (KIR) concepts. Under mild identifiability conditions, we prove that our online KIR-based estimator is strongly consistent. In simulation studies, we illustrate the convergence behaviour of our proposed online KIR-based estimator and provide a counter-example illustrating the local convergence properties of the well known recursive maximum likelihood estimator (arguably the best existing solution).

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The role of the screen producer is ramifying. Not only are there numerous producer categories, but the screen producer function is also found on a continuum across film, television, advertising, corporate video, and the burgeoning digital media sector. In recent years, fundamental changes to distribution and consumption practices and technologies should have had a correlate impact on screen production practices and on the role of existing screen producers. At the same time, new and recent producers are learning and practicing their craft in a field that has already been transformed by digitisation and media convergence. Our analysis of the work, experience and outlook of screen producers in this chapter is based on data collected in the Australian Screen Producer Survey (ASPS), a nation-wide survey conducted by the ARC Centre of Excellence for Creative Industries and Innovation, the media marketing firm Bergent Research, and the Centre for Screen Business at the Australian Film, Television and Radio School (AFTRS) in 2008/09 and 2011. We analyse the results to better understand the practice of screen production in a period of industry transition, and to recognise the persistence of established production cultures that serve to distinguish different industry sectors.

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Stream ciphers are symmetric key cryptosystems that are used commonly to provide confidentiality for a wide range of applications; such as mobile phone, pay TV and Internet data transmissions. This research examines the features and properties of the initialisation processes of existing stream ciphers to identify flaws and weaknesses, then presents recommendations to improve the security of future cipher designs. This research investigates well-known stream ciphers: A5/1, Sfinks and the Common Scrambling Algorithm Stream Cipher (CSA-SC). This research focused on the security of the initialisation process. The recommendations given are based on both the results in the literature and the work in this thesis.

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Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.

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In the companion paper, a fourth-order element formulation in an updated Lagrangian formulation was presented to handle geometric non-linearities. The formulation of the present paper extends this to include material non-linearity by proposing a refined plastic hinge approach to analyse large steel framed structures with many members, for which contemporary algorithms based on the plastic zone approach can be problematic computationally. This concept is an advancement of conventional plastic hinge approaches, as the refined plastic hinge technique allows for gradual yielding, being recognized as distributed plasticity across the element section, a condition of full plasticity, as well as including strain hardening. It is founded on interaction yield surfaces specified analytically in terms of force resultants, and achieves accurate and rapid convergence for large frames for which geometric and material non-linearity are significant. The solutions are shown to be efficacious in terms of a balance of accuracy and computational expediency. In addition to the numerical efficiency, the present versatile approach is able to capture different kinds of material and geometric non-linearities on general applications of steel structures, and thereby it offers an efficacious and accurate means of assessing non-linear behaviour of the structures for engineering practice.

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Finite element frame analysis programs targeted for design office application necessitate algorithms which can deliver reliable numerical convergence in a practical timeframe with comparable degrees of accuracy, and a highly desirable attribute is the use of a single element per member to reduce computational storage, as well as data preparation and the interpretation of the results. To this end, a higher-order finite element method including geometric non-linearity is addressed in the paper for the analysis of elastic frames for which a single element is used to model each member. The geometric non-linearity in the structure is handled using an updated Lagrangian formulation, which takes the effects of the large translations and rotations that occur at the joints into consideration by accumulating their nodal coordinates. Rigid body movements are eliminated from the local member load-displacement relationship for which the total secant stiffness is formulated for evaluating the large member deformations of an element. The influences of the axial force on the member stiffness and the changes in the member chord length are taken into account using a modified bowing function which is formulated in the total secant stiffness relationship, for which the coupling of the axial strain and flexural bowing is included. The accuracy and efficiency of the technique is verified by comparisons with a number of plane and spatial structures, whose structural response has been reported in independent studies.

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This paper emphasizes material nonlinear effects on composite beams with recourse to the plastic hinge method. Numerous combinations of steel and concrete sections form arbitrary composite sections. Secondly, the material properties of composite beams vary remarkably across its section from ductile steel to brittle concrete. Thirdly, concrete is weak in tension, so composite section changes are dependent on load distribution. To this end, the plastic zone approach is convenient for inelastic analysis of composite sections that can evaluate member resistance, including material nonlinearities, by routine numerical integration with respect to every fiber across the composite section. As a result, many researchers usually adopt the plastic zone approach for numerical inelastic analyses of composite structures. On the other hand, the plastic hinge method describes nonlinear material behaviour of an overall composite section integrally. Consequently, proper section properties for use in plastic hinge spring stiffness are required to represent the material behaviour across the arbitrary whole composite section. In view of numerical efficiency and convergence, the plastic hinge method is superior to the plastic zone method. Therefore, based on the plastic hinge approach, how to incorporate the material nonlinearities of the arbitrary composite section into the plastic hinge stiffness formulation becomes a prime objective of the present paper. The partial shear connection in this paper is by virtue of the effective flexural rigidity as AISC 1993 [American Institute of Steel Construction (AISC). Load and resistance factor design specifications. 2nd ed., Chicago; 1993]. Nonlinear behaviour of different kinds of composite beam is investigated in this paper, including two simply supported composite beams, a cantilever and a two span continuous composite beam.

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The use of Mahalanobis squared distance–based novelty detection in statistical damage identification has become increasingly popular in recent years. The merit of the Mahalanobis squared distance–based method is that it is simple and requires low computational effort to enable the use of a higher dimensional damage-sensitive feature, which is generally more sensitive to structural changes. Mahalanobis squared distance–based damage identification is also believed to be one of the most suitable methods for modern sensing systems such as wireless sensors. Although possessing such advantages, this method is rather strict with the input requirement as it assumes the training data to be multivariate normal, which is not always available particularly at an early monitoring stage. As a consequence, it may result in an ill-conditioned training model with erroneous novelty detection and damage identification outcomes. To date, there appears to be no study on how to systematically cope with such practical issues especially in the context of a statistical damage identification problem. To address this need, this article proposes a controlled data generation scheme, which is based upon the Monte Carlo simulation methodology with the addition of several controlling and evaluation tools to assess the condition of output data. By evaluating the convergence of the data condition indices, the proposed scheme is able to determine the optimal setups for the data generation process and subsequently avoid unnecessarily excessive data. The efficacy of this scheme is demonstrated via applications to a benchmark structure data in the field.

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This creative work is the production of the live and animated performance of The Empty City. With a significant period of creative development and script work behind it, the team engaged in a range of innovative performance-making practices in order to realise the work onstage as a non-verbal live and animated theatre work. This intermedial process was often led by music, and involved the creation and convergence of non-verbal action, virtual performers, performing objects and two simultaneous projections of animated images. The production opened at the Brisbane Powerhouse on June 27 2013, with a subsequent tour to Perth’s Awesome Festival in October 2013. Its technical achievements were noted in the critical responses. "The story is told on a striking set of two huge screens, the front one transparent, upon which still and moving images are projected, and between which Oliver performs and occasional “real” objects are placed. The effect is startling, and creates a cartoon three dimensionality like those old Viewmaster slide shows. The live action… and soundscape sync perfectly with the projected imagery to complete a dense, intricately devised and technically brilliant whole." (The West Australian 14.10.13)

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Cloud computing is a currently developing revolution in information technology that is disturbing the way that individuals and corporate entities operate while enabling new distributed services that have not existed before. At the foundation of cloud computing is the broader concept of converged infrastructure and shared services. Security is often said to be a major concern of users considering migration to cloud computing. This article examines some of these security concerns and surveys recent research efforts in cryptography to provide new technical mechanisms suitable for the new scenarios of cloud computing. We consider techniques such as homomorphic encryption, searchable encryption, proofs of storage, and proofs of location. These techniques allow cloud computing users to benefit from cloud server processing capabilities while keeping their data encrypted; and to check independently the integrity and location of their data. Overall we are interested in how users may be able to maintain and verify their own security without having to rely on the trust of the cloud provider.

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Addressing possibilities for authentic combinations of diverse media within an installation setting, this research tested hybrid blends of the physical, digital and temporal to explore liminal space and image. The practice led research reflected on creation of artworks from three perspectives – material, immaterial and hybrid – and in doing so, developed a new methodological structure that extends conventional forms of triangulation. This study explored how physical and digital elements each sought hierarchical presence, yet simultaneously coexisted, thereby extending the visual and conceptual potential of the work. Outcomes demonstrated how utilising and recording transitional processes of hybrid imagery achieved a convergence of diverse, experiential forms. "Hybrid authority" – an authentic convergence of disparate elements – was articulated in the creation and public sharing of processual works and the creation of an innovative framework for hybrid art practice.

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The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.