972 resultados para Forensics computer science


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Global warming can have a significant impact on the building thermal environment and energy performance. Because greenhouse gas concentrations are still continuing to increase, this warming process will continue and may accelerate. Adaptation to global warming is therefore emerging as one of the key requirements for buildings. This requires all the existing and new buildings not only to perform and operate satisfactorily in the new environment but also to satisfy the environmental performance criteria of sustainability. Through a parametric study using the building simulation technique, this paper investigates the adaptation potential of changing the building internal load densities to the future global warming. Case studies for office buildings in major Australian capital cities are presented. Based on the results of parametric study, possible adaptation strategies are also proposed and evaluated.

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Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.

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The aggregate structure which occurs in aqueous smectitic suspensions is responsible for poor water clarification, difficulties in sludge dewatering and the unusual rheological behaviour of smectite rich soils. These macroscopic properties are dictated by the 3-D structural arrangement of smectite finest fraction within flocculated aggregates. Here, we report results from a relatively new technique, Transmission X-ray Microscopy (TXM), which makes it possible to investigate the internal structure and 3-D tomographic reconstruction of the smectite clay aggregates modified by Al13 keggin macro-molecule [Al13(O)4(OH)24(H2O)12 ]7+. Three different treatment methods were shown resulted in three different micro-structural environments of the resulting flocculation.

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Network induced delay in networked control systems (NCS) is inherently non-uniformly distributed and behaves with multifractal nature. However, such network characteristics have not been well considered in NCS analysis and synthesis. Making use of the information of the statistical distribution of NCS network induced delay, a delay distribution based stochastic model is adopted to link Quality-of-Control and network Quality-of-Service for NCS with uncertainties. From this model together with a tighter bounding technology for cross terms, H∞ NCS analysis is carried out with significantly improved stability results. Furthermore, a memoryless H∞ controller is designed to stabilize the NCS and to achieve the prescribed disturbance attenuation level. Numerical examples are given to demonstrate the effectiveness of the proposed method.

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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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UCON is an emerging access control framework that lacks an administration model. In this paper we define the problem of administration and propose a novel administrative model. At the core of this model is the concept of attribute, which is also the central component of UCON. In our model, attributes are created by the assertions of subjects, which ascribe properties/rights to other subjects or objects. Through such a treatment of attributes, administration capabilities can be delegated from one subject to another and as a consequence UCON is improved in three aspects. First, immutable attributes that are currently considered as external to the model can be incorporated and thereby treated as mutable at- tributes. Second, the current arbitrary categorisation of users (as modifiers of attributes), to system and administrator can be removed. Attributes and objects are only modifiable by those who possess administration capability over them. Third, the delegation of administration over objects and properties that is not currently expressible in UCON is made possible.

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This article presents a survey of authorisation models and considers their ‘fitness-for-purpose’ in facilitating information sharing. Network-supported information sharing is an important technical capability that underpins collaboration in support of dynamic and unpredictable activities such as emergency response, national security, infrastructure protection, supply chain integration and emerging business models based on the concept of a ‘virtual organisation’. The article argues that present authorisation models are inflexible and poorly scalable in such dynamic environments due to their assumption that the future needs of the system can be predicted, which in turn justifies the use of persistent authorisation policies. The article outlines the motivation and requirement for a new flexible authorisation model that addresses the needs of information sharing. It proposes that a flexible and scalable authorisation model must allow an explicit specification of the objectives of the system and access decisions must be made based on a late trade-off analysis between these explicit objectives. A research agenda for the proposed Objective-based Access Control concept is presented.

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The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.

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With the emergence of multi-cores into the mainstream, there is a growing need for systems to allow programmers and automated systems to reason about data dependencies and inherent parallelismin imperative object-oriented languages. In this paper we exploit the structure of object-oriented programs to abstract computational side-effects. We capture and validate these effects using a static type system. We use these as the basis of sufficient conditions for several different data and task parallelism patterns. We compliment our static type system with a lightweight runtime system to allow for parallelization in the presence of complex data flows. We have a functioning compiler and worked examples to demonstrate the practicality of our solution.