980 resultados para GAUSSIAN-BASIS SET


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This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.

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Several fringing coral reefs in Moreton Bay, Southeast Queensland, some 300 km south of the Great Barrier Reef (GBR), are set in a relatively high latitude, estuarine environment that is considered marginal for coral growth. Previous work indicated that these marginal reefs, as with many fringing reefs of the inner GBR, ceased accreting in the mid-Holocene. This research presents for the first time data from the subsurface profile of the mid-Holocene fossil reef at Wellington Point comprising U/Th dates of in situ and framework corals, and trace element analysis from the age constrained carbonate fragments. Based on trace element proxies the palaeo-water quality during reef accretion was reconstructed. Results demonstrate that the reef initiated more than 7,000 yr BP during the post glacial transgression, and the initiation progressed to the west as sea level rose. In situ micro-atolls indicate that sea level was at least 1 m above present mean sea level by 6,680 years ago. The reef remained in "catch-up" mode, with a seaward sloping upper surface, until it stopped aggrading abruptly at ca 6,000 yr BP; no lateral progradation occurred. Changes in sediment composition encountered in the cores suggest that after the laterite substrate was covered by the reef, most of the sediment was produced by the carbonate factory with minimal terrigenous influence. Rare earth element, Y and Ba proxies indicate that water quality during reef accretion was similar to oceanic waters, considered suitable for coral growth. A slight decline in water quality on the basis of increased Ba in the later stages of growth may be related to increased riverine input and partial closing up of the bay due to either tidal delta progradation, climatic change and/or slight sea level fall. The age data suggest that termination of reef growth coincided with a slight lowering of sea level, activation of ENSO and consequent increase in seasonality, lowering of temperatures and the constrictions to oceanic flushing. At the cessation of reef accretion the environmental conditions in the western Moreton Bay were changing from open marine to estuarine. The living coral community appears to be similar to the fossil community, but without the branching Acropora spp. that were more common in the fossil reef. In this marginal setting coral growth periods do not always correspond to periods of reef accretion due to insufficient coral abundance. Due to several environmental constraints modern coral growth is insufficient for reef growth. Based on these findings Moreton Bay may be unsuitable as a long term coral refuge for most species currently living in the GBR.

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The prime objective of drying is to enhance shelf life of perishable food materials. As the process is very energy intensive in nature, researchers are trying to minimise energy consumption in the drying process. In order to determine the exact amount of energy needed for drying a food product, understanding the physics of moisture distribution and bond strength of water within the food material is essential. In order understand the critical moisture content, moisture distribution and water bond strength in food material, Thermogravimetric analysis (TGA) can be properly utilised. This work has been conducted to investigate moisture distribution and water bond strength in selected food materials; apple, banana and potato. It was found that moisture distribution and water bond strength influence moisture migration from the food materials. In addition, proportion of different types of water (bound, free, surface water) has been simply identified using TGA. This study provides a better understanding of water contents and its role in drying rate and energy consumption.

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IRE1 couples endoplasmic reticulum unfolded protein load to RNA cleavage events that culminate in the sequence-specific splicing of the Xbp1 mRNA and in the regulated degradation of diverse membrane-bound mRNAs. We report on the identification of a small molecule inhibitor that attains its selectivity by forming an unusually stable Schiff base with lysine 907 in the IRE1 endonuclease domain, explained by solvent inaccessibility of the imine bond in the enzyme-inhibitor complex. The inhibitor (abbreviated 4μ8C) blocks substrate access to the active site of IRE1 and selectively inactivates both Xbp1 splicing and IRE1-mediated mRNA degradation. Surprisingly, inhibition of IRE1 endonuclease activity does not sensitize cells to the consequences of acute endoplasmic reticulum stress, but rather interferes with the expansion of secretory capacity. Thus, the chemical reactivity and sterics of a unique residue in the endonuclease active site of IRE1 can be exploited by selective inhibitors to interfere with protein secretion in pathological settings.

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A crucial task in contractor prequalification is to establish a set of decision criteria through which the capabilities of contractors are measured and judged. However, in the UK, there are no nationwide standards or guidelines governing the selection of decision criteria for contractor prequalification. The decision criteria are usually established by individual clients on an ad hoc basis. This paper investigates the divergence of decision criteria used by different client and consultant organisations in contractor prequalification through a large empirical survey conducted in the UK. The results indicate that there are significant differences in the selection and use of decision criteria for prequalification.

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Two transgenic callus lines of rice, stably expressing a β-glucuronidase (GUS) gene, were supertransformed with a set of constructs designed to silence the resident GUS gene. An inverted-repeat (i/r) GUS construct, designed to produce mRNA with self-complementarity, was much more effective than simple sense and antisense constructs at inducing silencing. Supertransforming rice calluses with a direct-repeat (d/r) construct, although not as effective as those with the i/r construct, was also substantially more effective in silencing the resident GUS gene than the simple sense and antisense constructs. DNA hybridisation analyses revealed that every callus line supertransformed with either simple sense or antisense constructs, and subsequently showing GUS silencing, had the silence-inducing transgenes integrated into the plant genome in inverted-repeat configurations. The silenced lines containing i/r and d/r constructs did not necessarily have inverted-repeat T-DNA insertions. There was significant methylation of the GUS sequences in most of the silenced lines but not in the unsilenced lines. However, demethylation treatment of silenced lines with 5-azacytidine did not reverse the post-transcriptional gene silencing (PTGS) of GUS. Whereas the levels of RNA specific to the resident GUS gene were uniformly low in the silenced lines, RNA specific to the inducer transgenes accumulated to a substantial level, and the majority of the i/r RNA was unpolyadenylated. Altogether, these results suggest that both sense- and antisense-mediated gene suppression share a similar molecular basis, that unpolyadenylated RNA plays an important role in PTGS, and that methylation is not essential for PTGS.

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In Roberts v Prendergast [2013] QCA 89 the respondent had offered to settle the appeal, purporting to make the offer under Chapter 9 Part 5 of the Uniform Civil Procedure Rules 1999 (Qld) (UCPR). Differing views were expressed in the Court of Appeal regarding the impact in the circumstances of the offer to settle, with the majority concluding that the appellant should pay the respondent’s costs on the standard basis.

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An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

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Australia lacks a satisfactory, national paradigm for assessing legal capacity in the context of testamentary, enduring power of attorney and advance care directive documents. Capacity assessments are currently conducted on an ad hoc basis by legal and/or medical professionals. The reliability of the assessment process is subject to the skill set and mutual understanding of the legal and/or medical professional conducting the assessment. There is a growth in the prevalence of diseases such as dementia. Such diseases impact upon cognition which increasingly necessitates collaboration between the legal and medical professions when assessing the effect of mentally disabling conditions upon legal capacity. Miscommunication and lack of understanding between legal and medical professionals involved could impede the development of a satisfactory paradigm. This article will discuss legal capacity assessment in Australia and how to strengthen the relationship between legal and medical professionals involved in capacity assessments. The development of a national paradigm would promote consistency and transparency of process, helping to improve the professional relationship and maximising the principles of autonomy, participation and dignity.

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Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.

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Fire incident in buildings is common, so the fire safety design of the framed structure is imperative, especially for the unprotected or partly protected bare steel frames. However, software for structural fire analysis is not widely available. As a result, the performance-based structural fire design is urged on the basis of using user-friendly and conventional nonlinear computer analysis programs so that engineers do not need to acquire new structural analysis software for structural fire analysis and design. The tool is desired to have the capacity of simulating the different fire scenarios and associated detrimental effects efficiently, which includes second-order P-D and P-d effects and material yielding. Also the nonlinear behaviour of large-scale structure becomes complicated when under fire, and thus its simulation relies on an efficient and effective numerical analysis to cope with intricate nonlinear effects due to fire. To this end, the present fire study utilizes a second order elastic/plastic analysis software NIDA to predict structural behaviour of bare steel framed structures at elevated temperatures. This fire study considers thermal expansion and material degradation due to heating. Degradation of material strength with increasing temperature is included by a set of temperature-stress-strain curves according to BS5950 Part 8 mainly, which implicitly allows for creep deformation. This finite element stiffness formulation of beam-column elements is derived from the fifth-order PEP element which facilitates the computer modeling by one member per element. The Newton-Raphson method is used in the nonlinear solution procedure in order to trace the nonlinear equilibrium path at specified elevated temperatures. Several numerical and experimental verifications of framed structures are presented and compared against solutions in literature. The proposed method permits engineers to adopt the performance-based structural fire analysis and design using typical second-order nonlinear structural analysis software.

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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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Process mining has developed into a popular research discipline and nowadays its associated techniques are widely applied in practice. What is currently ill-understood is how the success of a process mining project can be measured and what the antecedent factors of process mining success are. We consider an improved, grounded understanding of these aspects of value to better manage the effectiveness and efficiency of process mining projects in practice. As such, we advance a model, tailored to the characteristics of process mining projects, which identifies and relates success factors and measures. We draw inspiration from the literature from related fields for the construction of a theoretical, a priori model. That model has been validated and re-specified on the basis of a multiple case study, which involved four industrial process mining projects. The unique contribution of this paper is that it presents the first set of success factors and measures on the basis of an analysis of real process mining projects. The presented model can also serve as a basis for further extension and refinement using insights from additional analyses.

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This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

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A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.