http://nova.newcastle.edu.au/vital/access/services/Feed ${session.getAttribute("locale")} 5 http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:3105 This paper examines a parameterized problem that we refer to as n - k GRAPH COLORING, i.e., the problem of determining whether a graph G with n vertices can be colored using n - k colors. 2012-03-08T22:50:02.245Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:7816 The aim of this study is to present an efficient method to generate imager-specific Monte Carlo (MC)-based dose kernels for amorphous silicon-based electronic portal image device dose prediction and determine the effective backscattering thicknesses for such imagers. EPID field size-dependent responses were measured for five matched Varian accelerators from three institutions with 6 MV beams at the source to detector distance (SDD) of 105 cm. For two imagers, measurements were made with and without the imager mounted on the robotic supporting arm. Monoenergetic energy deposition kernels with 0–2.5 cm of water backscattering thicknesses were simultaneously computed by MC to a high precision. For each imager, the backscattering thickness required to match measured field size responses was determined. The monoenergetic kernel method was validated by comparing measured and predicted field size responses at 150 cm SDD, 10×10 cm² multileaf collimator (MLC) sliding window fields created with 5, 10, 20, and 50 mm gaps, and a head-and-neck (H&N) intensity modulated radiation therapy (IMRT) patient field. Field size responses for the five different imagers deviated by up to 1.3%. When imagers were removed from the robotic arms, response deviations were reduced to 0.2%. All imager field size responses were captured by using between 1.0 and 1.6 cm backscatter. The predicted field size responses by the imager-specific kernels matched measurements for all involved imagers with the maximal deviation of 0.34%. The maximal deviation between the predicted and measured field size responses at 150 cm SDD is 0.39%. The maximal deviation between the predicted and measured MLC sliding window fields is 0.39%. For the patient field, gamma analysis yielded that 99.0% of the pixels have γ<1 by the 2%, 2 mm criteria with a 3% dose threshold. Tunable imager-specific kernels can be generated rapidly and accurately in a single MC simulation. The resultant kernels are imager position independent and are able to predict fields with varied incident energy spectra and a H&N IMRT patient field. The proposed adaptive EPID dose kernel method provides the necessary infrastructure to build reliable and accurate portal dosimetry systems. 2011-06-02T06:00:19.996Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:6653 The first part of the present chapter provides some theoretical background and explains in the next section the general idea of kernel machines and kernelisation. Then the three fundamental machine learning paradigms dimensionality reduction, regression, and classification as well as associated questions of kernel and parameter selection are addressed. The chapter's second part gives a survey of typical questions and tasks arising in finance applications and how kernel methods have been applied to solve them. Finally follows a brief overview of relevant software toolboxes. 2010-09-10T02:10:03.016Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2818 Dealing with the NP-complete Dominating Set problem on graphs, we demonstrate the power of data reduction by preprocessing from a theoretical as well as a practical side. In particular, we prove that Dominating Set restricted to planar graphs has a so-called problem kernel of linear size, achieved by two simple and easy-to-implement reduction rules. Moreover, having implemented our reduction rules, first experiments indicate the impressive practical potential of these rules. Thus, this work seems to open up a new and prospective way how to cope with one of the most important problems in graph theory and combinatorial optimization. 2010-04-27T07:00:02.534Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2616 Examines operating system support for persistent systems that execute on conventional hardware architectures. The focus of the paper is to examine the inadequacies of traditional operating systems as vehicles for the construction of persistent systems. The authors concentrate on four major areas, namely addressing, stability and resilience, process management and protection. They examine the consequences of making the operating system kernel itself persistent. They conclude by outlining the requirements which must be met by future operating systems designed to support orthogonal persistence. 2010-04-27T07:00:00.123Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2639 The Grasshopper operating system provides a flexible environment for conducting research into orthogonal persistence. In particular, it allows user-level software to perform memory management so that new techniques may be investigated without having to modify or even reboot the kernel. We describe the facilities provided to support this and show how they are used by both the kernel and user-level software. 2010-04-27T06:32:31.348Z ]]> http://nova.newcastle.edu.au/vital/access/manager/Repository/uon:2660 In this paper we describe a new persistent distributed operating system. The Grasshopper system is designed to allow flexibility in the way in which persistence is provided. A key element of this flexibility is concerned with issues of global consistency. The Grasshopper kernels cooperate with user level entities in order to maintain and find globally consistent states using vector time. Further flexibility is provided by allowing the kernels to implement either eager or lazy consistency policies. 2010-04-27T06:04:03.216Z ]]>