210 research outputs found
Spectral Analysis of Multi-dimensional Self-similar Markov Processes
In this paper we consider a discrete scale invariant (DSI) process with scale . We consider to have some fix number of
observations in every scale, say , and to get our samples at discrete points
where is obtained by the equality
and . So we provide a discrete time scale
invariant (DT-SI) process with parameter space . We find the spectral representation of the covariance function of
such DT-SI process. By providing harmonic like representation of
multi-dimensional self-similar processes, spectral density function of them are
presented. We assume that the process is also Markov
in the wide sense and provide a discrete time scale invariant Markov (DT-SIM)
process with the above scheme of sampling. We present an example of DT-SIM
process, simple Brownian motion, by the above sampling scheme and verify our
results. Finally we find the spectral density matrix of such DT-SIM process and
show that its associated -dimensional self-similar Markov process is fully
specified by where is
the covariance function of th and th observations of the process.Comment: 16 page
Bridging Proper Orthogonal Decomposition methods and augmented Newton-Krylov algorithms: an adaptive model order reduction for highly nonlinear mechanical problems
This article describes a bridge between POD-based model order reduction
techniques and the classical Newton/Krylov solvers. This bridge is used to
derive an efficient algorithm to correct, "on-the-fly", the reduced order
modelling of highly nonlinear problems undergoing strong topological changes.
Damage initiation problems are addressed and tackle via a corrected
hyperreduction method. It is shown that the relevancy of reduced order model
can be significantly improved with reasonable additional costs when using this
algorithm, even when strong topological changes are involved
Karhunen-Loeve representation of stochastic ocean waves
A new stochastic representation of a seastate is developed based on the Karhunen–Loeve spectral decomposition of stochastic signals and the use of Slepian prolate spheroidal wave functions with a tunable bandwidth parameter. The new representation allows the description of stochastic ocean waves in terms of a few independent sources of uncertainty when the traditional representation of a seastate in terms of Fourier series requires an order of magnitude more independent components. The new representation leads to parsimonious stochastic models of the ambient wave kinematics and of the nonlinear loads and responses of ships and offshore platforms. The use of the new representation is discussed for the derivation of critical wave episodes, the derivation of up-crossing rates of nonlinear loads and responses and the joint stochastic representation of correlated wave and wind profiles for use in the design of fixed or floating offshore wind turbines. The forecasting is also discussed of wave elevation records and vessel responses for use in energy yield enhancement of compliant floating wind turbines.ALSTOM (Firm)Ente nazionale per l'energia elettricab_TE
The scaling attractor and ultimate dynamics for Smoluchowski's coagulation equations
We describe a basic framework for studying dynamic scaling that has roots in
dynamical systems and probability theory. Within this framework, we study
Smoluchowski's coagulation equation for the three simplest rate kernels
, and . In another work, we classified all self-similar
solutions and all universality classes (domains of attraction) for scaling
limits under weak convergence (Comm. Pure Appl. Math 57 (2004)1197-1232). Here
we add to this a complete description of the set of all limit points of
solutions modulo scaling (the scaling attractor) and the dynamics on this limit
set (the ultimate dynamics). The main tool is Bertoin's L\'{e}vy-Khintchine
representation formula for eternal solutions of Smoluchowski's equation (Adv.
Appl. Prob. 12 (2002) 547--64). This representation linearizes the dynamics on
the scaling attractor, revealing these dynamics to be conjugate to a continuous
dilation, and chaotic in a classical sense. Furthermore, our study of scaling
limits explains how Smoluchowski dynamics ``compactifies'' in a natural way
that accounts for clusters of zero and infinite size (dust and gel)
PCA-based lung motion model
Organ motion induced by respiration may cause clinically significant
targeting errors and greatly degrade the effectiveness of conformal
radiotherapy. It is therefore crucial to be able to model respiratory motion
accurately. A recently proposed lung motion model based on principal component
analysis (PCA) has been shown to be promising on a few patients. However, there
is still a need to understand the underlying reason why it works. In this
paper, we present a much deeper and detailed analysis of the PCA-based lung
motion model. We provide the theoretical justification of the effectiveness of
PCA in modeling lung motion. We also prove that under certain conditions, the
PCA motion model is equivalent to 5D motion model, which is based on physiology
and anatomy of the lung. The modeling power of PCA model was tested on clinical
data and the average 3D error was found to be below 1 mm.Comment: 4 pages, 1 figure. submitted to International Conference on the use
of Computers in Radiation Therapy 201
Выявление понятий и их взаимосвязей в рамках технологии контент-мониторинга
Приведены подходы к решению проблемы выявления фактографической информации из неструктурированных текстовых потоков. Описаны технологические решения, позволяющие извлекать из полнотекстовых документов такие понятия как фирмы, фамилии, географические названия и т.п., а также выявлять силу их взаимосвязей на основе применения двух алгоритмов. Первый из этих алгоритмов основывается на учете совместного вхождения понятий в одни и те же документы, а второй на учете общего для рассматриваемых понятий контекста.Наведено підходи до вирішення проблеми виявлення фактографічної інформації з неструктурованих текстових потоків. Описано технологічні рішення, що дозволяють добути з повнотекстових документів такі поняття як фірми, прізвища, географічні назви тощо, а також виявляти силу їхніх взаємозв’язків на базі застосування двох алгоритмів. Перший з цих алгоритмів базується на врахуванні спільного входження понять до одних і тих самих документів, а другий — на врахуванні загального для понять, що розглядаються, контексту.Approaches to the solution of a problem of revealing factual information from unstructured text flows are given. The technological solutions, allowing to take from text-through documents such concepts as a firm, a surname, place names, etc., and also to reveal force of their interrelations on the basis of application of two algorithms are described. The first of these algorithms is based on the account of joint concepts occurrence in the same documents, and the second one on the account of the context common for considered concepts
Cost-effectiveness analysis of 3-D computerized tomography colonography versus optical colonoscopy for imaging symptomatic gastroenterology patients.
BACKGROUND: When symptomatic gastroenterology patients have an indication for colonic imaging, clinicians have a choice between optical colonoscopy (OC) and computerized tomography colonography with three-dimensional reconstruction (3-D CTC). 3-D CTC provides a minimally invasive and rapid evaluation of the entire colon, and it can be an efficient modality for diagnosing symptoms. It allows for a more targeted use of OC, which is associated with a higher risk of major adverse events and higher procedural costs. A case can be made for 3-D CTC as a primary test for colonic imaging followed if necessary by targeted therapeutic OC; however, the relative long-term costs and benefits of introducing 3-D CTC as a first-line investigation are unknown. AIM: The aim of this study was to assess the cost effectiveness of 3-D CTC versus OC for colonic imaging of symptomatic gastroenterology patients in the UK NHS. METHODS: We used a Markov model to follow a cohort of 100,000 symptomatic gastroenterology patients, aged 50 years or older, and estimate the expected lifetime outcomes, life years (LYs) and quality-adjusted life years (QALYs), and costs (£, 2010-2011) associated with 3-D CTC and OC. Sensitivity analyses were performed to assess the robustness of the base-case cost-effectiveness results to variation in input parameters and methodological assumptions. RESULTS: 3D-CTC provided a similar number of LYs (7.737 vs 7.739) and QALYs (7.013 vs 7.018) per individual compared with OC, and it was associated with substantially lower mean costs per patient (£467 vs £583), leading to a positive incremental net benefit. After accounting for the overall uncertainty, the probability of 3-D CTC being cost effective was around 60 %, at typical willingness-to-pay values of £20,000-£30,000 per QALY gained. CONCLUSION: 3-D CTC is a cost-saving and cost-effective option for colonic imaging of symptomatic gastroenterology patients compared with OC
Precision measurements of the top quark mass from the Tevatron in the pre-LHC era
The top quark is the heaviest of the six quarks of the Standard Model.
Precise knowledge of its mass is important for imposing constraints on a number
of physics processes, including interactions of the as yet unobserved Higgs
boson. The Higgs boson is the only missing particle of the Standard Model,
central to the electroweak symmetry breaking mechanism and generation of
particle masses. In this Review, experimental measurements of the top quark
mass accomplished at the Tevatron, a proton-antiproton collider located at the
Fermi National Accelerator Laboratory, are described. Topologies of top quark
events and methods used to separate signal events from background sources are
discussed. Data analysis techniques used to extract information about the top
mass value are reviewed. The combination of several most precise measurements
performed with the two Tevatron particle detectors, CDF and \D0, yields a value
of \Mt = 173.2 \pm 0.9 GeV/.Comment: This version contains the most up-to-date top quark mass averag
Number and Size Distribution of Colorectal Adenomas under the Multistage Clonal Expansion Model of Cancer
Colorectal cancer (CRC) is believed to arise from mutant stem cells in colonic crypts that undergo a well-characterized progression involving benign adenoma, the precursor to invasive carcinoma. Although a number of (epi)genetic events have been identified as drivers of this process, little is known about the dynamics involved in the stage-wise progression from the first appearance of an adenoma to its ultimate conversion to malignant cancer. By the time adenomas become endoscopically detectable (i.e., are in the range of 1–2 mm in diameter), adenomas are already comprised of hundreds of thousands of cells and may have been in existence for several years if not decades. Thus, a large fraction of adenomas may actually remain undetected during endoscopic screening and, at least in principle, could give rise to cancer before they are detected. It is therefore of importance to establish what fraction of adenomas is detectable, both as a function of when the colon is screened for neoplasia and as a function of the achievable detection limit. To this end, we have derived mathematical expressions for the detectable adenoma number and size distributions based on a recently developed stochastic model of CRC. Our results and illustrations using these expressions suggest (1) that screening efficacy is critically dependent on the detection threshold and implicit knowledge of the relevant stem cell fraction in adenomas, (2) that a large fraction of non-extinct adenomas remains likely undetected assuming plausible detection thresholds and cell division rates, and (3), under a realistic description of adenoma initiation, growth and progression to CRC, the empirical prevalence of adenomas is likely inflated with lesions that are not on the pathway to cancer
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