Adaptive Evolutionary Clustering

In many practical applications of clustering, the objects to be clustered evolve over time, and a clustering result is desired at each time step. In such applications, evolutionary clustering typically outperforms traditional static clustering by producing clustering results that reflect long-term trends while being robust to short-term variations. Several evolutionary clustering algorithms have recently been proposed, often by adding a temporal smoothness penalty to the cost function of a static clustering method. In this paper, we introduce a different approach to evolutionary clustering by accurately tracking the time-varying proximities between objects followed by static clustering. We present an evolutionary clustering framework that adaptively estimates the optimal smoothing parameter using shrinkage estimation, a statistical approach that improves a naive estimate using additional information. The proposed framework can be used to extend a variety of static clustering algorithms, including hierarchical, k-means, and spectral clustering, into evolutionary clustering algorithms. Experiments on synthetic and real data sets indicate that the proposed framework outperforms static clustering and existing evolutionary clustering algorithms in many scenarios.Comment: To appear in Data Mining and Knowledge Discovery, MATLAB toolbox available at http://tbayes.eecs.umich.edu/xukevin/affec

Прискорене моделювання стаціонарного розподілу кількості вимог у системі SMBAP|G| ∞

Розглядається система масового обслуговування з нескінченною кількістю обслуговуючих пристроїв. В систему надходить груповий потік вимог, який керується напівмарковським процесом. Запропоновано метод прискореного моделювання стаціонарної ймовірності кількості вимог у системі, що ґрунтується на методі істотної вибірки та використовує центральну граничну теорему. Оцінки є асимптотично незміщеними. Виграш в дисперсії порівняно з методом Монте-Карло становить в середньому два порядки.Рассматривается система массового обслуживания с бесконечным количеством обслуживающих устройств. В систему поступает групповой поток требований, управляемый полумарковским процессом. Предложен метод ускоренного моделирования стационарной вероятности количества требований в системе, основанный на методе существенной выборки и использующий центральную предельную теорему. Оценки — асимптотически несмещенные. Выигрыш в дисперсии по сравнению с методом Монте-Карло составляет в среднем два порядка.A queueing system with the infinite number of servers and batch arrival process controlled by the semi-Markov process is investigated. A fast simulation method for the evaluation of the steady-state distribution of the number of customers in the system is proposed, which is based on essential sampling and the central limit theorem. The estimates are asymptotically unbiased. The gain in variance compared to the Monte Carlo method is on the average two orders of magnitude

QUALICOPC, a multi-country study evaluating quality, costs and equity in primary care

Contains fulltext : 96249.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: The QUALICOPC (Quality and Costs of Primary Care in Europe) study aims to evaluate the performance of primary care systems in Europe in terms of quality, equity and costs. The study will provide an answer to the question what strong primary care systems entail and which effects primary care systems have on the performance of health care systems. QUALICOPC is funded by the European Commission under the "Seventh Framework Programme". In this article the background and design of the QUALICOPC study is described. METHODS/DESIGN: QUALICOPC started in 2010 and will run until 2013. Data will be collected in 31 European countries (27 EU countries, Iceland, Norway, Switzerland and Turkey) and in Australia, Israel and New Zealand. This study uses a three level approach of data collection: the system, practice and patient. Surveys will be held among general practitioners (GPs) and their patients, providing evidence at the process and outcome level of primary care. These surveys aim to gain insight in the professional behaviour of GPs and the expectations and actions of their patients. An important aspect of this study is that each patient's questionnaire can be linked to their own GP's questionnaire. To gather data at the structure or national level, the study will use existing data sources such as the System of Health Accounts and the Primary Health Care Activity Monitor Europe (PHAMEU) database. Analyses of the data will be performed using multilevel models. DISCUSSION: By its design, in which different data sources are combined for comprehensive analyses, QUALICOPC will advance the state of the art in primary care research and contribute to the discussion on the merit of strengthening primary care systems and to evidence based health policy development

Delimitation of Funga as a valid term for the diversity of fungal communities: the Fauna, Flora & Funga proposal (FF&F)

As public policies and conservation requirements for biodiversity evolve there is a need for a term for the kingdom Fungi equivalent to Fauna and Flora. Thisneed is considered to be urgent in order to simplify projects oriented toward implemention of educational and conservation goals. In an informal meeting held duringthe IX Congreso Latinoamericano de Micología by the authors, the idea of clarifying this matter initiated an extensive search of pertinent terminologies. As a result ofthese discussions and reviews, we propose that the word Funga be employed as an accurate and encompassing term for these purposes. This supports the proposal of thethree Fs, Fauna, Flora and Funga, to highlight parallel terminology referring to treatments of these macrorganism of particular geographical areas. Alternative terms andproposals are acknowledged and discussedFil: Kuhar, José Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Furci, Giuliana. Fundación Fungi; ChileFil: Drechsler-Santos, Elisandro Ricardo. Universidade Federal de Santa Catarina; BrasilFil: Pfister, Donald H.. Harvard University; Estados Unido

Inferring cellular networks – a review

In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations

Exploring new physics frontiers through numerical relativity

The demand to obtain answers to highly complex problems within strong-field gravity has been met with significant progress in the numerical solution of Einstein's equations - along with some spectacular results - in various setups. We review techniques for solving Einstein's equations in generic spacetimes, focusing on fully nonlinear evolutions but also on how to benchmark those results with perturbative approaches. The results address problems in high-energy physics, holography, mathematical physics, fundamental physics, astrophysics and cosmology