Gas materials in the inner Galactic disk continuously migrate toward the Galactic center (GC) due to interactions with the bar potential, magnetic fields, stars, and other gaseous materials. Those in forms of molecule...
Gas materials in the inner Galactic disk continuously migrate toward the Galactic center (GC) due to interactions with the bar potential, magnetic fields, stars, and other gaseous materials. Those in forms of molecules appear to accumulate around 200 pc from the center (the central molecular zone, CMZ) to form stars there and further inside. The bar potential in the GC is thought to be responsible for such accumulation of molecules and subsequent star formation, which is believed to have been continuous throughout the lifetime of the Galaxy. We present 3-D hydrodynamic simulations of the CMZ that consider self-gravity, radiative cooling, and supernova feedback, and discuss the efficiency and role of the star formation in that region. We find that the gas accumulated in the CMZ by a bar potential of the inner bulge effectively turns into stars, supporting the idea that the stellar cusp inside the central 200 pc is a result of the sustained star formation in the CMZ. The obtained star formation rate in the CMZ, 0.03–0.1 M⊙, is consistent with the recent estimate based on the mid-infrared observations by Yusef-Zadeh et al. (2009).
A method for using monotonicity information in multivariate Gaussian process regression and classification is proposed. Monotonicity information is introduced with virtual derivative observations, and the resulting po...
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A method for using monotonicity information in multivariate Gaussian process regression and classification is proposed. Monotonicity information is introduced with virtual derivative observations, and the resulting posterior is approximated with expectation propagation. Behaviour of the method is illustrated with artificial regression examples, and the method is used in a real world health care classification problem to include monotonicity information with respect to one of the covariates. Copyright 2010 by the authors.
Recently, many evolutionary computation methods such as GA for multiobjective optimization problems have been reported, and then many objective optimization problems, which have a lot of objective functions, have been...
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Temporal information extraction is a popular and interesting research field in the area of Natural Language Processing (NLP). The main tasks involve the identification of event-time, event-document creation time and e...
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In order to be able to form high strength steels with low ductility, multi‐step forming processes are becoming more common. Benchmark 4 of the NUMISHEET 2011 conference is an attempt to imitate such a process. A DP78...
In order to be able to form high strength steels with low ductility, multi‐step forming processes are becoming more common. Benchmark 4 of the NUMISHEET 2011 conference is an attempt to imitate such a process. A DP780 steel sheet with 1.4 mm thickness is considered. In order to understand the pre‐strain effect on subsequent forming and springback, a 2D draw‐bending is considered. Two cases are studied: one without pre‐strain and one with 8% pre‐stretching. The draw‐bending model is identical to the “U‐bend” problem of the NUMISHEET’93 conference. The purpose of the benchmark problem is to evaluate the capability of modern FE‐methods to simulate the forming and springback of these kinds of *** authors of this article have previously made exhaustive studies on material modeling in applications to sheet metal forming and springback problems, [1],[2],[3]. Models for kinematic hardening, anisotropic yield conditions, and elastic stiffness reduction have been investigated. Also procedures for material characterization have been studied. The material model that mainly has been used in the current study is based on the Banabic BBC2005 yield criterion, and a modified version of the Yoshida‐Uemori model for cyclic hardening. This model, like a number of other models, has been implemented as User Subroutines in LS‐DYNA. The effects of various aspects of material modeling will be demonstrated in connection to the current benchmark problems. The provided material data for the current benchmark problem are not complete in all respects. In order to be able to perform the current simulations, the authors have been forced to introduce a few additional assumptions. The effects of these assumptions will also be discussed.
Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one - three dimensions. Visualization by reduc...
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Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one - three dimensions. Visualization by reducing the dimensionality of Kansei data to less than or equal to three dimensions could help the analyzer to understand the data.
A lot of structural and microstructural brain image analysis methods exist in the literature. This review presents the different methods with special emphasis on their strengths and limitations. It aims to be a compac...
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Brain structures are subjected to changes caused by genetic, environmental factors or disease and gender, age related reasons. Different methods have been developed to capture these changes, but their agreement over t...
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In this paper, we present an innovative chart mining technique for improving parse coverage based on partial parse outputs from precision grammars. The general approach of mining features from partial analyses is appl...
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We explore the possibility of using Stochastic Bracketing Linear Inversion Transduction Grammars for a full-scale German–English translation task, both on their own and in conjunction with alignments induced with GIZ...
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