• Journal of The Korean Astronomical Society
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• v.46 no.2
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• pp.93-96
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• 2013

Modified Newtonian Dynamics (MOND) is a possible solution for the missing mass problem in galactic dynamics; its predictions are in good agreement with observations in the limit of weak accelerations. However, MOND does not derive from a physical mechanism and does not make predictions on the transitional regime from Newtonian to modified dynamics; rather, empirical transition functions have to be constructed from the boundary conditions and comparisons with observations. I compare the formalism of classical MOND to the scaling law derived from a toy model of gravity based on virtual massive gravitons (the "graviton picture") which I proposed recently. I conclude that MOND naturally derives from the "graviton picture" at least for the case of non-relativistic, highly symmetric dynamical systems. This suggests that-to first order-the "graviton picture" indeed provides a valid candidate for the physical mechanism behind MOND and gravity on galactic scales in general.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.347-363
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• 2007

A novel methodology, referred to as Auxiliary Domain Method (ADM), allowing for a very efficient solution of nonlinear reliability problems is presented. The target nonlinear failure domain is first populated by samples generated with the help of a Markov Chain. Based on these samples an auxiliary failure domain (AFD), corresponding to an auxiliary reliability problem, is introduced. The criteria for selecting the AFD are discussed. The emphasis in this paper is on the selection of the auxiliary linear failure domain in the case where the original nonlinear reliability problem involves multiple objectives rather than a single objective. Each reliability objective is assumed to correspond to a particular response quantity not exceeding a corresponding threshold. Once the AFD has been specified the method proceeds with a modified subset simulation procedure where the first step involves the direct simulation of samples in the AFD, rather than standard Monte Carlo simulation as required in standard subset simulation. While the method is applicable to general nonlinear reliability problems herein the focus is on the calculation of the probability of failure of nonlinear dynamical systems subjected to Gaussian random excitations. The method is demonstrated through such a numerical example involving two reliability objectives and a very large number of random variables. It is found that ADM is very efficient and offers drastic improvements over standard subset simulation, especially when one deals with low probability failure events.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.45.2-45.2
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• 2014

To measure the mass distribution of galaxy systems weak-lensing analysis has been widely used because it directly measures the total mass of a system regardless of its baryon content and dynamical state. However, the weak-lensing only provides a map of projected surface mass density. On the other hand, galaxy redshift surveys provide a map of the three-dimensional galaxy distribution. It thus can resolve the structures along the line of sight projected in the weak-lensing map. Therefore, the comparison of structures identified in the weak-lensing maps and in the redshift surveys is an important test of the issues limiting applications of weak-lensing to the identification of galaxy clusters. Geller et al. (2010) and Kurtz et al. (2012) compared massive clusters identified in a dense redshift survey with significant weak-lensing map convergence peaks. Both assessments of the efficiency of weak-lensing map for cluster identification did not draw a general conclusion, because the sample is so small. Thus, we additionally perform deep imaging observations of fields in a dense galaxy redshift survey that contain galaxy clusters at z~0.2-0.5, using CFHT Megacam.

• Kyungpook Mathematical Journal
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• v.56 no.3
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• pp.1017-1045
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• 2016

Using a combination of calculational and theoretical approaches, we establish results that relate two knot invariants, the Alexander polynomial, and the number of quandle colourings using any finite linear Alexander quandle. Given such a quandle, specified by two coprime integers n and m, the number of colourings of a knot diagram is given by counting the solutions of a matrix equation of the form AX = 0 mod n, where A is the m-dependent colouring matrix. We devised an algorithm to reduce A to echelon form, and applied this to the colouring matrices for all prime knots with up to 10 crossings, finding just three distinct reduced types. For two of these types, both upper triangular, we found general formulae for the number of colourings. This enables us to prove that in some cases the number of such quandle colourings cannot distinguish knots with the same Alexander polynomial, whilst in other cases knots with the same Alexander polynomial can be distinguished by colourings with a specific quandle. When two knots have different Alexander polynomials, and their reduced colouring matrices are upper triangular, we find a specific quandle for which we prove that it distinguishes them by colourings.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.135-140
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• 1998

The concept of dissipativity and passivity are of interest to us from a theoretical as well as a practical point of view. It is well known that the Riccati equation is derived from the dissipation inequality which expresses the fact that the system is dissipative; the energy stored inside the system doesn't exceed the amount of supply which flows into the system. The pencil model is regarded as a representation based on behavioral approach introduced by J.C. Willems. It has first order in the internal variable and zeroth order in the external variable. In general, any matrix pencil is transformed into a canonical form which is consist of several kind of sub-pencils, One of them has row full rank for $^\forall S\;\in\;\mathds{C}\;\bigcup{\infty}$, we call it under-determined mode of the model. In our opinion, most important properties of dynamical system lay in the mode. According to the properties of canonical form for pencil, it is shown that the storage function which characterizes the dissipativity of the system can be written as a LMI for the under-determined mode, if the system doesn't include impulse mode.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.