• 한국환경과학회지
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• 제28권1호
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• pp.19-35
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• 2019

This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

• 아태비즈니스연구
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• 제11권1호
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• pp.61-75
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• 2020

Purpose - The purpose of this study was to examine the efficiency of the foreign exchange markets in Korea, Japan and China. Design/methodology/approach - This study collected 1327 observations each of the daily closing exchange rates of the three currencies against the US dollar for the sample period from January 1, 2015 to January 31, 2020, based on the tests for autocorrelation, unit root tests and GARCH-M(1,1) model estimation. Findings - We have found that the autocorrelation test indicates the lack of autocorrelation and unit root test confirms the existence of unit roots in all times series of the three currencies, respectively. The GARCH-M(1,1) test results, however, suggest that the exchange rates do not follow a random walk process. In conclusion, the recent spot foreign exchange markets in Korea, Japan and China are believed to be informationally inefficient. Research implications or Originality - These findings have practical implications for both individual and institutional investors to be able to obtain excess returns on their investments in the foreign exchange markets in three countries by using appropriate risk management, portfolio strategy, technical analysis, etc. This study provides the first empirical examination on the foreign exchange market efficiency in the three biggest economies in Asia including China, which has been excluded from research due to its exchange rate regime.

• 지능정보연구
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• 제25권3호
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• pp.239-251
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• 2019

본 논문은 학습데이터의 크기에 따른 사례기반추론기법이 주가예측력에 어떻게 영향을 미치는지 살펴본다. 삼성전자 주가를 대상을 학습데이터를 2000년부터 2017년까지 이용한 경우와 2015년부터 2017년까지 이용한 경우를 비교하였다. 테스트데이터는 두 경우 모두 2018년 1월 1일부터 2018년 8월 31일까지 이용하였다. 시계 열데이터의 경우 과거데이터가 얼마나 유용한지 살펴보는 측면과 유사사례개수의 중요성을 살펴보는 측면에서 연구를 진행하였다. 실험결과 학습데이터가 많은 경우가 그렇지 않은 경우보다 예측력이 높았다. MAPE을 기준으로 비교할 때, 학습데이터가 적은 경우, 유사사례 개수와 상관없이 k-NN이 랜덤워크모델에 비해 좋은 결과를 보여주지 못했다. 그러나 학습데이터가 많은 경우, 일반적으로 k-NN의 예측력이 랜덤워크모델에 비해 좋은 결과를 보여주었다. k-NN을 비롯한 다른 데이터마이닝 방법론들이 주가 예측력 제고를 위해 학습데이터의 크기를 증가시키는 것 이외에, 거시경제변수를 고려한 기간유사사례를 찾아 적용하는 것을 제안한다.

• 대한기계학회논문집B
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• 제21권3호
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• pp.350-357
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• 1997

The transient incompressible flow behind the axisymmetric bluff body is numerically simulated using the random vortex method(RVM). Based on the vorticity formulation of the unsteady Navier-Stokes equations, the Lagrangian approach with a stochastic simulation of diffusion using random walk technique is employed to account for the transport processes of the vortex elements. The numerical solutions for 2-dimensional recirculating flow behind a backward-facing step in the laminar range of Reynolds number are compared with experimental data. The present simulation focuses on the transitional flow regime where the recirculation zone behind the bluff body becomes highly unsteady and large-scale vortex eddies are shed from the bluff body wake due to intrinsic shear layer instabilities. The unsteady vertical flow structures and the mixing characteristics behind the bluff body are discussed in detail.

• Journal of Information Processing Systems
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• 제7권1호
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• pp.17-28
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• 2011

Despite the fact that the deployment of sensor networks and target tracking could both be managed by taking full advantage of Voronoi diagrams, very little few have been made in this regard. In this paper, we designed an optimized barrier coverage and an energy-efficient clustering algorithm for forming Vonoroi-based Wireless Sensor Networks(WSN) in which we proposed a mobile target tracking scheme (CTT&MAV) that takes full advantage of Voronoi-diagram boundary to improve detectability. Simulations verified that CTT&MAV outperforms random walk, random waypoint, random direction and Gauss-Markov in terms of both the average hop distance that the mobile target moved before being detected and lower sensor death rate. Moreover, we demonstrate that our results are robust as realistic sensing models and also validate our observations through extensive simulations.

• 한국전산구조공학회논문집
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• 제36권2호
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• pp.75-83
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• 2023

이 논문에서는 보행교의 진동 사용성 평가에 있어서 보행자의 이동 질량 관성 효과의 고려 여부, 보행 패턴 등을 고려한 보행 시나리오 등에 따른 해석 결과를 제시하고, 그에 따라 보행교 설계 단계에서 동적 유한요소 해석을 통한 진동 사용성 평가에 있어 적절한 해석 방법과 유의점을 제안한다. 지간 40m의 강합성 박스 단면을 갖는 단경간 단순교 형식의 보행교에 대하여 보행자 밀도, 보행 속도, 임의 보행, 동기화 보행 등을 고려한 보행 시나리오에 대한 가속도 응답을 분석한다. 해석 결과 고정 질량 해석 방법은 임의 보행 시나리오 해석에서 이동 질량 해석과 큰 차이를 보이지 않으며 진동 사용성 평가시에는 더 넓은 진동수 대역을 가진할 수 있는 임의 보행 시나리오를 고려하는 것이 바람직할 수 있음을 보였다.

• 국토계획
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• 제54권3호
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• pp.106-118
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• 2019

In order to develop pedestrian navigation service that provides optimal pedestrian routes based on pedestrian satisfaction levels, it is required to develop a prediction model that can estimate a pedestrian's satisfaction level given a certain condition. Thus, the aim of the present study is to develop a pedestrian satisfaction prediction model based on three machine learning algorithms: Logistic Regression, Random Forest, and Artificial Neural Network models. The 2009, 2012, 2013, 2014, and 2015 Pedestrian Satisfaction Survey Data in Seoul, Korea are used to train and test the machine learning models. As a result, the Random Forest model shows the best prediction performance among the three (Accuracy: 0.798, Recall: 0.906, Precision: 0.842, F1 Score: 0.873, AUC: 0.795). The performance of Artificial Neural Network is the second (Accuracy: 0.773, Recall: 0.917, Precision: 0.811, F1 Score: 0.868, AUC: 0.738) and Logistic Regression model's performance follows the second (Accuracy: 0.764, Recall: 1.000, Precision: 0.764, F1 Score: 0.868, AUC: 0.575). The precision score of the Random Forest model implies that approximately 84.2% of pedestrians may be satisfied if they walk the areas, suggested by the Random Forest model.

• 대한수학회논문집
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• 제25권1호
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• pp.119-128
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• 2010

Let ${X_n,\;n\geq1}$ be a sequence of independent identically distributed (i.i.d.) random variables (r.vs.), defined on a probability space ($\Omega$,A,P), and let ${N_n,\;n\geq1}$ be a sequence of positive integer-valued r.vs., defined on the same probability space ($\Omega$,A,P). Furthermore, we assume that the r.vs. $N_n$, $n\geq1$ are independent of all r.vs. $X_n$, $n\geq1$. In present paper we are interested in asymptotic behaviors of the random sum $S_{N_n}=X_1+X_2+\cdots+X_{N_n}$, $S_0=0$, where the r.vs. $N_n$, $n\geq1$ obey some defined probability laws. Since the appearance of the Robbins's results in 1948 ([8]), the random sums $S_{N_n}$ have been investigated in the theory probability and stochastic processes for quite some time (see [1], [4], [2], [3], [5]). Recently, the random sum approach is used in some applied problems of stochastic processes, stochastic modeling, random walk, queue theory, theory of network or theory of estimation (see [10], [12]). The main aim of this paper is to establish some results related to the asymptotic behaviors of the random sum $S_{N_n}$, in cases when the $N_n$, $n\geq1$ are assumed to follow concrete probability laws as Poisson, Bernoulli, binomial or geometry.

• 한국운동역학회지
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• 제28권1호
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• pp.19-27
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• 2018

Objective: This study aimed to analyze the effects of freezing of gait on spatiotemporal variables, ground reaction forces (GRFs), and joint moments during the sit-to-walk task at the preferred and maximum speeds in patients with Parkinson's disease (PD). Method: The subjects were classified by a neurologist into 12 freezers, 12 non-freezers, and 12 controls. Sit-to-walk parameters were measured during three repetitions of the task in a random order at the preferred and maximum possible speeds. Results: In the sit-to-walk task at the preferred speed, the freezers and non-freezers exhibited a higher peak anterior-posterior GRF (p<0.001) in the sit-to-stand phase and lower step velocity (p<0.001), step length (p<0.001), and peak anterior-posterior GRF (p<0.001) in the first-step phase than the controls. The freezers had higher peak anterior-posterior GRF (p<0.001) and peak moment of the hip joint (p=0.008) in the sit-to-stand phase than the non-freezers. In the sit-to-walk phase at the maximum speed, the freezers and non-freezers had lower peak moment of the hip joint (p=0.008) in the sit-to-stand phase than the controls. The freezers and non-freezers displayed lower step velocity (p<0.001) and peak anterior-posterior GRF (p<0.001) in the first-step phase than the controls. The freezers showed higher peak moments of the hip joint in the sit-to-stand phase than the non-freezers (p=0.008). Conclusion: The PD patients had reduced control ability in sit-to-stand motions for efficient performance of the sit-to-walk task and reduced performance in the sit-to-walk task. Furthermore, the freezers displayed reduced control ability in the sit-to-stand task. Finally, the PD patients exhibited a lower ability to control dynamic stability with changes in speed than the controls.

• 정보처리학회논문지A
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• 제9A권3호
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• pp.387-398
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• 2002

최근 활발한 소단위 게놈 프로젝트의 수행으로 많은 생물체의 유전체 전체 서열이 밝혀짐에 따라서 전유전체(whole genome)를 기본 단위로 하여 개별 유전자나 그에 관련된 기능 연구가 매우 활발히 이루어지고 있다. 전유전체의 염기 서열은 수백만 bp(base pairs)에서 수백억 bp(base pairs) 정도의 대용량 텍스트 데이터이기 때문에 단순한 온라인 문자 일치(on-line string matching) 알고리즘으로 분석하는 것은 매우 비효율적이다. 본 논문에서는 대용량의 유전체 서열을 분석하는데 적합한 자료 구조인 스트링 B-트리를 사용하여 유전체 서열의 분석과 가시화를 위한 워크벤치를 개발한 과정을 소개한다. 본 연구에서 개발한 시스템은 크게 질의문 부분과 가시화 부분으로 나뉘어 진다. 질의문 부분에는 유전체 서열에 특정 서열이 나타나는 부분의 위치와 횟수를 알아보거나 k번 나타나는 서열을 조사하는 것과 같은 기본적인 패턴 검색 부분과 k-mer 분석을 위한 질의어가 다양하게 준비되어 있다. 가시화 부분은 전유전체 서열과 주석(annotation)을 보여주거나, 유전체 분석을 용이하도록 여러 가시화 방법, CGR(Chaos Game Representation), k-mer graph, RWP(Random Walk Plot) 등으로 생물학자들이 쉽게 전체 구조와 특성 파악할 수 있도록 도와준다. 본 논문이 제안하는 분석 시스템은 생물체의 진화적 관계를 밝히고, 염색체 내에 아직 알려지지 않은 새로운 유전자나 기능이 밝혀지지 않은 junk DNA들의 기능 등을 연구하는데 사용할 수 있다.