• 대한수학회지
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• 제59권6호
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• pp.1171-1184
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• 2022

We study the real-analytic continuation of local real-analytic solutions to the Cauchy problems of quasi-linear partial differential equations of first order for a scalar function. By making use of the first integrals of the characteristic vector field and the implicit function theorem we determine the maximal domain of the analytic extension of a local solution as a single-valued function. We present some examples including the scalar conservation laws that admit global first integrals so that our method is applicable.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.790-797
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• 2007

This paper proposes a new measure of cost function ruggedness in local optimization with DEAS. DEAS is a computational optimization method developed since 2002 and has been applied to various engineering fields with success. Since DEAS is a recent optimization method which is rarely introduced in Korean, this paper first provides a brief overview and description of DEAS. In minimizing cost function with this non-gradient method, information on function shape measured automatically will enhance search capability. Considering the search strategies of DEAS are well designed with binary matrix structures, analysis of search behaviors will produce beneficial shape information. This paper deals with a simple quadratic function contained with various magnitudes of noise, and DEAS finds local minimum yielding ruggedness measure of given cost function. The proposed shape information will be directly used in improving DEAS performance in future work.

• 대한예방한의학회지
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• 제17권2호
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• pp.69-78
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• 2013

Objectives : Health cooperative movement is of increasing concern among medical consumers and professionals in Korea. Most health cooperative clinics provide Western Medicine and Korean Medicine(KM) to patients. This study aimed to evaluate the primary care level of health cooperative KM clinics and compare it with local KM clinics in Korea. Methods : Face to face survey was performed at the 3 health cooperative KM clinics and 5 local KM clinics with the Korean Primary Care Assessment Tool (KPCAT). The KPCAT consists of 5 domains (21 items): first contact (5), coordination function (3), comprehensiveness (4), family/community orientation (4), and personalized care (5). Subjects were patients or guardians who had visited KM clinics five times or more during the last 3 months. We compared primary care scores of each domain between health cooperative KM clinics and local KM clinics. Results : Data were collected from 200 respondents (100 patients from health cooperative KM clinics and 100 local KM clinics). Total average scores of the KPCAT for health cooperative clinics and local KM clinics were $81.1{\pm}12.0$ and $75.4{\pm}9.5$, respectively. Among primary care domains, personalized care was the highest ($89.2{\pm}12.0$, $89.6{\pm}8.4$, respectively), and comprehensiveness function was the lowest ($68.5{\pm}22.5$, $54.5{\pm}22.0$, respectively). Significant differences between two groups were noted in comprehensiveness function (68.5 vs. 54.5, P=0.000), family-community orientation (79.5 vs. 73.0, P=0.004), first contact(89.2 vs 84.0, p=0.001) and coordination function(74.0 vs 68.7, p=0.025). Conclusions : Based on the patients assessment, health cooperative KM clinics provide more primary care-oriented services than local KM clinics. This means that health cooperative clinic can be one of alternatives to strengthen the primary health care in Korea. Future researches are recommended to measure patients satisfaction and treatment effectiveness in the health cooperative clinics.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제24권2호
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• pp.199-214
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• 2020

This paper describes the development of a parallel computational algorithm based on the finite element tearing and interconnecting (FETI) method that uses a local Lagrange multiplier. In this approach, structural computational domain is decomposed into non-overlapping sub-domains using local Lagrange multiplier. The local Lagrange multipliers are imposed at interconnecting nodes. 8-node solid element using extra shape function is adopted by using the representative volume element (RVE). The parallel computational algorithm is further established based on message passing interface (MPI). Finally, the present FETI-local approach is implemented on parallel hardware and shows improved performance.

• 천문학회지
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• 제38권2호
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• pp.161-164
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• 2005

We present a theoretical formalism by which the global and the local mass functions of dark matter substructures (dark subhalos) can be analytically estimated. The global subhalo mass function is defined to give the total number density of dark subhalos in the universe as a function of mass, while the local subhalo mass function counts only those sub halos included in one individual host halo. We develop our formalism by modifying the Press-Schechter theory to incorporate the followings: (i) the internal structure of dark halos; (ii) the correlations between the halos and the subhalos; (iii) the subhalo mass-loss effect driven by the tidal forces. We find that the resulting (cumulative) subhalo mass function is close to a power law with the slope of ${\~}$ -1, that the subhalos contribute approximately $10\%$ of the total mass, and that the tidal stripping effect changes the subhalo mass function self-similarly, all consistent with recent numerical detections.

• Communications for Statistical Applications and Methods
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• 제20권6호
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• pp.481-490
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• 2013

Classification is an important research area as data can be easily obtained even if the number of predictors becomes huge. The support vector machine(SVM) is widely used to classify a subject into a predetermined group because it gives sound theoretical background and better performance than other methods in many applications. The SVM can be viewed as a penalized method with the hinge loss function and penalty functions. Instead of $L_2$ penalty function Fan and Li (2001) proposed the smoothly clipped absolute deviation(SCAD) satisfying good statistical properties. Despite the ability of SVMs, they have drawbacks of non-robustness when there are outliers in the data. We develop a robust SVM method using a weight function with the SCAD penalty function based on the local quadratic approximation. We compare the performance of the proposed SVM with the SVM using the $L_1$ and $L_2$ penalty functions.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 춘계학술대회 논문집
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• pp.141-146
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• 1999

A new method, so called MMA(Method of Moving Asymptotes) was applied to the optimization problems of non-linear functions and non-linear structures. In each step of the iterative process, tile MMA generates a strictly convex approximation subproblems and solves them by using the dual problems. The generation of these subproblems is controlled by so called 'moving asymptotes', which may both make no oscillation and speed up tile convergence rate of optimization process. By contrast in generalized dual function, the generated function by MMA is always explicit type. Both the objective and behaviour constraints which were approximated are optimized by dual function. As the results of some examples, it was found that this method is very effective to obtain the global solution for problems with many local solutions. Also it was found that MMA is a very effective approximate method using the original function and its 1st derivatives.

• Journal of the Korean Data and Information Science Society
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• 제20권1호
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• pp.1-9
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• 2009

회귀모형의 분산함수가 알려져 있지 않은 한 점에서 불연속이라 가정하자. Yu와 Jones (2004)는 음이 아닌 값을 취하는 분산함수를 실수 값을 취하도록 하기 위하여 로그 변환하였고, 변환된 로그분산함수를 국소다항적합으로 추정하였다. 로그분산함수의 국소다항적합을 이용하여, Huh (2008)는 분산함수의 불연속점의 추정하는 대신 로그분산함수의 불연속점을 추정하였다. 본 연구는 Huh의 점프의 크기 추정량의 점근분포를 이용하여 로그분산함수의 불연속점의 존재여부에 대한 가설검정을 제안하고, 제안한 방법에 대한 모의실험 결과를 제시하고자 한다.

• 대한정형도수물리치료학회지
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• 제28권3호
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• pp.89-99
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• 2022

Background: The purpose of this study was to investigate the effects of physical therapy intervention with local vibration on the physical function of patients with traumatic patella fractures. Methods: This study recruited 6 subjects who had suffered traumatic patella fractures. The study was conducted for an average of 12.8 weeks. Before the treatment (2 weeks post-surgery), they were evaluated using the numeric pain rating scale (NPRS), the Korean-version of the impact of event scale-revised (IES-R-K), pressure pain threshold (PPT), range of motion (ROM) of the knee joint, and the Korean knee injury and osteoarthritis outcome score (K-KOOS) and were reevaluated after 7 and 12 weeks, post-surgery. This study was conducted according to ORIF Patella Fracture Post-Operative Rehabilitation Protocol after applying local vibration. The protocol consists of Phases 1~5 and this study has been applied from phase 2. Results: A comparison of the performance of the participants before and after the intervention showed a decrease in NPRS (9.83±.41→4.83±.98), IES-R-K (68.67±2.73→23.83±2.40), and K-KOOS (Function, Daily living: 70.5±5.96→34.0±3.35, Function, Sports and Recreational activities: 22.83±2.32→10.77±1.37, Quality of Life: 19.33±7.33→7.33±.52) scores. And the ROM (Knee flexion: 30.0±4.47°→128.73±3.6°, Knee extension: -6.83±2.48°→-1.33±1.03°) and PPT (9.67±.52kg/cm²→22.44±2.33kg/cm²) scores increased. Conclusion: These results show that physical intervention with local vibration using a Blackroll® booster and head can help to improve pain, physical function, and psychological status. Also, it was possible to select interventions depending on the patient's condition and the desired goal, using physical intervention with the Blackroll® booster technique.

• 제어로봇시스템학회논문지
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• 제6권12호
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• pp.1061-1069
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• 2000

In this paper, a new genetic algorithm is proposed for solving multimodal function optimization problems that are not easily solved by conventional genetic algorithm(GA)s. This algorithm finds one of local optima first and another optima at the next iteration. By repeating this process, we can locate all the local solutions instead of one local solution as in conventional GAs. To avoid converging to the same optimum again, we devise a new genetic operator, called a Mendel operator which simulates the Mendels genetic law. The proposed algorithm remembers the optima obtained so far, compels individuals to move away from them, and finds a new optimum.