• 한국수학교육학회지시리즈E:수학교육논문집
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• 제29권3호
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• pp.533-551
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• 2015

본 연구에서는 '동일한' 문제 조건으로부터 생성과 재구성을 모두 경험할 수 있는 문제제기 활동을 적용하되, 활동을 세분화하여 학생들의 자주적인 활동을 강조한 활동과 학생들의 보편적 사고를 유도하며 교사 안내가 수반되는 활동으로 구분하여 이에 대한 두 절차를 구안하고, 이 두 활동에 의거하여 문제생성과 재구성 활동에 관해 탐색하고자 한다. 이를 위하여, 본 연구에서는 예비교사들을 대상으로 연구자가 구안한 문제제기 활동을 적용한 실험 수업 후 설문조사를 통하여 문제생성과 재구성에 대한 난이도 및 흥미도, 인지적 정의적 측면에서의 효과, 그리고 수학 수업 및 평가에서의 활용성 등을 탐색하였다. 그 결과, 문제생성은 창의력을 증진시키고 수학에 대한 흥미를 유발하며, 문제 재구성은 문제 해결력 향상에 도움이 되고 자신감을 길러주는 것으로 나타났다. 또한 수업 상황에서는 문제생성 활동이 더 효과적이고, 평가 상황에서는 문제재구성 활동이 더 효과적인 것으로 나타났으나 각 상황에서 문제생성과 재구성에 대한 응답의 차이가 크지 않았으므로 두 활동 모두 수업 및 평가에 적용이 가능할 것으로 판단된다. 따라서 교사는 학습자의 수준, 가르칠 영역, 진도 등을 고려하여 수업 및 평가 상황에서 문제생성과 재구성 활동을 적절한 시기에 알맞게 적용함으로써 학습자의 인지적, 정의적 성취의 함양을 돕도록 해야 할 것이다.

• 한국경영과학회지
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• 제39권1호
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• pp.13-27
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• 2014

In this paper, we deal with a Steiner Ring Star (SRS) problem arising from the design of survivable telecommunication networks. We develop two mixed integer programming formulations for the SRS problem by implementing Miller-Tucker-Zemlin (MTZ) and Sarin-Sherali-Bhootra (SSB) subtour elimination constraints, and then apply the reformulation-linearization technique (RLT) to enhance the lower bound obtained by the LP relaxation. By exploiting the ring-star structure of underlying network, we devise some valid inequalities that tighten the LP relaxation. Computational results demonstrate the effectiveness of the proposed solution procedure.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1992년도 춘계공동학술대회 발표논문 및 초록집; 울산대학교, 울산; 01월 02일 May 1992
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• pp.232-232
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• 1992

• 한국수학교육학회지시리즈A:수학교육
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• 제57권3호
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• pp.289-309
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• 2018

There has been a gradually increasing focus on adopting mathematical modeling techniques into school curricula and classrooms as a method to promote students' mathematical problem solving abilities. However, this approach is not commonly realized in today's classrooms due to the difficulty in developing appropriate mathematical modeling problems. This research focuses on developing reformulation strategies for those problems with regard to mathematical modeling. As the result of analyzing existing textbooks across three grade levels, the majority of problems related to the real-world focused on the Operating and Interpreting stage of the mathematical modeling process, while no real-world problem dealt with the Identifying variables stage. These results imply that the textbook problems cannot provide students with any chance to decide which variables are relevant and most important to know in the problem situation. Following from these results, reformulation strategies and reformulated problem examples were developed that would include the Identifying variables stage. These reformulated problem examples were then applied to a 7th grade classroom as a case study. From this case study, it is shown that: (1) the reformulated problems that included authentic events and questions would encourage students to better engage in understanding the situation and solving the problem, (2) the reformulated problems that included the Identifying variables stage would better foster the students' understanding of the situation and their ability to solve the problem, and (3) the reformulated problems that included the mathematical modeling process could be applied to lessons where new mathematical concepts are introduced, and the cooperative learning environment is required. This research can contribute to school classroom's incorporation of the mathematical modeling process with specific reformulating strategies and examples.

• 한국경영과학회지
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• 제23권4호
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• pp.141-149
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• 1998

One of the difficulties in using the current Boolean-based information retrieval systems is that it is hard for a user, especially a novice, to formulate an effective Boolean query. One solution to this problem is to let the system formulate a query for a user from his relevance feedback documents in this research, an intelligent query reformulation mechanism based on ID3 is proposed and the sensitivity of its retrieval effectiveness, i.e., recall, precision, and E-measure, to various input settings is analyzed. The parameters in the input settings is the number of relevant documents. Experiments conducted on the test set of Medlars revealed that the effectiveness of the proposed system is in fact sensitive to the number of the initial relevant documents. The case with two or more initial relevant documents outperformed the case with one initial relevant document with statistical significances. It is our conclusion that formulation of an effective query in the proposed system requires at least two relevant documents in its initial input set.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.525-529
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• 1996

Decision environments involve a high degree of uncertainty as well as multiple, conflicting goals. Although traditional goal programming offers a means of considering multiple, conflicting goals and arrives at a satisficing solution in a deterministic manner, its major drawback is that decision makers often specify aspiration level of each goal as a single number. To overcome the problem of setting aspiration levels, chance constrained programming can be incorporated into goal programming formulation so that sampling information can be utilized to describe uncertainty distribution. Another drawback of goal programming is that it does not provide a systematic approach to set priorities and trade-offs among conflicting goals. To overcome this weekness, the analytic hierarchy process(AHP) is used in the model. Also, most goal programming models in the literature are of a linear form, although some nonlinear models have been presented. Consideration of risk in technological coefficients and right hand sides, however, leads to nonlinear goal programming models, which require a linear approximation to be solved. In this paper, chance constrained reformulation with linear approximation is presented for a 0-1 goal programming problem whose technological coefficients and right hand sides are stochastic. The model is presented with a numerical example for the purpose of demonstration.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.486-490
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• 1993

This paper presents an improved algorithm which enables to find a suboptimal $H^{\infty}$ controller. In the $H^{\infty}$ control problem with output multiplicative uncertainty, the Glover-Doyle algorithm has sorne constraints for the standard plant. The proposed algorithm removes them by reformulating the standard plant. We show the validity of this algorithm by investigating the variation of norm-bound.d.

• 충청수학회지
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• 제7권1호
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• pp.141-152
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• 1994

We consider a numerical scheme for solving a nonlinear boundary integral equation (BIE) obtained by reformulation the nonlinear boundary value problem (BVP). We give a simple alternative to the standard collocation method for the nonlinear BIE. This method consists of one conventional linear system and another coupled linear system resulting from an auxiliary BIE which is obtained by differentiating both side of the nonlinear interior integral equations. We obtain an analogue BIE through the perturbation of the fundamental solution of Laplace's equation. We procure the super-convergence of approximate solutions.

• 한국정보처리학회논문지
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• 제2권3호
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• pp.417-424
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• 1995

본 논문에서는 정량화(Quantification) 문제를 MFT(Mean Field Theroy)를 통해서 해결하는 기법을 제안한다. 통계학에서 중요한 문제의 하나인 정량화 문제는 주어진 공간에서 대상들간의 유사성에 따라서 최적의 상태를 갖도록 하는 문제이다. 평균장 접근 방법에 기초한 한개의 변수로 표현되는 확률적 시뮬레이티드 아닐링을 제안하고 정량화 문제를 패널티(penalty) 파라메타 항을 첨가한 비한정된 최적화 문제로 변형하 여 MFT를 적용하였다. 또한 연속변수를 갖는 신경회로망에서 실제 값을 계산하는 것 보다 평균장 접근방법으로 계산하는것이 더 빠르게 계산될 수 있음을 확인하였다. 본 논문에서 제안한 방법이 실험결과 해석적인 방법보다 좋은 정량적 결과를 보였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.