• 교육시설 논문지
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• 제24권6호
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• pp.27-36
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• 2017

Educational facilities have an affect to make a decently learning environment. After constructed, it needs a maintenance plan to keep the performance or function which provide the repair time, repair scope and ratio. But the fundamental data are so insufficient that the field worker can't provide the maintenance plan and has no choice use the other data which concerned with apartment or office building. Above all, the service life is indispensible to make a repair plan because the repair time and scope would be provided within the service life. This study aimed at providing the method to make a service life of component in educational facilities and applying the method into the roof proof and floor finishing. Results are shown that first, it is important to set the $1^{st}$ repair time after constructed. when it proposes the three ways with the probability approach, choice probability model and cumulative cost function. Second, the service life of roof proof is provided with about 35 years. In addition, the service life of the floor finishing is about 40 years. These result would be utilized to conduct the repair plan under the service life.

• 전기전자학회논문지
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• 제24권4호
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• pp.931-941
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• 2020

기계학습을 이용한 자연어처리 기술이 발전하면서 SHNS (Smart Home Network Service)가 다시 주목받고 있다. 그러나 SHNS는 구성 기기의 다양성과 사용자의 가변성 등으로 인하여 표준화된 인증 시스템 적용이 어렵다. 블록체인은 분산 환경에서 데이터 인증을 위한 기술로 제안되고 있지만, 작업증명시스템 구현 시 요구되는 계산 오버헤드 때문에 SHNS에 적용하는데 한계가 있다. 본 논문에서는 경량화된 작업증명시스템을 제안하였다. 제안하는 경량화된 작업증명시스템은 기기의 작업 권한을 제어함으로써 블록 생성을 관리하도록 제안되었다. 또한 본 논문에서는 이를 기반으로 SHNS의 접근통제 방안을 제안한다.

• International Journal of Precision Engineering and Manufacturing
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• 제3권1호
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• pp.33-42
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• 2002

Recently, various experiments to apply reinforcement learning method to the self-learning intelligent control of continuous dynamic system have been reported in the machine learning related research community. The reports have produced mixed results of some successes and some failures, and show that the success of reinforcement learning method in application to the intelligent control of continuous control systems depends on the ability to combine proper function approximation method with temporal difference methods such as Q-learning and value iteration. One of the difficulties in using function approximation method in connection with temporal difference method is the absence of guarantee for the convergence of the algorithm. This paper provides a proof of convergence of a particular function approximation method based on \"barycentric interpolator\" which is known to be computationally more efficient than multilinear interpolation .

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집B
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• pp.724-729
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• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• 대한전기학회논문지
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• 제39권4호
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• pp.393-402
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• 1990

An iterative learning contol method is presented for a class of linear periodic systems, in which a parameter estimator of the system together with an inverse system model is utilized to generate the control signal at each iteration. A convergence proof is given and two numerical examples are illustrated to show the validities of the algorithm. In particular, it is shown that the method is useful for the continuous path control of robot manipulators.

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 2008년도 연합학회학술대회
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• pp.163-182
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• 2008

이러닝 산업이 성장하면서 SCORM이라는 사실상 국제표준이 개발되었고 국내 외 활용이 증가하고 있다. 이렇게 SCORM 기반 이러닝을 통하여 학습하는 수강생이 증가되고 있는 상황에서 SCORM 기반 이러닝 교육효과에 영향을 미치는 요인을 분석하고, 이를 일반 콘텐츠 수강생의 교육효과에 미치는 요인과 비교하여 SCORM 표준을 적용 할 때의 수강생 교육효과에 영향을 미치는 요인의 변화를 분석하였다.

• 대한수학교육학회지:학교수학
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• 제4권3호
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• pp.361-373
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• 2002

In this paper, a series of tasks related on polygonal numbers and pyramidal numbers are suggested for using them as teaching unit materials for teaching and learning of sequences in junior high school mathematics. Especially, finding n-th term in those seque-nces, relations among polygonal numbers, and relations among Pyramidal numbers are focused on. A series of tasks related on polygonal numbers and pyramidal numbers have three math-eucational values. First, they have a value as natural materials for teaching and teaming of finding nth term of original sequences using pro-gression of differences. Second, they have a value as materials for teaching and learning of mathematical thinking such as general-ization, analogy, etc. Third, they have a value as materials for teaching and learning of algebraic operation, proof, and connecting mathematical knowledges.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• 대한전기학회논문지:전력기술부문A
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• 제48권5호
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• pp.629-635
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• 1999

A second-order iterative learning control algorithm with feedback is proposed in this paper, in which a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is givenl, and the sufficient condition for the convergence of the algorithm is provided. And it also includes the discussions about the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial. Simulation results show the validity and efficiency of the proposed algorithm.

• 한국학교수학회논문집
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• 제14권2호
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• pp.227-239
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• 2011

삼각형의 외심은 중학교 2학년에 처음 도입되는 논증기하의 부분에서 다루어진다. 증명을 통해 도형의 성질을 다루는 과정에 본질적으로 상당한 어려움이 내포되어 있긴 하나, 학생들 은 교과서에서 다루는 외심과 관련한 명제의 증명을 학습하는데 특히 많은 어려움을 겪는다. 따라서 본 연구에서는 우리나라 교과서에서 다루는 외심의 정의와 증명을 오랜기간 논증기 하의 교과서로 사용된 유클리드 원론 및 현행 미국 교과서의 방식과 비교함으로써 삼각형의 외심 지도에 관한 시사점을 끌어내고자 한다.