• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.979-983
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• 1989

This paper proposes a new concept, called merit factor Fr, for evaluating the randomness of binary random sequences. The merit factor Fr is obtained from the expected values of the autocorrelation function of the binary random sequence. Using this merit factor Fr, randomness of the binary random sequences generated by the random sampling method is evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.338-342
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• 1988

Recently, in sequence control systems, high flexibility and maintenance of control software are required. This is because product life cycles become shorter and control specification must be changed frequently. The authors extend the concept of Safe Petri Net to develop the design and analysis tool for sequence control systems taking the safeness and notation of input/output functions into consideration. Extended Safe Petri Net (S-Net) is proposed as such a new graph model and real time scanning algorithm based on S-Net is developed.

• Kyungpook Mathematical Journal
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• 제47권1호
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• pp.81-89
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• 2007

In this paper, we introduce the concept of a system of asymptotically quasinonexpansive type mappings. Furthermore, we define a $k$-step iterative sequence approximating common fixed point for a system of asymptotically quasi-nonexpansive type mappings and study its stability in real Banach spaces.

• 호남수학학술지
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• 제46권2호
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• pp.291-306
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• 2024

The concept of lacunary statistical convergence of triple sequences with respect to gradual 2-normed linear spaces is introduced in this research. We learn about its link to some inclusion and fundamental properties. The notion of lacunary statistical Cauchy triple sequences is introduced in the conclusion, and it is demonstrated that it is equivalent to the idea of lacunary statistical convergence.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권5호
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• pp.306-312
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• 2008

목적 지향성 대화에서 화자의 의도는 화행과 개념열 쌍으로 구성되는 의미 구조로 근사화될 수 있다. 그러므로 지능형 대화 시스템을 구현하기 위해서는 의미 구조를 올바르게 파악하는 것이 매우 중요하다. 본 논문에서는 능동학습(active learning) 방법을 이용하여 효율적으로 의미 구조를 분석하는 모델을 제안한다. 제안 모델은 언어 분석에 따른 부담을 덜기위하여 형태소 자질들과 이전 의미 구조만을 입력 자질로 사용한다. 그리고 정확률 향상을 위하여 자연어 처리 분야에서 높은 성능을 보이고 있는 CRFs(Conditional Random Fields)를 기본 통계 모델로 사용한다. 일정 관리 영역에서 제안 모델을 실험한 결과는 기존 모델들과 비교하여 1/3 정도의 훈련데이타를 사용하고도 비슷한 정확률(화행 92.4%, 개념열 89.8%)을 나타내고 있음을 알 수 있었다.

• 한국수학교육학회지시리즈A:수학교육
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• 제57권2호
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• pp.157-177
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• 2018

The students in secondary schools have been taught calculus as an important subject in mathematics. The order of chapters-the limit of a sequence followed by limit of a function, and differentiation and integration- is because the limit of a function and the limit of a sequence are required as prerequisites of differentiation and integration. Specifically, the limit of a sequence is used to define definite integral as the limit of the Riemann Sum. However, many researchers identified that students had difficulty in understanding the concept of definite integral defined as the limit of the Riemann Sum. Consequently, they suggested alternative ways to introduce definite integral. Based on these researches, the definition of definite integral in the 2015-Revised Curriculum is not a concept of the limit of the Riemann Sum, which was the definition of definite integral in the previous curriculum, but "F(b)-F(a)" for an indefinite integral F(x) of a function f(x) and real numbers a and b. This change gives rise to differences among ways of introducing definite integral and explaining the relationship between definite integral and area in each textbook. As a result of this study, we have identified that there are a variety of ways of introducing definite integral in each textbook and that ways of explaining the relationship between definite integral and area are affected by ways of introducing definite integral. We expect that this change can reduce the difficulties students face when learning the concept of definite integral.

• 산업경영시스템학회지
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• 제12권19호
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• pp.25-30
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique. This sampling technique has never been applied to develop the scheduling algorithms. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions. Thus, it is not only very difficult, but also taken too much time to develop the appropriate job schedules that satisfy the complex work conditions. The application areas of these algorithms are also very narrow. Under these circumstances it is very desirable to develop a simple job sequencing method which can produce the good solution with the short tine period under any complex work conditions. It is called a sampling job sequencing method in this study. This study is to examine the selection of the good job sequence of 1%-5% upper group by the sampling method. The result shows that there is the set of 0.5%-5% job sequence group which has to same amount of performance measure with the optimal job sequence in the case of experiment of 2/n/F/F max. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with a little effort and time consuming. The results of ANOVA show that the two factors, number of jobs and the range of processing time are the significant factors for determining the job sequence at $\alpha$=0.01. This study is extended to 3 machines to machines job shop problems further.

• 한국학교수학회논문집
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• 제11권3호
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• pp.421-438
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• 2008

구분구적법에 대한 이해는 리만합의 극한으로 정의되는 정적분에 대한 이해의 기초가 된다. 그러나 선행연구는 구분구적법과 리만합의 극한으로서 정적분 개념에 대한 학생들의 이해에 여러 가지 한계가 있음을 지적하였다. 이 연구에서는 선행연구 분석을 통해 구분구적법의 개념 지도에 있어 크게 두 가지 어려움이 있음을 확인하였으며, 이를 개선하는데 기여할 만한 교수학적 시사점을 각각 기술하였다. 나아가 미국, 영국, 일본 교과서에 비추어 우리나라 교과서에서만 고유하게 다루어지는 정적분과 무한급수의 관계가 리만합의 극한이라는 정적분의 개념 지도에 있어 필수적인 내용 요소인지를 반성적으로 검토하였다.

• 방송공학회논문지
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• 제24권1호
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• pp.48-57
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• 2019

본 연구는 목적 지향 대화 시스템 내에서 단일 한국어 텍스트 형식의 질문으로부터 질의자의 의도를 파악하는 것을 목적으로 한다. 목적 지향 대화 시스템은 텍스트 또는 음성을 통한 사용자의 특수한 요구를 만족시켜주는 대화 시스템을 의미한다. 의도 분석 과정은 답변 생성에 앞서 사용자의 질의 의도를 파악하는 단계로, 목적 지향 대화 시스템 전체의 성능에 큰 영향을 준다. 생활화학제품이라는 특정 분야에 제안 모델을 사용하였고, 해당 분야와 관련된 한국어 텍스트 데이터를 이용하였다. 특정 분야에 독립적이며 범용적인 의도를 의미하는 화행과, 특정 분야에 종속적인 의도를 의미하는 개념열로 나누어 분석한다. 화행과 개념열을 분석하기 위하여 단어 임베딩 모델, 합성곱 신경망을 이용한 분류 방법을 제안한다. 단어 임베딩 모델을 통하여 단어의 의미정보를 추상화하고, 추상화된 단어의 의미정보를 기반으로 합성곱 신경망을 통하여 개념열 및 화행 분류를 수행한다.

• 품질경영학회지
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• 제17권1호
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• pp.69-81
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique in the case of Job Shop. This is the follow study of Kang and Ro (1988) which examined the possibility of application of sampling technique to determine the Job Sequence in the case of Flow Shop. Not only it is very difficult, but also it takes too much time to develop the appropriate job schedules that satisfy the complex work conditions. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions or assumptions. The application areas of these algorithms are also very narrow, so it is very hard to find the appropriate algorithm which satisfy the complex work conditions. In this case it is very desirable to develop a simple job sequencing method which can select the optimal job sequence or near optimal job sequence with a little effort. This study is to examine the effect of sampling job sequencing which can select the good job of 0.01%~5% upper good group. The result shows that there is the sets of 0.05%~23% job sequence group which has the same amount of performance measure with the optimal job sequence in the case of experiment of N/M/G/$F_{max}$. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with consuming a small amount of time. The results of ANOVA show that the only one factor, number of machines is the significant factor for determining the job sequence at ${\alpha}=0.01$. It takes about 10 minutes to compare the number of 10,000 samples of job sequence by personal computer and it is proved that the selection rate of the same job sequence with optimal job sequence is 23.0%, 3.9% and 0.065% in the case of 2 machines, 3 machines and 4 machines, respectively. The area of application can readily be extended to the other work condition.