• Journal of Korea Game Society
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• v.9 no.1
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• pp.3-10
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• 2009

This paper presents the effects on logical thinking of the Korean LOGO programming used in teaching for the second grade of middle school with regard to cognitive styles and specific sub-classifications of logical thinking. In result, the LOGO programming teaching method significantly affected logical thinking and its sub-classifications.

• Journal of the Korean Institute of Telematics and Electronics
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• v.11 no.2
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• pp.1-4
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• 1974

Matrix inversion is very inefficient for computing direct solutions of the large sparse systems of linear equations that arise in many network problems. This paper describes some computer programming techniques for taking advantage of the sparsity of the admittance matrix. with this method, direct solutions are computed from sparse matrix. It is Possible to gain a significant reduction in computing time, memory and round-off emir[r. Retails of the method, numerical examples and programming are given.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.345-354
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• 2006

In this paper first, we find a canonical symmetrical trapezoidal(triangular) for the solution of the fuzzy linear system $A\tilde{x}=\tilde{b}$, where the elements in A and $\tilde{b}$ are crisp and arbitrary fuzzy numbers, respectively. Then, a model for fuzzy linear programming problem with fuzzy variables (FLPFV), in which, the right hand side of constraints are arbitrary numbers, and coefficients of the objective function and constraint matrix are regarded as crisp numbers, is discussed. A numerical procedure for calculating a canonical symmetrical trapezoidal representation for the solution of fuzzy linear system and the optimal solution of FLPFV, (if there exist) is proposed. Several examples illustrate these ideas.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.831-846
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• 2011

There are several methods, in the literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, a new method (based on fuzzy linear programming formulation) is proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems with a new representation of trapezoidal fuzzy numbers. The advantages of the proposed method over existing method are discussed. Also, it is shown that it is better to use the proposed representation of trapezoidal fuzzy numbers instead of existing representation of trapezoidal fuzzy numbers for finding the fuzzy optimal solution of fuzzy transportation problems. To illustrate the proposed method a fuzzy transportation problem (FTP) is solved by using the proposed method and the obtained results are discussed. The proposed method is easy to understand and to apply for finding the fuzzy optimal solution of fuzzy transportation problems occurring in real life situations.

• Journal of Educational Research in Mathematics
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• v.10 no.1
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• pp.85-102
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• 2000

The concept of variables is central to mathematics teaching and learning in junior and senior high school. Understanding the concept provides the basis for the transition from arithmetic to algebra and necessary for the meaningful use of all advanced mathematics. Despite the importance of the concept, however, much has been written in the last decade concerning students' difficulties with the concept. This Thesis is based on research to investigate the hypothesis that LOGO programming will contribute to 6th grader' learning of variables. The aim of the research were to; .investigate practice on pupils' understanding of variables before the activity with a computer; .identify functions of LOGO programming in pupils' using and understanding of variable symbols, variable domain and the relationship between two variable dependent expressions during the activity using a computer; .investigate the influence of pupils' mathematical belief on understanding and using variables. The research consisted predominantly of a case study of 6 pupils' discourse and activities concerning variable during their abnormal lessons and interviews with researcher. The data collected for this study included video recordings of the pupils'work with their spoken language.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.131-139
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• 2021

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.447-450
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• 2021

이 연구의 목적은 자유학기제 학생을 대상으로 한 아두이노 프로그래밍 체험 프로그램의 개발 사례를 제시하는데 있다. 이를 위해 연구자는 Lee(2020)의 저비용 마이크로컨트롤러 적용 교수학습 모형에 기반하여 아두이노 프로그래밍 체험 프로그래밍 2종을 개발하였다. 이 연구의 결론은 다음과 같다. 첫째, 개발된 프로그램은 '아두이노 음악 연주 프로그램'과 '아두이노 자동차 만들기 프로그램'이다. 둘째, 개발된 프로그램은 각각 7개와 8개의 하위 모듈로 구성되어 있으며, 참여 중학교의 여건에 따라 전부 또는 일부를 선택하여 적용할 수 있다. 셋째, 개발된 프로그램을 통해 프로그램 참여 중학생들은 매크로, 반복문, 배열, 함수 등의 C 프로그래밍 내용 요소를 체험할 수 있었다. 개발된 프로그램은 자유학기제 학생들을 대상으로 짧은 시간내에 프로그래밍을 온라인 환경하에서 체험시켰다는 점에서 의의가 있다. 향후 연구에서는 보다 검증된 설문지와 구체적인 실험 설계를 바탕으로 본 개발 프로그램의 교육 효과를 검증해 볼 필요가 있을 것이다.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.210-218
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• 2023

The author presents a simple data-driven intraday technical indicator trading approach based on Genetic Programming (GP) for return forecasting in the Bitcoin market. We use five trend-following technical indicators as input to GP for developing trading rules. Using data on daily Bitcoin historical prices from January 2017 to February 2020, our principal results show that the combination of technical analysis indicators and Artificial Intelligence (AI) techniques, primarily GP, is a potential forecasting tool for Bitcoin prices, even outperforming the buy-and-hold strategy. Sensitivity analysis is employed to adjust the number and values of variables, activation functions, and fitness functions of the GP-based system to verify our approach's robustness.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.15
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• pp.51-58
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• 1987

This paper describes a new variant of Successive Linear Programming (SLP) algorithm called PSLP (Penalty SLP, 1985) using the multiplicative formulation Proposed by Beale (1978). A Fortran computer implementation md its performance are also summarized.