• Journal of Engineering Education Research
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• v.12 no.2
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• pp.96-106
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• 2009

Problem-based learning has been considered as one of the effective educational methods in engineering education. However, in so far as professors who require practical insights in PBL and experiences of developing actual problems by subject, in particular, thorough understanding from experiences of PBL process as well as problem-development has not been sufficiently provided. The purpose of this paper is to present strategies focusing on problem design for PBL on engineering education. In order to do this, a literature review and a qualitative case study were performed. Especially, the study intended to identify differences and gap between professors' problems-development process and its output and those of authentic PBL. Professors were found that their PBL problems had lack of authenticity, consideration on experiences of students, and realistic thinking process. Professors in PBL had difficulty to link theory into real situation. In consequence, in designing a problem, we consider the followings; first, the problem should be designed based on real design process and its output. Second, the problem should be designed and implemented in all academic years for developing student's systematic and skillful thinking process. In conclusion, more supports are needed for engineering professors to extend their experiences of designing and developing actual problems that present real experience.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.31-34
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• 2024

태양광 에너지는 탄소 중립 이행을 위한 주요 방안으로 많은 주목을 받고 있다. 태양광 발전량은 여러 환경적 요인에 따라 크게 달라질 수 있으므로, 정확한 발전량 예측은 전력 네트워크의 안정성과 효율적인 에너지 관리에 근본적으로 중요하다. 대표적인 인공지능 기술인 신경망(Neural Network)은 불안정한 환경 변수와 복잡한 상호작용을 효과적으로 학습할 수 있어 태양광 발전량 예측에서 우수한 성능을 도출하였다. 하지만, 신경망은 모델의 구조나 초매개변수(Hyperparameter)를 최적화하는 것은 복잡하고 시간이 많이 드는 작업이므로, 에너지 분야에서 실제 산업 적용에 한계가 존재한다. 본 논문은 2단계 신경망 최적화를 통한 태양광 발전량 예측 기법을 제안한다. 먼저, 태양광 발전량 데이터 셋을 훈련 집합과 평가 집합으로 분할한다. 훈련 집합에서, 각기 다른 은닉층의 개수로 구성된 여러 신경망 모델을 구성하고, 모델별로 Optuna를 적용하여 최적의 초매개변숫값을 선정한다. 다음으로, 은닉층별 최적화된 신경망 모델을 이용해 훈련과 평가 집합에서는 각각 5겹 교차검증을 적용한 발전량 추정값과 예측값을 출력한다. 마지막으로, 스태킹 앙상블 방식을 채택해 기본 초매개변숫값으로 설정해도 우수한 성능을 도출하는 랜덤 포레스트를 이용하여 추정값을 학습하고, 평가 집합의 예측값을 입력으로 받아 최종 태양광 발전량을 예측한다. 인천 지역으로 실험한 결과, 제안한 방식은 모델링이 간편할 뿐만 아니라 여러 신경망 모델보다 우수한 예측 성능을 도출하였으며, 이를 바탕으로 국내 에너지 산업에 이바지할 수 있을 것으로 기대한다.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.243-248
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• 2013

This paper proposes an effective method using Adaptive Boosting to track a person's head in complex background. By only one way to feature extraction methods are not sufficient for modeling a person's head. Therefore, the method proposed in this paper, several feature extraction methods for the accuracy of the detection head running at the same time. Feature Extraction for the imaging of the head was extracted using sub-region and Haar wavelet transform. Sub-region represents the local characteristics of the head, Haar wavelet transform can indicate the frequency characteristics of face. Therefore, if we use them to extract the features of face, effective modeling is possible. In the proposed method to track down the man's head from the input video in real time, we ues the results after learning Harr-wavelet characteristics of the three types using AdaBoosting algorithm. Originally the AdaBoosting algorithm, there is a very long learning time, if learning data was changes, and then it is need to be performed learning again. In order to overcome this shortcoming, in this research propose efficient method using cascade AdaBoosting. This method reduces the learning time for the imaging of the head, and can respond effectively to changes in the learning data. The proposed method generated classifier with excellent performance using less learning time and learning data. In addition, this method accurately detect and track head of person from a variety of head data in real-time video images.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.375-385
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• 2011

Computer education is moving its focus from skill oriented education to improving students' creativity and problem solving ability. Thus, the importance of programming education is being strengthened. However, programming education was biased to grammar oriented language that has been limits of students' interest. Robot programming is problem solving itself, and by allowing students to directly see the robot which is the output of programming, can help interest and motivate to the students. In fact, it is still observed that the students are facing difficulties due to various kinds of errors during the programming education. Therefore, this study categorizes and analyzes the errors students are facing during robot programming, and based on that, a support tool to help treat errors developed. The developed supporting system for error solving reduces the frequency of errors and provides the set of coding instruction, NXC language and error message in Korean, examples and detailed information for each stage of education, function removing major coding errors, and code sorting and indication of row number. This study also confirmed that the supporting tool is helpful in reducing and solving errors after input.

• Journal of The Korean Association For Science Education
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• v.18 no.3
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• pp.337-345
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• 1998

This study examined the influences of computer-assisted instruction(CAl) upon high school students' conceptual understanding, algorithmic problem solving ability, learning motivation, and attitudes toward chemistry instruction. CAl programs were designed to supply animated molecular motions for emphasizing the particulate dynamic nature of matter and immediate feedbacks according to students' response types at each stage of four stage problem-solving strategy(understanding, planning, solving, and reviewing). The CAl and control groups (2 classes) were selected from a girls high school in Seoul, and taught about gas law for four class hours. Data analysis indicated that the students at the CAl group scored significantly higher than those at the control group in the tests on conceptual understanding and algorithmic problem solving ability. In addition, the students at the CAl group performed significantly better in the tests on the learning motivation and attitudes toward chemistry instruction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1165-1171
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• 2018

CNN requires a large amount of computation and memory in the process of extracting the feature of the object. Also, It is trained from the network that the user has configured, and because the structure of the network is fixed, it can not be modified during training and it is also difficult to use it in a mobile device with low computing power. To solve these problems, we apply a pruning method to the pre-trained weight file to reduce computation and memory requirements. This method consists of three steps. First, all the weights of the pre-trained network file are retrieved for each layer. Second, take an absolute value for the weight of each layer and obtain the average. After setting the average to a threshold, remove the weight below the threshold. Finally, the network file applied the pruning method is re-trained. We experimented with LeNet-5 and AlexNet, achieved 31x on LeNet-5 and 12x on AlexNet.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.2
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• pp.49-54
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• 2012

In this study, an E-learning system was developed for vocational rehabilitation training of intellectual disabilities. The developed system is available to have acquirement of knowledge through step by step learning and is configured to relearn through problem-solving and demonstration video. In addition, the learned information was composed to check the configuration which is correctly learning through rehearsal function. The device for rehearsal consists of a transmitter and the receiver. The transmitter is formed Pressure sensor, IR sensor for detecting client's work and Bluetooth module for wireless network. The receiver includes a Bluetooth module for wireless network and USB input terminal for communication with computer.

• Proceedings of the Technology Innovation Conference
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• 1997.12a
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• pp.45-69
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• 1997

최근들어 환경변화가 가속화되고 기업의 환경적응성이 중요해짐에 따라 R&D 활동의 평가과정이 학습의 핵심적인 단계로서 새롭게 부각되고 있다. 또한 R&D 활동에서 결과 중심적 접근, 사업부와의 연계 등이 강조되면서 구체적 R&D 성과평가가 연구관리(R&D management)의 중요한 이슈가 되고있다. 그러나 그동안 R&D 성과평가는 R&D 활동 자체가 불확실성을 가지는 특성으로 인하여 체계적 접근이 이루어지지 못하여 왔으며 최근에 들어 R&D 성과평가 부문이 연구관리 및 기술경영분야의 도전적 연구과제가 되고 있다. 본 연구는 이러한 R&D 성과평가를 어떻게 접근할 것인지에 대한 접근방법과 성과 지표의 내용, 성과지표의 선택 및 개발절차, 향후 연구과제를 중심으로 제시한다. 본 연구의 세부내용은 다음과 같다. 첫째, 민간기업 연구개발활동의 성과평가에 적용가능한 평가의 분석틀(framework) 및 관점(perspective)을 제시하였다. 기존 평가모형에 대한 문헌고찰을 바탕으로 종합적, 체계적인 평가분석틀을 도출하고, 측정가능한 성과지표군을 제시하였다. 또한 성과지표들을 다양한 기준에 따라 분류하고 각 분류에 따라 적용가능한 성과지표군을 제시하였다. 둘째, 각 기업별 특성을 고려하고 경영전략과의 연계를 명확히 할 수 있는 구체적인 성과지표를 개발하기 위하여 4단계의 R&D 성과 평가지표 개발절차를 도출하였다. 셋째, 향후연구를 위한 성과평가 연구분야의 주요 연구과제들을 5가지로 정리하여 제시하였다.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.407-414
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• 2002

Being recently increased interests of our healthcare, a host of symptoms-diagnostic sites has been introduced on the World Wide Web. But conventional healthcare sites provide users with only a very restricted functions. In this paper, we propose the use of Artificial Neural Networks (ANNs) as a flexible symptoms-diagnostic tool that enables learning effects of ANNs (not expert's knowledge) to be incorporated into the diagnostic process. We develop a novel algorithm for predicting patient\`s disease that satisfy user (or expert)-specified symptoms on WWW. Our algorithm provides two important benefits : 1) enables users (patients) to be taken early diagnostic, and 2) enables experts to perform confidently diagnostic by referencing the predicted diseases-list with its respective possibility.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.58-63
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• 2010

The purpose of this study is to establish a knowledge based system for education of CNC machining. The program is made based on various educational courses, teaching methodology and teaching medium etc. and has a good accessibility which can be used anywhere if computer is available. For the system, various variables according to materials, tools or shapes for machining are reviewed and analyzed. Also, the intelligent educational program is developed using Visual Basic language. It can be used to help trainees who want to refer cutting conditions for actual cutting process and also can be useful for beginner who wants to learn and to practice for CNC machining.