• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.48-55
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• 1997

A useful method to detect tool breakage suing neural network of cutting force signal is porposed and implemented in a basic cutting process. Cutting signal is gathered by tool dynamometer and normalized as a preprocessing. The cutting force signal level is continually monitored and compared with the predefined level. The neural network has been trained normalized sample data of the normal operation and cata-strophic tool failure using backpropagation learning process. The develop[ed system is verified to be very effective in real-time usage with minor modification in conventional cutting processes.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.41-43
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• 2001

This paper presents a Web-based educational tool for Power System Engineering, especially for power engineers. This tool has Web-oriented educational courses for power system education. The Web-based learning has become more popular year by year in the various fields[1-2]. The proposed educational tool provides some courses such as power system introduction Course, KEPCO's system introduction Course, Power system devices Course, Power Flow Course, OPF Course, ELD Course, Stability Analysis Course, Fault analysis Course, Voltage & Frequency control Course, and power system planning & operation Course. Finally, it will be scheduled to install for the education tool of the power system engineering for KEPS[3].

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.191-192
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• 2012

In this paper, we describe an educational tool for presentation which shows teacher's whole handwriting process to learners named HPT(Handwriting Presentation Tool). We assume that presenting writing processes has rich educational information. We believe this information influences learners' understandings of the provided learning contents. Animation functions of popular presentation tools are not enough to represent this information. Our presentation tool enables the lessons with a new type of presentation slides which combine advantages of traditional blackboards and popular presentation tools.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.120-129
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• 1995

This study introduces a tool wear monitoring technology in face milling operation comprised of an unsupervised neural network. The monitoring system employs two types of sensor signal such as cutting force and acceleration in sensory detection state. The RMS value and band frequency energy of the sensor signals are calculated for te input patterns of neural network. ART2 neural network, which is capable of self organizing without supervised learning, is used for clustering of tool wear states. The experimental results show that tool wear can be effectively detected under various cutting conditions without prior knowledge of cutting processes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.208-216
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• 2020

With the spread of smart manufacturing, one of the key topics of the 4th industrial revolution, manufacturing systems are moving beyond automation to smartization using artificial intelligence. In particular, in the existing automatic machining, a number of machining defects and non-processing occur due to tool damage or severe wear, resulting in a decrease in productivity and an increase in quality defect rates. Therefore, it is important to measure and predict tool life. In this paper, ν-ASVR (ν-Asymmetric Support Vector Regression), which considers the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, was proposed and applied to the tool wear prediction problem. In the case of tool wear, if the predicted value of the tool wear amount is smaller than the actual value (under-estimation), product failure may occur due to tool damage or wear. Therefore, it can be said that ν-ASVR is suitable because it is necessary to overestimate. It is shown that even when adjusting the asymmetry of ⲉ-tube and the asymmetry of penalties for data out of ⲉ-tube, the ratio of the number of data belonging to ⲉ-tube can be adjusted with ν. Experiments are performed to compare the accuracy of various kernel functions such as linear, polynomial. RBF (radialbasis function), sigmoid, The best result isthe use of the RBF kernel in all cases

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.49-59
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• 2006

Traditional programming education lacked consideration of contents, methods and learners. In particular, the importance of programming education has been decreased in school because almost no suitable teaching has been executed for elementary school students. To solve these problems, this study proposed the use of MINDSTORMS that is a programming education tool suitable for elementary school students, and verified its effects on learners' creativity. The results of this study show that the tool is highly effective in improving students' creativity. The objectives of programming education are not only learning programming languages but also improving problem-solving ability, logical thinking and creativity. We must offer environment, in which students can control their own learning activity and solve problems by themselves. In addition, MINDSTORMS can be a very useful and suitable tool for programming education.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.350-358
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• 2021

In modern years, the performance of the students is analysed with lot of difficulties, which is a very important problem in all the academic institutions. The main idea of this paper is to analyze and evaluate the academic performance of the college students with bipolar disorder by applying data mining classification algorithms using Jupiter Notebook, python tool. This tool has been generally used as a decision-making tool in terms of academic performance of the students. The various classifiers could be logistic regression, random forest classifier gini, random forest classifier entropy, decision tree classifier, K-Neighbours classifier, Ada Boost classifier, Extra Tree Classifier, GaussianNB, BernoulliNB are used. The results of such classification model deals with 13 measures like Accuracy, Precision, Recall, F1 Measure, Sensitivity, Specificity, R Squared, Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, TPR, TNR, FPR and FNR. Therefore, conclusion could be reached that the Decision Tree Classifier is better than that of different algorithms.

• Educational Technology International
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• v.14 no.1
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• pp.55-74
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• 2013

The diversity of students is getting increased in the contemporary classroom. To deal with the diversity, differentiated instruction (DI) should be considered as a way of providing alternative approaches to content, process and product according to the students' readiness, interest, and learning needs. Teachers have problems and difficulties in supporting different student's needs. In fact, teachers need proven tools including framework, guidelines or computing systems to help to practice DI in real context. According to the activity theory, tools influence on how people act and think and even their social practice, playing a crucial role in mediating the activities with people. In DI practice, there are also some studies about physical and abstract tools, but they have been not widely utilized by teachers in real schools. It means that more innovative tool to promote DI might be required. Therefore, to design a better tool to mediate the DI activities with teacher, case studies were conducted. In order to elicit the design implications, two physical and two abstract tools for DI practice were analyzed as case studies. Through the analysis of the case studies, eight design implications better to facilitate DI practice were suggested. This study has implications in suggesting design guidelines for teachers' tools to facilitate their DI practice by analyzing case studies in DI practices for an innovative tool in the educational practice.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.129-139
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• 2004

This society is rapidly changing into an information-oriented society. As such, revolutionary and efficient teaching methods are needed in school education rather than traditional methods. To be an efficient teaching lesson, teaching plans based on learners' prior knowledge are needed. The knowledge-space theory provides the methods of efficient analysis about learners' status of knowledge. This study designs and implements the support-learning tool based on the knowledge-space theory to increase the efficiency in classroom lessons through the development of various methods of analysis of learners' knowledge status.

• Journal of Engineering Education Research
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• v.13 no.2
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• pp.22-27
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• 2010

From a lot of survey, it is obvious that most students in universities lose their desire for learning just after entering their universities. In order to solve this problem, we developed a novel educational tool for the students, named "The thinking method based on matrix diagram". If they try hard with the help of this tool, they will be able to learn how to design and manage their splendid university lives in addition to get the basic knowledge and to improve their basic abilities. It is also found that they can earn the shared knowledge mutually after learning a common method, which supports to make them to improve their communication abilities drastically.