• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.204-205
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• 2005

The following instructions give you basic guidelines for preparing camera-ready papers for the proceeding of the KOSME. We recommend you to use the HWP word processor.

• The Mathematical Education
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• v.38 no.1
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• pp.87-94
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• 1999

A multimedia CD title is developed for learning simple closed curve and Mobius band which are one of mathematics contents in the first grade of middle school. This title visualizes various figures through graphics and animations so that students can easily understand the relevant concepts and learn them with fun. It is shown that 88.6% of 30 sampled teachers are positive for the title and that 86.7% want to use it as a teaching tool in their classes.

• Journal of The Korean Association For Science Education
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• v.28 no.7
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• pp.730-748
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• 2008

Students often have tenacious physics misconceptions and many studies were conducted on engendering conceptual change. Correspondingly, there is much literature on alternative assessment and its role in student learning. This is a comparison study on using alternative assessments to improve common students' misconceptions in GCE Advanced Level Physics. This research also aims to affirm alternative assessment as a valid tool for learning and promote its use. This study involved two classes with 24 students each. For four weeks, electromagnetism was taught to students using the same classroom pedagogies but with different assignments. The control group completeda standard drill-and-practice assignment while the experimental group finished an alternative assessment. From the preliminary results, students who undertook the alternative assessment and the traditional assessment both improved, however, the treatment group did not perform statistically significantly better than the control group. The reasons will be discussed and commented and it is expected to have significant improvement on rectifying misconceptionsupon next batch of experimentation groups.

• Journal of KSNVE
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• v.10 no.2
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• pp.331-337
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• 2000

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal defect diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised learning algorithm is used to improve the quality of the classifier decision regions.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.3
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• pp.515-521
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• 2020

Deep learning methods have been effectively used to provide great improvement in various research fields such as machine learning, image processing and computer vision. One of the most frequently used deep learning methods in image processing is the convolutional neural networks. Compared to the traditional artificial neural networks, convolutional neural networks do not use the predefined kernels, but instead they learn data specific kernels. This property makes them to be used as feature extractors as well. In this study, we compared the quality of CNN features for traditional texture feature extraction methods. Experimental results demonstrate the superiority of the CNN features. Additionally, the recognition process and result of a pioneering CNN on MNIST database are presented.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3036-3038
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• 1999

The conventional structure for an action selector of an Autonomous Mobile Robot (AMR) has been criticized for a repeated action. To overcome this problem recently many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we propose a learning aritificial immune network, the learning method is to use Genetic Algorithm (GA). The computer simulation show that the usefulness of the learning immune network.

• International Journal of Advanced Culture Technology
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• v.8 no.4
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• pp.77-81
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• 2020

Recently we have lots of Youtube contents and their influence. But Just a few Studies have announced Youtube content's effect. The purpose of this paper is to see if ASMR content, which is popular through Youtube recently, helps teenagers stabilize their minds and improve their learning abilities. To that end, a survey of teenagers found that ASMR content is very familiar to teenagers, and that 66.7 percent of teenagers use ASMR content for sleep and learning. About the change before and after watching, half of the respondents said they felt a positive difference in learning and psychological stability. As a result, ASMR is a significant content for teenagers with a specific purpose. Therefore, policies such as 'after-school' in terms of school education are proposed as alternatives rather than unilateral measures such as banning ASMR content to teenagers.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.283-287
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• 2022

Machine Learning is the most popular method used in data science. Growth of data is not only numeric data but also text data. Most of the algorithm of supervised and unsupervised machine learning algorithms use numeric data. Now it is required to convert text data into numeric. There are many techniques for this conversion. Researcher confuses which technique is best in what situation. Here in proposed work BOW (Bag-of-Words) and TF-IDF (Term-Frequency-Inverse-Document-Frequency) has been studied based on different features to determine best method. After experimental results on text data, TF-IDF and BOW both provide better performance at range from 100 to 150 number of features.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.97-105
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• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

• Educational Technology International
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• v.13 no.1
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• pp.175-205
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• 2012

The current study investigated whether SNS such as Twitter can be an assisting tool to compensate the limitations of online learning from social-affective and cognitive perspectives. Such limitations include low level of motivation to participate, feeling of isolation, rare exchanges of ideas and feedback from peers or instructors. This paper reports findings from a research study on the use of Twitter in online learning in Higher Education. Survey and subsequent interviews were conducted to examine students' perceptions about the cognitive and social-affective aspects of their participation in Twitter activities. Some of the challenges and potentials in integrating Twitter into online course are also addressed. It can be concluded that Twitter contributes not only to building close relationships among peers and instructors but also to opening a communication channel that can extend cognitive potentials.