• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.475-483
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• 2009

With the development of information communication and network technologies, ubiquitous era that supports various services regardless of places and time has been advancing. The development of such technologies have a great influence on educational environments. As a result, e-learning concepts that learners use learning contents in anywhere and anytime have been proposed. The various learning contents authoring systems that consider the e-learning environments have also been developed. However, since most of the existing authoring systems support only PC environments, they is not suitable for various ubiquitous mobile devices. In this paper, we design and implement a contents authoring system based on learning activities for u-learning environments. Our authoring system significantly improves the efficiency for authoring contents and supports various ubiquitous devices as well as PCs.

• Journal of the Korean Chemical Society
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• v.48 no.3
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• pp.291-299
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• 2004

The purpose of this study is to investigate views of high school students' learning of chemistry as one aspect of conceptual ecology. The results of this study will help us expand our understanding of conceptual change as it is used to evaluate learners. I made use of an interpretative research design based on principles of naturalistic inquiry. The participants in this study were six sophomore students. The picture of a chemistry class we draw from analyzing data is a play on stage with little interaction. Students accept passive and difficult-to-modify views of the learner roles that they should play in the chemistry classroom. Students identified chemistry classes as conservative places. 'Transmission' seems to remain the persistent and dominant classroom cultural dynamic for both the teaching and learning of chemistry. Students should understand about learning processes, and how to play, monitor, evaluate and regulate them. Students should experience the plausibility and fruitfulness of learning chemistry, and it will help students to feel a "love of learning chemistry." As students change their views of learning chemistry, it will help to improve their learning and to experience conceptual change in chemistry learning.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.51-60
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• 2020

Optical character recognition (OCR) has been studied for decades because it is very useful in a variety of places. Nowadays, OCR's performance has improved significantly due to outstanding deep learning technology. Thus, there is an increasing demand for commercial-grade but affordable OCR systems. We have developed a low-cost, high-performance OCR system for the industry with the cheapest embedded developer kit that supports GPU acceleration. To achieve high accuracy for industrial use on limited computing resources, we chose a state-of-the-art text recognition algorithm that uses an end-to-end deep learning network as a baseline model. The model was then improved by replacing the feature extraction network with the best one suited to our conditions. Among the various candidate networks, EfficientNet-B3 has shown the best performance: excellent recognition accuracy with relatively low memory consumption. Besides, we have optimized the model written in TensorFlow's Python API using TensorFlow-TensorRT integration and TensorFlow's C++ API, respectively.

• Steel and Composite Structures
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• v.44 no.1
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• pp.49-63
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• 2022

This study aims to develop ensemble machine learning (ML) models for estimating the peak floor acceleration and maximum top drift of steel moment frames. For this purpose, random forest, adaptive boosting, gradient boosting regression tree (GBRT), and extreme gradient boosting (XGBoost) models were considered. A total of 621 steel moment frames were analyzed under 240 ground motions using OpenSees software to generate the dataset for ML models. From the results, the GBRT and XGBoost models exhibited the highest performance for predicting peak floor acceleration and maximum top drift, respectively. The significance of each input variable on the prediction was examined using the best-performing models and Shapley additive explanations approach (SHAP). It turned out that the peak ground acceleration had the most significant impact on the peak floor acceleration prediction. Meanwhile, the spectral accelerations at 1 and 2 s had the most considerable influence on the maximum top drift prediction. Finally, a graphical user interface module was created that places a pioneering step for the application of ML to estimate the seismic demands of building structures in practical design.

• Journal of the Korean School Mathematics Society
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• v.3 no.1
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• pp.177-188
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• 2000

Mathematics is extreme the differences of the scholarly attainments in comparison with other subjects at a middle school. Specially, the students at islands and places leave much to be desired the scholarly attainments standards of mathematics. Therefore, every school takes movement class according to level these days. And the small schools put in effect the cooperation of group work through the small groups. These classes are effective at the scholarly attainments extension to some degree, but each student is extreme the differences of scholarly attainments. On this, the small school was the subject of study at the present research and put in effect the cooperation of group work through the small groups. The students were divided in three groups; the top class, average, the low class, And they were offered the fitting textbooks matching the cooperation of group work and the opportunities of discovery learning fitting an individual ability and standard. Consequently, some educational materials were made, for example, question papers, commonness learning materials, choice learning materials. These materials were put in effect to the students to be able to succeed discovery learning. With this, the students were investigated an interest of mathematics and the influence giving at the studies attainment. And the students were put in effect the cooperation of group work through the small groups to improve uniformity and sturdiness of the mathematical education. The conclusion at the present research is as follows. 1) When the students put in effect the cooperation of group work through the small groups, the scholarly attainments of mathematics totally didn't display useful changes as improvement. However, the students of average and the low class gradually seemed to improve the scholarly attainments of mathematics as the help of the top class positively. 2) An individual and cooperation learning in the method of the cooperation of group work through the small groups displayed many changes at the learning attitude of the students by means of discovery learning thanks to the learning heads. 3) When the investigator put in effect the cooperation of group work through rather the small groups than the large groups, the numbers of the students experiencing interest about mathematics increased in 26% and this learning method should continue to progress.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.9-12
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• 2016

This paper is concerned with the effective and efficient identification of the gender and motion of humans. Tracking this nonverbal behavior is useful for providing clues about the interaction of different types of people and their exact motion. This system can also be useful for security in different places or for monitoring patients in hospital and many more applications. Here we describe a novel method of determining identity using machine learning with Microsoft Kinect. This method minimizes the fitting or overlapping error between an ellipsoid based skeleton.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.612-615
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• 2007

This research studies the Virtual Reality simulation of Newton's physics law on rigid body type of objects for physics learning. With network support, collaborative interaction is enabled so that people from different places can interact with the same set of objects in Collaborative Virtual Environment. The taxonomy of the interaction in different levels of collaboration is described as: distinct objects and same object, in which there are same object - sequentially, same object - concurrently - same attribute, and same object - concurrently - distinct attributes. The case studies are the interaction of users in two cases: destroying and creating a set of arranged rigid bodies. We identify a specific type of application for contents authoring with modeling systems integrated with real-time physics and implemented in VR system. In our application called Virtual Dollhouse, users can observe physics law while constructing a dollhouse using existing building blocks, under gravity effects.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1118-1120
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• 1993

Fuzzy logic places a considerable burden on an inference engine for applications such as control or approximate reasoning. Various neural network architectures have been proposed to deal with the computational task, and yet, maintain flexibility in the desired traits of the final system. Recently, we introduced a trainable network architecture whose nodes implement weighted Yager additive hybrid operators for fuzzy logic inference in an approximate reasoning setting. In this paper we examine the utility of such networks for control situations. We show that they are capable of learning control functions which are piece-wise monotonic in each of the variables. The learning ability is demonstrated through an example.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.66-72
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• 2023

Little attention appears to have been paid to the relevance of learning a good representation function in solving long tail tasks. Therefore, we propose a new loss function to ensure a good representation is learnt while learning to classify. We call this loss function Triplet Class-Wise Difficulty-Based (TriCDB-CE) Loss. It is a combination of the Triplet Loss and Class-wise Difficulty-Based Cross-Entropy (CDB-CE) Loss. We prove its effectiveness empirically by performing experiments on three benchmark datasets. We find improvement in accuracy after comparing with some baseline methods. For instance, in the CIFAR-10-LT, 7 percentage points (pp) increase relative to the CDB-CE Loss was recorded. There is more room for improvement on Places-LT.

• Journal of Integrative Natural Science
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• v.16 no.4
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• pp.111-122
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• 2023

Invasive species are organisms that are introduced into places outside of their natural distribution range. The global pet trade is facilitating the introduction of invasive species into new countries and areas. Among the introduced alien species, turtles are one of the most common animal groups whether lives in wetland ecosystems, such as wetlands or reservoirs. Like other countries around the world, exotic turtles is becoming a growing concern for the wetland ecosystem in South Korea. In this study, we report new reports of subspecies of Painted turtle (Chrysemys spp.): Chrysemys picta marginata, C. p. bellii and C. dorsalis, from the reservoirs in downtown Cheongju and Gwangju, South Korea. We used morphological features, such as the characteristics of the legs, plastron, and carapace, to identify the turtles. It is assumed that all turtles were artificially released into nature. Considering the increasing number of reports on the introduction of alien invasive turtles in Korean wetlands, we recommend the formulation of an immediate and systematic management plan for pet trades and organized continuous monitoring programs.