• Journal of Korean Elementary Science Education
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• v.35 no.1
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• pp.98-110
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• 2016

The purpose of this study is to identify pre-service elementary school teachers' difficulties and needs in the science class utilizing smart technologies. The participants were nine pre-service elementary teachers who had practical training at an elementary school and took classes related to technology, pedagogy, and science knowledge. The data was collected through semi-constructed and in-depth interviews. The documents such as participants' guidance plans, daily records produced in teaching practice was collected and analyzed. The results of the research are as follow: Pre-service teachers have usually used the technology as a secondary transfer media to convey the knowledge. We found that the pre-service elementary teachers had 15 difficulties in the science class utilizing smart technologies. In addition, they needed a class to focus more on teaching them by integrating technology knowledge, pedagogy knowledge, and science knowledge, and by sharing a real case of science class utilizing smart technologies.

• Journal of Korean Elementary Science Education
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• v.40 no.2
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• pp.162-174
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• 2021

The purpose of this study was to investigate the types of questions raised by pre-service elementary teachers when planning a science class utilizing smart technology and the characteristics of their lesson plans. For this purpose, lesson plans and questions written by the 96 pre-service teachers were collected. The results of this study can be summarized as follows: (1) Pre-service teachers used simulation apps, information offering apps, clicker evaluation apps, astronomical observation apps. Simulation apps and clicker evaluation apps were used the most in the introduction stage of the class, simulation apps in the development stage, and clicker evaluation apps in the finishing stage. (2) In the lesson plans, the activities that elementary school students use smart technology showed more than those used by teachers, and its characteristics were more prominent in the development stage of the class. (3) As for the content type of smart technology, experience type was the highest, followed by tool type and resource type. In comparison, there were relatively few interaction support types and learning opportunity extensions. (4) There were many cases in which pre-service teachers replaced elementary school students with virtual experiences using experience type instead of providing opportunities to experiment or experience directly. (5) Pre-service teachers asked various questions while planning science class utilizing smart technology, and a total of 25 question types appeared in 7 categories.

• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.99-107
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• 2018

This study started from the public interest purpose to help accessibility for the information acquisition of the vulnerable groups due to visual difficulties such as the elderly and the visually impaired. In this study, the server resources are minimized and implemented in most of the user smart phones. In addition, we implement a method to gather necessary information by collecting only pattern information by utilizing crawl & clipping without having to visit the site of the information of the various sites having the data necessary for the user, and to have it in the server. Especially, we applied the TTS(Text-To-Speech) service composed of smart phone apps and tried to develop a unified customized information collection service based on voice-based information collection method.

• Journal of Korean Elementary Science Education
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• v.39 no.1
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• pp.84-99
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• 2020

The purpose of this study is to develop a STEAM program using technological pedagogical and content knowledge (TPACK) model to effectively utilize technology to solve the difficulties in the teaching of 'structure and function of our body' unit in the primary science curriculum and to confirm the effect on the academic achievement, creative problem solving ability and scientific interests of elementary students. The program was developed as the STEAM program of the 8th class by utilizing the construction knowledge of the TPACK model. The developed program was applied to 29 experimental group students in 5th grade. And the textbook-oriented circulatory system learning program was applied to 29 5th graders in the same school. As a result of the application of the program, the experimental group showed significant improvement over the comparison group in its creative problem solving ability and scientific interests, and the satisfaction of the class was also high. This caused a positive effect on students because the process of self-directing information about the circulatory system using smart devices, making outputs creatively using 3D printers, and presenting them through role play using produced outputs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1720-1728
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• 2022

The industrial 4.0 era has been opened with the development of artificial intelligence technology, and the realization of smart farms incorporating ICT technology is receiving great attention in the livestock industry. Among them, the quality management technology of livestock products and livestock operations incorporating computer vision-based artificial intelligence technology represent key technologies. However, the insufficient number of livestock image data for artificial intelligence model training and the severely unbalanced ratio of labels for recognizing a specific defective state are major obstacles to the related research and technology development. To overcome these problems, in this study, combining oversampling and adversarial case generation techniques is proposed as a method necessary to effectively utilizing small data labels for successful defect detection. In addition, experiments comparing performance and time cost of the applicable techniques were conducted. Through experiments, we confirm the validity of the proposed methods and draw utilization strategies from the study results.

• Smart Structures and Systems
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• v.21 no.4
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• pp.435-448
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• 2018

This paper reports the development of a theoretically rigorous method for permanent way engineers to assess the condition of railway ballast under a concrete sleeper with the potential to be extended to a smart system for long-term health monitoring of railway ballast. Owing to the uncertainties induced by the problems of modeling error and measurement noise, the Bayesian approach was followed in the development. After the selection of the most plausible model class for describing the damage status of the rail-sleeper-ballast system, Bayesian model updating is adopted to calculate the posterior PDF of the ballast stiffness at various regions under the sleeper. An obvious drop in ballast stiffness at a region under the sleeper is an evidence of ballast damage. In model updating, the model that can minimize the discrepancy between the measured and model-predicted modal parameters can be considered as the most probable model for calculating the posterior PDF under the Bayesian framework. To address the problems of non-uniqueness and local minima in the model updating process, a two-stage hybrid optimization method was developed. The modified evolutionary algorithm was developed in the first stage to identify the important regions in the parameter space and resulting in a set of initial trials for deterministic optimization to locate all most probable models in the second stage. The proposed methodology was numerically and experimentally verified. Using the identified model, a series of comprehensive numerical case studies was carried out to investigate the effects of data quantity and quality on the results of ballast damage detection. Difficulties to be overcome before the proposed method can be extended to a long-term ballast monitoring system are discussed in the conclusion.