• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.429-433
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• 2004

Most utiltity systems are subject to frequent changes, often due to increased loads and demand to up-grade quality of service provided. Urban renewal, expressway construction and suburban growth have also caused significant changes in urban utility distribution systems. Recently, it is required that a guideline for planning of a complete system, the reasonable design and construction methods for the efficient installation common utility tunnels must be estabilished. It prompts drastic measures to guard cities and their inhabitants against the horror of massive fires in the future. Preparedness holds the key to safety.

• The Mathematical Education
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• v.53 no.1
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• pp.147-162
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• 2014

The purpose of this study was to investigate the nature of pre-service elementary teachers' metaphors on mathematics textbooks. Their metaphors describe individual and collective patterns of thinking and action on mathematics teaching and learning. To analyze their metaphors, qualitative analysis method based on Lakoff and Johnson's theory of metaphor (1980) was adopted. Metaphors on mathematics textbooks were elicited from 161 pre-service elementary school teachers through writing prompts. The writing prompt responses revealed three types and thirteen categories: As Type I, there were (1) 'Principles', (2) 'Summary', (3) 'Manual', (4) 'Encyclopedia', (5) 'Code', (6) 'Guidelines', and (7) 'Example'. As TypeII, there were (9) 'Assistant', (10) 'Friend', (11) 'Scale', and (12) 'Ongoing'. As TypeIII, there was (13) 'Trap'. Among these categories, 'Guidelines', 'Assistant', and 'Ongoing' were the most frequently revealed. These results indicate that the relations of mathematics curriculum, textbooks, and classrooms are not a unilateral way but should communicate with each other.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.255-265
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• 2022

Educational programs for students with intellectual disabilities have undergone drastic changes in pursuit of the general curriculum. Accordingly, teachers in various fields, including mathematics, strive to find effective methods that enhance learning. The objective of this systematic review is to examine the field of teaching mathematics to students with intellectual disabilities to investigate relevant effective teaching strategies and required teaching skills. To achieve this goal, studies published during the period 2018-2021 were reviewed. Findings indicate the inclusion of nine studies that met the inclusion criteria out of 55 studies. The included studies found that the system of least prompts (SLP) in conjunction with feedback and error correction, and schema-based instruction are generally the most effective strategies in teaching mathematical skills to students with intellectual disabilities. Addition is the most targeted skill, followed by subtraction and algebra problem solving. The least targeted skills are multiplication, recognition of geometric shapes, calculating price after discount, rapid recognition of numbers, and rapid problem solving. The paper provides recommendations and suggests venues of future research.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.154-163
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• 2023

With the rapid development of AI technology, ChatGPT and other AI content creation tools are becoming common, and users are becoming curious and adopting them. These tools, unlike search engines, generate results based on user prompts, which puts them at risk of inaccuracy or plagiarism. This allows unethical users to create inappropriate content and poses greater educational and corporate data security concerns. AI content detection is needed and AI-generated text needs to be identified to address misinformation and trust issues. Along with the positive use of AI tools, monitoring and regulation of their ethical use is essential. When detecting content created by AI with an AI content detection tool, it can be used efficiently by using the appropriate tool depending on the usage environment and purpose. In this paper, we collect data on AI content detection tools and compare and analyze the functions and characteristics of AI content detection tools to help meet these needs.

• ETRI Journal
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• v.46 no.1
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• pp.106-117
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• 2024

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and introduce a new metric, pass-ratio@n, which captures the granularity of accuracy according to the pass rate of test cases. The framework is intended to be fully automatic to handle the repetitive work involved in generating prompts, conducting inferences, and executing the generated codes. A preliminary evaluation focusing on the prompt detail, problem publication date, and difficulty level demonstrates the successful integration of our framework with the LeetCode coding platform and highlights the applicability of the pass-ratio@n metric.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.447-456
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• 2021

This study analyzed 28 domestic and foreign studies related Prompts for Restructuring Oral Muscular Phonetic Targets treatment techniques from 1984 to 2020 to prepare basic data for the development of PROMPT intervention programs and examination tools. According to the analysis, continuous research has been conducted since 1984 when the prompt study was first started, and the method of research was 16 intervention studies, with the highest number of speech disorders, and the target age being 3 to 5 years old, the most frequently conducted for infancy. The treatment was the most frequent in the 16th sessions, and the activities were based on the Motor Speech Hierarchy(MSH), except for the subjects of the non-verbal autism spectrum disorder. According to the analysis of the dependent variables, 'speech production' was the most common, followed by 'speech motor control', 'articulation', and 'speech intelligibility' were highest. Combined with all these studies, it suggests that PROMPT, which are directly useful for exercise spoken word production, are effectively being used outside the country and that it is necessary to develop a PROMPT program that can be applied domestically, in Korea.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.195-204
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• 2023

In this study, prompt engineering that improves prompts was explored to improve the performance of teaching and learning materials recommendations using generative artificial intelligence such as GPT and Stable Diffusion. Picture materials were used as the types of teaching and learning materials. To explore the impact of the prompt composition, a Zero-Shot prompt, a prompt containing learning target grade information, a prompt containing learning goals, and a prompt containing both learning target grades and learning goals were designed to collect responses. The collected responses were embedded using Sentence Transformers, dimensionalized to t-SNE, and visualized, and then the relationship between prompts and responses was explored. In addition, each response was clustered using the k-means clustering algorithm, then the adjacent value of the widest cluster was selected as a representative value, imaged using Stable Diffusion, and evaluated by 30 elementary school teachers according to the criteria for evaluating teaching and learning materials. Thirty teachers judged that three of the four picture materials recommended were of educational value, and two of them could be used for actual classes. The prompt that recommended the most valuable picture material appeared as a prompt containing both the target grade and the learning goal.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.65-74
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• 2024

Objective : This study assessed ChatGPT, an artificial intelligence system based on a large language model, for its ability to pass the National Korean Occupational Therapy Licensure Examination (NKOTLE). Methods : Using NKOTLE questions from 2018 to 2022, provided by the Korea Health and Medical Personnel Examination Institute, this study employed English prompts to determine the accuracy of ChatGPT in providing correct answers. Two researchers independently conducted the entire process, and the average accuracy of both researchers was used to determine whether ChatGPT passed over the 5-year period. The degree of agreement between ChatGPT answers of the two researchers was assessed. Results : ChatGPT passed the 2020 examination but failed to pass the other 4 years' examination. Specifically, its accuracy in questions related to medical regulations ranged from 25% to 57%, whereas its accuracy in other questions exceeded 60%. ChatGPT exhibited a strong agreement between researchers, except for medical regulation questions, and this agreement was significantly correlated with accuracy. Conclusion : There are still limitations to the application of ChatGPT to answer questions influenced by language or culture. Future studies should explore its potential as an educational tool for students majoring in occupational therapy through optimized prompts and continuous learning from the data.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.92-101
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• 2015

As one type of power quality (PQ) disturbance sources, high-speed rail (HSR) can have major impacts on the power supply grid. Providing timely and accurate warning information for PQ problems of HSR is important for the safe and stable operation of traction power supply systems and the power supply grid. This study proposes a novel warning approach to identify PQ problems and provide warning prompts based on the monitored data of HSR. To embody the displacement and status change of monitored data, multi-features of different sliding windows are computed. To reflect the relative importance degree of these features in the overall evaluation, an analytic hierarchy process (AHP) is used to analyse the weights of multi-features. Finally, a multi-features similarity algorithm is applied to analyse the difference between monitored data and the reference data of HSR, and PQ warning results based on dynamic thresholds can be analysed to quantify its severity. Cases studies demonstrate that the proposed approach is effective and feasible, and it has now been applied to an actual PQ monitoring platform.

• English Language & Literature Teaching
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• v.17 no.2
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• pp.19-37
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• 2011

This study examines a Korean elementary school EFL teacher's practice of teacher-based assessment (TBA), a subject which has been little researched despite the authorities' strong call for its implementation. The classroom interactions for TBA were observed and audio-recorded in eight fifth-grade classes between March and June 2010. Additionally, the teacher and students were interviewed in a semi-structured way. The results showed that the teacher used three types of TBA: assessment of individual students on different topics, assessment of the entire class on the same topic, and assessment of individual students on the same topic. Due mainly to time constraints during class time and classroom management issues, the teacher preferred implementing the first two types of TBA. During the practice of the types, the teacher provided prompts or posed questions in ways that elicited responses which were short in length and easy. Although the third type of TBA was perceived by both the teacher and students as helping students enhance their EFL proficiency and was the most favored by the students, it was viewed by the teacher as having the potential of causing classroom management difficulties. Based on the findings, a number of implications are suggested.