• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.61-67
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• 2021

In this paper, we propose a method of extracting and recognizing related information for research from images of the unstructured pulmonary function test papers using character detection and recognition techniques. Also, we develop a post-processing method to reduce the character recognition error rate. The proposed structuring method uses a character detection model for the pulmonary function test paper images to detect all characters in the test paper and passes the detected character image through the character recognition model to obtain a string. The obtained string is reviewed for validity using string matching and structuring is completed. We confirm that our proposed structuring system is a more efficient and stable method than the structuring method through manual work of professionals because our system's error rate is within about 1% and the processing speed per pulmonary function test paper is within 2 seconds.

• Educational Technology International
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• v.24 no.2
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• pp.203-236
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• 2023

The purpose of this study is to explore the structural relationship between COVID-19-induced sub-dimensions of Online Self-Regulated Learning (OSRL) and satisfaction in online courses conducted in the 'post-COVID-19 era,' as well as to investigate the moderating effects of situational variables such as 'course planning,' 'device type,' and 'course repetition.' To achieve this, the study constructs a measurement model with sub-dimensions of Environment Structuring, Learning Strategy, Help Seeking, and Self-Evaluation as components of OSRL. Participants in this study were selected from university students who enrolled in online courses offered by the Department of Education at University A in the metropolitan area. The research findings reveal several key insights. First, among the sub-dimensions of Online Self-Regulated Learning, Environment Structuring, Learning Strategy, and Self-Evaluation significantly influence satisfaction with online courses. Second, students' satisfaction with online courses significantly influences their intention to continue participating in such courses. Third, 'course planning' during online course hours and 'course repetition' play a moderating role in the relationship between sub-dimensions of Online Self-Regulated Learning and satisfaction. Based on the discussion of these research results, this study concludes by suggesting some future implications and challenges of online courses.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.19-26
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• 2018

This paper presents a structuring process of unstructured social network service (SNS) messages on rail services. We crawl messages about rail services posted on SNS and extract keywords indicating date and time, rail operating company, station name, direction, and rail service types from each message. Among them, the rail service types are classified by machine learning according to predefined rail service types, and the rest are extracted by regular expressions. Words are converted into vector representations using Word2Vec and a conventional Convolutional Neural Network (CNN) is used for training and classification. For performance measurement, our experimental results show a comparison with a TF-IDF and Support Vector Machine (SVM) approach. This structured information in the database and can be easily used for services for railway users.

• Informatization Policy
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• v.27 no.4
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• pp.47-66
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• 2020

The rapid development of artificial intelligence technologies such as machine learning and deep learning is expanding its impact in the public administrative and public policy sphere. This paper is an exploratory study on policy decision-making in the age of artificial intelligence to design automated configuration and operation through data analysis and algorithm development. The theoretical framework was composed of the types of policy problems according to the degree of problem structuring, and the success and failure cases were classified and analyzed to derive implications. In other words, when the problem structuring is more difficult than others, the greater the possibility of failure or side effects of decision-making using artificial intelligence. Also, concerns about the neutrality of the algorithm were presented. As a policy suggestion, a subcommittee was proposed in which experts in technical and social aspects play a professional role in establishing the AI promotion system in Korea. Although the subcommittee works independently, it suggests that it is necessary to establish governance in which the results of activities can be synthesized and integrated.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.56-62
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• 2019

Recently, research using artificial neural networks has further expanded the field of neural network optimization and automatic structuring from improving inference accuracy. The performance of the machine learning algorithm depends on how the hyperparameters are configured. Open-source hyperparameter optimization software can be an important step forward in improving the performance of machine learning algorithms. In this paper, we review open-source hyperparameter optimization softwares.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.162-167
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• 2021

The aim of this paper is to analyze the development of effective online Problem-Based Learning (PBL) and Project-Based Learning (PjBL). The collaborative PBL/PjBL become one of the hot issues with the rapid growth of online learning in the era of COVID-19. Educators try to get innovative to continue instruction without sacrificing student engagement, thus adopting an instructional model of PBL/PjBL. The PBL process involves clarifying terms, defining complex problems, brainstorming, structuring and hypothesis while PjBL includes project-planning, implementation, communicating the results of a project in a presentation and evaluations with immediate individually tailored feedback within a predetermined period. Despite the differences between online and offline learning, the benefits of learning online or offline are practically the same if enough bidirectional interactions between instructors and students are possible. We argue that online qualifications are just the same as those of offline ones in PBL/PjBL models, therefore, the standards of online/offline learning are identical since education is a two-way communication.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.529-538
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• 2021

This article aims to describe the institutional structuring strategy of independent smallholders in accelerating sustainable economic development, by taking the example of the cow-coconut integration system (SISKA) problem in Sialang Palas Village, Riau. The method used identified stakeholders related to SISKA; the stakeholder's goals and interests, farmers' social and institutional bases, and self-help farmer socio-economic networks. First, identification of various factors through strengths, weaknesses, opportunities, and threats (SWOT) analysis techniques. Second, through the Modern Political Economy analysis technique. Third, imparting knowledge and skills to the farmers and village officials through a collective learning process in utilizing natural resource waste and social resources. The results showed that the farmer management strategy in the reform era started by clustering the interests of farmers. The dynamics of structuring group relations between the chairman and members with farmers outside the group are the basis for strengthening the local ideology of independence in the future. This institutional structuring strategy that focuses on access to farm power in the village decision-making process encourages a more integrated work of farmer organizations. The analysis above shows that the independent smallholder institutional engineering through regulation, organization, and resources are determined by the farmer household economic factors and the application of the value of local wisdom.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2424-2429
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• 2003

The importance of e-Learning, which supports to study anywhere and anytime, has been pointed out for improving education. There have been various research papers on e-Learning system for educations. Most of literatures have focused on guiding the student or measuring understanding their level etc. Design method of e-Learning system has not been discussed based on structure and analysis of the class. In this paper, scheme of the class is proposed by analyzing and structuring class, then design method of e-Learning system is discussed based on it.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.56-63
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• 2021

The narrative texts of industrial accident reports help to identify accident risk factors. They relate the accident triggers to the sequence of events and the outcomes of an accident. Particularly, a set of related keywords in the context of the narrative can represent how the accident proceeded. Previous studies on text analytics for structuring accident reports have been limited to extracting individual keywords without context. We proposed a context-based analysis using a Natural Language Processing (NLP) algorithm to remedy this shortcoming. This study aims to apply Word2Vec of the NLP algorithm to extract adjacent keywords, known as word embedding, conducted by the neural network algorithm based on supervised learning. During processing, Word2Vec is conducted by adjacent keywords in narrative texts as inputs to achieve its supervised learning; keyword weights emerge as the vectors representing the degree of neighboring among keywords. Similar keyword weights mean that the keywords are closely arranged within sentences in the narrative text. Consequently, a set of keywords that have similar weights presents similar accidents. We extracted ten accident processes containing related keywords and used them to understand the risk factors determining how an accident proceeds. This information helps identify how a checklist for an accident report should be structured.

• Education of Primary School Mathematics
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• v.21 no.2
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• pp.131-150
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• 2018

The structure of a mathematics task shapes the aspects of learning of those who solve the task. This study explores the process of understandings on the statistical variability of primary school students. Students were given two problems with different degrees of structuring - a well-structured problem (WSP) and an ill-structured problem (ISP) - and discussed in a group to solve each task. The highest level of development achieved in both cases appeared to be similar. However, when given the ISP, students dynamically proposed ideas and justified the conclusion based on their hypothesis. Furthermore, all students actively participated in solving the ISP until the end whereas some students were marginalized while solving the WSP. This discrepancy results from the difference in the degrees of task structuring.