• Informatization Policy
• /
• v.26 no.4
• /
• pp.85-106
• /
• 2019

Recently, there have been increasing cases of collective petitions filed in the electronic petitions system. However, there is no efficient management system, raising concerns on side effects such as increased administrative workload and mass production of social conflicts. Aimed at suggesting a methodology for estimating electronic collective petitions using anomaly detection and corpus linguistics-based content analysis, this study conducted the followings: i) a theoretical review of the concept of collective petitions, ii) estimation of electronic collective petitions using anomaly detection based on nonparametric unsupervised learning, iii) a content similarity analysis on petitions using n-gram cosine angle distance, and iv) a case study on the Voice of Citizens of Changwon City, through which the utility of the proposed methodology, policy implications and future tasks were reviewed.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.177-190
• /
• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of The Korean Association For Science Education
• /
• v.42 no.3
• /
• pp.325-340
• /
• 2022

This study attempts to analyze the causes of low affective achievement of elementary, middle, and high school students in Korea in science. To this end, a total of 27 students, three to four students per grade, were interviewed by grade from the fourth grade of elementary school to the first grade of high school, and a total of nine teachers were interviewed by school level. In the interview, related questions were asked in five sub-areas of the 'Indicators of Positive Experiences about Science': 'Science Academic Emotion', 'Science-Related Self-Concept', 'Science Learning Motivation', 'Science-Related Career Aspiration', and 'Science-Related Attitude'. Interview contents were recorded, transcribed, and categorized. As a result of examining the causes of low science academic emotion, it was found that students experienced negative emotions when experiments are not carried out properly, scientific theories and terms are difficult, and recording the inquiry results is burdensome. In addition, students responded that science-related self-concept changed negatively due to poor science grades, difficult scientific terms, and a large amount of learning. The reasons for the decline in science learning motivation were the lack of awareness of relationship between science class content and daily life, difficulty in science class content, poor science grades, and lack of relevance to one's interest or career path. The main reason for the decline in science-related career aspirations was that they feel their career path was not related to science, and due to poor science performance. Science-related attitudes changed negatively due to difficulties in science classes or negative feelings about science classes, and high school students recognized the ambivalence of science on society. Based on the results of the interview, support for experiments and basic science education, improvement of elementary school supplementary textbook 'experiment & observation', development of teaching and learning materials, and provision of science-related career information were proposed.

• Journal of Service Research and Studies
• /
• v.13 no.2
• /
• pp.99-113
• /
• 2023

In a customer-based industry, customer retention is the competitiveness of a company, and improving customer retention improves the competitiveness of the company. Therefore, accurate prediction and management of potential dormant customers is paramount to increasing the competitiveness of the enterprise. In particular, there are numerous competitors in the domestic card industry, and the government is introducing an automatic closing system for dormant card management. As a result of these social changes, the card industry must focus on better predicting and managing potential dormant cards, and better predicting dormant customers is emerging as an important challenge. In this study, the Recurrent Neural Network (RNN) methodology was used to predict potential dormant customers in the card industry, and in particular, Long-Short Term Memory (LSTM) was used to efficiently learn data for a long time. In addition, to redefine the variables needed to predict dormant customers in the card industry, Unified Theory of Technology (UTAUT), an integrated technology acceptance theory, was applied to redefine and group the variables used in the model. As a result, stable model accuracy and F-1 score were obtained, and Hit-Ratio proved that models using LSTM can produce stable results compared to other algorithms. It was also found that there was no moderating effect of demographic information that could occur in UTAUT, which was pointed out in previous studies. Therefore, among variable selection models using UTAUT, dormant customer prediction models using LSTM are proven to have non-biased stable results. This study revealed that there may be academic contributions to the prediction of dormant customers using LSTM algorithms that can learn well from previously untried time series data. In addition, it is a good example to show that it is possible to respond to customers who are preemptively dormant in terms of customer management because it is predicted at a time difference with the actual dormant capture, and it is expected to contribute greatly to the industry.

• Journal of the Korean Society for Library and Information Science
• /
• v.50 no.3
• /
• pp.293-308
• /
• 2016

Many universities are offering some of their offline courses for anyone to learn free online as an MOOC format. University libraries In response to changing university conditions, foreign university libraries are struggling to redefine their roles and provide new services. This study aimed to find the trends and models to support MOOCs in foreign libraries and Library and information science domain by conducting a systematic review of studies on foreign library and information journals which have been published from 2012 to 2015. A total of 34 out of 348 studies were included in the final analysis. This study also aimed to present the limits and the future models of MOOC support direction. The relevant articles could be identified, two criteria: 24 MOOCs studies relating to Libraries and 10 MOOCs studies related to LIS. The selected articles were summarized and analyzed yearly. The study identifies elements of library MOOC support models in 5 areas including MOOC design (copyright clearance and consulting, content licensing, open content), production support (course production, video editing, librarian MOOC production), management support (instructional design and content creation, students support), evaluation (MOOC data collection, analysis), reuse (MOOC metadata management, archive structure). Based on these findings, this study suggested the models of library MOOC support and set the theoretical fundamentals.

• Journal of Digital Convergence
• /
• v.13 no.8
• /
• pp.465-472
• /
• 2015

The virtual reality technology is currently used classifying functional types such as the observation operation type, the experimental activity type, the learning information type, the field problem-solving type, and other different types, based on the media's characteristics implementing 3D form of multi-sensory information. Using Virtual Reality, the restoration of the 'Doksu Palace' has been grafted onto J. Keller's ARCS model, suggesting a field restoration concept that reenacts the lives of the people that had been in the field with the cultural heritage and history based on a scenario based scene direction. This paper also summarizes 3 different types of implementation of the field restoration assorting multi-scene direction. Certain limitations exist, due to the fact that a completed prototype hasn't been suggested and that a detailed notion of the housing and 3D audio connection has been omitted.

• Archives of design research
• /
• v.13 no.1
• /
• pp.157-166
• /
• 2000

Since the cognitive science developed as a brandl of academic researdl, studies on human brains have flourished. Emotional features have been centered on the field of design, and the development of the design process has been diversified that makes use of the factors. The purpose of this study is to reflect the current trend and to convert the results into a method for designing. The researdl is based on the mind map techniques which spread like a trendy fashion, and tries to supply a theoretical explanation of how to overcome the fixed idea. Recognizing the importance of learned information in approaching a problem, I regarded the roles of left and right brain as analogue and digital images interpreting them by freely crossing language(digital images) and visual thought (analogue images), using mapping tedlniques. I pursued the research goal of the techniques focusing on the idea of using mapping. As a result of this. I established a logic system [figure 8] in that a proposition which starts as a problem introduction goes on until a problem solution, which is visualized with concept presentation, using a brainstorming technique. According to the suggested concept. I concluded that idea proliferation as a design demand can be solved by applying mapping techniques like one shown in figure 12.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.6A
• /
• pp.799-808
• /
• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.

• Journal of Science Education
• /
• v.44 no.2
• /
• pp.183-196
• /
• 2020

This study explores the effects of STEAM program using Arduino on preservice science teachers toward their STEAM core competencies. The STEAM program using Arduino consists of four stages: presentation of situation, creative design, emotional touch, and evaluation. The preservice science teachers learned the theoretical backgrounds of STEAM and Arduino. Then, they were given the chance to think about an environmental issue, which is fine dust. The preservice teachers designed an air cleaner and a fine dust measuring instrument using Arduino. The preservice science teachers also produced the air cleaner and the measuring instrument using Arduino. They measured the level of fine dust in the classroom before and after the use of the air cleaner. That is, the preservice teachers experienced each stage of STEAM: seriousness of fine dust, design and production of the measuring instrument of fine dust and air cleaner, and evaluation of the effectiveness of air cleaner. Further, they reflected on their experiences of STEAM program using Arduino. The results indicate that these preservice science teachers statistically improved communication competency, problem-solving competency, gathering information competency, logical analytical thinking competency, and creativity competency. However, there were no statistical improvements on teamwork competency and self-development competency. This study suggests that experiencing STEAM program using Arduino is valuable for the preservice science teachers to develop STEAM core competencies and further implement STEAM program their science classes in the future.

• Spatial Information Research
• /
• v.1 no.1
• /
• pp.73-87
• /
• 1993

This paper reviews the topic of GIS, the academic setting of GIS, GIS model curricula and the possibility GIS education in Korea. The topics which might be included in a science of geographic information consist of data collection and measurement, data capture, spatial statistics, data modeling and theories of spatial data, data structures, algorithms and processes, display, analytical tools, institutional, managerial and ethical issues. The problems in teaching a course on GIS in higher education are reviewed. Because of their technological, integrative, and rapidly changing nature, GIS pose major challenges to their education system which it is ill equipped to meet. In higher education a number of initiatives have been taken to provide education about and training with, GIS. The possible GIS curricula are suggested. These curricula are divided into 3 major sections, relating GIS context, technical issues and application issues. The prospects of GIS appears lo depend largely upon the future cooperation of academia, government, and industry