• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.31-39
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• 1998

This paper describes an electronic performance support system called HELPS(Handler Electronic Learning Performence Support) for semiconductor testing e equipment. The purpose of this system is to improve productivity of operators by providing just-in-time, on-the-job, mutimedia-based system information for operational support, training, and knowledge-based trouble shooting and repair. HELPS is composed of a operation module and a trouble shooting module. The operation module uses multimedia and hypermedia to provide the detailed and easily accessible information about equipment to users. Multimedia incorporate multiple. media forms including still and video images. animations 'texts' graphics. and audio. Hypermedia a are provided through a hierarchical information structure which offers not only specific information which is needed to perform a task to experienced operators. but detailed system guidance and information to novice operators. The trouble shooting module is composed of an integrated mutimedia-supported expert system which assists operators in trouble shooting and equipment repair. After diagnosis through the use of the expert system. multimedia advice is presented to the user in either still images with text or motion sequences with sound HELPS is evaluated in term of training time and trouble shooting and repair time. It improved productivity by saving more than 30% of the total time used without the system. This s system has the potential to improve productivity when it is used with ICAIOntellignet Computer Aided Instruction) and virtual reality.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Korean Journal of Food Science and Technology
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• v.51 no.2
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• pp.160-168
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• 2019

This study aimed to determine whether double-processed ginseng berry extract (PGBC) could improve learning and memory in an $A\hat{a}42$-induced Alzheimer's mouse model. Passive avoidance test (PAT) and Morris water-maze test (MWMT) were performed after mice were treated with PGBC, followed by acetylcholine (ACh) measurement and glial fibrillary acidic protein (GFAP) detection for brain damage. Furthermore, acetylcholinesterase (AChE) activity and choline acetyltransferase (ChAT) expression were analyzed using Ellman's and qPCR assays, respectively. Results demonstrated that PGBC contained a high amount of ginsenosides (Re, Rd, and Rg3), which are responsible for the clearance of $A{\hat{a}} 42$. They also helped to significantly improve PAT and MWMT performance in the $A{\hat{a}} 42-induced$ Alzheimer's mouse model when compared to the normal group. Interestingly, ACh and ChAT were remarkably upregulated and AChE activities were significantly inhibited, suggesting PGBC to be a palliative adjuvant for treating Alzheimer's disease. Altogether, PGBC was found to play a positive role in improving cognitive abilities. Thus, it could be a new alternative solution for alleviating Alzheimer's disease symptoms.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 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 Korean Home Economics Education Association
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• v.33 no.1
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• pp.101-127
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• 2021

The purpose of this study is to design and develop a teaching-learning process plan for process-based assessment, focusing on the unit related to life design in middle school home economics(HE: Home Economics part of 「Technology and Home Economics」), to propose a feedback plan after implementing it, and to evaluate the plan through participatory observation and interviews. The student reflection journals, teacher's class journals, participatory observation journals, interviews, and performance tasks, were collected and analyzed to provide foundational date to be utilized for feedback to students, and class improvement. The research results are as follows: First, the developed teaching-learning process plan consists of a total of 8 sessions, i.e. 2 sessions for each of the four learning themes, under the practical question of "What should I do to live the life I want?" The portfolio was composed of five evaluation topics and for evaluation, oral presentation, observational evaluation, self-assessment, and peer evaluation were considered. Second, during the class, feedback from teachers, feedback from fellow students, feedback through results, and a plan to record them were provided. Third, from the analysis of collected data including observation journals and interviews, it was apparent that the students recognized the necessity of process-based assessment after the class, and students acknowledged that through the process-based evaluation in which they are evaluated on the efforts they made and provided with feedbacks, they participated more in class, and it lead them to experience a sense of growth and a feeling that they took a step forward into their future. Teachers suggested that the class through feedback was suitable for the unit and the capacity of the class, but the difficulty they experienced in giving feedback was presented as a disadvantage. For the process-based assessment, follow-up research is needed on various ways to provide feedback on-line and off-line through changes in the perception of assessment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.43-65
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• 2010

Facing a complex environment driven by a decade, many companies are adopting new strategic frameworks such as Customer Relationship Management system to achieve sustainable profitability as well as overcome serious competition for survival. In many business areas, CRM system advanced a great deal in a matter of continuous compensating the defect and overall integration. However, pharmaceutical companies in Korea were slow to accept them for usesince they still have a tendency of holding fast to traditional way of sales and marketing based on individual networks of sales representatives. In the circumstance, this article tried to empirically address current status of CRM system as well as the effects of the system on the performance of pharmaceutical companies by applying BSC method's four perspectives, from financial, customer, learning and growth and internal process. Survey by e-mail and post to employers and employees who were working in pharma firms were undergone for the purpose. Total 113 cases among collected 140 ones were used for the statistical analysis by SPSS ver. 15 package. Reliability, Factor analysis, regression were done. This study revealed that CRM system had a significant effect on improving financial and non-financial performance of pharmaceutical companies as expected. Proposed regression model fits well and among them, CRM marketing information system shed the light on substantial impact on companies' outcome given profitability, growth and investment. Useful analytical information by CRM marketing information system appears to enable pharmaceutical firms to set up effective marketing and sales strategies, these result in favorable financial performance by enhancing values for stakeholderseventually, not to mention short-term profit and/or mid-term potential to growth. CRM system depicted its influence on not only financial performance, but also non-financial fruit of pharmaceutical companies. Further analysis for each component showed that CRM marketing information system were able to demonstrate statistically significant effect on the performance like the result of financial outcome. CRM system is believed to provide the companies with efficient way of customers managing by valuable standardized business process prompt coping with specific customers' needs. It consequently induces customer satisfaction and retentionto improve performance for long period. That is, there is a virtuous circle for creating value as the cornerstone for sustainable growth. However, the research failed to put forward to evidence to support hypothesis regarding favorable influence of CRM sales representative's records assessment system and CRM customer analysis system on the management performance. The analysis is regarded to reflect the lack of understanding of sales people and respondents between actual work duties and far-sighted goal in strategic analysis framework. Ordinary salesmen seem to dedicate short-term goal for the purpose of meeting sales target, receiving incentive bonus in a manner-of-fact style, as such, they tend to avail themselves of personal network and sales and promotional expense rather than CRM system. The study finding proposed a link between CRM information system and performance. It empirically indicated that pharmaceutical companies had been implementing CRM system as an effective strategic business framework in order for more balanced achievements based on the grounded understanding of both CRM system and integrated performance. It suggests a positive impact of supportive CRM system on firm performance, especially for pharmaceutical industry through the initial empirical evidence. Also, it brings out unmet needs for more practical system design, improvement of employees' awareness, increase of system utilization in the field. On the basis of the insight from this exploratory study, confirmatory research by more appropriate measurement tool and increased sample size should be further examined.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.151-166
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• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.129-147
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• 2019

This study aimed at exploring the influence of 'Healthy couple relationship' education on the relationship formation competencies and marriage values of high school students. To achieve the research objective, the 'Healthy couple relationship' lesson plan developed by the author was executed in two high schools for eight weeks from September 1 to November 3, 2018 from which the effects were analyzed. The results are as follows. First, the 'healthy couple relationship' education for high school students has been effective in improving their relationship performance, which is a part of the home economics curriculum. In S high school, the paired t-test of pre-/post-test comparison results showed statistically significant differences in the areas of 'communication', 'conflict resolution' and 'relationship formation performance'. For Sejong City campus-type joint curriculum group, where Wilcoxson signed-rank test was applied due to small sample size, showed that the overall scores as well as all the subsections of 'relationship formation performance' (i.e., 'communication', 'self-understanding', 'conflict resolution', and 'empathy') have improved, although not statistically significant. Second, the 'Healthy couple relationship' education for high school students had positive effects on the marriage values of high school students. In S high school, students' perception of marriage values rendered a statistically significant positive change, while in campus-type joint curriculum in Sejong City, no statistical significance was detected. In conclusion, the 'Healthy couple relationship' education can help high school students build positive values by cultivating their 'relationship formation competence', which is a part of the competencies listed in home economics curriculum, and also broaden their understanding of marriage, by acquiring knowledge and skills to build healthy couple relationships, and learning to implement the knowledge and skills in their own lives.

• Journal of agricultural medicine and community health
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• v.38 no.2
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• pp.97-107
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• 2013

Objective: This study aimed to evaluate attention, memory and executive function in patients with narcolepsy. Methods: This study included 23 narcoleptic patients whose diagnosis were confirmed by the International Classification of Sleep Disorders(ICSD) at Chonnam National University Hospital Sleep Disorders Clinic or an other hospital in Korea, from 2005 to 2008, as well as 23 normal controls. All participants were given an IQ test for Korean-Wechsler Adult Intelligence Scale and several neuropsychological function tests (the d2 test for attention function, the Rey Complex Figure Test for nonverbal memory, the Korean-California Verbal Learning Test [K-CVLT] for verbal memory, and the Wisconsin Card Sorting Test for executive function). Clinical features of narcoleptic patients, including the frequency of excessive daytime sleepiness, cataplexy, sleep paralysis and hypnagogic hallucination, were investigated by a structured clinical interview administered by a neuropsychiatist. Excessive daytime sleepiness was evaluated by the Epworth sleepiness scale. Results: Characteristic symptoms of narcolepsy observed in this study included excessive daytime sleepiness (n=23, 100.0%), cataplexy (n=19, 82.6%), hypnagogic hallucination (n=5, 21.7%) and sleep paralysis (n=12, 52.2%). In nocturnal polysomnographic findings, stage 2 sleep and REM latency were found to be significantly decreased in narcoleptic patients compared with the control group, and were accompanied by significant increases in stage 1 sleep. Narcoleptic patients had lower scores than the control group on total number, Total Number-Total Error, Concentration Performance and Fluctuation Rate on the d2 test, which measures attention. Also, there were significant differences between the performance of patient and control groups on the B list of the K-CVLT, which measures verbal memory. Conclusion: Narcoleptic patients showed decreased attention and verbal memory performance compared to the control group; however, in many areas, narcoleptic patients still demonstrated normal cognitive function.