• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.3
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• pp.129-140
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• 2017

This study aims to interpret the current landscape design of the place and landscape of memory, such as post-industrial parks and memorials that have an old, aging appearance from an aesthetic perspective. The objects of the study are large parks and open spaces that have collective memories for visitors. Visitors' aesthetic experience from these places and landscapes of memory could be explained by aesthetic concepts such as the sublime, nostalgia, and melancholy. Because these aesthetic concepts are associated with past traumas, visitors may be affected morbidly. However, due to the capability of the media to form an aesthetic experience when visitors visit a given place and landscape, visitors can autonomously adjust the distance to the place of memory and gain an aesthetic experience. The aesthetic experiences through the sublime, nostalgia, and melancholy are based on temporality and irreversibility. Temporality here refers to a characteristic of memory, and time in the place and landscape of memory and is based on the irreversibility of time, as time cannot go back. Both the place memory and the memory that is recalled from the combination with visitor's past memories and knowledge are two major factors involved in the construction of the aesthetic experience in the place and landscape of memory. The results of the present study are meaningful in that this study presents a framework for a better understanding and use of both the place memory and appreciators' memory in the design process of a place and landscape of memory and also criticizes a materialistic approach that fails to take into account the visitors' memories.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.13-20
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• 2020

One of the major issues surrounding big data is the availability of massive time-based or telemetry data. Now, the appearance of low cost capture and storage devices has become possible to get very detailed time data to be used for further analysis. Thus, we can use these time data to get more knowledge about the underlying system or to predict future events with higher accuracy. In particular, it is very important to define custom tailored contract offers for many households and businesses having smart meter records and predict the future electricity usage to protect the electricity companies from power shortage or power surplus. It is required to identify a few groups with common electricity behavior to make it worth the creation of customized contract offers. This study suggests big data transformation as a side effect and clustering technique to understand the electricity usage pattern by using the open data related to smart meter and KNIME which is an open source platform for data analytics, providing a user-friendly graphical workbench for the entire analysis process. While the big data components are not open source, they are also available for a trial if required. After importing, cleaning and transforming the smart meter big data, it is possible to interpret each meter data in terms of electricity usage behavior through a dynamic time warping method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.521-528
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• 2016

The tollbooths of a main motorway toll plaza are usually operated proactively responding to the variations of traffic demands of two-type vehicles, i.e. cars and the other (heavy) vehicles, respectively. In this vein, it is one of key elements to forecast accurate traffic volumes for the two vehicle types in advanced tollgate operation. Unfortunately, it is not easy for existing univariate short-term prediction techniques to simultaneously generate the two-vehicle-type traffic demands in literature. These practical and academic backgrounds make it one of attractive research topics in Intelligent Transportation System (ITS) forecasting area to forecast the future traffic volumes of the two-type vehicles at an acceptable level of accuracy. In order to address the shortcomings of univariate short-term prediction techniques, a Multiple In-and-Out (MIO) forecasting model to simultaneously generate the two-type traffic volumes is introduced in this article. The MIO model based on a non-parametric approach is devised under the on-line access conditions of large-scale historical data. In a feasible test with actual data, the proposed model outperformed Kalman filtering, one of a widely-used univariate models, in terms of prediction accuracy in spite of multivariate prediction scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.133-136
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• 2018

Today, the environment in which type 1 Diabetes children learn how to cope with their Diabetes is very vulnerable. Therefore, it is necessary to create an environment that can respond to changes in blood sugar level of children. The purpose of this study is to suggest game-based educational content on how to deal with changes in blood sugar level through behavioral methods for children with type 1 Diabetes. The purpose of this study is to suggest education type game contents using hybrid method which enhances efficiency in learning children 's expert knowledge. Based on the results of the interviews conducted with diabetes specialists for this study, we suggested the contents of coping with blood sugar change composed of education contents required for the children. As a result of this study, it was found that the hybrid factor was useful in learning diabetes through games. These game contents are expected to provide an environment that children with diabetes can learn more efficiently.

• Journal of Gifted/Talented Education
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• v.25 no.5
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• pp.731-747
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• 2015

The purpose of this RSP program is to enhance the invention gifted students' creative thinking and self-efficacy in studying. This program has 20 subcategories and interesting activities attracting students' attentions which are based on TRIZ's 40 principles of invention. 3-Steps to learning, which are - experiencing, recognizing, and inventing are arranged as teaching methods of RSP program. In the first step, experiencing, students are motivated and get a glimpse of the principles of invention while experiencing innovative products. In the next step, recognizing, students grasp the related scientific principles from the products. In the last step, inventing, students are given keys to solutions for problematic situations and then they create new ideas after repetitive encounters with several products made by similar principles. RSP program is different from other programs in that it has this 'inventing' step, where students can create new ideas based on related basic knowledge. In conclusion, RSP program is systematically well organized with 4 steps(purpose, contents, teaching method and evaluation) and is shown to enhance invention gifted students' creativity and self efficacy in studying. Therefore, the RSP program is shown to be a reliable and useful program, and may be used in the classes for positive results.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.219-227
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• 2019

This study aims to examine Blockchain research trend using bibliometrics-based network analysis. The data were collected from WoS, Scopus, Korea Citation Index and National science & Technology Information Service, from 2009 to 2018. As results, the number of publications has started increasing rapidly from 2017 and it showed the initial stage of formation of coauthor network. Words often used in the title of the publications were related to application development, controversy and technology development. In addition, the majority of domestic papers are in the subject of social science, while international papers tend to focus on engineering issues. The results of the temporal analysis show that Korean researchers' block chain 3.0 started in 2017 and are rapidly increasing in 2018. The number of citations was associated with publication year in a statistically signifiant way. By examining these research trends, we hope that this paper can be a useful basis for the development of blockchain. Future research is expected to reveal more clearly the knowledge structure and characteristics of blockchain around the world.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.83-90
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• 2021

In this paper, effects on industrial accident prevention based on better safety and health environment by utilizing ergonomics expert were studied. This study was mainly based on the data from 'the survey for occupational safety and health trend' conducted by Occupational Safety and Health Research Institute. The number of industries participated in the survey was 2,084. Main results of the study were as follows; 1) Only 22.9% of the industries participated in the survey utilized ergonomics expert. The rest of the industries have never had an ergonomics expert due to the reasons such as lack of knowledge for the field of ergonomics, etc. 2) Specific activities done by the industries with ergonomics expert in order to have better safety & health were 'providing work orders'(94.8%), 'providing monitoring guidelines'(85.5%), 'providing information for dangerous work'(95.8%), 'providing safety education'(96.6%), and 'other safety management'(94.1%). 3) When the odds ratio for the levels of communication and the levels of environmental stability regarding safety & health for the different groups(with experts and without experts), it was found that the group with ergonomics experts had a significant higher ORs(2.391, 95% confidence interval(1.949-2.932) and 2.128, 95% confidence interval(1.786-2.537)) respectively than those of the industries without ergonomics expert. The results suggested that ergonomics expert has been unique in most of time in terms of his/her contributions in the field of industrial safety and health.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• Journal of Animal Science and Technology
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• v.64 no.4
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• pp.770-781
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• 2022

Meteorological disasters caused by climate change like heat, cold waves, and unusually long rainy seasons affect the milk productivity of cows. Studies have been conducted on how milk productivity and milk compositions change due to heat stress (HS). However, the estimation of losses in milk production due to HS and hereby environmental impacts of greenhouse gas (GHG) emissions are yet to be evaluated in Korean dairy farms. Dairy milk production and milk compositions data from March to October 2018, provided by the Korea Dairy Committee (KDC), were used to compare regional milk production with the temperature-humidity index (THI). Raw data for the daily temperature and relative humidity in 2018 were obtained from the Korea Meteorological Administration (KMA). This data was used to calculate the THI and the difference between the maximum and minimum temperature changing rate, as the average daily temperature range, to show the extent to which the temperature gap can affect milk productivity. The amount of milk was calculated based on the price of 926 won/kg from KDC. The results showed that the average milk production rate was the highest within the THI range 60-73 in three regions in May: Chulwon (northern region), Hwasung (central region), and Gunwi (southern region). The average milk production decreased by 4.96 ± 1.48% in northern region, 7.12 ± 2.36% in central region, and 7.94 ± 2.57% in southern region from June to August, which had a THI range of 73 or more, when compared to May. Based on the results, the level of THI should be maintained like May. If so, the farmers can earn a profit of 9,128,730 won/farm in northern region, 9,967,880 won/farm in central region, and 12,245,300 won/farm in southern region. Additionally, the average number of cows raised can be reduced by 2.41 ± 0.35 heads/farm, thereby reducing GHG emissions by 29.61 ± 4.36 kg CO₂eq/day on average. Overall, the conclusion suggests that maintaining environmental conditions in the summer that are similar to those in May is necessary. This knowledge can be used for basic research to persuade farmers to change farm facilities to increase the economic benefits and improve animal welfare.