• Science of Emotion and Sensibility
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• v.22 no.2
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• pp.59-69
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• 2019

The present study explored consumer's perception and preference on providing information of fashion products by using QR code and suggested the possibility for consumer-to-consumer and consumer-to-company connection. A survey was conducted on males and females in their 20s-a population among whom the rate of smart phone penetration is higher than in any other age group and who tend to exchange information online. The results showed that consumers are dissatisfied with the amount of information, terms of instructions, and ambiguous washing symbols currently provided. Therefore, the study identified the need for better methods of providing information and found that QR code, which is able to deliver high-quality information on fashion products, can be an efficient alternative. Moreover, respondents felt the need for detailed washing instructions, information on handling, and functionality of material on high-involvement fashion products such as outdoor, padding, suit, and underwear worn next to the skin. They also desire styling tips or purchasing information such as SNS OOTD (Outfit Of The Day) utilizing the product, other products that may go well with the one purchased, and similar products on casual wear and coat used on a daily basis. Therefore, QR code used as a link to information web pages or a social network can help consumers to satisfy information needs and to use the products effectively.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.1
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• pp.37-43
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• 2019

This research studied production of lightweight filling production for sink hole restoration utilizing various industrial by-products(2kinds of fly ash, petro-cokes CFBC ash, blast furnace slag fine particle). For this purpose, the mixed raw material properties(compressive strength) behaviors according to the blending ratio of industrial by-products were examined by applying the experimental design method and statistical analysis was performed using the commercial program MINITAB. Compressive strengths of industrial by-products were strongly dependent on blast furnace slag powder. Compressive strength(3days aging) was 3~11MPa depending on the amount of blast furnace slag powder used. The use of CFBC fly ash was evaluated to have the least effect on compressive strength. In addition, the compressive strength and the coefficient of permeability were measured by preparing foamed concrete for the experimental batch 1 condition in the mixture experimental design. In this case, the bulk density is 0.9 to 1.0, the apparent porosity is 30 to 50%, the compressive strength(3days old) is 1 to 2MPa, and the permeability coefficient is $10^{-2}$ to $10^{-3}cm/sec$.

• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.1-6
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• 2019

Neural networks have been used to predict the direction of stock index movement from past data. The conventional research that predicts the upward or downward movement of the stock index predicts a rise or fall even with small changes in the index. It is highly likely that losses will occur when trading ETFs by use of the prediction. In this paper, a neural network model that predicts the movement direction of the daily KOrea composite Stock Price Index (KOSPI) to reduce ETF trading losses and earn more than a certain amount per trading is presented. The proposed model has outputs that represent rising (change rate in index ${\geq}{\alpha}$), falling (change rate ${\leq}-{\alpha}$) and neutral ($-{\alpha}$ change rate < ${\alpha}$). If the forecast is rising, buy the Leveraged Exchange Traded Fund (ETF); if it is falling, buy the inverse ETF. The hit ratio (HR) of PNN1 implemented in this paper is 0.720 and 0.616 in the learning and the evaluation respectively. ETF trading yields a yield of 8.386 to 16.324 %. The proposed models show the better ETF trading success rate and yield than the neural network models predicting KOSPI.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.184-193
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• 2021

The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

• Journal of Soil and Groundwater Environment
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• v.27 no.spc
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• pp.99-112
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• 2022

From early 2000, many researchers in the groundwater and soil environment remediation project tried to calculate the pollution level and pollution remediation cost and reflect it in the design. In addition, by identifying the movement characteristics of oil pollutants in the underground environment, many researchers tried to derive design factors necessary for pollution purification. However, although the test should be conducted in an area contaminated with oil, the toxicity and risk are too great for testing by deliberately leaking pollutants that are harmful to the human body. And as oil-contaminated areas are promoted by military units such as returned US military bases, there is a limit to access by the general public. In addition, since the indoor simulation test and the field application test have been carried out separately from each other, it was difficult to compare and review various simulation tests Therefore, in this study, PITT (Partitioning Interwell Tracer Test) and analysis methods were specifically presented through actual tests so that field workers could easily use them with the help of the military base and the Korea Rural Community Corporation Soil Environment Restoration Team. However, in order to directly reflect the distribution tracer test results in the pollution remediation design, it is necessary to reduce the analysis errors by comparing the analysis results of the existing soil pollution survey, physical exploration, and numerical modeling. In addition, it is judged to be cautious in the analysis because errors can easily occur due to various factors such as the type of oil at the polluted site, the hydraulic conductivity of the aquifer, and the skill of the researcher.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.169-174
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• 2023

Currently, overall power usage is also increasing as power demand such as homes, offices, and factories increases. The increase in power use also raised interest in standby power as a change in awareness of energy saving appeared. Home and office devices are consuming power even in standby conditions. Accordingly, there is a growing need to reduce standby power, and it aims to have standby power of 1W or less. An intelligent outlet uses a near-field wireless network to connect to a home network and cut or reduce standby power of a lamp or appliance connected to an outlet. This research aims to develop a monitoring system and an intelligent outlet that can remotely monitor the amount of electricity used in a lighting lamp or a home appliance connected to an outlet using a short-range wireless network (Zigbee). Also, The intelligent outlet and monitoring system developed makes it possible for a user to easily cut off standby power by using a portable device. Intelligent outlets will not only reduce standby power but also be applicable to fire prevention systems. Devices that cut off standby power include intelligent outlets and standby power cutoff switches, so they will prevent short circuits and fires.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.37-51
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• 2010

In this paper, we discuss the program implementation and system optimization for the effective transfer of huge amount of data. In VLBI which is observing the celestial bodies by using radio telescope hundreds thousands km apart, it is necessary for each VLBI observatory to transfer up to terabytes of observed data. For this reason, e-VLBI research based on advanced network is being actively carried out for the transfer of data efficiently. Following this trend, in this paper, we discuss design & implementation of system for the high speed Gbps data transfer rates. As a data transfer protocol, we use UDP for designing data transmission program with much higher speeds than currently available via VTP(VLBI Transport Protocol). Tsunami-UDP algorithms is applied to implementing data transfer program so that transmission performance could be maximize, also we make it possible to transfer observed data more fast and reliable through optimization of computer systems in each VLBI statopm.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.777-799
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• 2022

This study examined the latest EU regulatory strengthening trends for refrigerant gases with very large global warming potential (GWP) and derived implications for carbon neutrality. The European Commission recently unveiled an amendment that significantly strengthens the F-gas Regulation. This study presented the meaning of the main contents related to refrigerants in the amendment by comparing them with the current regulations. The main contents of the amendment include drastically reducing the maximum amount of HFCs that can be placed on the market, strengthening regulations related to HFCs allocation, adding products and equipment that use high GWP refrigerants, adding regulated F-gas and updating the GWP of existing gases, and other stricter regulatory designs. This movement of the EU will affect the policy stance of advanced countries such as the United States and Japan, and Korea's policy will also be further strengthened. Therefore, it will be inevitable for related industries to change to next-generation refrigerant gas. Meanwhile, this study also analyzed the latest policy trends related to per- and polyfluoralkyl substances (PFAS) regulation, which were not noted in previsou studies on refrigerants and F-gas. If PFAS's registration of REACH restricted substances, which are being promoted by five European countries, is made, it will have a very big impact on the industry regarding refrigerant gas. In addition, it will be inevitable to thoroughly review each country's greenhouse gas reduction strategies related to F-gas materials, including refrigerants.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.331-341
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• 2023

When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.