• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Korea Science and Art Forum
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• v.37 no.1
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• pp.87-97
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• 2019

The study began in recent years with the aim of grasping the nation's medical status following the fast-growing trend of international medical tourism and attracting foreign patients, among other things, Busan, which ranks second in attracting foreign patients after the nation's capital, Seoul, has been highly active in the past eight years, with foreign patients rising by about 426 percent, and Russian patients entering the sea. In addition, Gimhae and Changwon, the Busan-based Gyeongsangnam-do region, ranked first and second in number of foreign residents, and are inhabited by a variety of foreign workers. Medical institutions, such as hospitals, should be able to find directions within hospitals. It is also a space where information in various languages, including Korean, English, Chinese, or Russian, must be delivered in a single medium. Based on this research, the purpose of this research is to provide converged information that helps foreigners who are not familiar with Korean language easily understand the proposed recognition system when visiting hospitals. Therefore, this paper is applied to a multi-language survey of six medical institutions (A, B, C, D, E, F) at the university hospital in Busan, and 10 medical institutions (R, J) in Gimhae, South Gyeongsang Province with high foreign residents. Research results and contents are as follows. First, the results of analyzing the design of the sinusoidal system show that the font uses colorless Gothic fonts, arrows, and pictograms to introduce the design of a typical hospital sign system. Second, the results of the multi-lingual situation were found to have only two languages in the system, such as Korean and English, and to have four languages, including Korean, English, Chinese, and Russian, according to their geographical location. However, it was judged that most medical institutions currently have only two languages (Korean, English) that may cause some discomfort in terms of language for foreign patients in non-English speaking countries. Based on these findings, it is necessary to propose designs that are considered by Koreans as well as foreign users in the use of multilingual hospital sign systems.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.3
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• pp.375-388
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• 2019

Accurate evaluation of sea-to-air $CO_2$ flux and its variability is crucial information to the understanding of global carbon cycle and the prediction of atmospheric $CO_2$ concentration. $fCO_2$ observations are sparse in space and time in the East Sea. In this study, we derived high resolution time series of surface $fCO_2$ values in the southwest East Sea, by feeding sea surface temperature (SST), salinity (SSS), chlorophyll-a (CHL), and mixed layer depth (MLD) values, from either satellite-observations or numerical model outputs, to three machine learning models. The root mean square error of the best performing model, a Random Forest (RF) model, was $7.1{\mu}atm$. Important parameters in predicting $fCO_2$ in the RF model were SST and SSS along with time information; CHL and MLD were much less important than the other parameters. The net $CO_2$ flux in the southwest East Sea, calculated from the $fCO_2$ predicted by the RF model, was $-0.76{\pm}1.15mol\;m^{-2}yr^{-1}$, close to the lower bound of the previous estimates in the range of $-0.66{\sim}-2.47mol\;m^{-2}yr^{-1}$. The time series of $fCO_2$ predicted by the RF model showed a significant variation even in a short time interval of a week. For accurate evaluation of the $CO_2$ flux in the Ulleung Basin, it is necessary to conduct high resolution in situ observations in spring when $fCO_2$ changes rapidly.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Korea Science and Art Forum
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• v.37 no.4
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• pp.297-308
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• 2019

Air pollution due to the fine dust level updating every day, and the problem of indoor air pollution due to ventilation difficulties and indoor discharge pollutants is also serious. In order to improve the indoor air quality, the air purification effect using the plants is prominent. In this study was started to investigated the living environment of modern people, the risk of indoor air pollution and the improvement function of plants, and to activate plant application. The purpose of this study is to analyze the main functions and design status of domestic and overseas plant - related applications, and to understand the actual use of modern plant applications and to help them learn more convenient plant - related knowledge. Therefore, this paper attempted to establish a basis for suggesting a new plant application by conducting a survey on the health effects of indoor air pollution and user awareness of plant - related applications. The results and contents of the study are as follows. First, as a theoretical review, indoor air pollution is more dangerous to modern people who have a high proportion of indoor living time and adversely affects their health. In order to solve such a problem, it has been shown that air conditioning and stress reduction can be effectively achieved by placing plants in the indoor space. Second, the analysis of the previous study shows the risk of indoor air pollution and its adverse effects on health. In addition, I have been able to find some researches related to the improvement of the indoor air by using the air purifying plants, and I can see the improvement of the user's behavior through the development or improvement of the application. Third, as a result of the survey on the status of domestic and overseas plant application, the main function of the application having high installation number was watering notification, provision of basic information of plants, and most of the functions were plant discerment through cameras. Fourth, most of the survey respondents have either raised or raised plants. Those who have little experience with plant applications have also shown positive feedback in the future on the use of plant-related applications. In addition, due to social problems such as air pollution, air purification using plants and functional plants showed high interest. Based on these results, we propose the need for a multi-functional plant application that can improve the indoor air pollution and facilitate the provision of information related to it.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.202-217
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• 2022

Purpose: The recent increased use of Personal Mobility (PM) has been accompanied by a rise in the annual number of accidents. Accordingly, the safety requirements for PM use are being strengthened, but the laws/systems, infrastructure, and management systems remain insufficient for fostering a safe environment. Therefore, this study comprehensively searches the main problems and improvement methods through a review of previous studies that are related to PM. Then the priorities according to the importance of the improvement methods are presented through the Delphi survey. Method: The research method is mainly composed of a literature study and an expert survey (Delphi survey). Prior research and improvement cases (local governments, government departments, companies, etc.) are reviewed to derive problems and improvements, and a problem/improvement classification table is created based on keywords. Based on the classification contents, an expert survey is conducted to derive a priority improvement plan. Result: The PM-related problems were in 'non-compliance with traffic laws, lack of knowledge, inexperienced operation, and lack of safety awareness' in relation to human factors, and 'device characteristics, road-drivable space, road facilities, parking facilities' in relation to physical factors. 'Management/supervision, product management, user management, education/training' as administrative factors and legal factors are divided into 'absence/sufficiency of law, confusion/duplication, reduced effectiveness'. Improvement tasks related to this include 'PM education/public relations, parking/return, road improvement, PM registration/management, insurance, safety standards, traffic standards, PM device safety, PM supplementary facilities, enforcement/management, dedicated organization, service providers, management system, and related laws/institutional improvement', and 42 detailed tasks are derived for these 14 core tasks. The results for the importance evaluation of detailed tasks show that the tasks with a high overall average for the evaluation items of cost, time, effect, urgency, and feasibility were 'strengthening crackdown/instruction activities, education publicity/campaign, truancy PM management, and clarification of traffic rules'. Conclusion: The PM market is experiencing gradual growth based on shared services and a safe environment for PM use must be ensured along with industrial revitalization. In this respect, this study seeks out the major problems and improvement plans related to PM from a comprehensive point of view and prioritizes the necessary improvement measures. Therefore, it can serve as a basis of data for future policy establishment. In the future, in-depth data supplementation will be required for each key improvement area for practical policy application.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.447-460
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• 2022

It is well known that satellite synthetic aperture radar interferometry (InSAR) has been widely used for the observation of surface displacement owing to earthquakes, volcanoes, and subsidence very precisely. In wetlands where vegetation exists on the surface of the water, it is possible to create a water level change map with high spatial resolution over a wide area using the InSAR technique. Currently, a number of imaging radar satellites are in operation, and most of them support a ScanSAR mode observation to gather information over a large area at once. The Cienaga Grande de Santa Marta (CGSM) wetland, located in northern Colombia, is a vast wetland developed along the Caribbean coast. The CGSM wetlands face serious environmental threats from human activities such as reclamation for agricultural uses and residential purposes as well as natural causes such as sea level rise owing to climate change. Various restoration and protection plans have been conducted to conserve these invaluable environments in recognition of the ecological importance of the CGSM wetlands. Monitoring of water level changes in wetland is very important resources to understand the hydrologic characteristics and the in-situ water level gauge stations are usually utilized to measure the water level. Although it can provide very good temporal resolution of water level information, it is limited to fully understand flow pattern owing to its very coarse spatial resolution. In this study, we evaluate the L-band ALOS-2 PALSAR-2 ScanSAR mode to observe the water level change over the wide wetland area using the radar interferometric technique. In order to assess the quality of the interferometric product in the aspect of spatial resolution and coherence, we also utilized ALOS-2 PALSAR-2 stripmap high-resolution mode observations.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.28-43
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• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.52-64
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• 2023

As cities continue to develop rapidly, overcrowding, pollution, and urban sanitation problems arise, and the need to separate conflicting uses is emerging. From this perspective, there is no disagreement that urban land use should be planned. Therefore, all activities in land space must be predicted in advance and planned so that land use can be rationally established. This study used the constructed data to compare and analyze the use distribution characteristics of residential, commercial, and industrial areas in Busan Metropolitan City to identify the building area status, total floor area, and floor area ratio by use zone in districts and counties in Busan Metropolitan City. As a result, it was found that the residential area accounted for the largest proportion of the area by use zone at 51%, and that the residential area accounted for the largest proportion at 63% of the total floor area by use zone. And the analysis was conducted using a specialization coefficient that can identify regional characteristics based on land use composition ratio. Because it is difficult to determine the trend of the entire region just by counting the absolute value of the area, the area composition ratio was calculated and compared. Looking at the residential facilities among the specialization coefficients by use area, it is above 1.0 except for Gijang-gun, Sasang-gu, Saha-gu, and Jung-gu. Commercial facilities are over 1.0 except for Gijang-gun, Gangseo-gu, Nam-gu, Sasang-gu, and Saha-gu. Looking at industrial facilities, you can see that the industrial complex distribution area is Gangseo-gu (2.5), Gijang-gun (1.22), Sasang-gu (2.06), and Saha-gu (1.64). In addition, it was found that business facilities and educational welfare facilities were evenly distributed. Land use analysis was conducted through simulation of the current status of building heights according to each elevation in each use area and the height of buildings in each use area. In general, areas over 80m account for more than 43% of Busan City, showing that the distribution of use areas is designated in areas with high altitude due to the influence of topographical conditions.

• Journal of Popular Narrative
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• v.25 no.3
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• pp.303-345
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• 2019

This article analyzes the multi-layered communication in the Webtoon Princess Pari, released on the Daum portal site, created (written and illustrated) by Kim Naim, through analyzing the narrative structure and comments with the qualitative / quantitative methodology. The webtoon Princess Pari is structured in an omnibus style in which unit narratives are intermittently articulated, multi-lined, and interconnected. As integrated narratives which link with unitary narratives, Pari's growth story as a shaman and a romance narrative are structured. The classical original story of the shaman was used as a prehistory corresponding to the prequel of the webtoon through a preview, and the writer restructured the narrative to overcome the contradictions of the gender asymmetry and the patriarchal ideology of the original text. The viewer then creates a conversational space by giving critical and reflective comments. According to a statistical analysis conducted through sampling, the types of comments can be classified as follows: Appreciation and criticism of the contents ≫ Emotional response ≫ Intuitive overall review ≫ Knowledge and reflection ≫ Comments on comments. In the process of creation and acceptance of the Webtoon, a multi-layered dialogue between classical and modern, content and audience, acceptance and creation has been at play. In the creation dimension, the writer used a device to fill the gap of mythical symbols of the contents. At the level of the audience, they formed a culture of sharing information, knowledge, and reflection about tradition/folk/culture through comments. This corresponds to classical and modern dialogue through the webtoon. The viewers form a sympathetic bond, attempt hermeneutical coordination, supplement the information, and search for a balanced angle through controversial conversation. In addition, by commenting on attitudes, views, and perspective, the commentators showed a behavioral pattern corresponding to meta-criticism in literature. The viewers' comments acted as feedback on the creation of the webtoons, so that the creation and acceptance itself influenced the production of the content of the webtoon. The webtoon Princess Pari, which was based on Korean classical narrative, has been reorganized onto 'moving and dynamic' content, which leads to sense, thinking, criticism and reflection through the formation of various dialogues.