• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of Korean Society of Forest Science
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• v.111 no.2
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• pp.311-318
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• 2022

We conducted this study to derive the site index, which is a criterion for the planting of Robinia pseudoacacia, a honey plant, and to investigate the diameter distribution change by derived site index. We applied the Chapman-Richards equation model to estimate the site index of the Robinia pseudoacacia stand. The site index was distributed within the range of 16-22 when the base age was 30 years. The fitness index of the site index estimation model was low, but we judged that there was no problem in the application because the residual distribution of the equation had not shifted to one side. We used the Weibull diameter distribution function to determine the diameter distribution of the Robinia pseudoacacia stand by site index. We used the mean diameter and the dominant tree height as independent variables to present the diameter distribution, and our analysis procedure was to estimate and recover the parameters of the Weibull diameter distribution function. We used the mean diameter and the dominant tree height of the Robinia pseudoacacia stand to show distribution by diameter class, and the fitness index for dbh distribution estimation was about 80.5%. As a result of schematizing the diameter distribution by site indices as a 30-year-old, we found that the higher the site index, the more the curve of the diameter distribution moved to the right. This suggests that if the plantation were to be established in a high site index stand, considering the suitable trees on the site, the growth of Robinia pseudoacacia woul d become active, and not onl y the production of wood but al so the production of honey would increase. We therefore anticipate that the site index classification table and curve of this Robinia pseudoacacia stand will become the standard for decision making in the plantation and management of this tree.

• Journal of Life Science
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• v.30 no.11
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• pp.947-955
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• 2020

The foot-and-mouth disease virus (FMDV), a member of the Aphthovirus genus in the Picornaviridae family, affects wild and domesticated ruminants and pigs. During replication of the FMDV RNA (ribonucleic acid) genome, FMDV-encoding RNA polymerase 3D acts in a highly location-specific manner. This suggests that specific RNA structures recognized by 3D polymerase within non-coding regions of the FMDV genome assist with binding during replication. One such region is the cis-acting replication element (CRE), which functions as a template for RNA replication. The FMDV CRE adopts a stem-loop conformation with an extended duplex stem, supporting a novel 15-17 nucleotide loop that derives stability from base-stacking interactions, with the exact RNA nucleotide sequence of the CRE producing different RNA secondary structures. Here, we show that CRE sequences of FMDVs isolated in Korea from 2010 to 2017 exhibit A and O genotypes. Interestingly, variations in the RNA secondary structure of the Korean FMDVs are consistent with the phylogenetic relationships between these viruses and reveal the specificity of FMDV infections for particular host species. Therefore, we conclude that each genetic clade of Korean FMDV is characterized by a unique functional CRE and that the evolutionary success of new genetic lineages may be associated with the invention of a novel CRE motif. Therefore, we propose that the specific RNA structure of a CRE is an additional criterion for FMDV classification dependent on the host species. These findings will help correctly analyze CRE sequences and indicate the specificity of host species for future FMDV epidemics.

• Journal of Life Science
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• v.31 no.9
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• pp.840-848
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• 2021

This study was conducted to estimate annual trends and the environmental effects in the racing records of Jeju horses. The Korean Racing Authority (KRA) collected 48,645 observations for 2,167 Jeju horses from 2002 to 2019. Racing records were preprocessed to eliminate errors that occur during the data collection. Racing times were adjusted for comparison between race distances. A stepwise Akaike information criterion (AIC) variable selection method was applied to select appropriate environment variables affecting racing records. The annual improvement of the race time was -0.242 seconds. The model with the lowest AIC value was established when variables were selected in the following order: year, budam classification, jockey ranking, trainer ranking, track condition, weather, age, and gender. The most suitable model was constructed when the jockey ranking and age variables were considered as random effects. Our findings have potential for application as basic data when building models for evaluating genetic abilities of Jeju horses.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.379-392
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• 2015

Freight flow data in Korea has been collected for a variety of purposes by various organizations. However, since the representation and format of the data varies, it has not been substantially used for freight analyses and furthermore for freight policies. In order to increase the applicability of those data sets, it is required to bring them in a table and compare for finding the differences. Then, it is shown that the raw data can be aggregated by a particular criterion such as mode, origin and destination, and type commodity. This study aims to examine the freight data issue in terms of three different points of view. First, we investigated various freight volume data sets which are released by several organizations. Second, we tried to develop formulations for freight volume data. Third, we discussed how to apply the formulations to network models in which particular OR (Operations Research) techniques are used. The results emphasized that some data might be useless for modeling once they are aggregated. As a result of examining the freight volume data, this study found that 14 organizations share their data sets at various aggregation levels. This study is not an ordinary research article, which normally includes data analysis, because it seems to be impossible to conduct extensive case studies. The reason is that the data dealt in this study are diverse. Nevertheless, this study might guide the research direction in the freight transport research society in terms of data issue. Especially, it can be concluded that this study is a timely research because the governmemt has emphasized the importance of sharing data to public throughout 'government 3.0' for research purpose.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.