• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.189-198
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• 2019

This study aims to make meaning of the reactions of the Korean people through the text mining of comments on videos of the December 2018 MMA performance of intro on YouTube. For this, comments on 15 YouTube videos were collected over the past 10 months. With the collected data, a total of 5,135 comments were analyzed through crawling using the Python and BeautifulSoup programs, data was refined over a total of 3 sessions, and a final total of 5,080 comments were used as analysis material. A mining technique was used for data analysis and the process of refinement, analysis, and visualization was achieved using the Textom program. Research results showed that keyword analysis showed the keywords of 'performance', 'Korea', 'video', 'top', 'cool', 'dance', 'idol', 'legend', 'love', and 'gratitude' in that order and keywords such as 'patriotism' and 'Olympics' also appeared frequently. N-gram analysis showed that comments with contexts such as 'a top performance that will remain a legend among Korean idol performances', and 'an idol performance that displayed the traditional culture of Korea' were in higher ranks. Based on such keyword analysis results, topic modeling was applied and 5 top keywords were extracted from a total of 5 topics. Analysis results of topic contents and distribution showed that topics in the comments of this performance's videos largely consisted of the 3 reactions of 'high praise regarding the stage performance', 'affection towards the fusion and artistic sublimation of Korean traditional dance', and 'gratitude towards the uploading of cool dance videos'

• Knowledge Management Research
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• v.24 no.3
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• pp.95-125
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• 2023

As the aviation industry has rapidly been grown, there are more factors for customers to consider when choosing an airline. In response, airlines are trying to increase customer value by providing high-quality services and differentiated experiential value. While early customer value research centered on utilitarian value, which is the trade-off between cost and benefit in terms of utility for products and services, the importance of experiential value has recently been emphasized. However, experiential value needs to be studied in a specific context that fully represents customer preferences because what constitutes customer value changes depending on the product or service context. In addition, customer value has an important influence on customers' decision-making, so it is necessary for airlines to accurately understand what constitutes customer value. In this study, we collected customer reviews and ratings from Skytrax, a website specializing in airlines, and utilized the BERTopic technique to derive factors of customer value. The results revealed nine factors that constitute customer value in airlines, and six of them are related to customer satisfaction. This study proposes a new methodology that enables a granular understanding of customer value and provides airlines with specific directions for improving service quality.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1057-1063
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• 2023

The urban railway sleeper floating track, the subject of this study, is an anti-vibration track to reduce vibration transmitted to the structure. currently, the replacement cycle of resilience pad for sleeper floating tracks is set and operated based on load. however, most previous studies were conducted on load-based structural safety aspects, such as fatigue life evaluation of sleeper anti-vibration pads and increase in track impact coefficient and track support stiffness due to increase in spring stiffness. therefore, in this study, we measure the vibration acceleration of the ballast for each analysis section and use the results of 7 million fatigue tests to calculate the spring stiffness of the resilience pad for each section. the spring stiffness of the resilience pad calculated for each section was set as the analysis data and the concrete vibration acceleration was derived analytically. the adequacy of analysis modeling was verified as the analyzed concrete bed vibration acceleration for each section was within the field-measured concrete bed vibration acceleration range. using the vibration acceleration curve according to the derived spring stiffness change, the spring stiffness of the resilience pad is estimated from the measured vibration acceleration. therefore, we would like to present a technique that can estimate the spring stiffness of resilience pad of a running track using the vibration acceleration of the measured concrete bed.

• Knowledge Management Research
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• v.25 no.1
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• pp.1-19
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• 2024

This study analyzed the changes in social media reactions of data subjects to major personal data breach incidents in South Korea from January 2014 to October 2022. We collected a total of 1,317 posts written on Naver Blogs within a week immediately following each incident. Applying the LDA topic modeling technique to these posts, five main topics were identified: personal data breaches, hacking, information technology, etc. Analyzing the temporal changes in topic distribution, we found that immediately after a data breach incident, the proportion of topics directly mentioning the incident was the highest. However, as time passed, the proportion of mentions related indirectly to the personal data breach increased. This suggests that the attention of data subjects shifts from the specific incident to related topics over time, and interest in personal data protection also decreases. The findings of this study imply a future need for research on the changes in privacy awareness of data subjects following personal data breach incidents.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.413-426
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• 2023

Species distribution model (SDM) is used to preserve biodiversity and climate change impact. To evaluate biodiversity, various studies are being conducted to utilize and apply SDM. However, there is insufficient research to provide useful information by identifying the current status and recent trends of SDM research and discussing implications for future research. This study analyzed the trends and flow of academic papers, in the use of SDM, published in academic journals in South Korea and provides basic information that can be used for related research in the future. The current state and trends of SDM research were presented using philological methods and text-mining. The papers on SDM have been published 148 times between 1998 and 2023 with 115 (77.7%) papers published since 2015. MaxEnt model was the most widely used, and plant was the main target species. Most of the publications were related to species distribution and evaluation, and climate change. In text mining, the term 'Climate change' emerged as the most frequent keyword and most studies seem to consider biodiversity changes caused by climate change as a topic. In the future, the use of SDM requires several considerations such as selecting the models that are most suitable for various conditions, ensemble models, development of quantitative input variables, and improving the collection system of field survey data. Promoting these methods could help SDM serve as valuable scientific tools for addressing national policy issues like biodiversity conservation and climate change.

• Journal of Platform Technology
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• v.11 no.6
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• pp.68-78
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• 2023

In this paper, the color distortion in images with haze would be analyzed. When haze is included in the scene, the color signal reflected in the scene is accompanied by color distortion due to the influence of transmittance according to the haze component. When the influence of haze is excluded by a conventional de-hazing method, the distortion of color tends to not be sufficiently resolved. Khoury et al. used the dark channel priority technique, a haze model mentioned in many studies, to determine the degree of color distortion. However, only the tendency of distortion such as color error values was confirmed, and specific color distortion analysis was not performed. This paper analyzes the characteristic of color distortion and proposes a restoration method that can reduce color distortion. Input images of databases used by Khoury et al. include Macbeth color checker, a standard color tool. Using Macbeth color checker's color values, color distortion according to changes in haze concentration was analyzed, and a new color distortion model was proposed through modeling. The proposed method is to obtain a mapping function using the change in chromaticity by step according to the change in haze concentration and the color of the ground truth. Since the form of color distortion varies from step to step in proportion to the haze concentration, it is necessary to obtain an integrated thought function that operates stably at all stages. In this paper, the improvement of color distortion through the proposed method was estimated based on the value of angular error, and it was verified that there was an improvement effect of about 15% compared to the conventional method.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.1
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• pp.74-85
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• 2016

For the assessment of seawater exchange rates in Danghangpo bay, Dangdong bay, Wonmun bay, Gohyunsung bay, and Masan bay, which are small-scale inner bays of Jinhae bay, an EFDC model was used to reproduce the seawater flow of the entire Jinhae bay, and Lagrange (particle tracking) and Euler (dye diffusion) model techniques were used to calculate the seawater exchange rates for each of the bays. The seawater exchange rate obtained using the particle tracking method was the highest, at 60.84%, in Danghangpo bay, and the lowest, at 30.50%, in Masan bay. The seawater exchange rate calculated based on the dye diffusion method was the highest, at 45.40%, in Danghangpo bay, and the lowest, at 34.65%, in Masan bay. The sweater exchange rate was found to be the highest in Danghangpo bay likely because of a high flow velocity owing to the narrow entrance of the bay; and in the case of particle tracking method, the morphological characteristics of the particles affected the results, since once the particles get out, it is difficult for them to get back in. Meanwhile, in the case of the Lagrange method, when the particles flow back in by the flood current after escaping the ebb current, they flow back in intact. However, when a dye flows back in after escaping the bay, it becomes diluted by the open sea water. Thus, the seawater exchange rate calculated based on the dye diffusion method turned out to be higher in general, and even if a comparison of the sweater exchange rates calculated through two methods was conducted under the same condition, the results were completely different. Thus, when assessing the seawater exchange rate, more reasonable results could be obtained by either combining the two methods or selecting a modeling technique after giving sufficiently consideration to the purpose of the study and the characteristics of the coastal area. Meanwhile, through a comparison of the degree of closure and seawater exchange rates calculated through Lagrange and Euler methods, it was found that the seawater exchange rate was higher for a higher degree of closure, regardless of the numerical model technique. Thus, it was deemed that the degree of closure would be inappropriate to be used as an index for the closeness of the bay, and some modifications as well as supplementary information would be necessary in this regard.

• Journal of Bio-Environment Control
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• v.25 no.2
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• pp.106-110
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• 2016

In this study, a planting density-growth-harvest (PGH) chart was developed to easily read the growth and harvest factors such as crop growth rate, relative growth rate, shoot fresh weight, shoot dry weight, harvesting time, marketable rate, and marketable yield of common ice plant (Mesembryanthemum crystallinum L.). The plants were grown in a nutrient film technique (NFT) system in a closed-type plant factory using fluorescent lamps with three-band radiation under a light intensity of $140{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ and a photoperiod of 12 h. Growth and yield were analyzed under four planting densities ($15{\times}10cm$, $15{\times}15cm$, $15{\times}20cm$, and $15{\times}25cm$). Shoot fresh and dry weights per plant increased at a higher planting density until reached an upper limit and yield per area was also same tendency. Crop growth rate, relative growth rate and lost time were described using quadratic equation. A linear relationship between shoot dry weight and fresh weights was observed. PGH chart was constructed based on the growth data and making equations. For instance, with within row spacing (= 20 cm) and fresh weight per plant at harvest (= 100 g), we can estimate all the growth and harvest factors of common ice plant. The planting density, crop growth rate, relative growth rate, lost time, shoot dry weight per plant, harvesting time, and yield were $33plants/m^2$, $20g{\cdot}m^{-2}{\cdot}d^{-1}$, $0.27g{\cdot}g^{-1}{\cdot}d^{-1}$, 22 days, 2.5 g/plant, 26 days after transplanting, and $3.2kg{\cdot}m^{-2}$, respectively. With this chart, we could easily obtain the growth factors such as planting density, crop growth rate, relative growth rate, lost time and the harvest factors such as shoot fresh and dry weights, harvesting time, marketable rate, and marketable yield with at least two parameters, for instance, planting distance and one of harvest factors of plant. PGH charts will be useful tools to estimate the growth and yield of crops and to practical design of a closed-type plant production system.

• Journal of the Korea Concrete Institute
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• v.19 no.5
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• pp.613-621
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• 2007

Due to the increasing significance of durability, much researches on carbonation, one of the major deterioration phenomena are carried out. However, conventional researches based on fully hardened concrete are focused on prediction of carbonation depth and they sometimes cause errors. In contrast with steel members, behaviors in early-aged concrete such as porosity and hydrates (calcium hydroxide) are very important and may be changed under carbonation process. Because transportation of deteriorating factors is mainly dependent on porosity and saturation, it is desirable to consider these changes in behaviors in early-aged concrete under carbonation for reasonable analysis of durability in long term exposure or combined deterioration. As for porosity, unless the decrease in $CO_2$ diffusion due to change in porosity is considered, the results from the prediction is overestimated. The carbonation depth and characteristics of pore water are mainly determined by amount of calcium hydroxide, and bound chloride content in carbonated concrete is also affected. So Analysis based on test for hydration and porosity is recently carried out for evaluation of carbonation characteristics. In this study, changes in porosity and hydrate $(Ca(OH)_2)$ under carbonation process are performed through the tests. Mercury Intrusion Porosimetry (MIP) for changed porosity, Thermogravimetric Analysis (TGA) for amount of $(Ca(OH)_2)$ are carried out respectively and analysis technique for porosity and hydrates under carbonation is developed utilizing modeling for behavior in early-aged concrete such as multi component hydration heat model (MCHHM) and micro pore structure formation model (MPSFM). The results from developed technique is in reasonable agreement with experimental data, respectively and they are evaluated to be used for analysis of chloride behavior in carbonated concrete.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.