• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.439-441
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• 2023

National park is one of the important types of protected area management systems established by IUCN and a management model for effective conservation and sustainable use of natural and cultural heritage in countries around the world, and it assumes important roles in conservation, scientific research, education, recreation and driving community development. This study takes Liaohe National Park in China, a typical representative of global coastal wetlands, as a case study, and uses python technology to collect travelogues and reviews of visitors from Mafengwo.com, Ctrip.com, Go.com, Meituan.com and Dianping.com as a source, and the text spans from 2015 to 2022. The results show that wildlife resources, natural landscape with river and sea, wetland ecology and fishing and hunting culture of northern China are fully reflected in the perceptions of visitors to Liaohe National Park. However, there is still much room for improvement in terms of supporting services and facilities, public education and tourists' experience and participation in Liaohe National Park. In this paper, we use python data visualization technology to study the public perception of wetland wildlife as the theme, and grasp the satisfaction, spatial distribution, activity content and emotional tendency of the public in the process of wetland wildlife as the theme, so as to better promote the Liaohe National Park to better carry out the public experience while strictly adhering to ecological protection, and to provide the Liaohe National Park with a better opportunity to This will provide scientific basis for the Liaohe National Park to play a better role in ecological civilization construction and education of ecological civilization awareness.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.185-193
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• 2024

With the advent of smartphones, people can access various information through the internet anytime and anywhere. Even in the vehicle environment, users can use the internet. Users interact with web and applications every day and get information. However, as the amount of data to be processed by the program increases, users inevitably receive a message to wait. User waiting is an inconvenient experience, but minimizing user waiting is the best way because there is time required for data processing. However, if the service processing time exceeds the expected time, users experience more severe boredom and pain. Therefore, various methods and researches are being conducted to alleviate the boredom of user waiting. The most commonly used method to alleviate user waiting boredom is loading. In this study, we investigated the effect of skeleton loading, the latest loading technique, on user waiting experience, and how attractive it is as a design technique in terms of UI compared to other loading techniques.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.724-732
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• 2023

In this study, we tried to analyze the characteristics of color cosmetics information search and the major information of interest in the color cosmetics market after COVID-19 shown in the text mining analysis results by collecting data on online interest information of consumers in the color cosmetics market after COVID-19. In the empirical analysis, text mining was performed on all documents such as news, blogs, cafes, and web pages, including the word "color cosmetics". As a result of the analysis, online information searches for color cosmetics after COVID-19 were mainly focused on purchase information, information on skin and mask-related makeup methods, and major topics such as interest brands and event information. As a result, post-COVID-19 color cosmetics buyers will become more sensitive to purchase information such as product value, safety, price benefits, and store information through active online information search, so a response strategy is required.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.127-135
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• 2024

Background and Purpose: To ensure data privacy, the development of defacing processes, which anonymize brain images by obscuring facial features, is crucial. However, the impact of these defacing methods on brain imaging analysis poses significant concern. This study aimed to evaluate the reliability of three different defacing methods in automated brain volumetry. Methods: Magnetic resonance imaging with three-dimensional T1 sequences was performed on ten patients diagnosed with subjective cognitive decline. Defacing was executed using mri_deface, BioImage Suite Web-based defacing, and Defacer. Brain volumes were measured employing the QBraVo program and FreeSurfer, assessing intraclass correlation coefficient (ICC) and the mean differences in brain volume measurements between the original and defaced images. Results: The mean age of the patients was 71.10±6.17 years, with 4 (40.0%) being male. The total intracranial volume, total brain volume, and ventricle volume exhibited high ICCs across the three defacing methods and 2 volumetry analyses. All regional brain volumes showed high ICCs with all three defacing methods. Despite variations among some brain regions, no significant mean differences in regional brain volume were observed between the original and defaced images across all regions. Conclusions: The three defacing algorithms evaluated did not significantly affect the results of image analysis for the entire brain or specific cerebral regions. These findings suggest that these algorithms can serve as robust methods for defacing in neuroimaging analysis, thereby supporting data anonymization without compromising the integrity of brain volume measurements.

• The Research Journal of the Costume Culture
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• v.32 no.4
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• pp.517-546
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• 2024

The aim of this study is to investigate the fashion industry's response to climate change and how these discussions unfolded at the 28th Conference of the Parties (COP28) to the United Nations Framework Convention on Climate Change (UNFCCC). Climate change response projects by B Corp-certified fashion companies are examined, focusing on stakeholder efforts and reviewing online media reports. Text data were collected from web documents, interviews, and op-eds relating to COP28 from December 2018 to April 2024 and analyzed using text mining and semantic network analysis to identify critical keywords and contexts. The analysis revealed that the fashion industry is fulfilling its environmental responsibilities through various strategies, prompting changes in consumer behavior by advocating sustainable consumption, including carbon removal, energy transition, and recycling promotion. Stakeholders in online media and those present at COP28 discussed issues relating to climate change in the fashion industry, focusing on environmental protection, energy, greenhouse gas emissions, sustainable material usage, and social responsibility. Key issues at COP28 included policy and regulation, climate change response, energy transition, carbon emissions management, and environmental, social, and governance (ESG) standards. Additionally, by examining the main collections exhibited at the fashion show during COP28, the study analyzed how messages about climate change were conveyed. Fashion companies communicated the industry's response through exhibitions and fashion shows, suggesting a move toward balancing environmental protection and economic growth through the development of sustainable materials, the expansion of recycling and reuse practices, and the modern reinterpretation of cultural heritage.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.49-60
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• 2017

Recently, the use of mashup that integrates real-time data with spatial data such as tiled map and satellite imagery has been increased significantly. As the use of mashup has been extended to various fields of O2O, LBS, Smart City, and Autonomous Driving, the performance of mashup has become more important. Therefore, this study aims to compare and analyze the performance of various map platforms, when large amounts of real-time data are integrated with spatial data. Specifically, we compare the performance of most popular map platforms available in Korea, such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld. We also compare the performance using most common web browsers of Chrome, Firefox and Internet Explorer. In the performance analysis, we measured and compared the initialization time of basic map and the mashup time of real-time data for the above map platforms. From analysis results, we could find that Google Maps, OpenStreetMap, VWorld, and olleh Map platforms showed a better performance than the others.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.64-77
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• 2015

An effective method for produce munitions effectiveness data is to calculate weapon effectiveness indices in the US military's Joint Munitions Effectiveness Manuals (JMEM) and take advantage of the damage evaluation model (GFSM) and weapon Effectiveness Evaluation Model (Matrix Evaluator). However, a study about the Range Safety that can be applied in the live firing exercises is very insufficient in the case of ROK military. The Range Safety program is an element of the US Army Safety Program, and is the program responsible for developing policies and guidance to ensure the safe operation of live-fire ranges. The methodology of Weapon Danger Zone (WDZ) program is based on a combination of weapon modeling/simulation data and actual impact data. Also, each WDZ incorporates a probability distribution function which provides the information necessary to perform a quantitative risk assessment to evaluate the relative risk of an identified profile. A study of method to establish for K-Range Safety data is to develop manuals (pamphlet) will be a standard to ensure the effective and safe fire training at the ROK military education and training and environmental conditions. For example, WDZs are generated with the WDZ tool as part of the RMTK (Range Managers Tool Kit) package. The WDZ tool is a Geographic Information System-based application that is available to operational planners and range safety manager of Army and Marine Corps in both desktop and web-based versions. K-Range Safety Program based on US data is reflected in the Korean terrain by operating environments and training doctrine etc, and the range safety data are made. Thus, verification process on modified variables data is required. K-Range Safety rather than being produced by a single program, is an package safety activities and measures through weapon danger zone tool, SRP (The Sustainable Range Program), manuals, doctrine, terrain, climate, military defence M&S, weapon system development/operational test evaluation and analysis to continuously improving range safety zone. Distribution of this K-range safety pamphlet is available to Army users in electronic media only and is intended for the standing army and army reserve. Also publication and distribution to authorized users for marine corps commands are indicated in the table of allowances for publications. Therefore, this study proposes an efficient K-Range Safety Manual producing to calculate the danger zones that can be applied to the ROK military's live fire training by introducing of US Army weapons danger zone program and Range Safety Manual

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.567-584
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• 2004

As XML becomes popular as the way of presenting information on the web, how to secure XML data becomes an important issue. So far study on XML security has focused on security of data communications by using digital sign or encryption technology. But, it now requires not just to communicate secure XML data on communication but also to manage query process to access XML data since XML data becomes more complicated and bigger. We can manage XML data queries by access control technique. Right now current XML data access control only deals with read operation. This approach has no option to process update XML queries. In this paper, we present XML access control model and technique that can support both read and update operations. In this paper, we will propose the operation for XML document update. Also, We will define action type as a new concept to manage authorization information and process update queries. It results in both minimizing access control steps and reducing memory cost. In addition, we can filter queries that have no access rights at the XML data, which it can reduce unnecessary tasks for processing unauthorized query. As a result of the performance evaluation, we show our access control model is proved to be better than other access control model in update query. But it has a little overhead to decide action type in select query.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.546-559
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• 2021

This research aimed to develop the district unit plan simulation using procedural modeling based on shape grammar. For this, Esri's CityEngine 2020.0 was selected as a main development tool, and Inside Commercial Area in Bangi-dong, Songpa-gu, Seoul as the research site where about 25% of the total area was developed over the past five years. Specifically, the research developed the simulation through the following three phases of Data-Information-Knowledge after selecting necessary parameters. In the Data phase, 2 and 3 dimensional data were obtained by utilizing data sharing platforms. In the next Information phase, the acquired data were generated into various procedural models according to the shape grammar, and the 2D and 3D layers were then integrated using relevant applications. In the final Knowledge phase, three-dimensional spatial analysis and storytelling contents were produced based on the integrated layer. As a result, the research suggests the following three implications for the simulation development. First, data accuracy and improvement of sharing platforms are needed in order to effectively carry out the simulation development. Second, the guidelines for district unit plans could be utilized and developed into shape grammar for procedural modeling. Third, procedural modeling is expected to be used as an alternative tool for communication and information delivery.