• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.309-311
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• 2014

Despite increasing demands for big data application based on the analysis of scattered unstructured data, few relevant studies have been reported. Accordingly, the present study suggests a technique enabling a sentence-based semantic analysis by extracting objects from collected web information and automatically analyzing the relationships between such objects with collective intelligence and language processing technology. To be specific, collected information is stored in DBMS in a structured form, and then morpheme and feature information is analyzed. Obtained morphemes are classified into objects of interest, marginal objects and objects of non-interest. Then, with an inter-object attribute recognition technique, the relationships between objects are analyzed in terms of the degree, scope and nature of such relationships. As a result, the analysis of relevance between the information was based on certain keywords and used an inter-object relationship extraction technique that can determine positivity and negativity. Also, the present study suggested a method to design a system fit for real-time large-capacity processing and applicable to high value-added services.

• Informatization Policy
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• v.26 no.3
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• pp.36-52
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• 2019

The use of social media in government has expanded steadily around the world on the basis of Web 2.0 technology. The government uses social media as a tool for enhancing transparency, participation, collaboration, and saving costs. However, the use of social media in the public sector has not only been positive. It has also been described as a double-edged sword. Most local governments in South Korea use social media for a variety of reasons but there has not been enough practical study of the effectiveness of social media use in the public sector. Local governments generally have positive views of their social media use but the real application of social media is not consistent in each local government. This study tried to determine the reality of social media use in local government and what factors influenced its use. The research analyzed the data from a survey conducted by the Korea Local Information Research & Development Institute (KLID) in 2015 and data from Facebook in each local government. The results show that most local governments were using Facebook for promotional purposes and local government officials similarly recognized that they were using Facebook well. However, local governments showed great differences in their use and practical effect. Meanwhile, the study found that population, financial independence, level of government, the entity operating social media, the median age, and whether social media are used for interaction or to gather opinions were the most influential factors that make a difference in utilization in local government.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.253-265
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• 2019

In this study were analyzed the errors on the registration of details information, location of E-GEN (Emergency medical-GEN) AED (Automated External Defibrillator) installation site and the adequacy of spatial arrangement, which suggests an improvement methods of constructing an app or web based on time and space data for efficient operation of considering accessibility and usability. As a result of this study, first, it was not equal to each other for locations of each installation point of AED, that confirmed some area were dense or requiring additional installation. Second, it confirmed the inaccuracies in inputting and registering information about the installed location, such as the actual installation location information and the attribute information of the AED. Third, the main access node and the main address node were connected to a straight line that was found not be connected to the back door, the straight line, the stairs. Also, the opening times of AED installation sites varied according to the week and the season, the entrance was managed by the apartment management office in a separate place, it needs to be established on this information. In conclusion, it proposed a method to improve spatial equity and accessibility, a method to provide accurate distance and time according to actual movement routes in case of emergency, and a possibility of using each facility considering day and time.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.569-578
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• 2021

Thanks to web development today, we can easily access online news via various media. As much as it is easy to access online news, we often face fake news pretending to be true. As fake news items have become a global problem, fact-checking services are provided domestically, too. However, these are based on expert-based manual detection, and research to provide technologies that automate the detection of fake news is being actively conducted. As for the existing research, detection is made available based on contextual characteristics of an article and the comparison of a title and the main article. However, there is a limit to such an attempt making detection difficult when manipulation precision has become high. Therefore, this study suggests using a verifying article to decide whether a news item is genuine or not to be affected by article manipulation. Also, to improve the precision of fake news detection, the study added a process to summarize a subject article and a verifying article through the summarization model. In order to verify the suggested algorithm, this study conducted verification for summarization method of documents, verification for search method of verification articles, and verification for the precision of fake news detection in the finally suggested algorithm. The algorithm suggested in this study can be helpful to identify the truth of an article before it is applied to media sources and made available online via various media sources.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.305-317
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• 2022

To investigate the blossom infection risk of fire blight on pears, the program Maryblyt has been executed from 2018 to 2022 based on meteorological data from central-Korean cities where fire blight has occurred as well as from southern Korean cities where the disease has not yet occurred. In the past five years, years with the highest risk of pear blossom blight were 2022 and 2019. To identify the optimal time for spraying, we studied the spray mode according to the Maryblyt model and recommend spraying streptomycin on the day after a "High" warning and then one day before forecasted precipitation during the blossom period. Maryblyt also recommends to initiate surgical controls from mid-May for canker blight symptoms on pear trees owing to over-wintering canker in Korea. Web-cam pictures from pear orchards at Cheonan, Icheon, Sangju, and Naju during the flowering period of pear trees were used for comparing real data and constructing a phenological model. The actual starting dates of flowering at southern cities such as Sangju and Naju were consistently earlier than those calculated by the model. It is thus necessary to improve the forecasting model to include field risks by recording the actual flowering period and the first day of the fire blight symptoms, according to the farmers, as well as mist or dew-fall, which are not easily identifiable from meteorological records.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.1-25
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• 2021

In order to respond and prevent underground safety accidents, the Korean government has been preparing a submitting completion drawing web system project for converting the current manual-based 3D Underground Geospatial Map construction and its update system to an automation-based 3D underground information construction. However, research on standard drawings required for the automatic update of 3D underground structures is insufficient, so detailed research is needed. In this research paper, a standard map-based 3D underground structure construction plan was presented for the six types of underground structures constituting the 3D Underground Geospatial Map, enabling rapid and accurate drawing data creation and systematically 3D underground structure drawing data could be managed. In addition, we developed a 3D construction drawing tool that can be used in underground information practice so that ordinary CAD program users can easily produce processing drawings. The results derived from this paper are expected to be major reference materials for the establishment of standard frameworks and practical application guidelines for the construction of 3D underground structures in the future.

• The Korean Journal of Franchise Management
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• v.13 no.1
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• pp.35-46
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• 2022

Purpose: With the rapid changes in the technical development and the trend of consumption trend, the convenience store industry is facing an unprecedented competitive situation in the consumption environment where the boundary between online and offline is broken due to the stagnation of offline distribution channels and the spread of online shopping. The biggest innovation strategy of the major convenience store brands in recent years are introducing the O2O (Online to Offline) platform and presenting new products and services beyond the boundaries of online and offline to transform themselves into Omni Channel stores. The study is designed to analyze the effect of innovativeness of convenience store as a stimulus in O2O platform which customers perceive on store loyalty, the final response to external stimuli, through customer engagement with convenience store brands. Specifically, the innovativeness of convenience stores was divided into types of core activities in corporate marketing and focused on innovations in services, products(proposals), promotions and experiences. Research design, data, and methodology: Various hypotheses have been developed to achieve this research purpose. The data were collected from 1,128 questionnaires the age between 15 and 60 who had experience using retail store apps and delivery apps and were analyzed using SPSS 22.0 and SmartPLS 3.3.7 program. Measurement model analysis was carried out to assess convergent and discriminant validity. Also, common method bias was tested using the values of VIF (variance inflation factor). The hypotheses were tested using structural equation modeling with SmartPLS 3.3.7 program. Results: First, service innovation has a positive effect on cognitive engagement. Second, product, promotion and experience innovation have a positive effect on cognitive and affective engagement. Third, cognitive influences affective engagement. Finally, both cognitive and affective engagement affect store loyalty, but affective engagement has a stronger effect on store loyalty than cognitive engagement. Conclusions: All four types of innovation and cognitive engagement have a positive effect on emotional engagement, which has a stronger effect on store loyalty than cognitive engagement. Thus, while innovation can build loyalty through emotional engagement, innovation strategies must be designed and pursued with caution in terms of impact through cognitive engagement may not achieve the planned goals.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.419-430
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• 2023

Currently, NFTs have no dominant application except for the proof of ownership for digital content, and it also have small liquidity problem, which makes their price difficult to predict. Real estate usually has very high barriers to investment due to its high pricing. Real estate can be converted into NFTs and also divided into small value fungible tokens (FTs), and it can increase the the volume of the investor community due to more liquidity and better accessibility. In this document, we implement and design a system that allows ordinary users can invest on high priced real estate utilizing Black Litterman (BL) model-based Portfolio investment interface. To this end, we target a set of real estates pegged as collateral and issue NFT for the collateral using blockchain. We use oracle to get the current real estate information and to monitor varying real estate prices. After tokenizing real estate into NFTs, we divide the NFTs into easily accessible price FTs, thereby, we can lower prices and provide large liquidity with price volatility limited. In addition, we also implemented BL based asset portfolio interface for effective portfolio composition for investing in multiple of real estates with small investments. Using BL model, investors can fix the asset portfolio. We implemented the whole system using Solidity smart contracts on Flask web framework with public data portals as oracle interfaces.

• SUVANNABHUMI
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• v.10 no.2
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• pp.181-213
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• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.208-217
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• 2023

Accurate estimation of dormancy breaking and first bloom dates is crucial for effective fire blight control by disease model such as Maryblyt in apple orchards. The duration from dormancy breaking to first bloom in apple trees was influenced by daily minimum temperatures during the dormant period. The purpose of this study is to investigate the relationship between minimum temperatures during this period and the time taken for flowering to commence. Webcam data from eight apple orchards, equipped by the National Institute of Horticultural and Herbal Science, were observed from 2019 to 2023 to determine the dates of starting bloom (B1). Additionally, the dormancy breaking dates for these eight sites were estimated using an apple chill day model, with a value of -100.5 DD, based on collected weather data. Two regressions were performed to analyze the relationships: the first regression between the number of days under 0℃ (X₁) and the time from calculated dormancy breaking to observed first bloom (Y), resulting in Y = 0.87 × X₁ + 40.76 with R² = 0.84. The second regression examined the starting date of breaking dormancy (X₂) and the duration from dormancy breaking to observed first bloom (Y), resulting in Y = -1.07 × X₂ + 143.62 with R² = 0.92. These findings suggest that apple anti-chill days are significantly affected by minimum temperatures during the period from dormancy breaking to flowering, indicating their importance in fire blight control measures.