• Journal of agriculture & life science
• /
• v.45 no.1
• /
• pp.21-32
• /
• 2011

This study was conducted to estimate carbon dioxide $(CO_{2})$ absorption and bioenergy supply potential of forests in Muju county based on GIS RS In results, it was estimated that 7,800,130 $tCO_{2}$ was absorbed and all bioenergy supply potential of 11,868,202,837 Mcal was available. Futhermore, bioenergy supply potential of 314,876,637 Mcal was available each year that was able to be supplied for the hitting during winter period to 11,241 households. This was more than all households of 10,902 in Muju county. This study suggested the methodology for estimating $CO_{2}$ absorption and bioenergy supply potential of forests on the national scale, and it was believed that reliability would be increased by estimation on the national scale using detailed forest information based on the latest techniques such as GIS RS techniques.

• Korean Journal of Remote Sensing
• /
• v.15 no.2
• /
• pp.147-158
• /
• 1999

Remote sensing technique has offered better understanding of our environment for the decades by providing useful level of information on the landcover. In many applications using the remotely sensed data, digital image processing methodology has been usefully employed to characterize the features in the data and develop the models. Random field models, especially Markov Random Field (MRF) models exploiting spatial relationships, are successfully utilized in many problems such as texture modeling, region labeling and so on. Usually, remotely sensed imagery are very large in nature and the data increase greatly in the problem requiring temporal data over time period. The time required to process increasing larger images is not linear. In this study, the methodology to reduce the computational cost is investigated in the utilization of the Markov Random Field. For this, multiresolution framework is explored which provides convenient and efficient structures for the transition between the local and global features. The computational requirements for parameter estimation of the MRF model also become excessive as image size increases. A Bayesian approach is investigated as an alternative estimation method to reduce the computational burden in estimation of the parameters of large images.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.369-376
• /
• 2021

3D architectural visualization animation has become more important in architectural presentations due to the rapid development of digital technology. Unlike games and movies, architectural visualization animation most focuses on delivering visual information, and aims to express the sense of space that viewers feel in an architectural space, rather than simply providing an image of viewing buildings. The sense of space is affected not only by physical elements of architecture, but also by immaterial elements such as light, time, and human actions, and it is more advantageous to express it in animations that can contain temporality compared to a fixed image. Therefore, the purpose of this study is to search for elements to effectively convey a sense of space in architectural visualization animation. To this end, the works of renowned architectural visualization artists that are open to the public were selected and observed to search for elements to effectively convey a sense of space to viewers. The elements that convey the sense of space that are common to the investigated architectural animations can be classified into the movement and manipulation of the camera, the movement of surrounding objects, the change of the light environment, the change of the weather, the control of time, and the insertion of a surreal scene. It will be followed by a discussion on the immersion of architectural contents.

• Journal of Convergence for Information Technology
• /
• v.11 no.4
• /
• pp.83-101
• /
• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Journal of Korean Society of Archives and Records Management
• /
• v.22 no.4
• /
• pp.175-196
• /
• 2022

This study aims to determine the research trends in archival preservation through keyword analysis, understand the current research status, and identify the research topics' changes over time. The degree and betweenness centrality analyses were conducted and visualized on 463 "archival preservation studies" articles published from 2000 to 2021 in various academic journals, using NetMiner 4.0. The collected research papers were divided into three time periods according to when they were published: the first period (2000-2007), the second period (2008-2014), and the third period (2015-2021). The subject keywords for the research papers on archival preservation in Korea that have influence and expandability are as follows. Across all periods, these were "electronic records" and "long-term preservation." In addition, if taken separately per period, the "OAIS reference model" and "electronic records" dominated the first and second periods, respectively, while the "records management standard table" and "long-term preservation" both dominated the third period. A conceptual framework and theory-oriented study for archival preservation, such as "digital preservation," "digitalization," and the "OAIS reference model," dominated the first period. During the second period, more research focused on procedures and practical applications related to conservation activities, such as "electronic record," "appraisal," and "DRAMBORA." In contrast, the majority of the research in the third period was on technical implementation according to the changes in the records management environment, such as "data set," "administrative information system," and "social media."

• The Journal of the Korea Contents Association
• /
• v.22 no.9
• /
• pp.179-193
• /
• 2022

Amid the explosive growth of various metaverse platforms, there is no unified indicator to measure, analyze, and evaluate based on customer experience. Therefore, the usability evaluation factors in metaverse were identified through a heuristic methodology and literature review, to evaluate the metaverse, a two-to three-dimensional virtual world platform. A measurable system was established by subdividing 20 items in 5 fields, including user control, information structure, design and content, and usage environment, derived through Delphi technique. Based on this, after experiencing the actual contents of major metaverse platforms such as Roblox and Zepeto, usability was evaluated and comparative verification was conducted. As a result, it was estimated that metaverse user experience could be improved as its utility was derived relatively high in terms of user control and content. This study constitutes a theoretical contribution by extending the usability evaluation system, which has been widely used in the field of service design, to the fields of extended reality and mixed reality. At the same time, it has practical key findings of providing basic judgment standards to stakeholders in the metaverse field, as well as policy implications for digital capability enhancement and industry revitalization.

• Journal of Internet Computing and Services
• /
• v.23 no.6
• /
• pp.27-37
• /
• 2022

Virtual private network (VPN) services are used in various environments related to national security, such as defense companies and defense-related institutions where digital communication environment technologies are diversified and access to network use is increasing. However, the number of cyber attacks that target vulnerable points of the VPN has annually increased through technological advancement. Thus, this study identified security requirements by performing STRIDE threat modeling to prevent potential and new vulnerable points that can occur in the VPN. STRIDE threat modeling classifies threats into six categories to systematically identify threats. To apply the proposed security requirements, this study analyzed functions of the VPN and formed a data flow diagram in the VPN service process. Then, it collected threats that can take place in the VPN and analyzed the STRIDE threat model based on data of the collected threats. The data flow diagram in the VPN service process, which was established by this study, included 96 STRIDE threats. This study formed a threat scenario to analyze attack routes of the classified threats and derived 30 security requirements for each element of the VPN based on the formed scenario. This study has significance in that it presented a security guideline for enhancing security stability of the VPN used in facilities that require high-level security, such as the Ministry of National Defense (MND).

• Journal of Korean Society of Disaster and Security
• /
• v.15 no.4
• /
• pp.87-98
• /
• 2022

In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

• Design Convergence Study
• /
• v.14 no.1
• /
• pp.47-61
• /
• 2015

Along with the advent of the digital era, the media environment in which an informant would convey information one-sidedly has evolved more towards engaging customers to actively participate and produce contents themselves. This change in content consumption behavior has brought about the new marketing paradigm. The new communication strategy is interactive marketing, which enhances brand-imprinting Effects, and has been consistently proposed these days. This study aims to examine these brand-imprinting effects through an empirical study and to propose an application plan. Therefore, methods of approach for engaging customers' participation and the methods of experiences are categorized by types through the case analysis of various domestic as well as international interactive marketing techniques. In addition, in-depth interviews have been carried out in order to verify the influence of interactive marketing on brand-imprinting effects. Through the interview, potential needs of customers were found. Based on the findings, marketing strategies that utilize interactive media installation for brand-imprinting effects have been constructed. First, to utilize a space for a medium of communication between customers and advertising media. Second, using storytelling as a construct that focuses on the individual's situation. Third, to design interactions that are proper to the situation and context.

• Journal of Internet Computing and Services
• /
• v.24 no.6
• /
• pp.137-144
• /
• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.