Yun Jin-Il;Choi Jae-Yeon;Yoon Young-Kwan;Chung Uran
Korean Journal of Agricultural and Forest Meteorology
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v.2
no.4
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pp.175-182
/
2000
Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.
Kim Young-Man;Park Hong-Jae;Han Wang-Won;Choi Wan;Heo Seong-Jin
The KIPS Transactions:PartC
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v.13C
no.4
s.107
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pp.501-510
/
2006
Software streaming allows the execution of stream-enabled software on desktop or portable computing devices like PC, PDA, laptop, cellular phone, etc., even while the transmission/streaming from the server may still be in progress. In this paper, we present an efficient streaming system called Software On-Demand(SOD) streaming system to transmit stream-enabled applications in addition to automatic installation of program registry, environment variables, configuration files, and related components. In particular, we design and implement a SOD system in Linux to provide the user with the instant look-and-click software execution environment such that software download and installation are internally proceeded in a completely user-transparent way. Therefore, the SOD system relieves the user from the tricky, failure-prone installation business. In addition, the software developer now obtains a new, powerful means to advertise and propagate their software products since the user can use software packages via user-friendly UI window or web browser by look-and-click interactive operation. In the paper, we also make a couple of SOD streaming experiments using a spectrum of popular softwares. Based on the analysis of the experiment results, we also propose two performance improvement schemes.
Journal of the Korea Society of Computer and Information
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v.26
no.12
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pp.151-158
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2021
Internet of Things (IoT) technology, which provides services by connecting various objects in the real world and objects in the virtual world based on the Internet, is emerging as a technology that enables a hyper-connected society in the era of the 4th industrial revolution. Since IoT technology is a convergence technology that encompasses devices, networks, platforms, and services, various studies are being conducted. Among these studies, studies on measures that can measure service quality provided by IoT software are still insufficient. IoT software has hardware parts of the Internet of Things, technologies based on them, features of embedded software, and network features. These features are used as elements defining IoT software quality measurement metrics. However, these features are considered in the metrics related to IoT software quality measurement so far. Therefore, this paper presents a metric for reusability measurement among various quality factors of IoT software in consideration of these factors. In particular, since IoT software is used through IoT devices, services in IoT software must be designed to be changed, replaced, or expanded, and metrics that can measure this are very necessary. In this paper, we propose three metrics: changeability, replaceability, and scalability that can measure and evaluate the reusability of IoT software services were presented, and the metrics presented through case studies were verified. It is expected that the service quality verification of IoT software will be carried out through the metrics presented in this paper, thereby contributing to the improvement of users' service satisfaction.
Park, Min-Chul;Ha, Tae-Jun;Kwon, Sung-Dae;Oh, Seok-Jin
KSCE Journal of Civil and Environmental Engineering Research
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v.39
no.1
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pp.93-103
/
2019
In metropolitan cities have been reorganizing the routes of the city buses periodically due to changes in the spatial structure and traffic pattern and the lack of supply due to new developments. However, there is a lack of system to comprehensively evaluate the routes. Even if the evaluation index is not clearly defined, it may not be reasonable. Therefore, it is difficult to set the improvement direction when the bus route is reorganized. In this study, the existing evaluation indexes were reviewed and further investigation was conducted on the problematic indexes. In particular, the degree of curvature has been used as a very important index in the evaluation of the route system, but the existing curvature based curvature has a limitation in considering the traffic characteristics of individual users. For this purpose, a virtual city bus network was set up and the degree of curvature was calculated and compared based on the point - based curvature and stopping point based on individual user O/D. In this study, it is considered that more efficient and practical analysis and evaluation are possible in the evaluation of the city bus route system through the curvature considering the individual user O/D based on the stopping point. It is expected that it will be used at the time of reorganization of city bus route performed by individual local governments in the future.
Seo, Dong-Nam;Woo, Ji-Young;Woo, Kyung-Moon;Kim, Chong-Kwon;Kim, Huy-Kang
Journal of the Korea Institute of Information Security & Cryptology
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v.22
no.3
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pp.585-600
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2012
Security issues in online games are increasing as the online game industry grows. Real money trading (RMT) by online game users has become a security issue in several countries including Korea because RMT is related to criminal activities such as money laundering or tax evasion. RMT-related activities are done by professional work forces, namely gold-farmers, and many of them employ the automated program, bot, to gain cyber asset in a quick and efficient way. Online game companies try to prevent the activities of gold-farmers using game bots detection algorithm and block their accounts or IP addresses. However, game bot detection algorithm can detect a part of gold-farmer's network and IP address blocking also can be detoured easily by using the virtual private server or IP spoofing. In this paper, we propose a method to detect gold-farmer groups by analyzing their connection patterns to the online game servers, particularly information on their routing and source locations. We verified that the proposed method can reveal gold-farmers' group effectively by analyzing real data from the famous MMORPG.
Journal of the Korea Society of Computer and Information
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v.27
no.3
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pp.53-61
/
2022
Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.
The Journal of the Convergence on Culture Technology
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v.7
no.4
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pp.449-460
/
2021
The development process of cyber literature theory in the 1990s clearly shows the duality of the pursuit of symbolic power and desire through the formation and conflict of literary fields, collective intelligence. All desires are bound to be power-oriented, and cyber literature is meaningful in that network-space critics developed while advocating the humanities of coexistence. The failure of cyber literature theory is due to the conflicting desire of critical power between real and virtual spaces. Cyber literature theory in the 1990s was the first literary response to the birth of artificial nature, although the contradiction of desires revealed in symbolic power and the limitations of barking are clear. Literature discourse has always explored the relationship between the social conditions of the time (including technological progress) and art texts. Producing a new critical discourse encompassing the whole within the literary field of artificial nature is an important task in literature in the era of technology compilation, and humanities and technology must coexist. Through this paper, we examined the impact of the birth of artificial nature on humanities. This study is an important achievement of humanities engineering that understands, interprets, and leads technology.
Journal of Korean Society of Industrial and Systems Engineering
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v.45
no.2
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pp.48-55
/
2022
The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.
Eui Jung Kim;Won Joon Lee;Do Ha Jeong;Sung Mi Cho;Jung Hyun Chae
Human Ecology Research
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v.61
no.4
/
pp.673-686
/
2023
The purpose of this study was to identify home economics (HE) teachers' concerns about and perceptions of HE education using the latest technologies in the era of the 4th Industrial Revolution and to reveal whether they differ according to teachers' general background variables. The questionnaire survey method to measure HE teachers' concerns and perceptions of HE education using the latest technologies in the era of the 4th Industrial Revolution was conducted online using the Google Questionnaire from which 150 responses were received. The main results were as follows. Firstly, HE teachers scored an average of 3.46 out of 5 for the latest technology. Among these interests in the latest technology, interest in "augmented reality and virtual reality technologies" scored the highest at an average of 3.80, while interest in "neural network machine learning" (2.78) was low. HE teacher's concerns about HE education using the latest technologies in the era of the 4th Industrial Revolution were high, with an average score of 4.40. Among these concerns for the latest technology, "concern about the results of HE education using the latest technology" scored the highest at 4.53. HE teachers' anxiety about the latest teaching technology in the era of the 4th Industrial Revolution was moderate, averaging 3.05. The highest form of anxiety was "anxiety about the impact on the job" (4.03) and the lowest was fear of "the disappearance of the teacher's job" (2.50). HE teachers' innovation resistance to the latest teaching technology was low at 2.18. Expectations of the latest technology in HE classes in the era of the 4th Industrial Revolution averaged 3.85, slightly higher than the middle of 3.
Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).
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