• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.2
• /
• pp.93-103
• /
• 2023

Warships widely spread numerous chaffs using a blast, which form chaff clouds that create false radar cross-sections to deceive enemy radars. In this study, we established a numerical framework based on a one-way coupling of computational fluid dynamics and discrete element method to simulate the spatiotemporal distribution of chaff clouds for warships in the air. Using the framework, we investigated the effects of wind, initial chaff cartridge angle, and blast pressure on the distribution of chaff clouds. We observed three phases for the chaff cloud diffusion: radial diffusion by the explosion, omnidirectional diffusion by turbulence and collision, and gravity-induced diffusion by the difference in the fall speed. The wind moved the average position of the chaff clouds, and the diffusion due to drag force did not occur. The direction of radial diffusion by the explosion depended on the initial angle of the cartridge, and a more vertical angle led to a wider distribution of the chaffs. As the blast pressure increased, the chaff clouds spread out more widely, but the distribution difference in the direction of gravity was not significant.

• Geophysics and Geophysical Exploration
• /
• v.26 no.2
• /
• pp.62-76
• /
• 2023

Recently, machine learning (ML) techniques have been actively applied for seismic trace interpolation. However, because most research is based on training-inference strategies that treat missing trace gather data as a 2D image with a blank area, a sufficient number of fully sampled data are required for training. This study proposes trace interpolation using ML, which uses only irregularly sampled field data, both in training and inference, by modifying the training-inference strategies of trace-based interpolation techniques. In this study, we describe a method for constructing networks that vary depending on the maximum number of consecutive gaps in seismic field data and the training method. To verify the applicability of the proposed method to field data, we applied our method to time-migrated seismic data acquired from the Vincent oilfield in the Exmouth Sub-basin area of Western Australia and compared the results with those of the conventional trace interpolation method. Both methods showed high interpolation performance, as confirmed by quantitative indicators, and the interpolation performance was uniformly good at all frequencies.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.2
• /
• pp.195-211
• /
• 2023

For the commercialization For the commercialization of autonomous vehicles (AV), the operational design domain (ODD) of automated driving systems (ADS) is to be clearly defined. A common language and consistent format must be prepared so that AV-related stakeholders can understand ODD at the same level. Therefore, overseas countries are presenting a standardized ODD framework and developing scenarios that can evaluate ADS-specific functions based on ODD. However, ODD includes conditions reflecting the characteristics of each country, such as road environment, weather environment, and traffic environment. Thus, it is necessary to clearly understand the meaning of the items defined overseas and to harmonize them to reflect the specific domestic conditions. Therefore, in this study, domestic optimization of the ODD classification system was performed by analyzing the domestic driving environment based on international standards. The driving environment of currently operating self-driving car test districts (Sangam, Seoul, and Gwangju) was investigated using the developed domestic ODD items. Then, based on the results obtained, the ranges of the ODDs in each test district were determined and compared.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.9
• /
• pp.135-145
• /
• 2009

Generally, the phases of constructing information systems are consisted of systems planning and selection, system analysis, system design, and system implementation and operation. These systems require many efforts and costs for additional development of modification requirements due to a frequent changes of business environments and business processes. Especially, inconsistencies between system design and system implementation usually happen during development steps because of the difficulties of program developments due to difficulties of capturing exact user requirements and frequent changes of user requirements. This paper proposes a scheme of implementing meta-data based applications for enterprises in order to reduce inconsistencies between system design and system implementation and to overcome limits of the existing coding-based development methods of applications which must use until disuse if they are developed once. Also, this paper presents a framework of repository system to systematically manage and utilize meta-data. The core concept of the proposed scheme makes outputs generated in the phases of system analysis and design into meta-data and is to easily develop and customize application programs using meta-data repository. Also, to show the applicability of the proposed scheme, it is applied to implement ERP system of 'H' automotive part manufacturer. As a result, the proposed scheme can gain improvements such as easiness and productivity of program development, easiness of maintenance, reusability of program components, etc.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.2
• /
• pp.9-16
• /
• 2009

While the broadband network and multimedia technology are being developed, the commercial market of digital contents as well as using IPTV has been widely spreading. In this background, Time-Shift system is developed for requirement of multimedia. This system is independent of Time but is not independent of Place and Occasion. For solving these problems, in this paper, we propose the TPO(Time, Place, Occasion)-Shift system for mobile multimedia devices. The profile that can be applied to the mobile multimedia devices is much different from that of the setter-box. And general mobile multimedia devices could not have such large memories that is for multimedia data. So it is important to continuously store and manage those multimedia data in limited capacity with mobile device's profile. Therefore we compose the basket in a way using defined time unit and manage these baskets for effective buffer management. In addition. since the file name of basket is made up to include a basket's time information, we can make use of this time information as DTS(Decoding Time Stamp). When some multimedia content is converted to be available for portable multimedia devices, we are able to compose new formatted contents using such DTS information. Using basket based buffer systems, we can compose the contents by real time in mobile multimedia devices and save some memory. In order to see the system's real-time operation and performance, we implemented the proposed TPO-Shift system on the basis of mobile device, MS340. And setter-box are desisted by using directshow player under Windows Vista environment. As a result, we can find the usefulness and real-time operation of the proposed systems.

• Journal of the Korean Society for information Management
• /
• v.39 no.1
• /
• pp.309-330
• /
• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

• Journal of Cadastre & Land InformatiX
• /
• v.52 no.2
• /
• pp.17-34
• /
• 2022

With rapid advancements taking place in the Fourth Industrial Revolution, human-robot interactions have been garnering increasing attention. Robots are being actively adopted in building systems and facilities. In this study, we developed robot-friendly building certification indicators. Because these indicators were being developed for the first time, we focused only on commercial buildings. We conducted exploratory research using methodologies such as focus group interviews and the analytic hierarchy process. First, the concept of the robot-friendly building was defined through focus group interviews, and the requirements were categorized by the appropriateness of operating facilities and systems and the appropriateness of architectural and robot operating systems and networks. Next, the relative importance of the evaluation items (23 items in total) was calculated using the analytic hierarchy process. Their average score of the marks was 4.4, and the minimum and maximum were 2.0 and 11.3, respectively. This study is significant because we collected the basic data necessary to develop a one-of-its-kind evaluation system for certifying the robot-friendliness of buildings using scientific methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.51-57
• /
• 2023

Smart mirror is an IoT device that attaches a display and an embedded computer to the mirror and provides various information to the user along with the mirror function. This paper presents performance evaluation of the CoMirror system as an extension of the previous research in which proposed and implemented the CoMirror system that connects Smart Mirrors using a network. First, the login performance utilizing face recognition was evaluated. As result of the performance evaluation, it was concluded that the 40 face images are most suitable for face learning and only one face image is most suitable for face recognition for login. Second, as a result of evaluating the message transmission time, the average time was 0.5 seconds for text, 0.63 seconds for audio, and 2.9 seconds for images. Third, as a result of measuring a video communication performance, the average setup time for video communication was 1.8 seconds and the average video reception time was 1.9 seconds. Finally, according to the performance evaluation results, we conclude that the CoMirror system has high practicality.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.133-145
• /
• 2022

Compared to the continuously increasing dog population and industry size in Korea, systematic analysis of related data and research on breed classification methods are very insufficient. In this paper, an automatic breed classification method is proposed using deep learning technology for 14 major dog breeds domestically raised. To do this, dog images are collected for deep learning training and a dataset is built, and a breed classification algorithm is created by performing transfer learning based on VGG-16 and Resnet-34 as backbone networks. In order to check the transfer learning effect of the two models on dog images, we compared the use of pre-trained weights and the experiment of updating the weights. When fine tuning was performed based on VGG-16 backbone network, in the final model, the accuracy of Top 1 was about 89% and that of Top 3 was about 94%, respectively. The domestic dog breed classification method and data construction proposed in this paper have the potential to be used for various application purposes, such as classification of abandoned and lost dog breeds in animal protection centers or utilization in pet-feed industry.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.197-216
• /
• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.