• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.37-51
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• 2010

In this paper, we discuss the program implementation and system optimization for the effective transfer of huge amount of data. In VLBI which is observing the celestial bodies by using radio telescope hundreds thousands km apart, it is necessary for each VLBI observatory to transfer up to terabytes of observed data. For this reason, e-VLBI research based on advanced network is being actively carried out for the transfer of data efficiently. Following this trend, in this paper, we discuss design & implementation of system for the high speed Gbps data transfer rates. As a data transfer protocol, we use UDP for designing data transmission program with much higher speeds than currently available via VTP(VLBI Transport Protocol). Tsunami-UDP algorithms is applied to implementing data transfer program so that transmission performance could be maximize, also we make it possible to transfer observed data more fast and reliable through optimization of computer systems in each VLBI statopm.

• Korean Journal of Social Welfare Studies
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• v.42 no.2
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• pp.467-491
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• 2011

The purpose of this study is to examine relationship between social strains such as status strains and relational strains and adolescent suicidality by gender. As method, a self-report survey was completed by students (n = 819) from 3 middle schools in Seodaemun area, Seoul, Korea. Logistic regression analyses were conducted to identify factors associated with adolescent suicidality, t-test analyses were used to verify gender difference. Results show that male adolescents are more likely to experience abuse from their father, and school violence related to relational strains than female. Differences were found in strains for males and females contributing to suicidality; male are responsive to economic status, a dimension of status strain, whereas female are reactive to non-physical abuse from father, a type of relational strains. Non-physical school violence was appeared to be a significant factor influencing suicidality for both genders. Based on these findings, research draws implications for social work interventions. First, different approaches by gender are needed to prevent adolescent suicide in consideration of the tendency that men are status-oriented and women are relationship-oriented. Second, it is suggested to hire full-time school social worker to provide consistent social service for students. Third, intensive effort is necessary to reduce non-physical school violence.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.189-198
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• 2023

As crimes frequently occur on the street, the spread of CCTV is increasing. However, due to the shortcomings of passively operated CCTV, the need for intelligent CCTV is attracting attention. Due to the heavy system of such intelligent CCTV, high-performance devices are required, which has a problem in that it is expensive to replace the general CCTV. To solve this problem, an intelligent CCTV system that recognizes low-quality images and operates even on devices with low performance is required. Therefore, this paper proposes a Saying CCTV system that can detect threats in real time by using the AWS cloud platform to lighten the system and convert images into text. Based on the data extracted using YOLO v4 and OpenPose, it is implemented to determine the risk object, threat behavior, and threat situation, and calculate the risk using machine learning. Through this, the system can be operated anytime and anywhere as long as the network is connected, and the system can be used even with devices with minimal performance for video shooting and image upload. Furthermore, it is possible to quickly prevent crime by automating meaningful statistics on crime by analyzing the video and using the data stored as text.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.469-483
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• 2022

This paper aims to examine how and why the role of Seoul National University has evolved through the formation of Seoul National University's entrepreneurial ecosystems (SNUEEs). To identify this, we used secondary data on SNU entrepreneurship and did in-depth interviews with 17 student entrepreneurs and supportive actors in the ecosystems. First, the university-industry cooperation policy and the first start-up boom in the late 1990s gave rise to the first generation of SNUEEs. They entered the second generation with the second start-up boom in 2010. The third generation emerged through the government's start-up support policy and the venture investment market revitalization in 2017. Second, SNUEEs have experienced transformations of the university's role from an 'ivory tower' to a 'feeder of knowledge and labor' and have become a 'hub of knowledge networks.' Third, hub institutions and organizations were established and supported by government policies, and networks of SNUEEs have been embedded in these hub institutions and organizations. SNUEEs as a hub university are evolving through the formation of a voluntary entrepreneurial culture by student entrepreneurs, the supportive policy at the university level, and the establishment of linkages with the region where the university is located.

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

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.9-16
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• 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
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• v.39 no.1
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• pp.309-330
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• 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
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• v.52 no.2
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• pp.17-34
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• 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
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• v.23 no.3
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• pp.51-57
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• 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
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• v.27 no.1
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• pp.133-145
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• 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.