• Proceedings of the Korea Port Economic Association Conference
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• 2006.08a
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• pp.1-12
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• 2006

As national economies globalize, demand for intercontinental container shipping services is growing rapidly, providing a potential economic boon for the countries and communities that provide port services. On the promise of profits, many governments are investing heavily in port infrastructure, leading to a possible glut in port capacity, driving down prices for port services and eliminating profits as ports compete for business. Further, existing ports are making strategic investments to protect their market share, increasing the chance new ports will be overcapitalized and unprofitable. Governments and port researchers need a tool for understanding how local competition in their region will affect demand for port services at their location, and thus better assess the profitability of a prospective port. We propose to develop such a tool by extending our existing simulation model of global container traffic to incorporate demand-side shipper preferences and supply-side strategic responses by incumbent ports to changes in the global port network, including building new ports, scaling up existing ports, and unexpected port closures. We will estimate shipper preferences over routes, port attributes and port services based on US and international shipping data, and redesign the simulation model to maximize the shipper's revealed preference functions rather than simply minimize costs. As demand shifts, competing ports will adjust their pricing (short term) and infrastructure (long term) to remain competitive or defend market share, a reaction we will capture with a game theoretic model of local monopoly that will predict changes in port characteristics. The model's hypotheses will be tested in a controlled laboratory experiment tailored to local port competition in Asia, which will also serve to demonstrate the subtle game theoretic concepts of imperfect competition to a policy and industry audience. We will apply the simulation model to analyze changes in global container traffic in three scenarios: addition of a new large port in the US, extended closure of an existing large port in the US, and cooperative and competitive port infrastructure development among Korean partner countries in Asia.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Korean Journal of Breeding Science
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• v.42 no.3
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• pp.226-230
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• 2010

'Gwanghan' (Avena sativa L.), a winter oat for forage use, was developed by the breeding team at the Department of Rice and Winter Cereal Crop, NICS, RDA in 2009. It was derived from a cross between 'Early80' and 'Gwiri23'. A parent, 'Early80', has early heading and high yielding, while Gwiri23 has mid-heading with large-size grain. Subsequent generations followed by the cross were handled in bulk and pedigree selection programs at Suwon and Yeoncheon, respectively. A line, 'SO96016-B-112-YB-12-7', was selected for earliness, cold tolerance, and good agronomic characteristics and designated as a line name of 'Gwiri64'. The line was subsequently evaluated for cold tolerance, earliness, and forage yield in four different locations, Yesan, Iksan, Kimjae, and Jeju, from 2007 to 2009, and finally named as 'Gwanghan'. Over 3 years, the average forage dry matter yield of 'Gwanghan' harvested at milk-ripe stage was $16.4MT\;ha^{-1}$, compared with $15.4MT\;ha^{-1}$ of check cultivar 'Samhan'. 'Gwanghan's' heading date is about 3 days earlier than that of check cultivar, and is adapted primarily for winter cultivation in the mid-southern regions of Korean peninsula.

• Korean Journal of Breeding Science
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• v.42 no.3
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• pp.231-235
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• 2010

'Jopung' (Avena sativa L.), a winter oat for forage use, was developed by the breeding team at the Department of Rice and Winter Cereal Crop, NICS, RDA in 2009. It was derived from an original cross between the $F_1$ hybrid of 'Early80' and 'PA202-210-S' and 'Walken' in 1999. Subsequent generations followed by the cross were handled in bulk and pedigree selection programs at Suwon and Yeoncheon, respectively. A line, 'SO99006-B-YB-29-Y1', was selected for earliness and good agronomic characteristics and designated as a line name of 'Gwiri65'. The line 'Gwiri65' was subsequently evaluated for earliness and forage yield in four different locations, Yesan, Iksan, Kimjae, and Jeju, from 2007 to 2009 and finally named as 'Jopung'. Over 3 years, the average forage dry matter yield of cultivar 'Jopung' harvested at milk-ripe stage was $17.3MT\;ha^{-1}$, compared with $13.6MT\;ha^{-1}$ of check cultivar 'Swan'. The silage quality of 'Jopung' was superior to the check cultivar 'Swan' in crude protein content, and was similar to the check cultivar in percent total digestible nutrients (TDN). Cultivar 'Jopung' is suitable primarily for winter planting in the southern regions of Korean peninsula.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.405-411
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• 2019

The purpose of the study is to investigate a usability of using fashion and beauty service and suggest better user experience on Instagram's newly released mobile video platform, IGTV. The study expects to be a resource of improving the usability on fashion and beauty contents on IGTV and encourage further research for suggesting better guidelines. As a research method, it will experiment current mobile video service first with literature review. Afterwards, the research conducted tasks and in-depth interview with eight Instagram users to evaluate a usability of using fashion and beauty service on IGTV. As a result, it is able to derive two plans that needed improvement. Firstly, IGTV is required to have high accessibility for user's to use service longer and intuitive user experience. Secondly, unlike previous service that Instagram have offered, IGTV need to differentiate to share and get information of fashion and beauty trends.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.141-158
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• 2013

In this study, the projection of future heating and cooling degree days (HDDs and CDDs) has been conducted over South Korea for the period 1996~2005 with 2046~2055 and 2091~2100, using CCSM3 and MM5 simulations driven by the six IPCC SRES emission scenarios (A2, A1B, A1FI, A1T, B1, and B2). Annual mean surface air temperature increases by $1.2{\sim}3.4^{\circ}C$ at the end of the 21st century comparing to the present-day (1996~2005) in South Korea. HDDs decrease by 8~25% and CDDs increase up to 242~1,448% with corresponding changes in temperature. These increases and decreases also change the duration of HDDs and CDDs. HDDs duration decreases by 1 month, while the expansion of CDDs duration is much longer than 2 months. Thus, projected future HDDs and CDDs changes appear that cooling energy demand in summer season would increase and heating energy demand in winter would decrease in the future. Especially, these remarkable changes would be obvious at high mountain area, Gangwon-do and at south area, Jeju island. In the sense of future energy supply and policy, electrical energy for cooling in summer could be getting much more its importance rather than fossil energy used for heating in winter.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.283-292
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• 2018

UHD (Ultra High Definition) broadcasting technology, and UWV (Ultra Wide Vision) which is the high quality panoramic video of wide view angle based on UHD, were commercialized in Korea for the first time in the world, and those are representative realistic video technologies that maximize the user's sense of presence. By comparing the user's subjective reaction of UHD and UWV, the purpose of this study is to systematically establish the user's subjective video quality evaluation. For this purpose, a large screen projection experiment is designed by setting the screen size (4k x 2k, 8k x 2k) and content types (sports, landscape, concert) as variables to measure the user's subjective video quality evaluation and satisfaction. As a result of the study, the users' evaluation of UWV was higher than UHD in all items of subjective video quality, and satisfaction. Moreover, the results showed the significant differences depending on the video contents. Based on the results of the research, the study proposed the points necessary for the development and commercialization of UWV panoramic technology, and suggestions for the future research.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.239-247
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• 2019

An accurate prediction of emotion is a very important issue for the sake of patient-centered medical device development and emotion-related psychology fields. Although there have been many studies on emotion prediction, no studies have applied the heart rate variability and neuro-fuzzy approach to emotion prediction. We propose ANFEP(Adaptive Neuro Fuzzy System for Emotion Prediction) HRV. The ANFEP bases its core functions on an ANFIS(Adaptive Neuro-Fuzzy Inference System) which integrates neural networks with fuzzy systems as a vehicle for training predictive models. To prove the proposed model, 50 participants were invited to join the experiment and Heart rate variability was obtained and used to input the ANFEP model. The ANFEP model with STDRR and RMSSD as inputs and two membership functions per input variable showed the best results. The result out of applying the ANFEP to the HRV metrics proved to be significantly robust when compared with benchmarking methods like linear regression, support vector regression, neural network, and random forest. The results show that reliable prediction of emotion is possible with less input and it is necessary to develop a more accurate and reliable emotion recognition system.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.137-143
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• 2019

Fake news is a form of misinformation that has the advantage of rapid spreading of information on media platforms that users interact with, such as social media. There has been a lot of social problems due to the recent increase in fake news. In this paper, we propose a method to detect such false news. Previous research on fake news detection mainly focused on text analysis. This research focuses on a network where social media news spreads, generates qualities with DeepWalk, a network embedding method, and classifies fake news using logistic regression analysis. We conducted an experiment on fake news detection using 211 news on the Internet and 1.2 million news diffusion network data. The results show that the accuracy of false network detection using network embedding is 10.6% higher than that of text analysis. In addition, fake news detection, which combines text analysis and network embedding, does not show an increase in accuracy over network embedding. The results of this study can be effectively applied to the detection of fake news that organizations spread online.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.245-251
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• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.