• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.113-119
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• 2014

The positioning accuracy of GNSS surveys deteriorates due to various error factor, and many users sometimes ignore Phase Center Variation (PCV) of antennas. IGS provides an ANTEX file which contains PCV correction information to correct for PCVs. But it is not directly applicable because PCV correction information is provided at 5-degree intervals in the azimuth and elevation directions for the case of receiver antennas, and at 1-degree intervals in the nadir angle for the case of satellite antennas. So, we devised new and optimal ways of interpolating PCV in any desired line of sight to the GNSS satellite. We used spherical harmonics fitting methods in terms of the azimuth and elevation angle for interpolation, and found an optimal degree and order. It is shown that the best accuracy was obtained from the 8 by 8 spherical harmonics. If one requires lower burden on computing resources, the order and degree less than 8 could produce resonable accuracy except for 1st and 5th order.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.125-144
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• 2006

The development of mobile applications is fast in recent years. However, nearly all applications are for messaging, financial, locating services based on simple interactions with mobile users because of the limited screen size, narrow network bandwidth, and low computing power. Processing an algorithm for supporting a group decision process on mobile devices becomes impossible. In this paper, we introduce the mobile-oriented simple interactive procedure for support a group decision making process. The interactive procedure is developed for multiple objective linear programming problems to help the group select a compromising solution in the mobile Internet environment. Our procedure lessens the burden of group decision makers, which is one of necessary conditions of the mobile environment. Only the partial weak order preferences of variables and objectives from group decision makers are enough for searching the best compromising solution. The methodology is designed to avoid any assumption about the shape or existence of the decision makers' utility function. For the purpose of the experimental study of the procedure, we developed a group decision support system in the mobile Internet environment, MOBIGSS and applied to an allocation problem of investor assets.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.1029-1044
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• 2017

The Discrete Element Method (DEM) is one of the useful numerical methods to analyze the behavior of the ground formation by computing the motion and interaction using particles. The DEM has not been applied in civil engineering but also a wide range of industrial fields, such as chemical engineering, pharmacy, material science, food engineering, etc. In this study, to review a performance of the spoke-type earth pressure balance (EPB) shield TBM (Tunnel Boring Machine), the commercial software based on the DEM technology was used. An analysis of the TBM during excavation was conducted according to two pre-defined excavation conditions with the different rotation speed of a cutterhead. During the analysis, the resistant torque at the face of the cutterhead, the compressive force at the cutterhead and shield surface, the muck discharge at the screw auger were measured and compared. Upon the two kinds of excavation conditions, the applicability of the DEM analysis was reviewed as a modelling method for the TBM.

• Journal of Internet Computing and Services
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• v.10 no.2
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• pp.171-177
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• 2009

Optical packet switching(OPS) is a strong candidate for the next-generation internet, since it has a fine switching granularity at the packet level for providing flexible bandwidth, and provides seamless integration between WDM layer and IP layer. Optical packet switching have been studied in two categories: OPS in synchronous and OPS in asynchronous networks. In this article we are focused on contention resolution of OPS in asynchronous networks. The hybrid buffer have been addressed, to reduce packet loss further as one of the alternative buffer structures for contention resolution of asynchronous and variable length packets, which consists of the FDL buffer and the electronic buffer. The OPS design issue for the limited number of TWCs and internal wavelengths is important in the aspect of switch cost and resource efficiency. Therefore, an hybrid buffer structured optical packet switch and its scheduling algorithm is presented for considering the limited number of TWCs and internal wavelengths, for contention resolution of asynchronous and variable length packets. The proposed algorithm could lead to the packet loss improvement compared to the legacy LAUC-VF algorithm with only the FDL buffer.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.427-435
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• 2005

With the accumulation of protein and its related data on the Internet, many domain based computational techniques to predict protein interactions have been developed. However, most of the techniques still have many limitations to be used in real fields. They usually suffer from a low accuracy problem in prediction and do not provide any interaction possibility ranking method for multiple protein pairs. In this paper, we reevaluate a domain combination based protein interaction prediction method and develop an interaction possibility ranking method for multiple protein pairs. Probability equations are devised and proposed in the framework of domain combination based protein interaction prediction method. Using the ranking method, one can discern which protein pair is more probable to interact with each other than other protein pairs in multiple protein pairs. In the validation of the ranking method, we revealed that there exist some correlations between the interacting probability and the precision of the prediction in case of the protein pair group having the matching PIP(Primary Interaction Probability) values in the interacting or non interacting PIP distributions.

• Journal of Legislation Research
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• no.53
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• pp.269-310
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• 2017

This article aims at the study on Improvement of legal System which is related to automated vehicles in the era of the 4th industrial revolution. Legal aspects of driving automation have two view points. One is to permit a automated vehicle, the other is to regulate the behavior of driver on the road. Signifying elements of the 4th industrial revolution are IoT, AI, big data, cloud computing etc. Automated vehicles are the imbodiment of those new ICT technologies. The vehicle management act(VMA) rules about vehicle registration and approval of vehicle types. VMA defines a automated vehicle as a vehicle which can be self driven without handling of driver or passenger. Vehicle makers can take temporary driving permission for testing and research the driving automation. Current definition of automated vehicle of VMA is not enough for including all levels of SAE driving automation. In the VMA must be made also a new vehicle safty standard for automated vehicle. In the national assembly is curruntly pending three draft bills about legislation of artificial intelligence. Driving automation and AI technologies must be parallel developed. It is highly expected that more proceeding research of driving automation can be realized as soon as possible.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.469-481
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• 2018

DL (Deep Learning) is getting popular in various fields to implement artificial intelligence that resembles human learning and cognition. DL based on complicate structure of the ANN (Artificial Neural Network) requires computing power and computation cost. Variety of DL models with improved performance have been developed with powerful computer specification. The main purpose of this paper is to detect buildings from aerial images and evaluate performance of Mask R-CNN (Region-based Convolutional Neural Network) developed by FAIR (Facebook AI Research) team recently. Mask R-CNN is a R-CNN that is evaluated to be one of the best ANN models in terms of performance for semantic segmentation with pixel-level accuracy. The performance of the DL models is determined by training ability as well as architecture of the ANN. In this paper, we characteristics of the Mask R-CNN with various types of the images and evaluate possibility of the generalization which is the ultimate goal of the DL. As for future study, it is expected that reliability and generalization of DL will be improved by using a variety of spatial information data for training of the DL models.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.1-11
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• 2021

The purpose of our research is to efficiently deform a 3D models which is composed of a triangular mesh and a skeleton. We designed a novel inverse kinematics (IK) solver that calculates the updated positions of mesh vertices with fewer computing operations. Through our user interface, one or more markers are selected on the surface of the model and their target positions are set, then the system updates the positions of surface vertices to construct a deformed model. The IK solving process for updating vertex positions includes many computations for obtaining transformations of the markers, their affecting joints, and their parent joints. Many of these computations are often redundant. We precompute those redundant terms in advance so that the 3-nested loop computation structure was improved to a 2-nested loop structure, and thus the computation time for a deformation is greatly reduced. This novel IK solver can be adopted for efficient performance in various research fields, such as handling 3D models implemented by LBS method, or object tracking without any markers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1423-1431
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• 2022

Volatility is one of the variables that the Black-Scholes model requires for option pricing. It is an unknown variable at the present time, however, since the option price can be observed in the market, implied volatility can be derived from the price of an option at any given point in time and can represent the market's expectation of future volatility. Although volatility in the Black-Scholes model is constant, when calculating implied volatility, it is common to observe a volatility smile which shows that the implied volatility is different depending on the strike prices. We implement supervised learning to target implied volatility by adding V-KOSPI to ease volatility smile. We examine the estimation performance of KOSPI200 index options' implied volatility using various Machine Learning algorithms such as Linear Regression, Tree, Support Vector Machine, KNN and Deep Neural Network. The training accuracy was the highest(99.9%) in Decision Tree model and test accuracy was the highest(96.9%) in Random Forest model.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.107-114
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• 2022

In this paper, availabilities of student-evaluations of team activities in the computer science basic classes were analysed. For the purpose, correlation analysis was conducted to investigate the relationships among peer-evaluation, self-evaluation, and academic achievement, and it was found that there was a statistically significant positive correlation among them. Moreover, the gap between peer-evaluation scores and self-evaluation scores was analyzed. When a one-sample t-test was performed, it was found that the gap was very significant. However, the size of the gap was not different between the two classes. That is, regardless of grade level, the students' self-evaluation scores tended to be on average higher than the evaluation scores received from peers. Finally, when analyzing the relationship between the gap in peer-evaluation and self-evaluation scores and academic achievement, there was no significant correlation between the gap in scores and academic achievement. In other words, there was no difference in the tendency of evaluation for students with high or low academic achievement. The results of the analysis shows the availability of student-evaluations of team activities in the evaluation of team-based instruction. The high correlation between self-evaluation and peer-evaluation indicates the objectivity of student-evaluation. Although it is clear that the self-evaluation score is higher on average than the score received from peers, it is more useful in terms of objectivity because it does not vary according to grade, subject, or academic achievement.