• Journal of Korea Game Society
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• v.17 no.6
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• pp.19-28
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• 2017

There exist a variety of VR(Virtual Reality) contents that have been developed by the use of the latest VR technologies. Unlike the rapid advances in the recent VR devices however, the development of VR based game contents that fully utilize such cutting-edge devices has been lackluster. Using more accessible form of smartphone-based HMDs(Head-Mounted Displays), we compare two popular VR presentation methods(a realistic 3D VR karaoke room and a 360 degree video karaoke room) and analyze their users' immersion and realistic perception. We expect that our study can be utilized as a supporting guideline for future smartphone-based VR content developments.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.107-118
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• 2010

The user interface is the medium, which provides the users to have an access to the web-based information system. The user interface is the means of improving usability and accessibility for the user, as well as being the core component in the web-based information system. In this paper, the audit framework of the user interface was developed to upgrade the usability and accessibility; it was based on the three basic components of the current audit framework in the web-based information system. At the time of an audit, the UI process of the 'Analysis', 'UI Design', 'UI Production', and 'Test' was defined, which was analyzed through the web development methodology. Also, for the area of an audit, the 'Information', 'Design', and 'Technology' were defined by the analysis of the components that makes up the user interface, From the view of an audit, the standard criteria of an assessment were set as 'Usability', 'Accessibility', and 'Cross Browsing'. Through the framework that was proposed in this paper, practical audit applies the performed examples. By this, the efficiency of the proposed framework was verified.

• Journal of Dairy Science and Biotechnology
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• v.32 no.1
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• pp.17-29
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• 2014

GRAS probiotics can be used to modulate intestinal microbiota and to alleviate various gastrointestinal disorders. In several recent studies, researchers have explored the potential expansion and usability of probiotics to reduce the risk factors associated with diseases, including obesity, hypercholesterolemia, arterial hypertension, hyperhomocysteinemia, and oxidative stress. In this review, our aim was to clarify the mechanism underlying interactions between hosts (animal or human) and probiotics and the beneficial effects of probiotics on human health.

• The KIPS Transactions:PartA
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• v.18A no.5
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• pp.193-204
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• 2011

Since web applications are accessed by anonymous users via web, more security risks are imposed on those applications. In particular, because security vulnerabilities caused by insecure source codes cannot be properly handled by the system-level security system such as the intrusion detection system, it is necessary to eliminate such problems in advance. In this paper, to enhance the security of web applications, we develop a static analyzer for detecting the well-known security vulnerability of PHP file inclusion vulnerability. Using a semantic based static analysis, our vulnerability analyzer guarantees the soundness of the vulnerability detection and imposes no runtime overhead, differently from the other approaches such as the penetration test method and the application firewall method. For this end, our analyzer adopts abstract interpretation framework and uses an abstract analysis domain designed for the detection of the target vulnerability in PHP programs. Thus, our analyzer can efficiently analyze complicated data-flow relations in PHP programs caused by extensive usage of string data. The analysis results can be browsed using a JAVA GUI tool and the memory states and variable values at vulnerable program points can also be checked. To show the correctness and practicability of our analyzer, we analyzed the source codes of open PHP applications using the analyzer. Our experimental results show that our analyzer has practical performance in analysis capability and execution time.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.99-109
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• 2015

The investment in healthcare industry has recently increased not only for global ventures but also for the domestic ventures. However, there has been hardship of founding and investment caused by healthcare startups characteristics that are costly and time consuming. In this study, the applicability of 'Lean Startup' theory to healthcare ventures was explored through the case of a domestic startup which accomplished funding from VC and KOSDAQ after establishing based on its technology in healthcare industry. There have been numerous case studies that applied 'Lean Startup' to IT industry. However, this case study that applied 'Lean Startup' to healthcare industry have some implications as follow: First, it is critical to conduct a hypothesis testing at initial research stage through R&D of 'MVP' (Minimum Viable Product) as the prototype testing is strictly prohibited in healthcare industry. Second, healthcare R&D teams ought to be well organized as startup teams and all researchers should be equipped with entrepreneurship as the licensing process in healthcare industry is time-consuming and costly due to issues like clinical studies. Lastly, management skills as smart and light as 'Lean Startup' are required in order to encourage young engineers' technology startups.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.3
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• pp.229-238
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• 2013

Development of methodologies to generate the small scale map from the large scale map using map generalization has huge importance in management of the digital topographic map, such as producing and updating maps. In this study, the selection methodology of map generalization for the road network data in digital topographic map is investigated and evaluated. The existing maps with 1:5,000 and 1:25,000 scales are compared and the criteria for selection of the road network data, which are the number of objects and the relative importance of road network, are analyzed by using the T$\ddot{o}$pfer's radical law and Logit model. The selection model derived from the analysis result is applied to the test data, and the road network data of 1:18,000 and 1:72,000 scales from the digital topographic map of 1:5,000 scale are generated. The generalized results showed that the road objects with relatively high importance are selected appropriately according to the target scale levels after the qualitative and quantitative evaluations.

• Resources Recycling
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• v.26 no.2
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• pp.46-55
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• 2017

In this study, the design methodology of Radial Basis Function Neural Networks is developed with the aid of Laser Induced Breakdown Spectroscopy and also applied to the practical plastics sorting system. To identify black plastics such as ABS, PP, and PS, RBFNNs classifier as a kind of intelligent algorithms is designed. The dimensionality of the obtained input variables are reduced by using PCA and divided into several groups by using K-means clustering which is a kind of clustering techniques. The entire data is split into training data and test data according to the ratio of 4:1. The 5-fold cross validation method is used to evaluate the performance as well as reliability of the proposed classifier. In case of input variables and clusters equal to 5 respectively, the classification performance of the proposed classifier is obtained as 96.78%. Also, the proposed classifier showed superiority in the viewpoint of classification performance where compared to other classifiers.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.65-76
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• 2004

This study aims to estimate daily maximum air temperature estimated using satellite-derived surface temperature and Elevation Derivative Database (EDD). The analysis is focused on the establishment of a semi-empirical estimation technique of daily maximum air temperature through the multiple regression analysis. This tests the contribution of EDD in the air temperature estimation when it is added into regression model as an independent variable. The better correlation is shown with the EDD data as compared with the correlation without this data set. In order to provide a progressive estimation technique, we propose and compare three approaches: 1) seasonal estimation non-considering landcover, 2) seasonal estimation considering landcover, and 3) estimation according to landcover type and non-considering season. The last method shows the best fit with the root-mean-square error between 0.56$^{\circ}C$ and 3.14$^{\circ}C$. A cross-validation procedure is performed for third method to valid the estimated values for two major landcover types (cropland and forest). For both landcover types, the validation results show reasonable agreement with estimation results. Therefore it is considered that the estimation technique proposed may be applicable to most parts of South Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.129-143
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• 2019

As the importance of autonomous vehicle safety is emphasized, the application of ISO-26262, a development verification guideline for improving safety and reliability, and the safety verification of autonomous vehicles are becoming increasingly important, in particular, SAE standard level 3 or higher level autonomous vehicles detect and decision the surrounding environment instead of the human driver. Therefore, if there is and failure or malfunction in the autonomous driving function, safety may be seriously affected. So autonomous vehicles, it is essential to apply and verity the safety concept against failure and malfunctions. In this study, we study the fault injection scenarios for safety evaluation and verification of autonomous vehicles using ISO-26262 part3 process and STPA were studied and safety measures for safety concept design were studied through simulation bases fault injection test.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.37-51
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• 2023

Spatial information is essential for interpreting urban phenomena. Methodologies for spatializing urban information, especially when it lacks location details, have been consistently developed. Typical methods include Geocoding using structured address information or place names, spatial integration with existing geospatial data, and manual tasks utilizing reference data. However, a vast number of documents produced by administrative agencies have not been deeply dealt with due to their unstructured nature, even when there's demand for spatialization. This research utilizes the natural language processing model BERT to spatialize public documents related to urban planning. It focuses on extracting sentence elements containing addresses from documents and converting them into structured data. The study used 18 years of urban planning public announcement documents as training data to train the BERT model and enhanced its performance by manually adjusting its hyperparameters. After training, the test results showed accuracy rates of 96.6% for classifying urban planning facilities, 98.5% for address recognition, and 93.1% for address cleaning. When mapping the result data on GIS, it was possible to effectively display the change history related to specific urban planning facilities. This research provides a deep understanding of the spatial context of urban planning documents, and it is hoped that through this, stakeholders can make more effective decisions.