• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1624-1647
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• 2020

Vehicular network is one of the most important subjects for researchers in recent years. Anycast routing protocols have many applications in vehicular ad hoc networks. The aim of an anycast protocol is sending packets to at least one of the receivers among candidate receivers. Studies done on anycast protocols over vehicular networks, however, have capability of implementation on some applications; they are partial, and application specific. No need to say that the lack of a comprehensive study, having a strong analytical background, is felt. Mathematical modeling in vehicular networks is difficult because the topology of these networks is dynamic. In this paper, it has been demonstrated that vehicular networks can be modeled based on time-expanded networks. The focus of this article is on geographical anycast. Three different scenarios were proposed including sending geographic anycast packet to exactly-one-destination, to at-least-one-destination, and to K-anycast destination, which can cover important applications of geographical anycast routing protocols. As the proposed model is of MILP type, a decentralized heuristic algorithm was presented. The evaluation process of this study includes the production of numerical results by Branch and Bound algorithm in general algebraic modeling system (GAMS) software and simulation of the proposed protocol in OMNET++ simulator. The comprehension of the result of proposed protocol and model shows that the applicability of this proposed protocol and its reactive conformity with the presented models based on presented metrics.

• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.219-233
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• 2016

In social science fields, statistical models are used almost exclusively for causal explanation, and explanatory modeling has been a mainstream until now. In contrast, predictive modeling has been rare in the fields. Hence, we focus on constructing the predictive non-parametric model, instead of the explanatory model. Gangnam-gu, Seoul was chosen as a study area and we collected single-family house sales data sold between 2011 and 2014. We applied non-parametric models proposed in machine learning area including generalized additive model(GAM), random forest, multivariate adaptive regression splines(MARS) and support vector machines(SVM). Models developed recently such as MARS and SVM were found to be superior in predictive power for house price estimation. Finally, spatial autocorrelation was accounted for in the non-parametric models additionally, and the result showed that their predictive power was enhanced further. We hope that this study will prompt methodology for property price estimation to be extended from traditional parametric models into non-parametric ones.

• Journal of the Korean Geographical Society
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• v.38 no.6
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• pp.906-921
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• 2003

This paper discusses the price effects of local growth controls on the housing markets of California jurisdictions in the late 1980s empirically. Particularly, based on spatial econometric modeling, the study focuses on the homebuilding constrained by growth controls which is one of the price effects. The modeling produces the California-wide generalizable results, differentiates among the individual effects of various growth controls on homebuilding, and covers spatial effects. Thereby, this study intends to supplement the existing work on the price effects of growth controls. The modeling results find that restrictive residential zoning had the effect of significantly restricting housing construction in the late 1980s. On the other hand, urban growth boundaries had the effect of accommodating homebuilding. Population growth or housing permit caps and adequate public facility ordinances had no significant effects on housing construction.

• Fire Science and Engineering
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• v.29 no.1
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• pp.7-11
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• 2015

In Korea, The protective action distance based on Canada's ERG has been adopted for safety of residents in case of hazardous chemicals leakage accident. However, it couldn't respond properly on the accidents because of geographical and meteorological differences between two nations. In this study, It was found that the protective action distance varies depending on season and terrain, Through AERMOD modeling analysis for the petrochemical complex reflected local geographical data and meteorological conditions.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.136-138
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• 2003

UML cannot meet all the requirements offered in different software system for diverse application domain. GNSS (Global Navigation Satellite System) application domain is an especial environment that requires precise measurement and precision calculation of real-world geographical entities with the help of GPS (Global Position System) in both temporal and spatial factor. Therefore in the paper new extended iconic stereotypes for better modeling GNSS application in the UML Diagram are proposed, and the implementation of a program called StereotypeCreator, which is able to create iconic stereotypes used in one of the most popular visual modeling tools for software development, Rational Rose, will be also proposed.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.1-8
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• 2017

In recent years, the quixotic nature and concentration of rainfall due to global climate change has intensified. To monitor localized heavy rainfalls, a reliable disaster monitoring and warning system with advanced remote observation technology and high-precision display is important. In this paper, we propose a GIS-based intuitive and realistic 3D radar data display technique for accurate and detailed weather analysis. The proposed technique performs 3D object modeling of various radar variables along with ray profiles and then displays stereoscopic radar data on detailed geographical locations. Simulation outcomes show that 3D object modeling of weather radar data can be processed in real time and that changes at each moment of rainfall events can be observed three-dimensionally on GIS.

• Fourth Industrial Review
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• v.4 no.1
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• pp.11-18
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• 2024

Purpose: The purpose of this study is to develop a geography class teaching and learning guide that enables learners to realistically explore the characteristics of the world's climate and geographical environment using digital tools. Research design, data and methodology: We review previous research on classes using goal-based scenario learning models, gamification, and digital tools, and explore tools that can be applied to world geography classes. Based on the exploration results, a goal-based scenario learning module is designed and a strategy for promoting educational gamification is established based on the ADDIE instructional design model. Results: The study comprises four sessions. Sessions 1-3 involve performance evaluations using a goal-based scenario learning module. Learners create game characters reflecting geographical characteristics, present results, and proceed with 3D modeling. In Session 4, a gamification class using Google Sites on the CoSpaces metaverse platform will be conducted. Conclusions: The study introduces a goal-based scenario learning model and a gamification class using digital tools to empower learners in exploring geographical diversity and its impact on lifestyles. Utilizing an accessible online platform, the study provides practical measures for integrating digital tools into geography education, addressing the current importance of digital technology in teaching.

• Journal of the Korean Geographical Society
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• v.36 no.3
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• pp.278-291
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• 2001

This paper is to build a spatial decision support system designed to solve problems relevant to the decision-making for retail center locations. For construction of the system this paper discusses the primary procedures of spatial modeling and issues of data, which are required for integrating spatial interaction models to GIS having capability of managing, analyzing and visualizing spatial data sets. Lexington, Kentucky, is selected as a case study to implement the spatial decision support system based on the spatial modeling module. This system for retail center locations is useful of estimating the catchment areas more accurately and analyzing resultant flow patterns. And this system can make spatial analysis efficiently for what-if scenarios such as an intended retail center or changing demand. The benefits of adopting this system allow the decision makers to plan the investment strategies and search for stable market structure.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.322-324
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• 2003

Leaf C:N ratio is a new factor in the field of biochemical inversion with hyperspectral data. Effects of common-used spectral transformations including log(R), log(1/R), 1/R, etc. from 400nm to 2490nm on its inversion are compared. Results show that their effects on statistical modeling are not apparent. Continuum removal is used on original reflectance in the range of 2030nm to 2220nm, in which exists an apparent absorption peak due to cellulose, lignin, protein, etc. The effect is distinctive and tends to improve the precision of C:N ratio inversion. Further, it is a robust and physically based transformation.