Young-Kyu Yang

Spatial applications using 4S technology for mobile environment

The provision of spatial data is a key infrastructural requirement for the promotion of economic growth, environmental quality, social progress, etc. 4S technology integrates 4 kinds of systems that process spatial Information: GIS, GNSS, ITS, and SIIS. We use 4S technology for mobile environment and develop spatial applications. Spatial applications can be classified to 3 phases: construction, exchange, and usage. Standard specifications from OpenGIS are used to provide interoperabillty. We implement location-based services such as, fire report application for disaster management on Java phone, mobile event application, parking management system, and car navigation system.

Vehicle Detection from Aerial Images Using Local Shape Information

Detection and extraction of vehicle objects in high resolution satellite imagery are required in many transportation applications. This paper presents an approach to automatic vehicle detection from aerial images. The initial extraction of candidate vehicle is based on Mean-shift algorithm with symmetric character of blob-like car structure. By fusing the density and the symmetry, the method can remove the ambiguous blobs and reduce the cost of the detected ROI processing in the subsequent stage. To verify the blob as a vehicle, log-polar shape descriptor is used for measuring similarity. The edge strengths are obtained and represented as its spatial histogram by the orientation and distance from the center of blob. The proposed algorithm is able to successfully detect the vehicle and very useful for the traffic surveillance system.

Image fusion using multiresolution analysis

The objective of this study is to propose multiresolution data fusion scheme using multiresolution analysis (MRA). Three techniques compared, respectively based on Haar wavelet basis (HWB), Daubechies wavelet basis (DWB), and IHS transform. Daubechies wavelet basis (DWB) is far more efficient than the HWB and IHS transform, thus establishing the advantages for data fusion of formally multiresolution analysis. DWB is best for image sharpening and to maintain the information of original data. Especially, Daubechies wavelet basis is able to enhance image sharpening and preserve spectral information.

Managing scheme for 3-dimensional geo-features using XML

Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-manage and how-to-model the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3D GIS have lots to be considered to model regarding the efficient manipulation, analysis and visualization. The authors built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. They separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own 3D GIS data, the authors devised a file format named VGFF 2.0(Virtual GIS File Format). It is to describe the three dimensional geo-information in XML (eXtensible Markup Language). They also developed the authoring tools for users to create their own 3D geo-features and geo-objects and to edit and save them in VGFF 2.0 format.

Level-of-detail-based rendering and compression for 3D GIS

Since geographic data sets tend to be quite large, problems arise when visualizing large GIS data. Terrain visualization is also a difficult problem for 3D GIS applications requiring accurate images of large datasets at high frame rates. In this paper we present algorithms for compressing and visualizing large 3D GIS datasets. We propose two algorithms which have different purposes. The goal of the first algorithm is to minimize the number of bits needed to encode connectivity information of TIN (triangulated irregular network) by using Delaunay triangulation. We found that most of the terrain triangulations are quite similar to the plane-projected Delaunay angular mesh. This experimental work shows that more than 93% of the edges of a common terrain data are included in Delaunay triangulation. By exploiting this result, we can on average compress the common terrain data by 0.23 bits per vertex. The second algorithm is an interactive visualization algorithm for 3D GIS datasets using surface simplification. Whenever a viewer gets closer to the 3D GIS object, a geometry with a high level of detail is visualized. Our algorithms achieve compression ratios that are better than those of the currently available algorithms, and moreover, it allows progressive and interactive visualization or the 3D GIS datasets.

A Distributed Data Mining System for a Novel Ubiquitous Healthcare Framework

Recent years have shown impressive growth in the development of ubiquitous healthcare (u-Healthcare) systems which aim for the next generation in e-Health services and associated research. Such systems are primarily being designed to provide emergency and preventive healthcare to citizens anywhere/anytime using wired and wireless mobile technologies. Data mining is an indispensable aspect of such systems and represents the process of analyzing databases to extract hidden knowledge and relationships. This paper introduces and studies the development framework of a prototype ubiquitous healthcare system initiated by the South Korean government. Preliminary results with a distributed data mining system are presented in the context of a larger future integration with the ubiquitous healthcare framework.

A hybrid soft computing approach to link travel speed estimation

The field of dynamic vehicle routing and scheduling is growing at a strong pace nowadays due to the many potential applications in urban traffic management. In recent times there have been many attempts to estimate the vehicle travel times over congested links. As opposed to the previous decade where traffic information was collected mainly by fixed devices with high maintenance costs, the advent of GPS has resulted in data being progressively collected using probe cars equipped with GPS-based communication modules. Typically traditional methods used for analyzing the data collected using fixed devices need to be extended. The aim of this research is to propose a hybrid method for estimating the optimal link speed using the data acquired from probe cars using combination of the fuzzy c-means (FCM) algorithm with multiple regression analysis. The paper describes how the probe data are analyzed and automatically classified into three groups of speed patterns and the link speed is predicted from these clusters using multiple regression. In performance tests, the proposed method is robust and is able to provide accurate travel time estimates.

Adaptive Mobility Management Scheme for Proxy Mobile IPv6 Networks with IP Paging Support

Proxy Mobile IPv6 (PMIPv6) is a network-based localized mobility support in IP network. The main advantage of using PMIPv6 is the freeing up of the mobile host in doing any mobility related activities and thereby saving its resources. However, the Mobile Access Gateway (MAG) incurs a high signaling cost to update the location of a mobile node to the remote Local Mobility Anchor (LMA) if it moves frequently. It may cause excessive signaling traffic and increase a high traffic load on LMA. Therefore, we propose an adpative mobility management scheme in PMIPv6 networks with IP paging support. To minimize signaling overhead, in our proposed scheme, an idle mobile node does not register when moving within a paging area. Moreover, we will employ the anchor-subnet concept and techniques to reduce signaling costs for paging and delay. The cost analysis using Stop-or-Move Mobility (SMM) model presented in this paper shows that our proposed scheme can achieve performance superior that of the PMIPv6 scheme.

Performance analysis of dynamic mobility management for proxy mobile IPv6 networks

Proxy Mobile IPv6 (PMIPv6) is a network-based mobility management protocol that does not require mobile node involvement in mobility management. In PMIPv6, the mobile access gateway (MAG) incurs a high signaling cost to update the location of a mobile node to the remote local mobility anchor (LMA) if it moves frequently. It may cause excessive signaling traffic and increase a high traffic load on the LMA. Therefore, we propose a new mobility management scheme in proxy mobile IPv6 networks with dynamic paging support. To minimize the signaling overhead, in the proposed scheme, an idle mobile node does not register when moving within a paging area. Moreover, the size of the paging area is determined dynamically according to the changes of in the mobility and traffic patterns of the mobile node. An analytic model is applied to determine the optimal size of the paging area. The cost analysis using random walk on a connected graph model presented in this paper shows that the proposed scheme can achieve superior performance much better than of the PMIPv6 scheme.

Efficient method for manipulating complex features in 3D-GIS

The 3D-GIS is one of the emerging issues in GIS and IT fields because it provides new solutions in many application areas today. Most of the research and commercial packages for 3D-GIS can handle only simple features. For many applications, functionalities for handling complex features are necessary. In this paper, we suggest an efficient method for manipulating complex features and applied it to building features in 3D-GIS. The key concept of the applied method is the general features which can be simple features or complex features and is defined by the user. We applied this method to the facility management system supporting floor-based search and analysis.