• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.13-23
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• 2007

Recently there is growing Interest in LBS(Location Based Service) requiring real-time services and the spatial main memory DBMS for efficient Telematics services. In order to optimize existing disk-based multi-dimensional Indexes of the spatial main memory DBMS in the main memory, multi-dimensional index structures have been proposed, which minimize failures in cache access by reducing the entry size. However, because the reduction of entry size requires compression based on the MBR of the parent node or the removal of redundant MBR, the cost of MBR reconstruction increases in index update and the efficiency of search is lowered in index search. Thus, to reduce the cost of MBR reconstruction, this paper proposed the RSMBR(Relative-Sized MBR) compression technique, which applies the base point of compression differently in case of broad distribution and narrow distribution. In case of broad distribution, compression is made based on the left-bottom point of the extended MBR of the parent node, and in case of narrow distribution, the whole MBR is divided into cells of the same size and compression is made based on the left-bottom point of each cell. In addition, MBR was compressed using a relative coordinate and size to reduce the cost of search in index search. Lastly, we evaluated the performance of the proposed RSMBR compression technique using real data, and proved its superiority.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.87-93
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• 1999

This study is focus on exploring the relationship between the index of shape and the factor of perception. This study site is a Sorak National Park which sciences of road-landscape. Slides, which were used in the study, were taken in the Sorak National Park along the roads. For this purpose, the study used the questionnairy about the Road-landscape which was presented by a slide projection, also used th index of Shape. This research used analysis method of multi-regression between the preference and perceptional factors, and between the preference and index of shape. 1) The regression result of $R^2$ is 00827 between the preference and perceptional factors, therefore we can positively consider that the preference is related to the perception. The preference is affected highly by the intimacy which is the one of perceptional factors. 2) The regression result of $R^2$ is 0.692 between the preference and the index of shape. The preference has a relation with the index of shape, and it is affected highly by the index of sky. 3) Therefore, this study identifies the relationship between the preference and the perceptional factors, and the index of shape makes this relationship possible.

• ETRI Journal
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• v.22 no.2
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• pp.32-42
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• 2000

The existing multi-dimensional index structures are not adequate for indexing higher-dimensional data sets. Although conceptually they can be extended to higher dimensionalities, they usually require time and space that grow exponentially with the dimensionality. In this paper, we analyze the existing index structures and derive some requirements of an index structure for content-based image retrieval. We also propose a new structure, for indexing large amount of point data in a high-dimensional space that satisfies the requirements. in order to justify the performance of the proposed structure, we compare the proposed structure with the existing index structures in various environments. We show, through experiments, that our proposed structure outperforms the existing structures in terms of retrieval time and storage overhead.

• Structural Engineering and Mechanics
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• v.10 no.1
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• pp.37-51
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• 2000

Identification of damage location based on modal measurement is an important problem in structural health monitoring. The damage index method that attempts to evaluate the changes in modal strain energy distribution has been found to be effective under certain circumstances. In this paper two damage index methods using bending strain energy and shear strain energy have been evaluated for numerous cases at different locations and degrees of damage. The objective is to evaluate the feasibility of the damage index method to localize the damage on large span concrete bridge. Finite element models were used as the test structures. Finally this method was used to predict the damage location in an actual structure, using the results of a modal survey from a large concrete bridge.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.691-694
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• 2010

Since the data collected at a sensor node is the stream data, for processing efficiently user queries, the query index should be constructed at each node. To construct the minimized query index at the node, it is required to reduce the number of query constraints inserted into the query index. In this paper, we propose the scheme of the query constraints distribution using the multi-dimensional data index in order to diminish the number of the inserted query constraints.

• Asian Journal of Atmospheric Environment
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• v.9 no.2
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• pp.101-113
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• 2015

Air quality index (AQI) or air pollution index (API) is commonly used to report the level of severity of air pollution to public. A number of methods were developed in the past by various researchers/environmental agencies for determination of AQI or API but there is no universally accepted method exists, which is appropriate for all situations. Different method uses different aggregation function in calculating AQI or API and also considers different types and numbers of pollutants. The intended uses of AQI or API are to identify the poor air quality zones and public reporting for severity of exposure of poor air quality. Most of the AQI or API indices can be broadly classify as single pollutant index or multi-pollutant index with different aggregation method. Every indexing method has its own characteristic strengths and weaknesses that affect its suitability for particular applications. This paper attempt to present a review of all the major air quality indices developed worldwide.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.783-789
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• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.420-423
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• 2001

In this paper, the Multi-FNNs(Fuzzy-Neural Networks) architecture is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNNs architecture uses simplified inference and linear inference as fuzzy inference method and error back propagation algorithm as learning rules. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNNs according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNNs model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model we use the time series data for gas furnace and the NOx emission process data of gas turbine power plant.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.267-269
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• 2017

We report the results of a multi-wavelength study in the North Ecliptic Pole (NEP) deep field and examine the far infrared-radio correlation (FIRC) for high and low redshift objects. We have found a correlation between the GMRT data at 610 MHz and the Herschel data at $250{\mu}m$ that has been used to define a spectral index. This spectral index shows no evolution against redshift. As a result of the study, we show a radio colour-infrared diagram that can be used as a redshift indicator.