• 한국조경학회지
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• 제27권4호
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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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• 제22권2호
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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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• 제10권1호
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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.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 추계학술대회
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• pp.691-694
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• 2010

센서 노드에서 수집되는 데이터는 지속적으로 삽입되는 스트림 데이터이기 때문에 효율적인 사용자 질의 처리를 위하여 노드별로 질의 색인을 구축해야 한다. 노드에서 최소 크기의 질의 색인을 구축하기 위해서는 질의 색인에 삽입되는 질의 조건을 수를 줄여야 할 필요가 있다. 이 논문에서는 삽입되는 질의 조건의 수를 줄이기 위하여 다차원 데이터 색인을 이용한 질의 조건 배분 기법에 대하여 제안한다.

• Asian Journal of Atmospheric Environment
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• 제9권2호
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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.

• 제어로봇시스템학회논문지
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• 제17권8호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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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.

• 대한원격탐사학회지
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• 제19권5호
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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.

• 천문학논총
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• 제32권1호
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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.

• 환경영향평가
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• 제14권3호
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• pp.127-134
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• 2005

Recently, aquaculture farm sites have been increased with demand of the expensive fish species and sea food like as seaweed, laver and oyster. Therefore coastal water quality have been deteriorated by organic contamination from marine aquaculture farm sites. For protecting of coastal environment, we need to control the location of aquaculture sites. The purpose of this study is to detect the laver aquaculture sites using multispectral remotely sensed data with autodetection algorithm. In order to detect the aquaculture sites, density slice and contour and vegetation index methods were applied with SPOT and IKONOS data of Shinan area. The marine aquaculture farm sites were extracted by density slice and contour methods with one band digital number(DN) carrying 65% accuracy. However, vegetation index algorithm carried out 75% accuracy using near-infra red and red bands. Extraction of the laver aquaculture site using remotely sensed data will provide the efficient digital map for coastal water management strategies and red tide GIS management system.