• 터널과지하공간
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• 제11권2호
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• pp.182-189
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• 2001

터널 발파시 발파효율은 암반의 특성에 큰 영향을 받기 때문에 암반 특성을 분석하고 이를 기초로 발파설계를 수행하는 것이 중요하다. 그럼에도 불구하고 현재까지 국내에서의 발파설계는 무결암의 단축압축강도만으로 발파암을 분류한 후 각 발파암의 발파계수를 구하는 방법을 이용하거나 공학적 암반분류법의 하나인 RMR분류를 이용하여 발파암을 분류하되 객관적 근거가 미약한 경험적인 발파계수를 산정하는 방식을 통하여 이루어졌다. 본 연구에서는 절리특성을 고려한 발파설계를 위하여 Ashby의 접근법을 활용하였다. 또한 절리조사 결과를 통한 발파암 분류방법과 발파패턴설계를 추가하여 발파설계 전과정을 수행할 수 있도록 Ashby의 접근법을 응용하였다. 따라서 절리 분포 특성을 고려한 발파암 분류가 가능하고, 절리암반 특성을 고려한 발파설계 를 수행할 수 있을 것으로 기대된다.

• 한국인터넷방송통신학회논문지
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• 제10권5호
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• pp.133-138
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• 2010

본 논문에서는 이미지에 대한 공간 특성(Spatial properties) 및 통계적 특성(Statistical properties)을 포함한 특징이미지를 구성하고, 지역 분산 크기를 이용한 공분산 행렬을 생성하여 텍스쳐 분류에 이용함으로서 조도(illumination) 및 노이즈(Noise) 그리고 회전(Rotation)에 강인한 텍스쳐 분류 방법을 제안한다. 또한 영역 합계의 빠른 연산을 위해 사용된 중간 이미지 표현인 적분 이미지(Integral Image)를 이용함으로서 텍스쳐 검출 프로세스의 수행 시간을 최소화 하는 방법을 제공한다. 제안한 방법의 성능 평가를 위해 브로다츠(Brodatz) 질감 이미지를 이용하여 잡음 추가 및 히스토그램 명세화 그리고 회전 이미지를 생성하여 실험하였으며, 96% 이상의 성능을 얻을 수 있었다.

• Journal of applied mathematics & informatics
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• 제19권1_2호
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• pp.57-75
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• 2005

Quasigroups are algebraic structures closely related to Latin squares which have many different applications. There are several classifications of quasigroups based on their algebraic properties. In this paper we propose another classification based on the properties of strings obtained by specific quasigroup transformations. More precisely, in our research we identified some quasigroup transformations which can be applied to arbitrary strings to produce pseudo random sequences. We performed tests for randomness of the obtained pseudo-random sequences by random walks on torus. The randomness tests provided an empirical classification of quasigroups.

• Spatial Information Research
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• 제18권5호
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• pp.13-26
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• 2010

본 논문에서는 항공 라이다 데이터를 이용하여 지형의 유형을 분류하는 과정에서 지형의 특성에 따라 지형 분류의 판정 단위를 가변적으로 변화시키는 동적 가변 윈도우 기반 지형 분류 기법을 제안한다. 제안된 동적 가변 윈도우 기반 지형 분류 기법에서는 지형의 특성과 반복 패턴에 따라 지형 분류의 판정 단위를 가변적으로 결정하여 지형 분류에 소요되는 시간을 감소시키고자 하였다. 또한, 본 논문에서는 실험을 통하여 동적 가변 윈도우 기반 지형 분류 기법의 시간효율과 정확도를 분석하고 최적의 최대 판정 윈도우 크기를 제시하였다. 실험 결과에 따르면 제안된 동적 가변 윈도우 기반 지형 분류 기법은 고정 윈도우 크기를 이용하는 기법과 유사한 정도의 정확성을 유지하면서도 빠른 지형 분류가 가능한 것으로 판명되었다.

• International Journal of Knowledge Content Development & Technology
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• 제7권2호
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• pp.85-105
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• 2017

Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter's Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider's International Classification, Bibliothecal Bibliographic Klassification (BBK), and Broad System of Ordering (BSO). We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design.

• Communications for Statistical Applications and Methods
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• 제21권1호
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• pp.61-68
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• 2014

We propose binary classification methods by modifying logistic regression classification. We use variable selection procedures instead of original variables to select the principal components. We describe the resulting classifiers and discuss their properties. The performance of our proposals are illustrated numerically and compared with other existing classification methods using synthetic and real datasets.

• Communications for Statistical Applications and Methods
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• 제20권3호
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• pp.225-233
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• 2013

The linear support vector machine(SVM) is motivated by the maximal margin separating hyperplane and is a popular tool for binary classification tasks. Many studies exist on the consistency properties of SVM; however, it is unknown whether the linear SVM is consistent for estimating the optimal classification boundary even in the simple case of two Gaussian classes with a common covariance, where the optimal classification boundary is linear. In this paper we show that the linear SVM can be inconsistent in the univariate Gaussian classification problem with a common variance, even when the best tuning parameter is used.

• 한국토양비료학회지
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• 제50권6호
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• pp.520-529
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• 2017

In Korea, the largest agricultural lands are paddy fields which have poor infiltration and drainage properties. Recently, Korean government pursuits cultivating upland crops in paddy fields to reduce overproduced rice in Korea. In order to succeed this policy, it is critical to set criteria suitability classification for upland crops cultivating in paddy field soils. The objective of this study was developing guideline of suitability classification for sesame cultivation in paddy field soils. Yields of sesame cultivated in paddy field soils and soil properties were investigated at 40 locations at nationwide scale. Soil properties such as topography, soil texture, soil moisture contents, slope, and drainage level were investigated. The guideline of suitability classification for sesame was determined by multi-regression method. As a result, sesame yields had the greatest correlation with topography, soil moisture content, and slope. Since sesame is sensitive to excessive soil moisture content, paddy fields with well drained, slope of 7-15% and mountain foot or hill were best suit for cultivating sesame. Sesame yields were greater with less soil moisture contents. Based on these results, area of best suitable paddy field land for sesame was 161,400 ha, suitable land was 62,600 ha, possible land was 331,600 ha, and low productive land was 1,075,500 ha. Compared to existing suitability classification, the new guideline of classification recommended smaller area of best or suitable areas to cultivate sesame. This result may suggest that sesame cultivation in paddy field can be very susceptible to soil moisture contents.

• 경영과정보연구
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• 제3권
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.255-256
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• 1998

In this paper, we propose the multi-axial classification system using parallel coding method that is systemic and flexible properties for representing dental clinical behavior. The methodology and organization of this thesis as follows. First, an analysis of other classification systems. Second, the domain of medical behavior and axises using selected elements was were determined. Third, the new code system is constructed of these common factors in properties of prediction of hierarchy, brevity, simplicity, flexibility and mnemonic usage. Finally, the framework of classification system for dental was made using multi-axial code system. The result of the this study, the eight bases axis of multi-axial code system is composed and can be basic information of research for construction of classification system of all medical domain.