• Title/Summary/Keyword: random pattern

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Effects of Mixing Characteristics at Fracture Intersections on Network-Scale Solute Transport

  • 박영진;이강근
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2000.11a
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    • pp.69-73
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    • 2000
  • We systematically analyze the influence of fracture junction, solute transfer characteristics on transport patterns in discrete, two-dimensional fracture network models. Regular lattices and random fracture networks with power-law length distributions are considered in conjunction with particle tracking methods. Solute transfer probabilities at fracture junctions are determined from analytical considerations and from simple complete mixing and streamline routing models. For regular fracture networks, mixing conditions at fracture junctions are always dominated by either complete mixing or streamline routing end member cases. Moreover bulk transport properties such as the spreading and the dilution of solute are highly sensitive to the mixing rule. However in power-law length networks there is no significant difference in bulk transport properties, as calculated by assuming either of the two extreme mixing rules. This apparent discrepancy between the effects of mixing properties at fracture junctions in regular and random fracture networks is explained by the statistics of the coordination number and of the flow conditions at fracture intersections. We suggest that the influence of mixing rules on bulk solute transport could be important in systematic orthogonal fracture networks but insignificant in random networks.

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Identifying the Expression Patterns of Depression Based on the Random Forest (랜덤 포레스트 기반 우울증 발현 패턴 도출)

  • Jeon, Hyeon Jin;Jihn, Chang-Ho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.4
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    • pp.53-64
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    • 2021
  • Depression is one of the most important psychiatric disorders worldwide. Most depression-related data mining and machine learning studies have been conducted to predict the presence of depression or to derive individual risk factors. However, since depression is caused by a combination of various factors, it is necessary to identify the complex relationship between the factors in order to establish effective anti-depression and management measures. In this study, we propose a methodology for identifying and interpreting patterns of depression expressions using the method of deriving random forest rules, where the random forest rule consists of the condition for the manifestation of the depressive pattern and the prediction result of depression when the condition is met. The analysis was carried out by subdividing into 4 groups in consideration of the different depressive patterns according to gender and age. Depression rules derived by the proposed methodology were validated by comparing them with the results of previous studies. Also, through the AUC comparison test, the depression diagnosis performance of the derived rules was evaluated, and it was not different from the performance of the existing PHQ-9 summing method. The significance of this study can be found in that it enabled the interpretation of the complex relationship between depressive factors beyond the existing studies that focused on prediction and deduction of major factors.

Spatial Distribution Pattern and Association of Crowns and Saplings for Major Tree Species in the Mixed Broadleaved-Korean Pine Forest of Xiaoxing'an Mountains, China

  • Jin, Guangze;Li, Zhihong;Tang, Yan;Kim, Ji-Hong
    • Journal of Korean Society of Forest Science
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    • v.98 no.2
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    • pp.189-196
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    • 2009
  • This study was conducted to evaluate spatial distribution pattern and spatial association of crowns (${\geq}10m$ of height) and saplings (<10 m of height and ${\geq}2cm$ of DBH) for four major tree species (Pinus koraiensis, Abies nephrolepis, Acer mono, and Tilia amurensis) in the mixed broadleaved-Korean pine forest of Xiaoxing'an Mts. Vegetation data were collected in the 9 ha permanent sample plot, and the analysis adopted the point pattern analysis method. Main results are as follows; 1) crowns and saplings of major species showed clumped distribution pattern in small scale, became random distribution as the scale was increased. 2) Saplings of Pinus koraiensis performed poor regeneration under the crowns of Pinus koraiensis and Abies nephrolepis; Saplings of Abies nephrolepis did good regeneration under the crowns of Pinus koraiensis and Abies nephrolepis; and crowns of Acer mono and Tilia amurensis had little effect on the distribution of saplings of Pinus koraiensis and Abies nephrolepis. Saplings of Acer mono and Tilia amurensis made good regeneration under the crowns of Pinus koraiensis and Tilia amurensis; and the crowns of Acer mono and Abies nephrolepis had little effect on the distribution of saplings of Acer mono.

The Air Quality Analysis in Underground Shopping Centers Using Pattern Recognition (Pattern Recognition을 이용한 지하상가에서의 대기오염물질의 농도 분석에 관한 연구)

  • 김동술;김형석
    • Journal of Korean Society for Atmospheric Environment
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    • v.6 no.1
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    • pp.1-10
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    • 1990
  • The purpose of the study was to analyze air quality in underground shopping centers using pattern recognition methods. In order to perform this, the concentraion of air pollutants such as $CO, NO_2, NO_x, SO_2$, and particulate matters was measured at the 11 different shopping centers in Seoul metropolitan area and the total of 47 samples were obtained at random based on the size of shopping centers. To introduce a new concept of the "average concentration" for the indoor air quality analyses, the various multivariate statistical analyses have been studied. Thus, a cluster analysis was applied to separate the samples into pseudo-patterns and a disjoint principal component analysis was used to generate homogeneous patterns after removing outliers from the pseudo-patterns. The 6 homogeneous patterns were then obtained as follows:the first pattern was a group of clean sites;the second a group of sites having high dust concentration;the third a group of sites having high dust and $NO_x$ concentration;the fourth a group of sites having low dust and $SO_2$ concentraion and high CO concentration;the fifth a group of sites having high $NO_2 and SO_2$ concentration;and the final a group of miscellaneous sites. Thus, the average concentration could be estimated for each pattern.h pattern.

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Implementation of IDDQ Test Pattern Generator for Bridging Faults (합선 고장을 위한 IDDQ 테스트 패턴 발생기의 구현)

  • 김대익;전병실
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.12A
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    • pp.2008-2014
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    • 1999
  • IDDQ testing is an effective testing method to detect various physical defects occurred in CMOS circuits. In this paper, we consider intra-gate shorts within circuit under test and implement IDDQ test pattern generator to find test patterns which detect considered defects. In order to generate test patterns, gate test vectors which detect all intra-gate shorts have to be found by type of gates. Random test sets of 10,000 patterns are applied to circuit under test. If an applied pattern generates a required test vector of any gate, the pattern is saved as an available test pattern. When applied patterns generate all test vectors of all gats or 10,000 patterns are applied to circuit under test, procedure of test pattern generation is terminated. Experimental results for ISCAS'85 bench mark circuits show that its efficiency is more enhanced than that obtained by previously proposed methods.

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Area Extraction of License Plates Using an Artificial Neural Network

  • Kim, Hyun-Yul;Lee, Seung-Kyu;Lee, Geon-Wha;Park, Young-rok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.7 no.4
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    • pp.212-222
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    • 2014
  • In the current study, the authors propose a method for extracting license plate regions by means of a neural network trained to output the plate's center of gravity. The method is shown to be effective. Since the learning pattern presentation positions are defined by random numbers, a different pattern is submitted to the neural network for learning each time, which enables it to form a neural network with high universality of coverage. The article discusses issues of the optimal learning surface for a license plate covered by the learning pattern, the effect of suppression learning of the number and pattern enlargement/reduction and of concentration value conversion. Results of evaluation tests based on pictures of 595 vehicles taken at an under-ground parking garage demonstrated detection rates of 98.5%, 98.7%, and 100%, respectively.

Characterization of Fusarium oxysporum f. sp. fragariae Based on Vegetative Compatibility Group, Random Amplified Polymorphic DNA and Pathogenicity

  • Nagarajan Gopal;Kang Sung-Woo;Nam Myeong-Hyeon;Song Jeong-Young;Yoo Sung-Joon;Kim Hong-Gi
    • The Plant Pathology Journal
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    • v.22 no.3
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    • pp.222-229
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    • 2006
  • Twenty-two isolates of Fusarium oxysporum f. sp. fragariae were obtained from diseased strawberry plants and their characteristics were investigated by vegetative compatibility group (VCG), random amplified polymorphic DNA (RAPD), and pathogenicity. Three major VCGs (A, B, and C) and one incompatible group were identified by nitrate reductase complementation test. The virulence pattern of the 22 isolates was studied in relation to four cultivars including Dochiodome, Red-pearl, Maehyang and Akihime. RAPD markers were used to determine genetic relationship, and created three major clusters among the 22 isolates of F. oxysporum f. sp. fragariae. Isolates belong to VCG-C were strongly pathogenic, and relatively high correlation was existed among VCG and RAPD, and virulence. In addition, VCG and RAPD pattern between pathogenic and non-pathogenic isolates were distinctly different.

A Method for Improving Object Recognition Using Pattern Recognition Filtering (패턴인식 필터링을 적용한 물체인식 성능 향상 기법)

  • Park, JinLyul;Lee, SeungGi
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.6
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    • pp.122-129
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    • 2016
  • There have been a lot of researches on object recognition in computer vision. The SURF(Speeded Up Robust Features) algorithm based on feature detection is faster and more accurate than others. However, this algorithm has a shortcoming of making an error due to feature point mismatching when extracting feature points. In order to increase a success rate of object recognition, we have created an object recognition system based on SURF and RANSAC(Random Sample Consensus) algorithm and proposed the pattern recognition filtering. We have also presented experiment results relating to enhanced the success rate of object recognition.

A Histological Study on the Visual Cell Layer of the Endemic Korean Species Liobagrus mediadiposalis (Pisces: Amblycipitidae)

  • Kim, Jae Goo;Park, Jong Young
    • Applied Microscopy
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    • v.47 no.4
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    • pp.238-241
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    • 2017
  • A study on the visual cell and eyeball of the endemic Korean species Liobagrus mediadiposalis was investigated by light and electron microscopes. The retina of a small and 2 mm-diameter round eye was thin, $151.0{\pm}4.0{\mu}m$ and has two visual cells, a single cone and a rod cell. The single cone cells are short and thick, $18.0{\pm}0.9{\mu}m$ in length and $5.1{\pm}0.7{\mu}m$ (n=30) in diameter, while the rod cells are longer and thinner, $54.8{\pm}2.9{\mu}m$ in length and $3.3{\pm}0.6{\mu}m$ in diameter. The cone cells are seen an irregular and random mosaic pattern, and the rod cells are also randomly situated at between cone cells. As a rare phenomenon, such structure is one of characteristics reflecting the eye of a nocturnal and bottom-dwelling freshwater fish. The ultrastructure of visual cells was observed with scanning and transmission electron microscopy, both cone and rod cells are divided into an inner segment with numerous mitochondria and an outer segment with stacks of membrane discs.

Conditional Moment-based Classification of Patterns Using Spatial Information Based on Gibbs Random Fields (깁스확률장의 공간정보를 갖는 조건부 모멘트에 의한 패턴분류)

  • Kim, Ju-Sung;Yoon, Myoung-Young
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.6
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    • pp.1636-1645
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    • 1996
  • In this paper we proposed a new scheme for conditional two dimensional (2-D)moment-based classification of patterns on the basis of Gibbs random fields which are will suited for representing spatial continuity that is the characteristic of the most images. This implementation contains two parts: feature extraction and pattern classification. First of all, we extract feature vector which consists of conditional 2-D moments on the basis of estimated Gibbs parameter. Note that the extracted feature vectors are invariant under translation, rotation, size of patterns the corresponding template pattern. In order to evaluate the performance of the proposed scheme, classification experiments with training document sets of characters have been carried out on 486 66Mhz PC. Experiments reveal that the proposed scheme has high classification rate over 94%.

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