• Title/Summary/Keyword: Classification surface right

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A study on system improvement to utilization of underground space for the right complementary - Focused on land of exceeding the depth limit - (지하공간 활용의 권리보완을 위한 제도적 개선에 관한 연구 - 한계심도 초과 토지를 중심으로 -)

  • Seo, Yong-Su;Choi, Seung-Young
    • Journal of Cadastre & Land InformatiX
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    • v.44 no.1
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    • pp.97-111
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    • 2014
  • As urbanization and industrialization develops, the necessity of utilizing scarce land in three dimensions is raising. The issue of utilizing underground space is being actively discussed particularly when Geyeonggi-do announced GTX(Great Train Express) construction plan which aims to relieve traffic congestion in metropolitan areas. The current regulation on compensation of underground space is based on "Regulations on compensation standard complied by using underground space for construction of urban railway" but it is difficult for covering the whole rights to protect a three-dimensional right. In this context, the study is to propose the improvement plans of land right's problem and compensation issues to utilization of underground space for the right complementary. To do this, the study reviews the use situation of the classification surface right and using adjudication which defines the effect scope of underground space extending land ownership. As well as it analyzes issues about compensation standard for utilizing of underground space.

Artificial Neural Network based Motion Classification Algorithm using Surface Electromyogram (표면 근전도를 이용한 Artificial Neural Network 기반의 동작 분류 알고리즘)

  • Jeong, E.C.;Kim, S.J.;Song, Y.R.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
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    • v.6 no.1
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    • pp.67-73
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    • 2012
  • In this paper, Artificial Neural Network(ANN) based motion classification algorithm is proposed to classify wrist motions using surface electromyograms(sEMG). surface EMGs are obtained from two electrodes placed on the flexor carpi ulnaris muscle and extensor carpi ulnaris muscle of 26 subjects under no strain condition during wrist motions and used to recognize wrist motions such as up, down, left, right, and rest. Feature is extracted from obtained EMG signals in time domain for fast processing and used to classify wrist motions using ANN. DAMV, DASDV, MAV, and RMS were used as features and accuracies of motion classification based on ANN were 98.03% for DAMV, 97.97% for DASDV, 96.95% for MAV, 96.82% for RMS.

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A Gaussian Mixture Model Based Surface Electromyogram Pattern Classification Algorithm for Estimation of Wrist Motions (손목 움직임 추정을 위한 Gaussian Mixture Model 기반 표면 근전도 패턴 분류 알고리즘)

  • Jeong, Eui-Chul;Yu, Song-Hyun;Lee, Sang-Min;Song, Young-Rok
    • Journal of Biomedical Engineering Research
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    • v.33 no.2
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    • pp.65-71
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    • 2012
  • In this paper, the Gaussian Mixture Model(GMM) which is very robust modeling for pattern classification is proposed to classify wrist motions using surface electromyograms(EMG). EMG is widely used to recognize wrist motions such as up, down, left, right, rest, and is obtained from two electrodes placed on the flexor carpi ulnaris and extensor carpi ulnaris of 15 subjects under no strain condition during wrist motions. Also, EMG-based feature is derived from extracted EMG signals in time domain for fast processing. The estimated features based in difference absolute mean value(DAMV) are used for motion classification through GMM. The performance of our approach is evaluated by recognition rates and it is found that the proposed GMM-based method yields better results than conventional schemes including k-Nearest Neighbor(k-NN), Quadratic Discriminant Analysis(QDA) and Linear Discriminant Analysis(LDA).

Palynological contributions to the taxonomy of family Oleaceae, with special empahsis on genus Forsythia (tribe Forsytheae)

  • Lee, Sangtae
    • Korean Journal of Plant Taxonomy
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    • v.41 no.3
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    • pp.175-181
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    • 2011
  • Traditionally, the Oleaceae has been divided into subfamilies Oleoideae and Jasminoideae. In the present paper, the taxonomical results so far made on the family were reviewed on the basis of palynology. The subfamilial classification is not well supported palynoligically, because both Myxopyrum of Jasminoideae and Comoranthus of Oleoideae having foveolate surface are well distinguished from the rest of the family having reticulate surface. The recent subfamily Nyctanthoideae (Takhtajan, 1977) including the monotypic Nyctanthus, was suggested to be included within the Jasminoideae although its closest relative on the palynological basis is different from that on the molecular basis. Tribal classification systems of the Jasminoideae are not well supported palynologically on the basis of surface character: presence or absence of bands on the mural ridge surface of the reticulum. On the basis of palynology, tribe Forsythiae including Abeliophyllum, Fontanesia, and Forsythia is monophyletic, and Fontanesia is well distinguished from the rest two. Korean species of Forsythia is divided into two: Forsythia koreana group and F. ovata-nakaii-saxatilis group. Recent discovery of F. saxatilis at a locality of F. ovata raised a question if the distinction between the two species on the basis of hairiness would be right. In the recent molecular studies, F. saxatilis var. lanceolata seems to be identified as F. saxatilis. Molecular studies showed that F. saxatilis (seemingly var. lanceolata or var. pilosa) is close to F. koreana. The fact in which the molecular result showed a close relationship between F. saxatilis varieties and F. koreana, is controversial to the result by floral and vegetative morphology. An intensive taxonomic study of these taxa would be needed.

Development of an Optimal EEG and Artifact Classifier Using Neural Network Operating Characteristics (신경망 운영특성곡선을 이용한 최적의 뇌파 및 Artifact 분류기 구성)

  • Lee, T.Y.;Ahn, C.B.;Lee, S.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1995 no.05
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    • pp.160-163
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    • 1995
  • An optimal EEG and artifact classifier is proposed using neural network operating characteristics. The neural network operating characteristics are two dimensional parametric representations of the right and false identification probabilities of the network classifier. Since the EEG and EP signals acquired from multi -channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG), the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. Using the neural-network based classification, human expert's efforts and time can be substantially reduced. From experiments, the neural-network based classification performs as good as human experts: variation of decisions between the neural network and human expert appears even smaller than that between human experts.

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Improvement of Classification Accuracy of Different Finger Movements Using Surface Electromyography Based on Long Short-Term Memory (LSTM을 이용한 표면 근전도 분석을 통한 서로 다른 손가락 움직임 분류 정확도 향상)

  • Shin, Jaeyoung;Kim, Seong-Uk;Lee, Yun-Sung;Lee, Hyung-Tak;Hwang, Han-Jeong
    • Journal of Biomedical Engineering Research
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    • v.40 no.6
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    • pp.242-249
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    • 2019
  • Forearm electromyography (EMG) generated by wrist movements has been widely used to develop an electrical prosthetic hand, but EMG generated by finger movements has been rarely used even though 20% of amputees lose fingers. The goal of this study is to improve the classification performance of different finger movements using a deep learning algorithm, and thereby contributing to the development of a high-performance finger-based prosthetic hand. Ten participants took part in this study, and they performed seven different finger movements forty times each (thumb, index, middle, ring, little, fist and rest) during which EMG was measured from the back of the right hand using four bipolar electrodes. We extracted mean absolute value (MAV), root mean square (RMS), and mean (MEAN) from the measured EMGs for each trial as features, and a 5x5-fold cross-validation was performed to estimate the classification performance of seven different finger movements. A long short-term memory (LSTM) model was used as a classifier, and linear discriminant analysis (LDA) that is a widely used classifier in previous studies was also used for comparison. The best performance of the LSTM model (sensitivity: 91.46 ± 6.72%; specificity: 91.27 ± 4.18%; accuracy: 91.26 ± 4.09%) significantly outperformed that of LDA (sensitivity: 84.55 ± 9.61%; specificity: 84.02 ± 6.00%; accuracy: 84.00 ± 5.87%). Our result demonstrates the feasibility of a deep learning algorithm (LSTM) to improve the performance of classifying different finger movements using EMG.

Application of 1mm fictitious notch radius approach to the fatigue strength assessment of welded joint (1mm 가상 노치 반경을 이용한 용접부 피로강도 평가에 관한 연구)

  • Kim Yu Il;Gang Jung Gyu;Heo Ju Ho
    • Proceedings of the KWS Conference
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    • v.43
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    • pp.275-277
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    • 2004
  • Fictitious notch radius approach is based on the Neuter's microstructural support hypothesis which assumes that fatigue crack is governed by highly stressed volume of the material right on the weld toe area rather than the surface stress at a pin point of weld toe area. Variety of successes have been achieved in applying this methodology to the fatigue of welded joint, hence, it became one of recommended design procedure in IIW's recommendation as well as many ship classification societies. 1mm fictitious notch radius approach was applied to the various fatigue problems of welded joints in this study covering the effect of weld size, notch stress calculation for 3D geometry and low cycle fatigue problem. It was found that fictitious notch radius approach fumed out to be very effective and accurate in dealing with fatigue strength of welded joint.

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Critical Comments on Akagki's Pediment Morphology in Korea (한국 Pediment 지형의 연구성과에 관한 비판과 문제점)

  • Park, No-Sik
    • Journal of the Speleological Society of Korea
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    • no.68
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    • pp.99-120
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    • 2005
  • It is a wrong decision to use only topographic and geological maps for the study of pediment morphology in Korea. For the study of pediment morphology it is necessary to survey the earth structure by field techniques. In Korea, pediments are mostly found in granite areas with hardrock cover. But, pediments also developed in gneiss areas and what is worse in limestone areas. So, all areas in Korea developed pediment morphology. Only in South Korea pediments show a direction from south to north or from west to east. They developed only in right angles to each other, either parallel or in right angles to the strike, depending on the bedrock structure. Pediments are found in two levels. The upper level pediments are correlated with the lower level erosion surface. Besides this pediments are found in Hoenggye-ri of the Taegwolryong area in a third level 800m above sea level. The pediments developed in basins, at the lower margins of steep slopes dividing three levels of erosion surfaces and around the residual mountains on the erosion surfaces. The first belong to the early stage of pedimentation, the second to the middle stage and the third to the last stage. Also, in Korea monadnock and residual mountain have developed the pediments are correlated the slope of the hinter mountains. Akagki states that the only pedimentation times have been times of arid climate and that they are dissected by gulley erosion with climatic change, but writer's study proves that pedimentation takes place with eustatic movement, reckless defore-station and convectional rain. These facts indicate that the landforms, geological character and process of erosional cycle of the pediments in Korea resemble much those in the Chugoku Mountains of south wertern Japan, but they are larger in scale than those in the Chugoku Mountains. In conclusion, while Akagki emphasizes the geological character and climatic change in pedimentation, the writer studies prove that eustatic movements, especially the sea level rise after the Wurm age are important factors for pedimentation. Besides this the author's studies allow a classification of gentle slopes.

A Case of Nasal T/NK-cell Lymphoma (비강 T/NK 세포형 림프종 1례)

  • Lee, Jung Bok;Jeon, In-sang;Im, Ho Joon;Oh, Young Ha;Kim, Ji Hye
    • Clinical and Experimental Pediatrics
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    • v.46 no.12
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    • pp.1266-1270
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    • 2003
  • The advance of the immunobiology clarifies the nature of non-Hodgkin's lymphoma(NHL). In addition the proceed in the immunophenotyping renders the classification of NHL. According to the Revised European American Lymphoma(REAL) classification, classified by the etiologic factors, molecular biological characteristics, immunophenotype, cytogenetics and histologic feature, nasal T/NK-cell lymphoma(=angiocentric lymphoma) belongs to the category of peripheral T-cell and natural killer cell lymphoma. Nasal T/NK-cell lymphoma is a distinct clinicopathologic entity characterized by progressive necrotic lesions in the nasal cavity, nasopharynx, and palate. The cellular origin of this tumor has been controversial. Although most nasal T/NK-cell lymphomas are of NK-cell lineage, being CD56+, negative for surface CD3(Leu4), and unassociated with rearrangements of the T-cell receptor genes, other minor variants have been reported. This lymphoma is a rare disease and usually experienced in adult. Recently, we experienced a rare type lymphoma, nasal T/NK-cell lymphoma, in 14 years old boy. His soft mass occupied the right nasal cavity including the nasal septum and turbinate. Pathologically this nasal mass showed the infiltration into the vascular wall, illustrating angiodestructive lesion. The cellular origin was NK-cell lineage, being CD56+ and negative to CD3. Now, we report the case with a brief review of related literatures.

Human-Computer Interface using sEMG according to the Number of Electrodes (전극 개수에 따른 근전도 기반 휴먼-컴퓨터 인터페이스의 정확도에 대한 연구)

  • Lee, Seulbi;Chee, Youngjoon
    • Journal of the HCI Society of Korea
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    • v.10 no.2
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    • pp.21-26
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    • 2015
  • NUI (Natural User Interface) system interprets the user's natural movement or the signals from human body to the machine. sEMG (surface electromyogram) can be observed when there is any effort in muscle even without actual movement, which is impossible with camera and accelerometer based NUI system. In sEMG based movement recognition system, the minimal number of electrodes is preferred to minimize the inconvenience. We analyzed the decrease in recognition accuracy as decreasing the number of electrodes. For the four kinds of movement intention without movement, extension (up), flexion (down), abduction (right), and adduction (left), the multilayer perceptron classifier was used with the features of RMS (Root Mean Square) from sEMG. The classification accuracy was 91.9% in four channels, 87.0% in three channels, and 78.9% in two channels. To increase the accuracy in two channels of sEMG, RMSs from previous time epoch (50-200 ms) were used in addition. With the RMSs from 150 ms, the accuracy was increased from 78.9% to 83.6%. The decrease in accuracy with minimal number of electrodes could be compensated partly by utilizing more features in previous RMSs.