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  • Title/Summary/Keyword: 상태 분류

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A Suggestion of In-situ Rock Mass Evaluation and Correlation between Rock Mass Classfication Methods (현장암반 평가에 관한 제안 및 암반분류법들간의 상관관계 고찰)

  • Kim, Hong-Pyo;Chang, Ho-Min;Kang, Choo-Won;Ko, Chin-Surk
    • Explosives and Blasting
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    • v.28 no.2
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    • pp.133-147
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    • 2010
  • A Suggestion of In-situ Rock Mass Evaluation and Correlation between Rock Mass Classfication MethodsThe purpose of this study is to find out rock mass classification method which is practically applicable to a field and to consider a correlation between the new method and the old method. Rock mass is an aggregate of separated blocks. To express the aggregate, the properties of both intact rock and rock mass should be considered. In this study, therefore, parameters for rock mass description are classified into rock strength and rock structure. Indices for parameters evaluation are obtained from old method and the strength and structure property of rock is described by using those indices. Value of 25 is allocated to each parameter obtained. RMRbasic =0.86(X=Method)+14.47 is derived between RMRbasic and this study and RMR = 0.87(X-Method)+9.20 is derived between revised RMR and this study. Coefficient of determination is R2=0.841 and R2=0.846 each.

Performance Evaluation of Attention-inattetion Classifiers using Non-linear Recurrence Pattern and Spectrum Analysis (비선형 반복 패턴과 스펙트럼 분석을 이용한 집중-비집중 분류기의 성능 평가)

  • Lee, Jee-Eun;Yoo, Sun-Kook;Lee, Byung-Chae
    • Science of Emotion and Sensibility
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    • v.16 no.3
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    • pp.409-416
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    • 2013
  • Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

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A Suggestion of Korean Names for the Orders and Families Included in the APG III Classification System (APG III 분류체계의 목명 및 과명 국문화에 대한 제안)

  • Lee, Yoonkyung;Jung, Jongduk;Kim, Sangtae
    • Korean Journal of Plant Taxonomy
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    • v.45 no.3
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    • pp.278-297
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    • 2015
  • With the development of the internet and international agreements such as the Convention on Biological Diversity (CBD) and the Convention on International Trade in Endangered Species (CITES), Korean researchers frequently encounter scientific names of foreign species, and these are named on a case-by-case basis in Korean without any standard naming method. Therefore, standard Korean names for entire orders and families in the world are required for better communications in Korea. However, there have been no comprehensive discussions of the standardization of Korean names for the orders and families found in the world. In this study, we 1) compare the Korean names of orders and families in the references, 2) discuss naming methods in Korean for foreign taxa, and 3) then suggest standard Korean names for the orders and families in the APG III, which is an up-to-date angiosperm classification system. This study will be a starting point for the national standardization of Korean names for orders and families found throughout the world.

EMD based Cardiac Arrhythmia Classification using Multi-class SVM (다중 클래스 SVM을 이용한 EMD 기반의 부정맥 신호 분류)

  • Lee, Geum-Boon;Cho, Beom-Joon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.1
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    • pp.16-22
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    • 2010
  • Electrocardiogram(ECG) analysis and arrhythmia recognition are critical for diagnosis and treatment of ill patients. Cardiac arrhythmia is a condition in which heart beat may be irregular and presents a serious threat to the patient recovering from ventricular tachycardia (VT) and ventricular fibrillation (VF). Other arrhythmias like atrial premature contraction (APC), Premature ventricular contraction (PVC) and superventricular tachycardia (SVT) are important in diagnosing the heart diseases. This paper presented new method to classify various arrhythmias contrary to other techniques which are limited to only two or three arrhythmias. ECG is decomposed into Intrinsic Mode Functions (IMFs) by Empirical Mode Decomposition (EMD). Burg algorithm was performed on IMFs to obtain AR coefficients which can reduce the dimension of feature vector and utilized as Multi-class SVM inputs which is basically extended from binary SVM. We chose optimal parameters for SVM classifier, applied to arrhythmias classification and achieved the accuracies of detecting NSR, APC, PVC, SVT, VT and VP were 96.8% to 99.5%. The results showed that EMD was useful for the preprocessing and feature extraction and multi-class SVM for classification of cardiac arrhythmias, with high usefulness.

A Study of Runoff Curve Number Estimation Using Land Cover Classified by Artificial Neural Networks (신경망기법으로 분류한 토지피복도의 CN값 산정 적용성 검토)

  • Kim, Hong-Tae;Shin, Hyun-Suk
    • Journal of Korea Water Resources Association
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    • v.36 no.4
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    • pp.633-645
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    • 2003
  • The techniques of GIS and remote sensing are being applied to hydrology, geomorphology and various field of studies are performed by many researcher, related those techniques. In this paper, curve number change detection is tested according to soil map and land cover in mountain area. Neural networks method is applied for land cover classification and GIS for curve number calculation. The first, sample area are selected and tested land cover classification, NN(84.1%) is superior to MLC(80.9%). So we selected NN with land cover classifier. The second, curve number from the land cover by neural network classifier(57) is compared with that(curve number) from the land cover by manual work(55). Two values are so similar. The third, curve number classified by NN in sample area was applied and tested to whole study area. As results of this study, it is shown that curve number is more exact and efficient by using NN and GIS technique than by (using) manual work.

선박의 윤활

  • 김주환
    • Tribology and Lubricants
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    • v.8 no.1
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    • pp.17-23
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    • 1992
  • 발전기용 원동기에는 증기 Turbine engine과 디이젤 Engine으로 분류한다. 일반적으로 발전기 Bearing의 윤활유는 구동용(驅動用) 원동기와 동일한 윤활유를 사용하고 있다. 또한 디이젤 발전기는 연료가 A중유로서 비교적 양질의 연료유를 사용하고 있다고 하더라도 고부하로서 연속운전되고 있기 때문에, 윤활조건이 가혹하게 되어지고 있다. 따라서 항상 사용유의 상태를 파악할 필요가 있다.

지혜 깊어지는 건강: 40대를 지켜라 -휴식을 취해도 풀리지 않는 만성피로증후군

  • Choe, Se-Hui
    • 건강소식
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    • v.35 no.3
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    • pp.18-20
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    • 2011
  • 피로(疲勞)의 사전적 의미는 과로로 인해 정신이나 몸이 지쳐 힘든 상태를 말한다. 과도한 업무나 스트레스, 수면부족, 지나친 음주 등으로 인해 신체 리듬이 깨지면 피곤함을 쉽게 느끼게 된다. 대부분 충분한 휴식을 취하면 피곤함이 덜어지는데 휴식을 취해도 1개월 이상 피로가 계속되면 지속성(prolonged)피로, 6개월 이상 지속되면 만성(chronic)피로를 분류된다.

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A Energy Saving Method using Cluster State Transition in Sensor Networks (센서 네트워크에서 클러스터 상태 전이를 이용한 에너지 절약 방안)

  • Kim, Jin-Su
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.141-150
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    • 2007
  • This paper proposes how to reduce the amount of data transmitted in each sensor and cluster head in order to lengthen the lifetime of sensor network. The most important factor of reducing the sensor's energy dissipation is to reduce the amount of messages transmitted. This paper proposed is to classify the node's cluster state into 6 categories in order to reduce both the number and amount of data transmission: Initial, Cluster Head, Cluster Member, Non-transmission Cluster Head, Non-transmission Cluster Member, and Sleep. This should increase the efficiency of filtering and decrease the inaccuracy of the data compared to the methods which enlarge the filter width to do more filtering. This method is much more efficient and effective than the previous work. We show through various experiments that our scheme reduces the network traffic significantly and increases the network's lifetime than existing methods.

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Online Reinforcement Learning to Search the Shortest Path in Maze Environments (미로 환경에서 최단 경로 탐색을 위한 실시간 강화 학습)

  • Kim, Byeong-Cheon;Kim, Sam-Geun;Yun, Byeong-Ju
    • The KIPS Transactions:PartB
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    • v.9B no.2
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    • pp.155-162
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    • 2002
  • Reinforcement learning is a learning method that uses trial-and-error to perform Learning by interacting with dynamic environments. It is classified into online reinforcement learning and delayed reinforcement learning. In this paper, we propose an online reinforcement learning system (ONRELS : Outline REinforcement Learning System). ONRELS updates the estimate-value about all the selectable (state, action) pairs before making state-transition at the current state. The ONRELS learns by interacting with the compressed environments through trial-and-error after it compresses the state space of the mage environments. Through experiments, we can see that ONRELS can search the shortest path faster than Q-learning using TD-ewor and Q(λ)-learning using TD(λ) in the maze environments.

Correlation analysis between cerebral activation status and blood type (대뇌 활성화 상태 변화와 혈액형간의 상관성 분석)

  • Park, Yeon-Tae;Shin, Jeong-Hoon
    • Annual Conference of KIPS
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    • 2017.11a
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    • pp.1097-1099
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    • 2017
  • 본 논문은 대뇌 활성화 상태 변화와 혈액형간의 상관성 분석을 목적으로 한다. 혈액은 인체의 혈관을 통하여 몸 전체로 순환하는 액체 성 물질이다. 이 혈액을 구성하는 물질의 이질적 차이를 나타내는 차별적 유형을 혈액형이라 하며, 혈액형은 멘델의 법칙에 따라 부모에서 자식으로 유전된다. [1] 최근 들어 혈액형이 가지는 유전적 특징을 통한 질병 진단 및 치료, 예방을 위한 연구가 진행되고 있으나, 대부분의 연구는 육체적인 질병과 관련되어 있는 실정이다. 그러나, 혈액형의 경우 유전적 특성을 가지고 있으며, 신경 전달 망에 영향을 끼칠 것으로 추정 되는바 육체적 질병뿐만 아닌 정신적인 질환에도 혈액형에 따른 치료 및 예방방법을 차별화 하여, 보다 효율적인 치료 및 예방을 수행 할 수 있을 것으로 판단된다. 본 논문에서는 이를 위하여, 외부자극에 따른 대뇌 활성화 상태 변화를 분석하며, 특히 혈액형에 따른 상태변화의 상관성을 분석하고자 한다. 본 논문에서 활용하는 외부 자극은 청각 자극을 활용하며, 먼저 혈액형에 따른 피험자 군의 분류를 수행하여 동일 군 내 공통반응 및 상이한 군 간의 특이반응을 분석하여, 혈액형이 대뇌 활성화 상태 변화 및 정신질환에 따른 증상발현 등과 유관함을 검증하고자 한다.