• Title/Summary/Keyword: 패턴 개수

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Electrophoretic karyotype of Flammulina velutipes and its variation among cultivars (팽이버섯의 핵형분석과 균주 사이의 핵형 다양성)

  • Lee, Song Hee;Lee, Mi-Kyoung;Kim, Na-Ri;Lee, Chang-Yun;Lee, Hyun-Sook
    • Journal of Mushroom
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    • v.12 no.1
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    • pp.63-66
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    • 2014
  • The karyotype of F. velutipes Korean cultivar, Fv 3-6, was compared with those of Japanese cultivars, Fv 0-1, Fv 1-5, Fv 11-1, by CHEF gel electrophoresis. The Korean cultivar, Fv 3-6, showed the difference from the three Japanese cultivars in number and size of chromosomes; the Fv 3-6 had two and one more chromosomes then Fv 0-1 and Fv 11-4, and Fv 1-5 had, respectively. The karyotyping by CHEF gel electrophoresis is quite suitable to define new Korean cultivars against Japanese cultivars.

Recognization of Inflammable Gases Using Sensor Array and Principal Component Analysis (센서 어레이와 주성분 기법을 이용한 가연성 가스 인식)

  • Lee, Dae-Sik;Huh, Jeung-Soo;Lee, Duk-Dong
    • Journal of Sensor Science and Technology
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    • v.10 no.2
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    • pp.108-117
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    • 2001
  • A sensor array with 10 discrete sensors integrated on a substrate w3s developed for discriminating the kinds and quantities of inflammable gases, like butane, propane, methane, LPG, carbon monoxide. The sensor array consisted of 10 metal oxide semiconductor gas sensors using the nano-sized $SnO_2$ as base material and had differentiated sensitivity patterns to specific gas. The sensor array was designed with uniform thermal distribution and had also high sensitivity and good reproductivity to low gas concentration through nano-sized sensing materials with different additives. By using the sensing patterns of the sensor array at $400^{\circ}C$, we could reliably discriminate the kinds and quantities of the tested inflammable gases under the lower explosion limit through the principal component analysis(PCA).

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Study on Influence of Air Flow of Ceiling Type Air Conditioner on Fire Detector Response (천장형에어컨 기류가 화재감지기 작동에 미치는 영향 분석)

  • Choi, Moon-Soo;Lee, Keun-Oh
    • Fire Science and Engineering
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    • v.32 no.5
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    • pp.40-45
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    • 2018
  • This paper is an analysis of the influence of ceiling air conditioner airflow on fire detector response. In order to analyze the response characteristics of fire detector while forming air flow of a ceiling-type air conditioner, fire tests were carried out in accordance with ISO standard. This experiment was carried out in a fire test site of 10 m (width) ${\times}$ 7 m (length) ${\times}$ 4 m (height). As a result of the experiment, the response of fire detector shows a normal pattern that is delayed as the distance from the fire source is increased in the absence of the air conditioner, but it is confirmed that the pattern is not maintained in the strong air flow. When the air flow of air conditioner was strong, the response time was increased by 121% in the smoke detector and by 39% in the heat detector. In the case of ceiling type air conditioners, it is considered that the number of fire detectors should be increased, or a detector with high sensitivity should be installed for early detection of fire.

Sequence Stream Indexing Method using DFT and Bitmap in Sequence Data Warehouse (시퀀스 데이터웨어하우스에서 이산푸리에변환과 비트맵을 이용한 시퀀스 스트림 색인 기법)

  • Son, Dong-Won;Hong, Dong-Kweon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.2
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    • pp.181-186
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    • 2012
  • Recently there has been many active researches on searching similar sequences from data generated with the passage of time. Those data are classified as time series data or sequence data and have different semantics from scalar data of traditional databases. In this paper similar sequence search retrieves sequences that have a similar trend of value changes. At first we have transformed the original sequences by applying DFT. The converted data are more suitable for trend analysis and they require less number of attributes for sequence comparisons. In addition we have developed a region-based query and we applied bitmap indexes which could show better performance in data warehouse. We have built bitmap indexes with varying number of attributes and we have found the least cost query plans for efficient similar sequence searches.

The Characteristics of Analogies Generated by Science-Gifted Students Depending on the Consideration of Attributes and Relationships in the Processes of Generating Analogies (비유 생성 과정에서 속성과 관계에 대한 고려 여부에 따라 과학영재들이 생성한 비유의 특징)

  • Kim, You-Jung;Park, Won;Noh, Tae-Hee
    • Journal of the Korean Chemical Society
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    • v.54 no.5
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    • pp.621-632
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    • 2010
  • In this study, we examined the characteristics of analogies generated by science-gifted students depending on the consideration of attributes and relationships in the processes of generating analogies and investigated the applicability of analogy-generating activities in science-gifted education programs. The analyses of the results revealed that the analogy-generating processes of science-gifted students were categorized into three kinds of patterns depending on the consideration of attributes and relationships of the target concept and the source analog. There are also some differences in the types of analogies generated and selected to be good, and in the proper mapping numbers by the patterns depending on the consideration of attributes and relationships. Most science-gifted students used the analogy-generating activities to other target concept, and recognized them to be useful. However, they had difficulties in selecting source analogs at the processes of generating analogy. These obtained in this study will help to explore a potential use of the analogy-generating activities in an effective education program for fostering the creativity of science-gifted students.

Segmentation and Recognition of Traffic Signs using Shape Information and Edge Image in Real Image (실영상에서 형태 정보와 에지 영상을 이용한 교통 표지판 영역 추출과 인식)

  • Kwak, Hyun-Wook;Oh,Jun-Taek;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.11B no.2
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    • pp.149-158
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    • 2004
  • This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.

Daily Behavior Pattern Extraction using Time-Series Behavioral Data of Dairy Cows and k-Means Clustering (행동 시계열 데이터와 k-평균 군집화를 통한 젖소의 일일 행동패턴 검출)

  • Lee, Seonghun;Park, Gicheol;Park, Jaehwa
    • Journal of Software Assessment and Valuation
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    • v.17 no.1
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    • pp.83-92
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    • 2021
  • There are continuous and tremendous attempts to apply various sensor systems and ICTs into the dairy science for data accumulation and improvement of dairy productivity. However, these only concerns the fields which directly affect to the dairy productivity such as the number of individuals and the milk production amount, while researches on the physiology aspects of dairy cows are not enough which are fundamentally involved in the dairy productivity. This paper proposes the basic approach for extraction of daily behavior pattern from hourly behavioral data of dairy cows to identify the health status and stress. Total four clusters were grouped by k-means clustering and the reasonability was proved by visualization of the data in each groups and the representatives of each groups. We hope that provided results should lead to the further researches on catching abnormalities and disease signs of dairy cows.

Estimation of urban drinking water consumption patterns based on smart water grid monitoring data by k-means clustering in Vietnam (k-means 군집화 기법을 이용한 베트남 스마트워터그리드 계측 데이터 기반 도시 물 사용 패턴 추정)

  • Koo, Kang Min;Han, Kuk Heon;Lee, Gyumin;Jun, Kyung Soo;Yum, Kyung Taek
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.419-419
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    • 2021
  • 수자원 관리 패러다임은 공급 위주에서 수요관리로 전환되고 있다. 가용한 수자원은 한정적이나 급속한 인구증가와 도시화로 인한 물 수요의 증가로 수요관리의 효율성이 중시되고 있기 때문이다. 기존 상수도시스템은 노후화로 가동효율이 점차 낮아지고 있으며, 인력으로 월 또는 격월로 소비자의 물 사용량을 검침해 실시간 관리가 불가능하여 수요와 공급의 불균형을 초래한다. 이러한 문제를 해결할 대안으로 IT 기술과 전통적인 물관리 기술을 접목한 Smart Water Grid는 양방향 통신장치를 이용해 실시간으로 소비자의 물 사용량을 모니터링한다. 물 사용 특성을 잘 파악하면 보다 정확한 물 수요 예측이 가능하다. 특히 소비자들의 시간별, 평일, 주말, 그리고 주별 물 사용 특성을 파악하면 미래 물 수요 예측에 도움이 된다. 예측된 물 수요량에 따라 물 공급 배분 계획을 수립하여 운영 효율성을 높일 수 있다. 물 수요예측 방법 중 k-mean 군집분석은 시간별 물 사용량을 이용해 서로 유사한 여러 개의 부분집합으로 할당하여 분류하는 Machine learing 방법으로 물 사용의 유사성을 파악할 수 있다. SWG 연구단은 2019년 Vietnam Hai Duong province에 SWG Pilot plant를 구축하고 27개의 Smart water meter를 설치하여 운영하고 있다. 이에 본 연구에서는 소비자의 물 사용 특성을 분석하기 위해 27개 SWM로부터 수신된 2019년 11월 14일부터 2020년 12월 3일까지 1시간 단위의 물 사용량 데이터를 수집하였다. 그리고 k-mean 군집 방법을 이용해 시간별, 평일, 주말, 그리고 주별 물 사용 특성을 분석하였다. 이 때 최적의 군집 개수 결정을 위해 Elbow 방법을 적용하였다. 분석 결과 각 소비자의 물 사용량 특성에 따라 평균 물 수요패턴 추정이 가능하며, 향후 물 수요 예측에 도움이 될 것으로 사료된다.

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Development of RFID Biometrics System Using Hippocampal Learning Algorithm Based on NMF Feature Extraction (NMF 특징 추출기반의 해마 학습 알고리즘을 이용한 RFID 생체 인증시스템 구현)

  • Kwon, Byoung-Soo;Oh, Sun-Moon;Joung, Lyang-Jae;Kang, Dae-Seong
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2005.11a
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    • pp.171-174
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    • 2005
  • 본 논문에서는 인가의 인지학적인 두뇌 원리인 대뇌피질과 해마 신경망을 공학적으로 모델링하여 얼굴 영상의 특징 벡터들을 고속 학습하고, 각 영상의 최적의 특징을 구성할 수 있는 해마 학습 알고리즘(Hippocampal Learning Algorithm)을 개발하여 RFID를 이용한 생체인식 시스템을 제안한다. 입력되는 얼굴 영상 데이터들은 NMF(Non-negative Matrix Factorization)를 이용하여 특징이 구성되고, 이러한 특징들은 해마의 치아 이랑 영역에서 호감도 조정에 따라서 반응 패턴으로 이진화 되고, CA3 영역에서 자기 연상 메모리 단계를 거쳐 노이즈를 제거한다. CA3의 정보를 받는 CA1영역에서는 단층 신경망에 의해 단기기억과 장기기억으로 나누어서 저장되고 해당 특징의 누적 개수가 문턱치(threshold)를 만족하면 장기 기억 장소로 저장시키도록 한다. 위와 같은 개념을 바탕으로 구현되는 RFID 생체인식 시스템은 특징의 분별력과 학습속도면에서 우수한 성능을 보일 수 있다.

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Feature Selection and Performance Analysis using Quantum-inspired Genetic Algorithm (양자 유전알고리즘을 이용한 특징 선택 및 성능 분석)

  • Heo, G.S.;Jeong, H.T.;Park, A.;Baek, S.J.
    • Smart Media Journal
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    • v.1 no.1
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    • pp.36-41
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    • 2012
  • Feature selection is the important technique of selecting a subset of relevant features for building robust pattern recognition systems. Various methods have been studied for feature selection from sequential search algorithms to stochastic algorithms. In this work, we adopted a Quantum-inspired Genetic Algorithm (QGA) which is based on the concept and principles of quantum computing such as Q-bits and superposition of state for feature selection. The performance of QGA is compared to that of the Conventional Genetic Algorithm (CGA) with respect to the classification rates and the number of selected features. The experimental result using UCI data sets shows that QGA is superior to CGA.

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