• 제목/요약/키워드: detect

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A Dimensionality Assessment for Polytomously Scored Items Using DETECT

  • Kim, Hae-Rim
    • Communications for Statistical Applications and Methods
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    • 제7권2호
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    • pp.597-603
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    • 2000
  • A versatile dimensionality assessment index DETECT has been developed for binary item response data by Kim (1994). The present paper extends the use of DETECT to the polytomously scored item data. A simulation study shows DETECT performs well in differentiating multidimensional data from unidimensional one by yielding a greater value of DETECT in the case of multidimensionality. An additional investigation is necessary for the dimensionally meaningful clustering methods, such as HAC for binary data, particularly sensitive to the polytomous data.

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선박화재감지를 위한 Addressable Type Smoke Detect System 구현 (An Addressable Type Smoke Detect System Implementation to detect the Fire on a Ship)

  • 김태석;김종수
    • 한국정보통신학회논문지
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    • 제15권12호
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    • pp.2543-2548
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    • 2011
  • 대형 화물선, 벌크선과 같은 선박에서 일어날 수 있는 해상화재를 초기에 진압하기 위한 요구사항을 바탕으로 선박용 연기감지시스템이 제작되어 선박에 장착되고 있다. Addressable Type으로 화재감지설비를 설계하는 것은 기존의 방식으로 설계를 했을 경우에 화재가 발생하면 전선의 단선으로 인해 전체 설비의 화재감지가 불가능하게 되는 단점을 보완할 수 있다. 본 논문에서는 ATmega 마이크로컨트롤러를 사용한 연기감지시스템의 개발을 위한 시스템을 구현하였고, 평가하였다.

A Refinement on DETECT for Polytomous Test Data

  • Kim, Hae-Rim
    • Communications for Statistical Applications and Methods
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    • 제13권3호
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    • pp.467-477
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    • 2006
  • A multidimensionality detecting procedure DETECT, based on conditional covariances between items, is extended and refined to deal with polytomous item data as well as binary one. A large body of simulation study shows extraordinary performance of DETECT in both enumerating degrees of multidimensionality in a test and discovering dimensionally distinctive item clusters. Real data study also provides very meaningful results, making DETECT a strong dimensionality assessment tool for the test data analysis.

A NEW INDEX OF DIMENSIONALITY - DETECT

  • Kim, Hae-Rim
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제3권2호
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    • pp.141-154
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    • 1996
  • A data-driven index of dimensionality for an educational or psychological test - DETECT, short for Dimensionality Evaluation To Enumerate Contributing Traits, is proposed in this paper. It is based on estimated conditional covariances of item pairs, given score on remaining test items. Its purpose is to detect whatever multidimensionality structure exists, especially in the case of approximate simple structure. It does so by assigning items to relatively dimensionally homogeneous clusters via attempted maximization of the DETECT over all possible item cluster partitions. The performance of DETECT is studied through real and simulated data analyses.

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토마토 잎의 비파괴 계측에 의한 N, P, Ca 결핍 장해 진단법 비교 (Comparison of Non-destructive Measuring Methods of Tomato Plant to Detect N, P and Ca Deficient Stresses)

  • 서상룡;류육성;정갑채;성제훈;이성희
    • Journal of Biosystems Engineering
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    • 제25권6호
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    • pp.517-526
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    • 2000
  • A series of experiments was conducted to evaluate the capability of detecting nutrimental deficient stress of N, P and Ca of a tomato plant using several fast and intact type physiological properties measuring devices - a chlorophyll content meter an infra-red thermometer to measure leaf temperature a chlorophyll fluorescence meter a porometer an optical spectrometer a multi-scan radiometer and a canopy analyzer. to detect N deficient stress a chlorophyll content meter a spectrometer and a multi-scan radiometer were useful and their possibility to detect was estimated as about 50%, 100% and 100% respectively. To detect P deficient stress the infra-red thermometer the porometer and the spectrometer proved their usefulness an their possibility to detect was estimated as about 70%, 70% and 70% respectively. To detect Ca deficient stress an thermometer a porometer a spectrometer and a multi-scan radiometer were useful and their possibility to detect was estimated as about 60%, 70%,80% and 100% respectively. The experiments resulted that use of a spectrometer and a multi-scan radiometer in combination with a chlorophyll content meter an infra-red thermometer and a porometer were desirable to distinguish the nutrimental stress tested in the study.

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유방 초음파 검사 시 S-detect 방법을 활용한 인자 분석 (Factor analysis using S-detect Method in Breast Ultrasound)

  • 천혜리;장현철;조평곤
    • 한국방사선학회논문지
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    • 제13권1호
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    • pp.9-14
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    • 2019
  • 본 연구는 유방 초음파 검사 시 S-detect 성능에 관한 내용을 알아보고 이에 따라 조직 검사와 비교하여 불필요한 조직 검사를 줄일 수 있는 방안을 알아보고자 하였다. 2018년 8월에서 10월까지 유방초음파 검사를 시행한 환자 중 유방결절이 발견되어 조직 검사가 계획된 30명의 환자를 대상으로 후향적으로 분석하였다. S-detect 방법에서의 악성 감별과 Biopsy에서의 악성감별에 유의한 차이가 있는지 알아보기 위해 Mc Nemar test 분석을 실시하였다. S-detector 방법의 분석 결과 민감도는 90.9 %, 특이도 84.21 %, 정확도 86.66%, 양성예측도 76.92%, 음성예측도 94.11 %로 나타났다. S-detect 방법과 Biopsy 방법 간에 일치도 분석 결과 kappa 값이 0.724(p<0.05)로 높게 나타났으며, 두 방법 간에 좋은 일치도를 보였다. 유방초음파 검사 시 S-detect를 활용한 검사 방법에 있어서 유방 종괴에 악성과 양성 감별 진단에 있어서 진단적으로 가치가 있었으며, 유방조직 검사 실시 전 적절히 활용한다면 불필요한 조직 검사를 줄일 수 있는데 도음을 줄 것이다.

Some Asymptotic Properties of Conditional Covariance in the Item Response Theory

  • Kim, Hae-Rim
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.959-966
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    • 2000
  • A dimensionality assessment procedure DETECT uses the property of being near zero of conditional covariances as an indication of unidimensionality .This study provides the convergent properties to zero of conditional covariances when the dta is unidimensional, with which DETECT extends its theoretical grounds.

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특정 물질 검출을 위한 비 접촉식 마이크로웨이브 센서 (A Contactless Microwave Sensor for Detection of particular Materials)

  • 기현철
    • 한국인터넷방송통신학회논문지
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    • 제12권4호
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    • pp.1-6
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    • 2012
  • 전자기파와 반응하는 주파수가 너무 높아 기존의 UWB 센서로 검출하기 어려운 공기 중의 특정 물질 입자를 검출하기위한 마이크로웨이브 센서 구조를 제시하고 실험 제작하였다. 10GHz의 상향주파수로 공기 중의 수분입자를 검출하는 실험 결과 수분입자의 유무에 따라 75%의 검출 신호 크기의 변화가 발생함을 확인하였다. 이는 다른 물질을 검출하는 데도 같은 방법이 적용될 수 있으므로 수십 GHz이상의 높은 주파수 대역에서 특정 물질을 검출하기에 유용한 구조가 될 수 있을 것이다.

A Feature-Based Malicious Executable Detection Approach Using Transfer Learning

  • Zhang, Yue;Yang, Hyun-Ho;Gao, Ning
    • 인터넷정보학회논문지
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    • 제21권5호
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    • pp.57-65
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    • 2020
  • At present, the existing virus recognition systems usually use signature approach to detect malicious executable files, but these methods often fail to detect new and invisible malware. At the same time, some methods try to use more general features to detect malware, and achieve some success. Moreover, machine learning-based approaches are applied to detect malware, which depend on features extracted from malicious codes. However, the different distribution of features oftraining and testing datasets also impacts the effectiveness of the detection models. And the generation oflabeled datasets need to spend a significant amount time, which degrades the performance of the learning method. In this paper, we use transfer learning to detect new and previously unseen malware. We first extract the features of Portable Executable (PE) files, then combine transfer learning training model with KNN approachto detect the new and unseen malware. We also evaluate the detection performance of a classifier in terms of precision, recall, F1, and so on. The experimental results demonstrate that proposed method with high detection rates andcan be anticipated to carry out as well in the real-world environment.

암순응 환경에서 조도수준과 표적크기가 탐지시간에 미치는 영향 (Effects of Illumination and Target Size on Time-To-Detect while Recovering Dark Adaptation)

  • 박재규;박성하;오현승
    • 대한인간공학회지
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    • 제28권4호
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    • pp.71-76
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    • 2009
  • Effects of dark adaptation have large safety implications. This study was aimed to investigate the effects of varying illuminance and the size of critical detail on visual performance (i.e., time-to-detect) in a dark room environment. While adapting to the dark environment, ten subjects were asked to detect and answer simple numerical expressions under 9 experimental conditions (3 illuminance level $\times$ 3 target size). The ANOVA results revealed that the time-to-detect was significantly affected by both of the illumination level and the size of critical detail. As illumination increased from 10 lux to 20 lux, the time-to-detect was significantly declined. For the size of critical detail, 0.5/min size (i.e., equal to 2 minutes of visual angle) resulted in a shorter time-to-detect, as compared to 0.7/min size (i.e., equal to 1.6 minutes of visual angle). Potential applications of this research include the development of design guidelines for illumination and warning signs in poorly illuminated viewing environments.