• 제목/요약/키워드: pre-set

검색결과 976건 처리시간 0.027초

ON PC-CLOSED SETS

  • Ekici, Erdal;Tunc, A. Nur
    • 충청수학회지
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    • 제29권4호
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    • pp.565-572
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    • 2016
  • In this paper, the concept of $PC^{\star}$-closed sets is introduced. $PC^{\star}$-closed sets contain $pre^*_I$-open and $pre^*_I$-closed sets, ${\mathcal{RPC}}_I$ and $pre^*_I$-closed sets, ${\mathcal{RPC}}_I$ and weakly $I_{rg}$-closed sets.

가공공정 중 열처리 온도에 의한 PET/PBT 혼섬사 직물의 형태와 태의 변화 (The Effect of Heat Treatment Temperature on the Dimension and Handle of PET/PBT Fabric)

  • 신혜원
    • 한국의류학회지
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    • 제27권5호
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    • pp.582-587
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    • 2003
  • To examine the effect of heat treatment temperature in finishing process on PET/PBT Fabric, PET/PBT Fabrics were treated at different relaxing temp., pre-set temp., and final-set temp.. The dimensions such as thickness and density were measured, and the handles were evaluated by Kawabata system. In relaxing which was wet heat treatment, thickness and bulkiness were increased, and NUMERI, FUKURAMI, SOFUTOSA, and THV also were increased but KOSHI was decreased with elevating temperature. With elevating pre-set temp., thickness and bulkiness were decreased, but KOSHI was increased. NUMERI, FUKURAMI, SOFUTOSA, and THV were the best at 180$^{\circ}C$ pre-set treatment. In final-set which was dry heat treatment like pre-set, thickness, bulkiness, NUMERI, HUKURAMI, SOFUTOSA, and THV were decreased, but KOSHI value was increased with elevating temperature. Therefore the best heat treatment condition was 130$^{\circ}C$ relaxing, 180$^{\circ}C$ pre-set, and 160$^{\circ}C$ final-set. And the handle of PET/PBT Fabric was affected much more by relaxing temp. than pre-set temp. and final-set temp.

SEVERAL KINDS OF INTUITIONISTIC FUZZY OPEN SETS AND INTUITIONISTIC FUZZY INTERIORS

  • Kim, Chang-Su;Kang, Jeong-Gi;Kim, Myoung-Jo;Ko, Mi-Young;Park, Mi-Ran
    • 호남수학학술지
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    • 제32권2호
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    • pp.307-331
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    • 2010
  • The notion of intuitionistic fuzzy semi-pre interior (semi-pre closure) is introduced, and several related properties are investigated. Characterizations of an intuitionistic fuzzy regular open set, an intuitionistic fuzzy semi-open set and an intuitionistic fuzzy ${\gamma}$-open set are provided. A method to make an intuitionistic fuzzy regular open set (resp. intuitionistic fuzzy regular closed set) is established. A relation between an intuitionistic fuzzy ${\gamma}$-open set and an intuitionistic fuzzy semi-preopen set is considered. A condition for an intuitionistic fuzzy set to be an intuitionistic fuzzy ${\gamma}$-open set is discussed.

ON SPECIAL SETS IN PRE-LOGICS

  • Ahn, Sun-Shin;Yoo, Jae-Kwang
    • 호남수학학술지
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    • 제33권1호
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    • pp.61-71
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    • 2011
  • The notion of a complicated pre-logic is introduced and investigated some properties of it. A special set in a pre-logic is established and some related its properties are discussed. Also more extended special sets in a pre-logic are introduced and some relations with deductive systems are obtained.

OBTAINING WEAKER FORM OF CLOSED SETS IN TOPOLOGICAL SPACE USING PYTHON PROGRAM

  • Prabu, M. Vivek;Rahini, M.
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제29권1호
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    • pp.93-102
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    • 2022
  • The impact of programming languages in the research sector has helped lot of researchers to broaden their view and extend their work without any limitation. More importantly, even the complex problems can be solved in no matter of time while converting them into a programming language. This convenience provides upper hand for the researchers as it places them in a comfort zone where they can work without much stress. With this context, we have converted the research problems in Topology into programming language with the help of Python. In this paper, we have developed a Python program to find the weaker form of closed sets namely alpha closed set, semi closed set, pre closed set, beta closed set and regular closed set.

Flows over Concave Surfaces: Development of Pre-set Wavelength Görtler Vortices

  • Winoto, S.H.;Tandiono, Tandiono;Shah, D.A.;Mitsudharmadi, H.
    • International Journal of Fluid Machinery and Systems
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    • 제1권1호
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    • pp.10-23
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    • 2008
  • The development of pre-set wavelength G$\ddot{o}$rtler vortices are studied in the boundary-layer flows on concave surfaces of 1.0 and 2.0 m radius of curvature. The wavelengths of the vortices were pre-set by thin wires of 0.2 mm diameter placed 10 mm upstream and perpendicular to the concave surface leading edge. Velocity contours were obtained from velocity measurements using a single hot-wire anemometer probe. The most amplified or dominant wavelength is found to be 15 mm for free-stream velocity of 2.1 m/s and 3.0 m/s on the concave surface of R = 1 m and 2 m, respectively. The velocity contours in the cross-sectional planes at several streamwise locations show the growth and breakdown of the vortices. Three different regions can be identified based on the growth rate of the vortices. The occurrence of a secondary instability mode is also shown in the form of mushroom-like structures as a consequence of the non-linear growth of the G$\ddot{o}$rtler vortices. By pre-setting the vortex wavelength to be much larger and much smaller than the most amplified one, the splitting and merging of G$\ddot{o}$rtler vortices can be respectively observed.

기계학습을 이용한 벼 수발아율 예측 (Predicting the Pre-Harvest Sprouting Rate in Rice Using Machine Learning)

  • 반호영;정재혁;황운하;이현석;양서영;최명구;이충근;이지우;이채영;윤여태;한채민;신서호;이성태
    • 한국농림기상학회지
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    • 제22권4호
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    • pp.239-249
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    • 2020
  • 본 연구는 자연 조건에서 쌀가루용 벼의 수발아율을 예측하기 위한 것으로 기계학습을 이용하여 기상요소들에 따른 수발아율을 간단히 예측할 수 있는 초기 시스템을 개발하기 위해 수행되었다. 이를 위하여 강원도, 충청북도, 경상북도에 위치한 6개 지역에서 쌀가루용 벼 3품종을 재배하였다. 수확 후 수발아율과 출수일을 조사하였으며, 각 지역의 종관기상대의 일평균 기온과 상대 습도, 그리고 강수량 정보를 이용하여 기계학습 모델 중 하나이며, 정확도가 높은 GBM 모델로 수발아율을 예측하였다. 2017년부터 2019년까지 강원과 충북, 그리고 경북의 6개 지역에서 쌀가루 용 벼 3품종에 대해 재배 실험을 수행하였다. 조사 항목은 출수일과 수발아율이었다. 기상자료는 동일한 지역명의 종관기상대를 이용하여 일 평균 기온 및 상대 습도, 그리고 강수량 자료를 수집하였다. 수발아율 예측을 위해 기계학습 모델인 Gradient Boosting Machine (GBM)을 이용하였으며, 학습 투입 변수로는 평균 기온과 상대 습도, 그리고 총 강수량이었다. 또한 수발아 피해 관련 기간을 설정하기 위해 출수 후 몇일 후부터 그 이후의 기간에 대한 실험도 수행하였다. 자료는 수발아 피해 관련 기간의 교정을 위한 training-set과 vali-set, 검증을 위한 test-set으로 구분하였다. training-set과 vali-set으로 교정한 결과, 출수 후 22일 후부터 24일동안에서 가장 높은 score를 나타내었다. test-set으로 검증한 결과는 3.0%보다 낮은 구간에서 수발아율을 약간 높게 예측한 경향이 있었지만, 높은 예측력을 보였다(R2=0.76). 따라서, 기계학습을 이용하여 특정기간동안의 기상요소들로 수발아율을 간단하게 예측할 수 있을 것으로 예상된다. 본 연구의 결과를 종합해 볼 때, 기계학습을 이용하여 특정 기간 동안에 평균 기온과 상대 습도, 그리고 총 강수량으로 높은 수발아율 예측 성능을 보였으며, 이 시스템을 이용하여 일반 농가들을 대상으로 수발아에 관한 피해를 예방할 수 있는 조기 수발아 예측 시스템으로 이용가능 할 것으로 판단된다. 하지만 품종마다 휴면 정도 차이로 인한 수발아 관련 기간에 차이가 있으므로, 다른 쌀가루용 벼 품종에 대해서도 추가로 조사하고, 개별 품종으로 세분화하여 분석한다면 좀 더 정확도 높은 예측 시스템을 개발할 수 있을 것으로 판단된다.