• Title/Summary/Keyword: MaxMin

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A Parallel Algorithm for Merging Relaxed Min-Max Heaps (Relaxed min-max 힙을 병합하는 병렬 알고리즘)

  • Min, Yong-Sik
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.5
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    • pp.1162-1171
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    • 1998
  • This paper presents a data structure that implements a mergable double-ended priority queue : namely an improved relaxed min-max-pair heap. By means of this new data structure, we suggest a parallel algorithm to merge priority queues organized in two relaxed heaps of different sizes, n and k, respectively. This new data-structure eliminates the blossomed tree and the lazying method used to merge the relaxed min-max heaps in [9]. As a result, employing max($2^{i-1}$,[(m+1/4)]) processors, this algorithm requires O(log(log(n/k))${\times}$log(n)) time. Also, on the MarPar machine, this method achieves a 35.205-fold speedup with 64 processors to merge 8 million data items which consist of two relaxed min-max heaps of different sizes.

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Merging Algorithm for Relaxed Min-Max Heaps Relaxed min-max 힙에 대한 병합 알고리즙

  • Min, Yong-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.1E
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    • pp.73-82
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    • 1995
  • This paper presents a data structure that implements a mergeable double-ended priority queue ; namely, an improved relaxed min-max-pair heap. It suggests a sequential algorithm to merge priority queues organized in two relaxed min-max heaps : kheap and nheap of sizes k and n, respecrively. This new data sturuture eliminates the blossomed tree and the lazying method used to merge the relaxed min-max heaps in [8]. As a result, the suggested method in this paper requires the time complexity of O(log(log(n/k))*log(k)) and the space complexity of O(n+), assuming that $k{\leq}{\lfloor}log(size(nheap)){\rfloor}$ are in two heaps of different sizes.

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Prediction of VO2max Using Submaximal PACER in Obese Middle School Boys (최대하 PACER 검사를 통한 비만 남자 중학생의 VO2max 추정)

  • Kim, Do-Youn;Kim, Won-Hyun
    • Journal of Digital Convergence
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    • v.11 no.3
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    • pp.371-380
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    • 2013
  • The purpose of this study was to develop the equation of $\dot{V}O_{2max}$ by $sub_{max}imal$ PACER method for obese middle school boys. For this, $_{max}$imal test using Bruce protocol in lab was performed and then PACER $_{max}imal$ test with portable $\dot{V}O_{2max}$ equipment. To decide the level of submaximal test, during PACER with portable equipment, we found the section in which target hreat rate(over 75%$HR_{max}$) and then per section(75%,80%,85%,90%,95%) metabolic responses were recorded, with which we analyzed multiple regression by stepwise method. Model 1(at 90%$HR_{max}$): $\dot{V}O_{2max}$(ml/kg/min) = 142.721-0.275(repetition)-0.48(HR)+0.177(weight)-1.536(age)[%error 3.90ml/kg/min; performance until 2 stage(13 repetition)]. Model 2(at 95%$HR_{max}$): $\dot{V}O_{2max}$(ml/kg/min) = 182.851-0.103(repetition)-0.744(HR)+0.186(weight)-0.324(age)[%error 4.51ml/kg/min; performance until 3 stage(25 repetitions)]. estimated $\dot{V}O_{2max}$ from Model 1 was different about $3.25{\pm}6.32ml/kg/min$(%error=6.84%), otherwise model 2 was $3.16{\pm}4.54ml/kg/min$(%error=5.75%). considering %HRmax, as the submaximal test model 1 might be fit more than model 2 for obese middle school boys.

Damaged Traffic Sign Recognition using Hopfield Networks and Fuzzy Max-Min Neural Network (홉필드 네트워크와 퍼지 Max-Min 신경망을 이용한 손상된 교통 표지판 인식)

  • Kim, Kwang Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.11
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    • pp.1630-1636
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    • 2022
  • The results of current method of traffic sign detection gets hindered by environmental conditions and the traffic sign's condition as well. Therefore, in this paper, we propose a method of improving detection performance of damaged traffic signs by utilizing Hopfield Network and Fuzzy Max-Min Neural Network. In this proposed method, the characteristics of damaged traffic signs are analyzed and those characteristics are configured as the training pattern to be used by Fuzzy Max-Min Neural Network to initially classify the characteristics of the traffic signs. The images with initial characteristics that has been classified are restored by using Hopfield Network. The images restored with Hopfield Network are classified by the Fuzzy Max-Min Neural Network onces again to finally classify and detect the damaged traffic signs. 8 traffic signs with varying degrees of damage are used to evaluate the performance of the proposed method which resulted with an average of 38.76% improvement on classification performance than the Fuzzy Max-Min Neural Network.

An Enhanced Max-Min Neural Network using a Fuzzy Control Method (퍼지 제어 기법을 이용한 개선된 Max-Min 신경망)

  • Kim, Kwang-Baek;Woo, Young-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.8
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    • pp.1195-1200
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    • 2013
  • In this paper, we proposed an enhanced Max-Min neural network by auto-tuning of learning rate using fuzzy control method. For the reduction of training time required in the competition stage, the method was proposed that arbitrates dynamically the learning rate by applying the numbers of the accuracy and the inaccuracy to the input of the fuzzy control system. The experiments using real concrete crack images showed that the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

Recognition of Concrete Surface Cracks Using Enhanced Max-Min Neural Networks (개선된 Max-Min 신경망을 이용한 콘크리트 균열 인식)

  • Kim, Kwang-Baek;Park, Hyun-Jung
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.77-82
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    • 2007
  • In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the enhanced Max-Min neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation or morphological techniques, the Sobel masking for extracting for edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions of the cracks with the enhanced Max-Min neural network. Also, we propose an enhanced Max-Min neural network by auto-tuning of learning rate using delta-bar-delta algorithm. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

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View Maintenance Policy for considering MIN/MAX query in Data warehousing (데이터웨어하우징에서 MIN/MAX질의를 고려한 뷰관리 정책)

  • 김근형;김두경
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1336-1345
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    • 2002
  • Materialized views in data warehouse play important roles in rapidly answering to users's requests for information Processing. More views in data warehouse, can respond to the users more rapidly because the user's requests may be processed by using only the materialized views with higher probabilities rather than accessing base relations. The limited duration, during which the materialized views are updated due to base relations's changes, limits the number of materialized views in data warehouse. In this paper, we propose efficient policy for updating the materialized views, which can save the update duration of views although MIN/MAX values frequently change in base relation. The policy updates the materialized views by distinguishing whether MIN/MAX values's changes in the base relation are insert value or delete value. Then, the number of accesses to the base relation is descreased when updating the MIN/MAX values in the materialized views.

An Adaptive Neuro-Fuzzy System Using Fuzzy Min-Max Networks (퍼지 Min-Max 네트워크를 이용한 적응 뉴로-퍼지 시스템)

  • 곽근창;김성수;김주식;유정웅
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.367-367
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    • 2000
  • In this paper, an Adaptive neuro-fuzzy Inference system(ANFIS) using fuzzy min-max network(FMMN) is proposed. Fuzzy min-max network classifier that utilizes fuzzy sets as pattern classes is described. Each fuzzy set is an aggregation of fuzzy set hyperboxes. Here, the proposed method transforms the hyperboxes into gaussian membership functions, where the transformed membership functions are inserted for generating fuzzy rules of ANFIS. Finally, we applied the proposed method to the classification problem of iris data and obtained a better performance than previous works.

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Study of Contrast Sensitivities using Polarizer-Transmittance (편광 투과율을 이용한 대비 민감도(Cs) 특성 연구)

  • Park, Sang-An;Kim, Yong-Geun
    • Journal of Korean Ophthalmic Optics Society
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    • v.6 no.2
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    • pp.59-63
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    • 2001
  • Using the rotation of two polarizer plate and the area of transmittance In the visual light region measured by spectrophotometer, we obtained the luminance to measure the Contrast Sensitivity, and calculated the values of $L_{min}$ and ${\theta}_{min}$ after fixed the average contrast, $L_{max}$ and ${\theta}_{max}$ values from the values of two contrasts. Then, when it was fixed by $L_{max}=4000(T%nm)$ and ${\theta}_{max}=44.1^{\circ}$, $L_{min}$ and ${\theta}_{min}$ values were respectively given by 1333, 2666, 3920(T%nm) and 56.6, 54.3, $45^{\circ}$ in Cs values of 2.5, 100.

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COB, COH Package LED Module Thermal Analysis Simulation (COB, COH Package LED Module 열 해석 시뮬레이션)

  • Choi, Keum-Yeon;Eo, Ik-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.11
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    • pp.5117-5122
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    • 2011
  • In this paper, thermal analysis simulation program by taking advantage of COMSOL Multiphysics, LED Module for the production of the most preferred package type, omitting the COH Type COB Type and board simulation of the thermal analysis is in progress. LED Module that passes through the Heat-sink of the simulation results, depending on the location of the COB Type Max. Approximately $78^{\circ}C$ ~ Min. Approximately $62^{\circ}C$, COH Type the Max. Approximately $88^{\circ}C$ ~ Min. Approximately $67^{\circ}C$ has been confirmed that the temperature stability. Compared with COB Type Max. AIthough temperature difference is about $10^{\circ}C$, Min. At a temperature of about $5^{\circ}C$ confirmed to be enough to reduce the gap, LED Point confirming the results of the temperature curves for COB Type Max. Approximately $100^{\circ}C$ ~ Min. Approximately $77^{\circ}C$, COH Type the Max. Approximately $100^{\circ}C$ ~ Min. Approximately $86^{\circ}C$ temperature stability was confirmed that, COB Type COH Type, compared to approximately $10^{\circ}C$ temperature was higher.