• 대한수학회보
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• 제34권4호
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• pp.603-615
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• 1997

In this paper, we introduce and study a new class of random completely generalized nonlinear variational inclusions with non-compact valued random mappings and construct some new iterative algorithms. We prove the existence of random solutions for this class of random variational inclusions and the convergence of random iterative sequences generated by the algorithms.

• 한국컴퓨터정보학회논문지
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• 제24권8호
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• pp.9-17
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• 2019

In this paper, we propose a block mapping technique applicable to NAND flash memory. In order to use the NAND flash memory with the operating system and the file system developed on the basis of the hard disk which is mainly used in the general PC field, it is necessary to use the system software known as the FTL (Flash Translation Layer). FTL overcomes the disadvantage of not being able to overwrite data by using the address mapping table and solves the additional features caused by the physical structure of NAND flash memory. In this paper, we propose a new mapping method based on the block mapping method for efficient use of the NAND flash memory. In the case of the proposed technique, the data modification operation is processed by using a blank page in the existing block without using an additional block for the data modification operation, thereby minimizing the block unit deletion operation in the merging operation. Also, the frequency of occurrence of the sequential write request and random write request Accordingly, by optimally adjusting the ratio of pages for recording data in a block and pages for recording data requested for modification, it is possible to optimize sequential writing and random writing by maximizing the utilization of pages in a block.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.306-306
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• 2019

전지구적 기온상승으로 인해 미래기후의 관한 연구가 중요시 되고 있다. 위와 같은 현상으로 인하여 다양한 기후변화 연구가 진행되고 있다. 미래기후 연구에는 GCM (General Circulation Model) 모의 결과가 이용된다. 격자 자료로 구성된 GCM은 연구 지점으로 지역적 상세화와 연구지역의 관측자료 사이의 편이 보정(bias correction)이 필수적이다. 위와 같은 근거로 편이 보정 방법의 선택은 매우 중요하며 편의 보정의 방법에 따라서 결과가 다르게 도출될 수 있다. 또한 국내외 연구에서는 다양한 상세화 기법과 편이 보정 기법을 분석 및 평가하는 연구가 진행되고 있으며, 편의 기법 중 대표적인 기법인 Quantile mapping과 Random Forest 기법이 있다. Quantile mapping 기법은 GCM의 과거 모의 데이터와의 편이 보정에 있어서 우수하게 나타났으나, GCM 데이터의 미래 예측 기간(2010년~2018년)까지의 데이터에서는 극한 강수를 정량적으로 분석 가능한 Random Forest 기법이 편이 보정 과정에서 성능이 우수할 것으로 판단된다. 본 연구에서는 우리나라 21개 관측소를 기준으로 총 4개의 GCM(GISS, CSIRO, CCSM4,MIROC5)의 과거 기간 자료(1970년~2005년)를 실제 관측소에서 관측된 강수량을 편의 보정하는 방법에 있어서 편의 보정 기법의 성능을 비교한 결과와 GCM 미래 예측 기간 자료(2010년~2018년)에서의 편의 보정 기법의 성능 결과를 비교하였다. 이를 토대로 편이 보정 기법의 결과를 6개의 평가지수를 이용하여 정량적으로 분석하였으며, 다기준의사결정기법인 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution)를 이용하여 편이 보정기법들의 성능에 있어서 우선순위를 선정하였다. 본 연구에서 편이 보정 방법으로 Quantile mapping 방법을 사용했으며, Quantile mapping의 기법으로는 비모수 변환법(non-parametric transformation)과 분포기반 변환법(distribution derived transformation)이 사용되었다. 또한 머신러닝 방법 중 하나인 Random Forest 방법을 동시에 사용하여 결과를 비교하였다. 또한 GCM 자료가 격자식으로 제공하고 있기 때문에 관측소 강수량도 공간적으로 환산하여야 하는데, 본 연구에서는 역거리 가중치법(inverse distance weighting, IDW) 방법을 이용하였다.

• 대한원격탐사학회지
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• 제40권2호
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• pp.123-139
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• 2024

Forest vertical structure is vital for comprehending ecosystems and biodiversity, in addition to fundamental forest information. Currently, the forest vertical structure is predominantly assessed via an in-situ method, which is not only difficult to apply to inaccessible locations or large areas but also costly and requires substantial human resources. Therefore, mapping systems based on remote sensing data have been actively explored. Recently, research on analyzing and classifying images using machine learning techniques has been actively conducted and applied to map the vertical structure of forests accurately. In this study, Sentinel-2 and digital surface model images were obtained on two different dates separated by approximately one month, and the spectral index and tree height maps were generated separately. Furthermore, according to the acquisition time, the input data were separated into cases 1 and 2, which were then combined to generate case 3. Using these data, forest vetical structure mapping models based on random forest, support vector machine, and extreme gradient boost(XGBoost)were generated. Consequently, nine models were generated, with the XGBoost model in Case 3 performing the best, with an average precision of 0.99 and an F1 score of 0.91. We confirmed that generating a forest vertical structure mapping model utilizing bi-seasonal data and an appropriate model can result in an accuracy of 90% or higher.

• ETRI Journal
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• 제35권4호
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• pp.714-717
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• 2013

Peak power reduction techniques in orthogonal frequency division multiplexing (OFDM) has been an important subject for many researchers for over 20 years. In this letter, we propose a side-information-free technique that is based on the concept of random variable (RV) transformation. The suggested method transforms RVs into other RVs, aiming to reshape the constellation that will consequently produce OFDM symbols with a reduced peak-to-average power ratio. The proposed method has no limitation on the mapping type or the mapping order and has no significant effect on the bit error rate performance compared to other methods presented in the literature. Additionally, the computational complexity does not increase.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
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• pp.730-732
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• 2001

클러스터 환경에서 최근의 다양한 서비스의 증가로 인해 단순한 부하의 균등화만으로 적절한 지연 시간을 기대할 수 없게 되어, 내용-기반 맵핑(content-based mapping)이 제안되었다. 본 논문에서는 요구되는 내용을 기반으로 맵핑하며, 이질적 서버들에 대해 능력에 따라 우선 순위를 부여하여, 내용-기반 맵핑 방식을 이질적 환경에 적합하도록 개선시킨 우선순위 최상임의 가중치 맵핑(Prioritized Highest Random Weight Mapping, PHRW Mapping)을 제안하였다.

• Korean Journal of Mathematics
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• 제26권1호
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• pp.129-141
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• 2018

In this slush pile, we introduce a new kind of variational inclusions problem stated as random extended generalized nonlinear variational inclusions for random fuzzy mappings. We construct an iterative scheme for the this variational inclusion problem and also discuss the existence of random solutions for the problem. Further, we show that the approximate solutions achieved by the generated scheme converge to the required solution of the problem.

• 대한전기학회논문지
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• 제43권4호
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• pp.553-563
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• 1994

This paper presents a filtering method using neural networks to extract fundamental frequency components of the transient wave signals in power systems. Based on the ability of multilayer feedforward neural networks to approximate any continuous function, a neural networks mapping filter is proposed for the protective distance relaying systems to extract the effective components efficiently. A characteristic feature of this mapping filter is composed of the multilayer perceptron neural networks which are trained by using random signals and those are mapped to the DFT filtering computational structure by GDR(Generalized Delta Rule). The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks.

• 대한임베디드공학회논문지
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• 제14권2호
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• pp.71-78
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• 2019

As the capacity of SSDs rapidly increases, the amount of DRAM to keep a mapping table size in SSDs becomes very huge. To address a Demand-based FTL (DFTL) scheme that caches part of mapping entries in DRAM is considered to be a feasible alternative. However, owing to its unpredictable behaviors, DFTL fails to provide consistent I/O response times. In this paper, we a) analyze a root cause that results in fluctuation on read latency and b) propose a new demand-based FTL scheme that ensures guaranteed read response time with low write amplification. By preventing mapping evictions while serving reads, the proposed technique guarantees every host read requests to be done in 2 NAND read operations. Moreover, only with 25% of a cache ratio, the proposed scheme improves random write performance and random mixed performance by 1.65x and 1.15x, respectively, over the traditional DFTL.

• Asian-Australasian Journal of Animal Sciences
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• 제24권4호
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• pp.457-462
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• 2011

The purpose of this study was to detect QTL for carcass quality on bovine chromosome (BTA) 6 using a high density SNP map in a Hanwoo population. The data set comprised 45 sires and their 427 Hanwoo steers that were born between spring of 2005 and fall of 2007. The steers that were used for progeny testing in the Hanwoo Improvement Center in Seosan, Korea, were genotyped with the 2,535SNPs on BTA6 that were embedded in the Illumina bovine SNP 50K chip. Four different linkage disequilibrium (LD) mapping models were applied to detect significant SNPs for carcass quality traits; the fixed model with a single marker, the random model with a single marker, the random model with haplotype effects using two adjacent markers, and the random model at hidden state. A total of twelve QTL were detected, for which four, one, three and four SNPs were detected on BTA6 under the respective models (p<0.001). Among the detected QTL, four, two, five and one QTL were associated with carcass weight, backfat thickness, longissimus dorsi muscle area, and marbling score, respectively (p<0.001). Our results suggest that the use of multiple LD mapping approaches may be beneficial in increasing power to detect QTL given a limited sample size and magnitude of QTL effect.