• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.483-483
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• 2022

댐과 저수지의 운영 최적화를 위한 수문학적 예보는 현재 수동적인 댐 운영이 주를 이루면서 활용도가 높지 않다. 불확실한 기후변화나 기후재난 상황에서 우리 사회에 악영향을 최소화하기 위해 선제적으로 대응/대비할 수 있는 댐 운영 방안이 불가피하다. 강우량 예측 기술은 기후변화로 인해 제한적인 상황이다. 실례로, 2020년 8월에 섬진강의 댐이 극심한 집중 강우로 인해 무너지는 사태가 발생하였고 이로 인해 지역사회에 막대한 경제적 피해가 발생하였다. 선제적 댐 방류량 운영 기술은 또한 환경적인 변화로 인한 영향을 완화하기 위해 필요한 것이다. 제한적인 기상 예보 기술을 극복하고자 심화학습이나 강화학습 같은 인공지능 모델들의 활용성에 대한 연구가 시도되고 있다. 따라서 본 연구는 섬진강 댐의 시간당 수문 데이터를 이용하여 댐 운영을 위한 심화학습 모델을 개발하고 그 활용도를 평가하였다. 댐 운영을 위한 심화학습 모델로서 시계열 데이터 예측에 적합한 Long Sort Term Memory(LSTM)과 Gated Recurrent Unit(GRU) 알고리즘을 구축하고 댐 수위를 예측하였다. 분석 자료는 WAMIS에서 제공하는 2000년부터 2021년까지의 시간당 데이터를 사용하였다. 입력 데이터로서 시간당 유입량, 강우량과 방류량을, 출력 데이터로서 시간당 수위 자료를 각각 사용하였으며. 결정계수(R2 Score)를 통해 모델의 예측 성능을 평가하였다. 댐 수위 예측값 개선을 위해 하이퍼파라미터의 '최적값'이 존재하는 범위를 줄여나가는 하이퍼파라미터 최적화를 두 가지 방법으로 진행하였다. 첫 번째 방법은 수동적 탐색(Manual Search) 방법으로 Sequence Length를 24, 48, 72시간, Hidden Layer를 1, 3, 5개로 설정하여 하이퍼파라미터의 조합에 따른 LSTM와 GRU의 민감도를 평가하였다. 두 번째 방법은 Grid Search로 최적의 하이퍼파라미터를 찾았다. 이 두가지 방법에서는 같은 하이퍼파라미터 안에서 GRU가 LSTM에 비해 더 높은 예측 정확도를 보였고 Sequence Length가 높을수록 정확도가 높아지는 경향을 보였다. Manual Search 방법의 경우 R2가 최대 0.72의 정확도를 보였고 Grid Search 방법의 경우 R2가 0.79의 정확도를 보였다. 본 연구 결과는 가뭄과 홍수와 같은 물 재해에 사전 대응하고 기후변화에 적응할 수 있는 댐 운영 개선에 도움을 줄 수 있을 것으로 판단된다.

• 전기전자학회논문지
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• 제22권3호
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• pp.658-663
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• 2018

본 논문에서는 실내 위치 추정시스템에 주로 사용되는 시퀀스 기반 위치추정(Sequence-Based Localization, SBL) 알고리즘의 성능향상을 위한 노드배치 알고리즘에 대해 연구한다. 기존의 노드선택 또는 배치알고리즘은 다수의 타겟이 위치하는 공간의 중심값에 노드들을 위치시켜 성능향상을 이루는 반면, SBL에서는 위치추적 알고리즘 특성상 타겟을 에워싸는 공간에서의 노드배치가 효율적일 수 있음에 주목한다. 이를 실현하기 위해 K-means clustering 알고리즘을 통한 노드배치 가능 공간을 선정하고, 그 선정된 공간상의 효율적 노드위치를 찾기 위해 2분법을 활용하여, 설계 복잡도가 낮은 노드배치 알고리즘을 제시한다. 제안된 노드배치알고리즘은 다양한 모의실험을 통해 무작위 노드배치 알고리즘 대비 뛰어난 위치추정성능을 보여주며, 노드위치를 위한 전역탐색 (full search)과 비교하여, 상당히 낮은 설계복잡도를 유지하면서도 만족할 만한 성능을 보인다.

• 한국컴퓨터산업학회논문지
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• 제4권10호
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• pp.731-740
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• 2003

움직임 추정은 연속한 비디오 프레임간의 시간적 상관성을 이용하여 동영상 내에 존재하는 중복된 데이터를 제거하기 때문에 동영상 부호화에 있어서 중요한 역할을 한다. 그리고 서로 다른 형태와 크기를 가지는 탐색 패턴과 움직임 벡터의 분포는 블록 정합 기법에서 탐색 속도와 화질을 좌우하는 중요한 요소이다. 본 논문에서는 작은 크로스 탐색 패턴과 블록 기반 경사 하강 탐색 패턴을 이용한 새로운 고속 블록 정합 알고리즘을 제안한다 이 방법은 작은 크로스 탐색 패턴을 이용하여 적은 탐색점으로 움직임이 적은 벡터를 우선 찾은 다음에 움직임이 큰 벡터에 대해서는 블록 기반 경사 하강 탐색 패턴을 이용하여 고속으로 움직임 벡터를 찾게 하였다. 실험결과, 제안된 알고리즘은 블록 기반 경사 하강 탐색 기법에 비하여 움직임 벡터 예측의 속도에 있어서 약 26-40% 이상의 높은 성능 향상을 보였다.

• 한국정밀공학회지
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• 제11권4호
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• pp.77-87
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• 1994

This paper deals with an automated forming sequence design system by which designers can determine desirable operation sequences even if they have little experience in the design of cold forging process. The forming sequence design in the cold forging is very important and requires many kinds of technical and empirical knowledge. They system isproposed, which generates forming sequence plans for the multistage cold forging of axisymmtrical solid products. Since the process of metal forming can be considered as a transformation of geometry, treatment of the geometry of the product is a key in planning process. To recognize the geometry of the product section, section entity representation and primitive geometries were used. Section entity representation can be used for the calculation of maximum diameter, maximum height, and volume. Forming sequence for the part can be determined by means of primitive geometries such as cylinder, cone, convex, and concave. By utilizing this geometrical characteristics (diameter, height, and radius), the product geometry is expressed by a list of the priitive geometries. Accordingly the forming sequence design is formulated as the search problem which starts with a billet geometry and finishes with a given product one. Using the developed system, the sequence drawing with all dimensions, which includes the proper sequence of operations for the part, is generated under the environment of AutoCAD. Based on the results of forming sequence, process variables(strain, punch pressure, die inner pressure, and forming load) are determined.

• 대한가정학회지
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• 제30권1호
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• pp.149-161
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• 1992

The purpose of this study is to analyze information search activity in purchasing behavior of household electric goods. Qusetionare survey method was used in this research. The sample was taken from 302 housewives living in Seoul, from 9th of Nov. to 20th of Nov, in 1991. Used statical methods were Frequency, Percentage, Crosstab, Anova, and Regression Analysis. The major findings are summarized as follows : 1) Component elements of information search : The means of acquiring information is that friends, neighbors, sales are most. A cause of choosing information is the sequence of satisfaction after using, easiness of interaction. The time in choosing goods is more month. 2) Component element of information search as social economic status housewife : children numbers and means of acquiring information(P<.01), education and a cause of choosing information(P<.05), life cost per month and a cause of choosing information(P<.05), social economic status and a time information search are significant. 3) A perception of risk as searching information : Among searching content of information a price influence a perception of risk. 4) Content of searching information and satisfaction of purchasing experience : Best choice is significant as quality of goods, difference of quality is significant as safety and degree of offering information is significant as a brand. 5) Satisfaction of purchasing experience following practical use of information : Best choice is significant as viewing of an exhibit and opinion of user. Difference of quality is not significant as any vairable. Degree of offer information influence searching pamphlet, searching an advertisement and opinion of user. 6) A perception of risk following source of an information : A perception of risk is most influenced by pamphlet.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권5호
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• pp.492-506
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• 2009

Index structures that are based on sequence matching for XPath processing such as ViST, PRIX and LCS-TRIM have recently been proposed to reduce the search time of XML documents. However, ViST can cause a lot of unnecessary computation and I/O when processing structural joint queries because its numbering scheme is not optimized. PRIX and LCS-TRIM require much processing time for matching XML data trees and queries. In this paper, we propose a novel index structure that solves the problems of ViST and improves the performance of PRIX and LCS-TRIM. Our index structure provides the minimum sequence matching scheme to efficiently process structural queries. Finally, to verify the superiority of the proposed index structure with the minimum sequence matching scheme, we compare our index structure with ViST, PRIX and LCS-TRIM in terms of query processing of a single path or of a branching path including wild-cards ('*' and '//' ).

• Interdisciplinary Bio Central
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• 제4권4호
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• pp.14.1-14.6
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• 2012

Splice site prediction in DNA sequence is a basic search problem for finding exon/intron and intron/exon boundaries. Removing introns and then joining the exons together forms the mRNA sequence. These sequences are the input of the translation process. It is a necessary step in the central dogma of molecular biology. The main task of splice site prediction is to find out the exact GT and AG ended sequences. Then it identifies the true and false GT and AG ended sequences among those candidate sequences. In this paper, we survey research works on splice site prediction based on support vector machine (SVM). The basic difference between these research works is nucleotide encoding technique and SVM kernel selection. Some methods encode the DNA sequence in a sparse way whereas others encode in a probabilistic manner. The encoded sequences serve as input of SVM. The task of SVM is to classify them using its learning model. The accuracy of classification largely depends on the proper kernel selection for sequence data as well as a selection of kernel parameter. We observe each encoding technique and classify them according to their similarity. Then we discuss about kernel and their parameter selection. Our survey paper provides a basic understanding of encoding approaches and proper kernel selection of SVM for splice site prediction.

• Journal of Plant Biotechnology
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• 제5권4호
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• pp.193-195
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• 2003

A major goal of agricultural biotechnology is the discovery of genes or genetic loci which are associated with characteristics beneficial to crop production. This knowledge of genetic loci may then be applied to improve crop breeding. Agriculturally important genes may also benefit crop production through transgenic technologies. Recent years have seen an application of high throughput technologies to agricultural biotechnology leading to the production of large amounts of genomic data. The challenge today is the effective structuring of this data to permit researchers to search, filter and importantly, make robust associations within a wide variety of datasets. At the Plant Biotechnology Centre, Primary Industries Research Victoria in Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data to aid its application to agricultural biotechnology resear-ch. These tools include a sequence database, ASTRA, for the processing and annotation of expressed sequence tag data. Tools have also been developed for the discovery of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) molecular markers from large sequence datasets. Application of these tools to Brassica research has assisted in the production of genetic and comparative physical maps as well as candidate gene discovery for a range of agronomically important traits.

• Genomics & Informatics
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• 제16권4호
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• pp.23.1-23.5
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• 2018

Virus taxonomy was initially determined by clinical experiments based on phenotype. However, with the development of sequence analysis methods, genotype-based classification was also applied. With the development of genome sequence analysis technology, there is an increasing demand for virus taxonomy to be extended from in vivo and in vitro to in silico. In this study, we verified the consistency of the current International Committee on Taxonomy of Viruses taxonomy using an in silico approach, aiming to identify the specific sequence for each virus. We applied this approach to norovirus in Caliciviridae, which causes 90% of gastroenteritis cases worldwide. First, based on the dogma "protein structure determines its function," we hypothesized that the specific sequence can be identified by the specific structure. Firstly, we extracted the coding region (CDS). Secondly, the CDS protein sequences of each genus were annotated by the conserved domain database (CDD) search. Finally, the conserved domains of each genus in Caliciviridae are classified by RPS-BLAST with CDD. The analysis result is that Caliciviridae has sequences including RNA helicase in common. In case of Norovirus, Calicivirus coat protein C terminal and viral polyprotein N-terminal appears as a specific domain in Caliciviridae. It does not include in the other genera in Caliciviridae. If this method is utilized to detect specific conserved domains, it can be used as classification keywords based on protein functional structure. After determining the specific protein domains, the specific protein domain sequences would be converted to gene sequences. This sequences would be re-used one of viral bio-marks.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 학술대회
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• pp.109-114
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• 1999

Due to the temporal correlation of the image sequence, the motion vector of a block is highly related to the motion vector of the same coordinate block in the previous image frame. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous image frames, the total number of search points used to find the motion vector of the current block may be reduced significantly. Using that idea, an efficient new predicted direction search algorithm (PDSA) for block matching motion estimation is proposed in this paper.