• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.3-5
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• 2007

Many continuous queries are important to be process efficiently in a data stream environment. It is applied a query index technique that takes linear performance irrespective of the number and width of intervals for processing many continuous queries. Previous researches are not able to support the dynamic insertion and deletion to arrange intervals for constructing an index previously. It shows that the insertion and search performance is slowed by the number and width of interval inserted. Many intervals have to be inserted and searched linearly in a data stream environment. Therefore, we propose Hashed Multiple Lists in order to process continuous queries linearly. Proposed technique shows fast linear search performance. It can be utilized the systems applying a sensor network, and preprocessing technique of spatiotemporal data mining.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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• pp.245-253
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• 1998

Recently, the importance of multi-objective optimization techniques and stochastic search methods is increasing. The stochastic search methods have the concepts of the survival of the fittest and natural selection such as genetic algorithms(GA), simulated annealing(SA) and evolution strategies (ES). As many accidents of oil tankers cause marine pollution, oil tankers of double hull or mid deck structure are being built to minimize the marine pollution. For the improvement of oil tanker design technique, an efficient optimization technique is proposed in this study. Multi-objective optimization problem of weight and cost of double hull and mid deck tanker is formulated. Discrete design variables are used considering real manufacturing, and the concept of relative production cost is also introduced. The ES method is used as an optimization technique, and the ES algorithm was developed to generate a more efficient Pareto optimal set.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1994년도 춘계학술대회논문집
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• pp.75-84
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• 1994

A control panel layout method based on the constraint satisfaction problem(CSP) technique was developed to generate an ergonomically sound panel design. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constrains, and generate an optimal or, at least, a "satisfactory" solution through the efficient search algorithm. The problem of seeking an ergonomically sound panel design should be viewed as a multiple criteria problem, and most of the design objectives should be understood as constraints. Hence, a CSP technique was employed in this study for dealing with the multi-constraiants layout problem. The efficient search algorithm using "preprocess" and "look ahead" procedures was developed to handle the vast amount of computational effort. In order to apply the CSP technique to the panel layout procedure, the ergonomic principles such as spatial compatibility, frequency-of- use, importance, functional grouping, and sequence-of-use were formalized as CSP terms. The effectiveness of the developed panel layout method was evaluated by example problems, and the results clearly showed that the generated layouts took various ergonomic design principles into account.esign principles into account.

• 대한안전경영과학회지
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• 제4권3호
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• pp.95-105
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• 2002

This paper considers the sequencing of products in car assembly lines under Just-In-Time systems. Under Just-In-Time systems, the most important goal for the sequencing problem is to keep a constant rate of usage every part used by the systems. In this paper, tabu search technique for this problem is proposed. Tabu search is a heuristic method which can provide a near optimal solution in real time. The performance of proposed technique is compared with existing heuristic methods in terms of solution quality and computation time. Various examples are presented and experimental results are reported to demonstrate the efficiency of the technique.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권9호
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• pp.1142-1149
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• 2004

움직임 추정은 동영상내에 존재하는 중복된 데이타를 제거하기 때문에 비디오 영상 압축에서 중요한 역할을 하지만 높은 계산 복잡도로 인하여 실시간 영상 전송에 많은 어려움을 가지고 있다. 이러한 문제점을 해결하기 위해서는 낮은 계산 복잡도를 지닌 움직임 추정 기법들이 필요한데, 본 논문에서는 현재 블록과 높은 시간적, 공간적 상관성을 가지고 있는 블록들의 움직임 벡터들, 즉 참조 프레임에서 동일한 위치에 있는 블록의 움직임 벡터와 현재 프레임에서 현재 블록의 이웃에 있는 블록들의 움직임 벡터들을 이용하여 현재 블록의 탐색 시작점과 탐색 패턴을 적응적으로 결정하여 움직임 벡터를 추정하는 움직임 추정 기법을 제안한다. 실험을 통하여, 제안된 기법을 낮은 계산 복잡도를 지닌 움직임 벡터 필드 적응적 탐색 기법 (Motion Vector Field Adaptive Search Technique : MVFAST)과 예측된 움직임 벡터필드 적응적 탐색 기법(Predictive Motion Vector Field Adaptive Search Technique : PMVFAST)과 비교하였을 경우, 제안된 기법은 약 0.01～0.3 (dB) 정도의 화질 향상과 낮은 계산 복잡도로 인하여 약 1.12～l.33 배의 속도 향상을 보였다.

• 정보과학회 논문지
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• 제42권10호
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• pp.1247-1253
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• 2015

유사도 검색에서는 효율적으로 유사성을 만족하는 문자열을 찾기 위해서 데이터에 대한 역 색인을 구축하여 이용한다. 일반적으로 기존의 기법들은 빠른 응답속도의 질의처리를 위해서 역 색인을 메모리에 상주시킨다. 하지만 구축된 역 색인은 그 크기가 매우 크다는 문제점을 가지고 있다. 따라서 데이터의 크기가 매우 큰 경우나 자원이 제약적인 환경에서는 역 색인을 이용한 질의처리가 불가능할 수 있다. 본 논문에서는 동일한 q-그램을 포함하는 문자열들이 서로 인접한 위치가 되도록 재배치시킨 후 해당 문자열들을 범위로 표현한다. 실험을 통하여 질의처리의 성능을 희생하지 않으면서도 색인의 크기가 줄어드는 것을 보인다.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1899-1909
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• 2015

Glaucoma is one of the most common causes of blindness which is caused by increase of fluid pressure in the eye which damages the optic nerve and eventually causing vision loss. An automated technique to diagnose glaucoma disease can reduce the physicians’ effort in screening of Glaucoma in a person through the fundal retinal images. In this paper, optimal hyper analytic wavelet transform for Glaucoma detection technique from fundal retinal images is proposed. The optimal coefficients for transformation process are found out using the hybrid GSO-Cuckoo search algorithm. This technique consists of pre-processing module, optimal transformation module, feature extraction module and classification module. The implementation is carried out with MATLAB and the evaluation metrics employed are accuracy, sensitivity and specificity. Comparative analysis is carried out by comparing the hybrid GSO with the conventional GSO. The results reported in our paper show that the proposed technique has performed well and has achieved good evaluation metric values. Two 10- fold cross validated test runs are performed, yielding an average fitness of 91.13% and 96.2% accuracy with CGD-BPN (Conjugate Gradient Descent- Back Propagation Network) and Support Vector Machines (SVM) respectively. The techniques also gives high sensitivity and specificity values. The attained high evaluation metric values show the efficiency of detecting Glaucoma by the proposed technique.

• 지구물리와물리탐사
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• 제23권3호
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• pp.157-167
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• 2020

최근 인공지능 기술의 발전과 함께 물리탐사의 다양한 분야에서도 인공지능의 핵심 기술인 머신러닝의 활용도가 증가하고 있다. 또한 머신러닝 및 딥러닝을 활용한 연구는 이미지, 비디오, 음성, 자연어 등 다양한 태스크의 추론 정확도를 높이기 위해 복잡한 알고리즘들이 개발되고 있고, 더 나아가 자료의 특성, 알고리즘 구조 및 하이퍼 파라미터의 최적화를 위한 자동 머신러닝(AutoML) 분야로 그 폭을 넓혀가고 있다. 본 연구에서는 AutoML 분야 중에서도 하이퍼 파라미터(hyperparameter) 자동 탐색을 위한 베이지안 최적화 기술에 중점을 두었으며, 본 기술을 물리탐사 분야에서도 암상 분류(facies classification) 문제에 적용했다. Vincent field의 현장 물리검층 및 탄성파 자료를 이용하여 암상 및 공극유체를 분류하는 지도학습 기반 모델에 적용하였고, 랜덤 탐색 기법의 결과와 비교하여 베이지안 최적화 기반 예측 프레임워크의 효율성을 검증하였다.

• 대한건축학회논문집:구조계
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• 제33권12호
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• pp.53-62
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• 2017

Many gradient-based mathematical methods have been developed and are in use for structural size optimization problems, in which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. The main objective of this paper is to propose an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm that is derived using penalty function. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. In this paper, a discrete search strategy using the HS algorithm with a static penalty function is presented in detail and its applicability using several standard truss examples is discussed. The numerical results reveal that the HS algorithm with the static penalty function proposed in this study is a powerful search and design optimization technique for structures with discrete-sized members.

• ETRI Journal
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• 제45권3호
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• pp.418-432
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• 2023

In this work, we proposed a low-complexity hybrid layered tabu-likelihood ascent search (LTLAS) algorithm for large multiple-input multiple-output (MIMO) system. The conventional layered tabu search (LTS) approach involves many partial reactive tabu searches (RTSs), and each RTS requires an initialization and searching phase. In the proposed algorithm, we restricted the upper limit of the number of RTS operations. Once RTS operations exceed the limit, RTS will be replaced by low-complexity likelihood ascent search (LAS) operations. The block-based detection approach is considered to maintain a higher signal-to-noise ratio (SNR) detection performance. An efficient precomputation technique is derived, which can suppress redundant computations. The simulation results show that the bit error rate (BER) performance of the proposed detection method is close to the conventional LTS method. The complexity analysis shows that the proposed method has significantly lower computational complexity than conventional methods. Also, the proposed method can reduce almost 50% of real operations to achieve a BER of 10^-3.