• 터널과지하공간
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• 제7권1호
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• pp.1-12
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• 1997

Engineering rock mass classification is extensively used to determine the reasonable support system throughout the tunneling process in the field. Selection of support system based on the results of engineering rock mass classification is simple and straight-forward. However, this method cannot consider the effect of in-situ stresses, mechanical properties of support material, and support installation time on the behavior or rock-support system To handle the various conditions encountered in the underground excavation sites rock-support system. To handle the various conditions encountered in th eunderground excavation sites rock-support interaction program has been developed. This program can analyze the interaction between rock mass and support materials and also can simulate the tunnel excavation-support insstallation process by controlling the support installation time and the stiffness of support system. Practical applicability of this program was verfied by comparing the results of support design to those from rock mass classification for virtual underground excavation at the drilling site KD-06 in Geoje island.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2010년도 하계학술대회
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• pp.9-11
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• 2010

Multiple-input multiple-output (MIMO) systems assisted by multi-relays with single antenna are considered. Signal transmission consists of two hops. In the first hop, the source node broadcasts the vector symbols to all relays, then all relays forward the received signals multiplied by each power gain to the destination simultaneously. Unlike the case of full cooperation between relays such as single relay with multiple antennas, in our case there is no closed form solution for optimal relay power gain with respect to minimum mean square error (MMSE). Thus we propose an alternative approach in which we use an approximation of the cost function based on rank-one matrix decomposition. As a cost function, we choose the trace of MSE matrix. We give several simulation results to validate that our proposed method obtains a negligible performance loss compared to optimal solution obtained by exhaustive search.

• The Journal of the Acoustical Society of Korea
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• 제23권3E호
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• pp.91-97
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• 2004

In this paper, we propose a classification system of TV program scenes based on audio information. The system classifies the video scene into six categories of commercials, basketball games, football games, news reports, weather forecasts and music videos. Two type of audio feature set are extracted from each audio frame-timbral features and coefficient domain features which result in 58-dimensional feature vector. In order to reduce the computational complexity of the system, 58-dimensional feature set is further optimized to yield l0-dimensional features through Sequential Forward Selection (SFS) method. This down-sized feature set is finally used to train and classify the given TV program scenes using κ -NN, Gaussian pattern matching algorithm. The classification result of 91.6% reported here shows the promising performance of the video scene classification based on the audio information. Finally, the system stability problem corresponding to different query length is investigated.

• Journal of Communications and Networks
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• 제13권6호
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• pp.633-638
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• 2011

In this paper, we consider resource allocation with proportional fairness in the downlink orthogonal frequency division multiple access relay networks, in which relay nodes operate in decode-and-forward mode. A joint optimization problem is formulated for relay selection, subcarrier assignment and power allocation. Since the formulated primal problem is nondeterministic polynomial time-complete, we make continuous relaxation and solve the dual problem by Lagrangian dual decomposition method. A near-optimal solution is obtained using Karush-Kuhn-Tucker conditions. Simulation results show that the proposed algorithm provides superior system throughput and much better fairness among users comparing with a heuristic algorithm.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.157-157
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• 2018

A reliable and accurate downscaling model which can provide climate change information, obtained from global climate models (GCMs), at finer resolution has been always of great interest to researchers. In order to achieve this model, linear methods widely have been studied in the past decades. However, nonlinear methods also can be potentially beneficial to solve downscaling problem. Therefore, this study explored the applicability of some nonlinear machine learning techniques such as neural network (NN), extreme learning machine (ELM), and ELM autoencoder (ELM-AE) as well as a linear method, least absolute shrinkage and selection operator (LASSO), to build a reliable temperature downscaling model. ELM is an efficient learning algorithm for generalized single layer feed-forward neural networks (SLFNs). Its excellent training speed and good generalization capability make ELM an efficient solution for SLFNs compared to traditional time-consuming learning methods like back propagation (BP). However, due to its shallow architecture, ELM may not capture all of nonlinear relationships between input features. To address this issue, ELM-AE was tested in the current study for temperature downscaling.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.367-370
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• 2017

본 논문은 확률적 DTN 모델 내에서 효율적인 중계 노드를 선택하기 위한 방법을 제안한다. Delay Tolerant Network(DTN)은 효율적인 통신을 위해 묶음 계층(bundle layer)를 생성해 서로 다른 네트워크 및 이기종간의 네트워크 간 중계 노드를 선택하고 메시지를 전달하는 Carry and forward 방식을 사용한다. DTN은 기본적으로 유동적인 노드로 구성되어 고정된 라우팅 루트가 없으며 간헐적인 연결로 인해 긴 지연시간을 가진다. 따라서 DTN을 구성하는 노드들은 필수적으로 메시지를 저장하기 위한 특성을 가지며 저장된 메시지와 노드의 용량은 네트워크의 성능에 영향을 주게 된다. 확률적 DTN 모델은 이러한 DTN의 성능을 분석하기 위해 시간에 따라 무작위적으로 변화하는 Markov 모델을 제안하였다. 하지만 제안된 확률적 DTN 모델에서는 네트워크의 성능을 향상시키기 위한 방법에 대한 연구가 미비하였다. 본 논문은 네트워크의 성능을 향상시키기 위해 확률적 DTN 모델에서 메시지의 생성과 소멸을 통해 분석된 확률적 메시지 분포와 상호 접촉 시간을 이용해 효율적인 중계 노드를 선택하는 알고리즘을 제안한다.

• 한국통신학회논문지
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• 제28권3A호
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• pp.111-118
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• 2003

적응형 송신 빔 성형 시스템에서 순방향 링크의 채널 특성을 기지국에 정확히 전달하는 것은 시스템 성능을 결정하는 중요한 요소이다. FDD 방식 시스템의 경우 순방향 채널의 정보는 일반적으로 귀환 채널을 통해 전달되며 송신 안테나 수에 비례하여 증가하게 된다. 이 논문에서는 N개의 송신안테나를 갖는 빔 성형 시스템이 2N개의 송신 안테나 시스템으로 확장되는 반면, 귀환 채널은 귀환 전송 비트율의 제한으로 인해 기존의 N-안테나 시스템의 귀환 채널이 그대로 유지된다. 제한된 귀환 채널 정보의 사용 효율을 높여 시스템의 성능을 향상시키기 위해 적응형 송신 빔 성형 방식과 안테나 선택 다이버시티 방식을 결합한 순방향 링크 CDMA 시스템을 제안하고 모의 실험을 통해 성능을 연구한다. 제한된 귀환 채널 비트를 갖는 시스템에서, 송신 안테나 수와 안테나 선택 방식에 따른 시스템 성능을 주파수 비선택적 페이딩 채널 및 다중 경로 페이딩 채널에서 모의 실험을 통해 정량화 한다. 모의 실험 결과는 송신 안테나 선택 방식을 적용함으로써 각 안테나당 할당되는 정보 비트 수를 증가시켜 양자화로 인한 오류를 줄이고, 선택 다이버시티 이득을 얻음으로써 전체 시스템 성능이 개선됨을 보인다.

• 대한자원환경지질학회:학술대회논문집
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• 대한자원환경지질학회 2002년도 춘계 공동학술발표회
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• pp.167-169
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• 2002

The extended Born, or localized nonlinear approximation of integral equation (IE) solution has been applied to inverting single-hole electromagnetic (EM) data using a cylindrically symmetric model. The extended Born approximation is less accurate than a full solution but much superior to the simple Born approximation. When applied to the cylindrically symmetric model with a vertical magnetic dipole source, however, the accuracy of the extended Born approximation is greatly improved because the electric field is scalar and continuous everywhere. One of the most important steps in the inversion is the selection of a proper regularization parameter for stability. Occam's inversion (Constable et al., 1987) is an excellent method for obtaining a stable inverse solution. It is extremely slow when combined with a differential equation method because many forward simulations are needed but suitable for the extended Born solution because the Green's functions, the most time consuming part in IE methods, are repeatedly re-usable throughout the inversion. In addition, the If formulation also readily contains a sensitivity matrix, which can be revised at each iteration at little expense. The inversion algorithm developed in this study is quite stable and fast even if the optimum regularization parameter Is sought at each iteration step. Tn this paper we show inversion results using synthetic data obtained from a finite-element method and field data as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4738-4753
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• 2018

Efficient rendezvous node selection and routing algorithm (RNSRA) for wireless sensor networks with mobile sink that visits rendezvous node to gather data from sensor nodes is proposed. In order to plan an optimal moving tour for mobile sink and avoid energy hole problem, we develop the RNSRA to find optimal rendezvous nodes (RN) for the mobile sink to visit. The RNSRA can select the set of RNs to act as store points for the mobile sink, and search for the optimal multi-hop path between source nodes and rendezvous node, so that the rendezvous node could gather information from sensor nodes periodically. Fitness function with several factors is calculated to find suitable RNs from sensor nodes, and the artificial bee colony optimization algorithm (ABC) is used to optimize the selection of optimal multi-hop path, in order to forward data to the nearest RN. Therefore the energy consumption of sensor nodes is minimized and balanced. Our method is validated by extensive simulations and illustrates the novel capability for maintaining the network robustness against sink moving problem, the results show that the RNSRA could reduce energy consumption by 6% and increase network lifetime by 5% as comparing with several existing algorithms.

• 응용통계연구
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• 제23권5호
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• pp.967-975
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• 2010

데이터마이닝 분야에서의 회귀모형에는 연관성이 높은 설명변수들이 포함되어 다중공선성을 유발하는 경우가 많은데, 다중공선성이 야기하는 문제를 해결하기 위하여 주성분회귀분석을 적용할 수 있다. 이 분석에서는 적절한 주성분을 선정하는 과정이 핵심인데, 기존의 선정방법들은 다중공선성을 잘 해결하지 못하거나 모형의 적합성을 저하시킨다는 지적을 받고 있다. 따라서 본 논문에서는 다중공선성 문제와 적합성 저하 현상을 동시에 해결할 수 있는 새로운 선정방법을 제안하였다. 다중공선성에 의해 최소제곱추정량의 분산이 팽창되는 문제를 주성분회귀에 의해 해결할 수 있지만, 주성분의 일부를 선정함에 따라 발생하는 편의도 동시에 통제해야 한다. 따라서 주성분회귀추정량의 평균제곱오차를 최소가 되게 하는 상태지수를 측정하고, 이 값에 영향을 미치는 주요 요인들을 컨조인트분석에 의해 파악하여 주성분 선정기준 모형을 구축하였다. 선정기준의 상한과 하한을 설정하고, 상태지수가 상한을 초과하면 해당 주성분을 제외시키고, 하한에 미달하면 해당 주성분을 포함시킨다. 그리고 상한과 하한 사이의 상태지수에 대응하는 주성분들에 대해서는 일반화선형검정을 순차적으로 적용하여 주성분을 선정하는 방법이다.