• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3815-3835
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• 2022

Density-based outlier detection is one of the hot issues in data mining. A point is determined as outlier on basis of the density of points near them. The existing density-based detection algorithms have high time complexity, in order to reduce the time complexity, a new outlier detection algorithm DODMD (Density-based Outlier Detection in Multidimensional Datasets) is proposed. Firstly, on the basis of ZH-tree, the concept of micro-cluster is introduced. Each leaf node is regarded as a micro-cluster, and the micro-cluster is calculated to achieve the purpose of batch filtering. In order to obtain n sets of approximate outliers quickly, a greedy method is used to calculate the boundary of LOF and mark the minimum value as LOF_min. Secondly, the outliers can filtered out by LOF_min, the real outliers are calculated, and then the result set is updated to make the boundary closer. Finally, the accuracy and efficiency of DODMD algorithm are verified on real dataset and synthetic dataset respectively.

• 전기학회논문지
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• 제60권1호
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• pp.205-213
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• 2011

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time-and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.

• 상하수도학회지
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• 제30권2호
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• pp.179-185
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• 2016

In this study, the RDII predictions were compared using two methodologies, i.e., the RTK-based and regression methods. Long-term (1/1/2011~12/31/2011) monitoring data, which consists of 10-min interval streamflow and the amount of precipitation, were collected at the domestic study area (1.36 km2 located in H county), and used for the construction of the RDII prediction models. The RTK method employs super position of tri-triangles, and each triangle (called, unit hydrograph) is defined by three parameters (i.e., R, T and K) determined/optimized using Genetic Algorithm (GA). In regression method, the MovingAverage (MA) filtering was used for data processing. Accuracies of RDII predictions from these two approaches were evaluated by comparing the root mean square error (RMSE) values from each model, in which the values were calculated to 320.613 (RTK method) and 420.653 (regression method), respectively. As a results, the RTK method was found to be more suitable for RDII prediction during extreme rainfall event, than the regression method.

• Smart Structures and Systems
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• 제22권3호
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• pp.291-302
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• 2018

This paper presents a flexibility based method for damage identification from static measurements in beam-type structures. The response of the beam at the Damaged State is decomposed into the response at the Reference State plus the response at an Incremental State, which represents the effect of damage. The damage is localized by detecting slope discontinuities in the deflection of the structure at the Incremental State. A denoising filtering technique is applied to reduce the effect of experimental noise. The extent of the damage is estimated through comparing the experimental flexural stiffness of the damaged cross-sections with the corresponding values provided by analytical models of cracked beams. The paper illustrates the method by showing a numerical example with two cracks and an experimental case study of a simply supported steel beam with one artificially introduced notch type crack at three damage levels. A Digital Image Correlation system was used to accurately measure the deflections of the beam at a dense measurement grid under a set of point loads. The results indicate that the method can successfully detect and quantify a small damage from the experimental data.

• 한국경영과학회지
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• 제39권4호
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• pp.75-84
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• 2014

In this paper, we dealt with feature selection problem of large-scale and high-dimensional biological data such as omics data. For this problem, most of the previous approaches used simple score function to reduce the number of original variables and selected features from the small number of remained variables. In the case of methods that do not rely on filtering techniques, they do not consider the interactions between the variables, or generate approximate solutions to the simplified problem. Unlike them, by combining set covering and clustering techniques, we developed a new method that could deal with total number of variables and consider the combinatorial effects of variables for selecting good features. To demonstrate the efficacy and effectiveness of the method, we downloaded gene expression datasets from TCGA (The Cancer Genome Atlas) and compared our method with other algorithms including WEKA embeded feature selection algorithms. In the experimental results, we showed that our method could select high quality features for constructing more accurate classifiers than other feature selection algorithms.

• Smart Structures and Systems
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• 제14권2호
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• pp.191-207
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• 2014

In this research, an internal model based method is proposed to estimate the structural displacements and velocities under ambient excitation using only acceleration measurements. The structural response is assumed to be within the linear range. The excitation is assumed to be with zero mean and relatively broad bandwidth such that at least one of the fundamental modes of the structure is excited and dominates in the response. Using the structural modal parameters and partial knowledge of the bandwidth of the excitation, the internal models of the structure and the excitation can be respectively established, which can be used to form an autonomous state-space representation of the system. It is shown that structural displacements, velocities, and accelerations are the states of such a system, and it is fully observable when the measured output contains structural accelerations only. Reliable estimates of structural displacements and velocities are obtained using the standard Kalman filtering technique. The effectiveness and robustness of the proposed method has been demonstrated and evaluated via numerical simulations on an eight-story lumped mass model and experimental data of a three-story frame excited by the ground accelerations of actual earthquake records.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제10권4호
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• pp.293-298
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• 2004

콘텐츠 스트림서비스를 이용하는 사용자들의 서비스 수락률 및 서비스 품질의 안정에 대한 요구를 만족시키기 위해 사용자 등급 기반의 자원 배분 및 서비스 수락률 제어 방안이 필요하다. 이를 위해 본 논문에서는 이동에이전트 개념을 적용한 CIMA와 사용자 등급 기반의 서비스 수락 제어 알고리즘을 제안한다. 에이전트 기술을 접목한 알고리즘의 성능 평가를 위해 사용자들의 요금 실적과 서비스 이용 실적 등을 고려하여 사용자 등급(우수등급, 기본등급)을 나누고 등급별 서버의 수락률을 제어하면서 클라이언트/서버 환경과 이동에이전트 환경 하에서의 네트워크 자원 이용률, 수락률 및 수행시간의 비교 평가 실험을 하였다. 실험 결과로부터 에이전트 기술을 적용할 경우 더 높은 네트워크 사용 효율, 우승 등급사용자들의 수락률 상승 및 수행시간 단축의 결과를 얻을 수 있었다.

• 정보처리학회논문지B
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• 제12B권3호
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• pp.223-232
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• 2005

본 논문에서는 블록 기반으로 부호화된 영상에 대하여 블록 경계 영역 특성에 따른 적응적 필터링을 이용한 양자화 잡음 제거 알고리즘을 제안하였다 제안한 방법에서는 블록 경계에 인접한 네 개 화소들의 통계적 특성을 이용하여 각 블록 경계 영역을 평탄 부영역(smooth sub-region)과 복잡 부영역(complex sub-region)으로 분류한 후, 인접 블록간 영역 특성을 이용하여 서로 다른 블록간 필터링을 수행한다. 먼저 인접 블록 모두 평탄 부영역인 경우에는 평탄 블록 경계 영역 중 블록화 현상이 발생하지 않은 영역도 존재하기 때문에 계산량을 줄이기 위하여 평탄 영역 중 블록화 현상이 발생한 영역만을 검출하여 필터링을 수행한다. 그리고, 두 부영역이 서로 다른 부영역인 경우에 대하여서는 기존의 방법들과는 달리 실제 에지 성분을 보존하면서 블록화 현상과 에지 주위에서 발생하는 링잉 현상을 동시에 제거하기 위하여 인접 블록의 영역 특성에 따라 적응적으로 일차원 필터링을 수행한다. 두 부영역이 모두 복잡 부영역일 경우에는 블록화 현상을 제거하면서 실제 에지를 보존하기 위하여 블록화 강도 및 양자화 파라미터에 따라 블록 경계 영역의 두 화소에 대하여 필터링을 수행한다. 모의실험 결과를 통하여 제안한 방법이 객관적 화질 및 주관적 화질 측면에서 기존의 방법보다 그 성능이 우수함을 확인하였다.

• 감성과학
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• 제7권4호
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• pp.57-65
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• 2004

본 논문에서는 color, texture, shape의 정보를 통합 이용하여 내용기반 영상검색 시스템의 성능을 향상시키는 기법을 고찰하였다. 먼저 영상에 내재되어 있는 color를 분석 추출하여 몇 개의 대표색으로 요약 표현한 다음, 이를 활용한 근사치 측정도를 고안하였다. Texture정보 분석에 있어서는 영상의 주축 행렬 데이터를 통계적 접근 방법으로 추출하였다. Edge분석의 방법으로는 Edge 막대그래프에서 색상변환, 양자화, 필터링에 관련된 정보를 선행처리 후 Edge 정보를 추출하였다. 마지막으로, 본 연구의 결과인 내용기반 영상검색 시스템의 효율성을 precision-recall 분석과 실험적 결과를 통하여 입증하였다.

• 한국측량학회지
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• 제35권5호
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• pp.405-414
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• 2017

Spatial data processing often poses challenges due to the unique characteristics of spatial data and this becomes more complex in spatial big data processing. Some tools have been developed and provided to users; however, they are not common for a regular user. This paper presents a benchmark test between two notable tools of spatial big data processing: GIS Tools for Hadoop and SpatialHadoop. At the same time, a MapReduce application is introduced to be used as a baseline to evaluate the effectiveness of two tools and to derive the impact of number of maps/reduces on the performance. By using these tools and New York taxi trajectory data, we perform a spatial data processing related to filtering the drop-off locations within Manhattan area. Thereby, the performance of these tools is observed with respect to increasing of data size and changing number of worker nodes. The results of this study are as follows 1) GIS Tools for Hadoop automatically creates a Quadtree index in each spatial processing. Therefore, the performance is improved significantly. However, users should be familiar with Java to handle this tool conveniently. 2) SpatialHadoop does not automatically create a spatial index for the data. As a result, its performance is much lower than GIS Tool for Hadoop on a same spatial processing. However, SpatialHadoop achieved the best result in terms of performing a range query. 3) The performance of our MapReduce application has increased four times after changing the number of reduces from 1 to 12.