• 대한원격탐사학회지
• /
• 제34권1호
• /
• pp.45-74
• /
• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• Journal of Power Electronics
• /
• 제16권3호
• /
• pp.946-959
• /
• 2016

A novel Virtual Space Vector (VSV) modulation strategy for complete control of potential neutral point (NP) issues is proposed in this paper. The neutral point potential balancing problems of multi-level converters, which include elimination of low frequency oscillations and self-balancing for NP dc unbalance, are investigated first. Then a set of improved virtual space vectors with dynamic adjustment factors are introduced and a multi-objective optimization algorithm which aims to optimize these adjustment factors is presented in this paper. The improved virtual space vectors and the multi-objective optimization algorithm constitute the novel Virtual Space Vector modulation. The proposed novel Virtual Space Vector modulation can simultaneously recover NP dc unbalance and eliminate low frequency oscillations of the neutral point. Experiment results show that the proposed strategy has excellent performance, and that both of the neutral point potential issues can be solved.

• Korean Chemical Engineering Research
• /
• 제48권2호
• /
• pp.212-217
• /
• 2010

본 연구에서는 유기현탁제로 폴리비닐알콜(PVA: Poly(vinyl alcohol)을 사용하여 현탁중합토너를 제조하였다. 스타이렌과 부틸아크릴레이트 모노머를 동시에 사용하고 카본블랙을 첨가하여, 좁은 입경분포를 갖는 미세 구형 중합토너를 제조하였다. 최적의 현탁중합조건을 설정하기 위하여 카본블랙이 배제된 예비입자 중합실험을 먼저 수행하였다. 예비입자는 다양한 중합조건에서 제조하였으며, 각각의 특징을 비교 분석하여 최적의 중합조건을 결정하였다. 최적화된 중합조건을 선택하여 제조된 흑색중합토너는 입경 및 형상이 우수하였으며 유리전이온도도 $53.6^{\circ}C$인 것으로 나타나 열적 특성 및 인쇄특성도 우수한 것으로 관찰되었다.

• 한국통신학회논문지
• /
• 제35권1C호
• /
• pp.40-44
• /
• 2010

MQASK 디지털 수신기의 타이밍 복원 루프에서는 self-noise의 영향으로 발생하는 타이밍 jitter에 의해 성능이 저하된다. 타이밍 jitter는 타이밍 복원 루프 내에 전치필터를 사용함으로써 해결할 수 있지만, 전치필터에 의해 루프지연이 발생하고, 타이밍 복원 루프의 안정성 및 acquisition 성능이 감소하게 된다. 또한, 전치필터에 의해 타이밍 복원 루프의 복잡도가 증가한다. 본 논문에서는 jitter-free 타이밍 복원 루프에서 전치필터로 인해 발생하는 루프지연을 제거하기 위해 정합필터, resampler, 그리고 전치필터의 기능을 포함한 다상필터 구조의 resampler를 제안하였다. 본 논문에서 제안한 다상필터 구조의 resampler를 사용한 타이밍 복원 루프에서는 타이밍 jitter를 제거하기 위해 사용된 전치필터로 인해 발생하는 루프지연을 해결함으로써 타이밍 복원 루프의 안정성을 향상시키고, 타이밍 jitter를 효과적으로 제거한다. 또한, 타이밍 복원 루프의 구조가 간단해지기 때문에 하드웨어 구현 시에 유리하다.

• 한국지능시스템학회논문지
• /
• 제18권4호
• /
• pp.555-561
• /
• 2008

GA 기반의 4족 보행로봇의 걸음새의 속도와 안정성을 최적화하는 걸음새의 자동 생성 방법을 구현한다. 기존에 사용된 걸음새 파라미터 집합에서 중요 파라미터의 영향을 분석하였고, 이를 통해 효율적인 탐색 방향을 설정하였다. 또한 속도 위주의 기존 연구와는 달리 반 정확도가 수반된 결과를 얻도록 하였다. 제안된 기법의 검증을 위하여 SONY Aibo 4족 보행 로봇에 대해서 ODE 기반의 물리적 특성을 포함한 정교한 시뮬레이션이 가능한 Webots 을 이용하여 실험을 수행하였고, 속도와 안정성 면에서 향상된 결과를 얻었다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2015년도 학술발표회
• /
• pp.218-218
• /
• 2015

Urbanization and waterworks construction in natural watershed have been causing higher flood risks in lowland areas. Detention basins have become one of the most efficient fundamental instruments for storm water and environmental management at watershed scale. Nowadays, there are many studies coupled numerical methods of flood routing with optimization algorithms to investigate factors that impact on the efficiency of detention basins in flood reduction in a watershed, such as detention basin location, size, and cost and watershed characteristics. Although these couplings have been become more widespread but cumbersome computation and hydraulic data requirement still are their limitations. To tackle the procedure efforts due to numerical integration and data collection, simple approach is proposed to primarily estimate effects of detention basins. The approach basis is the linear system theory applied to the solution of hydrologic flood routing. The paper introduces an analytical method for estimating detention effects deriving by recent studies and innovatively analyses this equation on fractal perspective. Then, an optimization technique is performed by applying harmony search algorithms (HSA) to optimize efficiency of detention basins at watershed scale. The location and size of upstream detention basin are simultaneously obtained. Finally, the proposed methodology, practically applied for a real watershed in Kan river, Iran.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권8호
• /
• pp.2749-2763
• /
• 2021

The desirable result of infrared (IR) and visible (VIS) image fusion should have textural details from VIS images and salient targets from IR images. However, detail information in the dark regions of VIS image has low contrast and blurry edges, resulting in performance degradation in image fusion. To resolve the troubles of fuzzy details in dark regions of VIS image fusion, we have proposed a method of reflectance estimation for IR and VIS image fusion. In order to maintain and enhance details in these dark regions, dark region approximation (DRA) is proposed to optimize the Retinex model. With the improved Retinex model based on DRA, quasi-Newton method is adopted to estimate the reflectance of a VIS image. The final fusion outcome is obtained by fusing the DRA-based reflectance of VIS image with IR image. Our method could simultaneously retain the low visibility details in VIS images and the high contrast targets in IR images. Experiment statistic shows that compared to some advanced approaches, the proposed method has superiority on detail preservation and visual quality.

• Journal of Information Processing Systems
• /
• 제15권2호
• /
• pp.359-373
• /
• 2019

For clustering large-scale data, which cannot be loaded into memory entirely, incremental clustering algorithms are very popular. Usually, these algorithms only concern the within-cluster compactness and ignore the between-cluster separation. In this paper, we propose two incremental fuzzy compactness and separation (FCS) clustering algorithms, Single-Pass FCS (SPFCS) and Online FCS (OFCS), based on a fuzzy scatter matrix. Firstly, we introduce two incremental clustering methods called single-pass and online fuzzy C-means algorithms. Then, we combine these two methods separately with the weighted fuzzy C-means algorithm, so that they can be applied to the FCS algorithm. Afterwards, we optimize the within-cluster matrix and betweencluster matrix simultaneously to obtain the minimum within-cluster distance and maximum between-cluster distance. Finally, large-scale datasets can be well clustered within limited memory. We implemented experiments on some artificial datasets and real datasets separately. And experimental results show that, compared with SPFCM and OFCM, our SPFCS and OFCS are more robust to the value of fuzzy index m and noise.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권12호
• /
• pp.5614-5633
• /
• 2018

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

• ETRI Journal
• /
• 제43권5호
• /
• pp.799-811
• /
• 2021

This paper considers a challenging problem: to simultaneously optimize the cost and the quality of service in opaque wavelength division multiplexing (WDM) networks. An optimization problem is proposed that takes the information including network topology, traffic between end nodes, and the target level of congestion at each link/ node in WDM networks. The outputs of this problem include routing, link channel capacities, and the optimum number of switch ports locally added/dropped at all switch nodes. The total network cost is reduced to maintain a minimum congestion level on all links, which provides an efficient trade-off solution for the network design problem. The optimal information is utilized for dynamic traffic in WDM networks, which is shown to achieve the desired performance with the guaranteed quality of service in different networks. It was found that for an average link blocking probability equal to 0.015, the proposed model achieves a net channel gain in terms of wavelength channels (𝛾_w) equal to 35.72 %, 39.09 %, and 36.93 % compared to shortest path first routing and 𝛾_w equal to 29.41 %, 37.35 %, and 27.47 % compared to alternate routing in three different networks.