• 천문학회보
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• 제41권2호
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• pp.66.2-66.2
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• 2016

KASI and NAOJ are making collaborating efforts to implement faster mapping capability into the new 275-500 GHz Atacama Submillimeter Telescope Experiment focal plane array (FPA). Feed horn antenna is one of critical parts of the FPA. Required fractional bandwidth is almost 60 % while that of traditional conical horn is less than 50 %. Therefore, to achieve this wideband performance, we adopted a horn of which the corrugation depths have a longitudinal profile. A profiled horn has features not only of wide bandwidth but also of shorter length compared to a linear-tapered corrugated horn, and lower cost fabrication with less error can be feasible. In our design process the flare region is represented by a cubic splined curve with several parameters. Parameters of the flare region and each dimension of the throat region are optimized by a differential evolution algorithm to keep >20 dB return loss and >30 dB maximum cross-polarization level over the operation bandwidth. To evaluate RF performance of the horn generated by the optimizer, we used a commercial mode matching software, WASP-NET. Also, Gaussian beam (GB) masks to far fields were applied to give better GB behavior over frequencies. The optimized design shows >23 dB return loss and >33 dB maximum cross-polarization level over the whole band. Gaussicity of the horn is over 96.6 %. The length of the horn is 12.5 mm which is just 57 % of the ALMA band 8 feed horn (21.96 mm).

• Journal of Power Electronics
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• 제17권5호
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• pp.1308-1316
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• 2017

The distributed maximum power point tracking (DMPPT) concept is widely adopted in photovoltaic systems to avoid mismatch loss. However, the high cost and complexity of DMPPT hinder its further promotion in practice. Based on the concept of DMPPT, this paper presents an integrated submodule level half-bridge stack structure along with an optimal current point tracking (OCPT) control algorithm. In this full power processing integrated solution, the number of power switches and passive components is greatly reduced. On the other hand, only one current sensor and its related AD unit are needed to perform the ideal maximum power generation for all of the PV submodules in any irradiance case. The proposal can totally eliminate different small-scaled mismatch effects in real-word condition and the true maximum power point of each PV submodule can be achieved. As a result, the ideal maximum power output of the whole PV system can be achieved. Compared with current solutions, the proposal further develops the integration level of submodule DMPPT solutions with a lower cost and a smaller size. Moreover, the individual MPPT tracking for all of the submodules are guaranteed.

• 대한원격탐사학회지
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• 제34권1호
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• pp.45-74
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• 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.

• 한국추진공학회지
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• 제6권2호
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• pp.65-74
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• 2002

전압력 회복율을 최대로 하기 위한 IRR형 램젯 공기 흡입구 초음속 확산부의 최적형상 설계를 수행하였다. 질량유량을 제약조건으로 고려하고 외부램프에서의 두 번째 경사충격파와 카울립 형상, 그리고 흡입구 목의 단면적을 설계변수로 선택하였다. 효율적인 최적화를 위해 설계변수 변환을 통한 개선된 반응면 기법을 사용하였으며 설계반복을 통해 높은 신뢰도의 반응면을 구성할 수 있었다. 최적화 기법으로 유전자 알고리즘을 사용하였으며, 이차원 Euler Code를 사용하여 공력해석을 수행하였다. 배압조건의 적용을 위해 흡입구 목 뒤로 가상의 노즐을 장착하였고 총 20회의 계산으로 종말충격파 이후의 전압력 회복율이 기준형상에 비하여 14% 향상된 초음속 확산부 최적형상을 설계할 수 있었다.

• Nuclear Engineering and Technology
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• 제49권6호
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• pp.1358-1367
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• 2017

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector responses (using the adjoint transport solution) with measured responses. DIMP performs well with forward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search volume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

• Smart Structures and Systems
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• 제29권4호
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• pp.523-533
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• 2022

A novel metaheuristic search method, namely black widow optimization (BWO) is employed to increase the accuracy of slope stability analysis. The BWO is a recently-developed optimizer that supervises the training of an artificial neural network (ANN) for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The designed slope bears a loaded foundation in different distances from the crest. A sensitivity analysis is conducted based on the number of active individuals in the BWO algorithm, and it was shown that the best performance is acquired for the population size of 40. Evaluation of the results revealed that the capability of the ANN was significantly enhanced by applying the BWO. In this sense, the learning root mean square error fell down by 23.34%. Also, the correlation between the testing data rose from 0.9573 to 0.9737. Therefore, the postposed BWO-ANN can be promisingly used for the early prediction of FOS in real-world projects.

• Smart Structures and Systems
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• 제30권2호
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• pp.195-207
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• 2022

Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.

• Steel and Composite Structures
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• 제44권6호
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• pp.867-882
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• 2022

Predicting the compressive strength of concrete (CSoC) is of high significance in civil engineering. The CSoC is a highly dependent and non-linear parameter that requires powerful models for its simulation. In this work, two novel optimization techniques, namely evaporation rate-based water cycle algorithm (ER-WCA) and equilibrium optimizer (EO) are employed for optimally finding the parameters of a multi-layer perceptron (MLP) neural processor. The efficiency of these techniques is examined by comparing the results of the ensembles to a conventionally trained MLP. It was observed that the ER-WCA and EO optimizers can enhance the training accuracy of the MLP by 11.18 and 3.12% (in terms of reducing the root mean square error), respectively. Also, the correlation of the testing results climbed from 78.80% to 82.59 and 80.71%. From there, it can be deduced that both ER-WCA-MLP and EO-MLP can be promising alternatives to the traditional approaches. Moreover, although the ER-WCA enjoys a larger accuracy, the EO was more efficient in terms of complexity, and consequently, time-effectiveness.

• 소성∙가공
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• 제33권2호
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• pp.96-102
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• 2024

This study addresses evaluation of performance of hardening model for a titanium alloy (Ti6Al4V) based on the artificial neural network (ANN) regarding the strain rate and the temperature. Uniaxial compression tests were carried out at different strain rates from 0.001 /s to 10 /s and temperatures from 575 ℃ To 975 ℃. Using the experimental data, ANN models were trained and tested with different hyperparameters, such as size of hidden layer and optimizer. The input features were determined with the equivalent plastic strain, strain rate, and temperature while the output value was set to the equivalent stress. When the number of data is sufficient with a smooth tendency, both the Bayesian regulation (BR) and the Levenberg-Marquardt (LM) show good performance to predict the flow behavior. However, only BR algorithm shows a predictability when the number of data is insufficient. Furthermore, a proper size of the hidden layer must be confirmed to describe the behavior with the limited number of the data.

• 대한방사선치료학회지
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• 제26권1호
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• pp.11-19
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• 2014

목 적 : 최적화 알고리즘에 적용되는 최적화 인자들의 영향을 고려하여, 가장 적합한 인자 값을 도출함으로써 이상적인 치료계획을 쉽게 설계할 수 있도록 하고자 한다. 대상 및 방법 : 본 연구의 세기조절방사선치료에서 선량계산 알고리즘은 PBC(Pencil Beam Convolution)이고, 최적화 알고리즘은 DVO(Dose Volume Optimizer 10.0.28)이다. 두경부 환자의 세기조절방사선치료에서 치료계획용적의 처방선량은 동시에 2.2 Gy와 2.0 Gy가 될 수 있도록 하였다. 치료계획은 6 MV, 7개의 조사야로 역선량계산방법으로 수립하였다. 최적화 알고리즘 인자는 용적선량-조건강도(Priority, Constrain), 선량부 드럼강도(Smooth)로 선정하고, 각 인자들의 변화량에 따른 치료계획의 영향을 분석하였다. 용적선량-조건강도는 기준 조건강도를 정하고, 비율은 같지만 절대 값은 다른 최적화 과정을 실시하였다. 또한 조건강도의 절대 값에 변화에 따른 치료용적과 주변 정상장기들을 평가하였다. 선량부드럼강도는 기준 조건의 단순 변화와 용적선량-조건강도와 관련시킨 변화를 치료계획에 반영시켰다. 치료계획은 처방선량지수(Conformal Index, CI), 처방선량포함지수(Paddick's Conformal Index, PCI), 선량균질지수(Homogeneity Index, HI)와 각 장기의 평균선량으로 평가하였다. 결 과 : 용적선량-조건강도의 비율을 동일하게 하고 절대 값을 변화 시켰을 때 CI값은 다르지만, PCI는 $1.299{\pm}0.006$, HI는 $1.095{\pm}0.004$, D5%/D95%는 $1.090{\pm}1.011$으로 처방선량에 대한 영향은 유사하였다. 이하선의 평균선량은 용적선량-조건강도의 절대 값이 40, 60, 70, 90으로 증가될 때, 67.4, 50.3, 51.2, 47.1 Gy로 감소하였다. 각각의 치료계획에서 선량부드럼강도를 증가시켰을 때, PCI는 $1.338{\pm}0.006$로 증가된 값을 보였다. 결 론 : 용적선량-조건강도는 절대적인 값보다 각 조건의 비율에 따라 최적화 알고리즘에 영향을 주었다. 절대 값이 다르더라도 같은 비율을 유지하면 유사한 치료계획이 수립되었다. 성공적인 치료계획을 수립하기 위해 특히 보호해야할 정상장기의 용적선량-조건강도는 치료용적의 용적선량-조건강도의 50%이상 되어야한다. 선량부드럼강도는 용적선량-조건강도에 따라 비례하여 증가하거나 감소하여야 한다. 단순히 절대 값으로 적용하면 용적선량-조건강도는 그 조건을 충분히 만족시키지 못한다.