• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.83.2-83.2
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• 2012

Type I AGNs are classified by the presence of broad emission lines while Type II AGNs show narrow emission lines only. All-sky surveys such as SDSS provide large AGN samples for statistical studies. However, the AGN samples suffer selection bias due to the incomplete selection criteria. To investigate the missing Type I AGNs in optical spectroscopic surveys, we start with a sample of SDSS Type II AGNs at 0.02 < z < 0.05, using the MPA-JHU SDSS DR7 catalog. We search for the hidden broad $H{\alpha}$ component with both visual inspection and the multi-component spectral decomposition method. Out of 1383 Type II AGNs, we find a total of 62 missing Type I AGNs (~4.5%). The sample has mean black hole mass, log $(M_{BH}/M_{SUN))=6.48{\pm}0.53$, and luminosity, log $(L_{H{\alpha}}/ergs^{-1})=40.52{\pm}0.33$, with Eddington ratio, log $(L_{bol}/L_{Edd})=-1.51{\pm}0.41$. We will describe the sample and present the $M_{BH}-{\sigma}_*$, and $M_{BH}-M_*$ relations of the sample in the context of the BH-galaxy coevolution.

• Journal of Power Electronics
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• v.14 no.4
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• pp.722-732
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• 2014

The power-voltage (P-V) curve of photovoltaic (PV) arrays connected in parallel to bypass diodes would have several local maximum power points (LMPP) under partial shading conditions (PSC). Conventional maximum power point tracking (MPPT) methods fail to search for the global maximum power point (MPP) because the searched peak point may remain at the LMPP on the P-V curve under PSC. This study proposes an improved MPPT algorithm to ensure that PV arrays operate at global maximum power point (GMPP) under PSC. The proposed algorithm is based on a critical study and a series of observations of PV characteristics under PSC. Results show the regularity of voltage interval between LMPPs. The algorithm has the advantages of rapidly reaching GMPP, maintaining stability, and recovering GMPP quickly when the operating condition changes. Simulation and experimental results demonstrate the feasibility of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.6-8
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• 2009

This paper presents the novel implementation of memetic algorithm with GA (Genetic Algorithm) and MADS (Mesh Adaptive Direct Search), which is applied for optimal design methodology of electric machine. This hybrid algorithm has been developed for obtaining the global optimum rapidly, which is effective for optimal design of electric machine with many local optima and much longer computation time. In particular, the proposed memetic algorithm has been forwarded to optimal design of direct-driven PM wind generator for maximizing the Annual Energy Production (AEP), of which design objective should be obtained by FEA (Finite Element Analysis). After all, it is shown that GA combined with MADS has contributed to reducing the computation time effectively for optimal design of PM wind generator when compared with purposely developed GA implemented with the parallel computing method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1484-1490
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• 2007

The Cross Reference Point(CRP) is a robust method for finding salient points in watermarking systems because it is based on the geometrical structure of a normalized image in order to avoid pointing error caused by digital attacks. After normalization of an image, the 100 CRPs are calculated. Next, the 100 blocks centered by CRPS are formed. These 100 blocks are arranged using a secrete key. Each boundary of 50 out of 100 blocks is surrounded by 8 blocks which are selected by the ordered number of a preceding block. This number is a seed of random number generator for selecting 8 out of 50 blocks. The search area of a center block is formed by a secrete key. The pixels of a center block are quantized to 10 levels by predefined thresholds. The watermarks are generated by the 50 quantized center blocks. These watermarks are embedded directly in the remaining 50 blocks. In other words, 50 out of 100 blocks are utilized to generate watermarks and the remaining 50 blocks are used to watermark embedding. Because the watermarks are generated in the given images, we can successfully detect watermarks after several digital attacks. The reason is that the blocks for the generation and detection of watermarks are equally affected by digital attacks except for the case of local distortion such as cropping.

• Nuclear Engineering and Technology
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• v.49 no.6
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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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.935-942
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• 2002

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.

• Journal of Oriental Neuropsychiatry
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• v.30 no.2
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• pp.71-88
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• 2019

Objectives: The present study aims to review the antidepressant effect of herbal medicines reported in Korean local journals. Methods: We searched in electronic databases (Koreantk, KISS, OASIS, NDSL) for studies, published in Korean national journals, that assessed herbal medicine effect of depression model. The search term was 'depression' in the abstract or whole text. Depression model, herbal material, experimental results, mechanisms were extracted. Results: We included 43 articles in which 38 studies were in vitro experiments, and the rest 5 were in vivo experiments. The most common experiment subject model was a rat and the most widely used method to induce depression was Despair behavior test. 21 studies used simple herbal medicines, and 22 studies used complex herbal medication. Glycyrrhizae Radix was the most commonly used herbal material to improve depression model. The most common mechanisms of herbal medicine with antidepressant effect were inhibition of Monoamine activation mechanism and depression related neurohormone secretion. Conclusions: Herbal medicines may be a promising resource for treating depression.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.77-85
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• 2019

In this paper, we propose a "Safe Web Using Scrapable Headless Browse" Because in a network separation environment for security, It does not allow the Internet. The reason is to physically block malicious code. Many accidents occurred, including the 3.20 hacking incident, personal information leakage at credit card companies, and the leakage of personal information at "Interpark"(Internet shopping mall). As a result, the separation of the network separate the Internet network from the internal network, that was made mandatory for public institutions, and the policy-introduction institution for network separation was expanded to the government, local governments and the financial sector. In terms of information security, network separation is an effective defense system. Because building a network that is not attacked from the outside, internal information can be kept safe. therefore, "the separation of the network" is inefficient. because it is important to use the Internet's information to search for it and to use it as data directly inside. Using a capture method using a Headless Web browser can solve these conflicting problems. We would like to suggest a way to protect both safety and efficiency.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.143-148
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• 2022

Brain tumor classification is an important process that allows doctors to plan treatment for patients based on the stages of the tumor. To improve classification performance, various CNN-based architectures are used for brain tumor classification. Existing methods for brain tumor segmentation suffer from overfitting and poor efficiency when dealing with large datasets. The enhanced CNN architecture proposed in this study is based on U-Net for brain tumor segmentation, RefineNet for pattern analysis, and SegNet architecture for brain tumor classification. The brain tumor benchmark dataset was used to evaluate the enhanced CNN model's efficiency. Based on the local and context information of the MRI image, the U-Net provides good segmentation. SegNet selects the most important features for classification while also reducing the trainable parameters. In the classification of brain tumors, the enhanced CNN method outperforms the existing methods. The enhanced CNN model has an accuracy of 96.85 percent, while the existing CNN with transfer learning has an accuracy of 94.82 percent.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.605-618
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• 2022

Glass fiber reinforced polymer (GFRP) elastic gridshells consist of long continuous GFRP tubes that form elastic deformations. In this paper, a method for the form-finding of gridshell structures is presented based on the interpretable machine learning (ML) approaches. A comparative study is conducted on several ML algorithms, including support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), AdaBoost, XGBoost, category boosting (CatBoost), and light gradient boosting machine (LightGBM). A numerical example is presented using a standard double-hump gridshell considering two characteristics of deformation as objective functions. The combination of the grid search approach and k-fold cross-validation (CV) is implemented for fine-tuning the parameters of ML models. The results of the comparative study indicate that the LightGBM model presents the highest prediction accuracy. Finally, interpretable ML approaches, including Shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions of the ML model since it is essential to understand the effect of various values of input parameters on objective functions. As a result of interpretability approaches, an optimum gridshell structure is obtained and new opportunities are verified for form-finding investigation of GFRP elastic gridshells during lifting construction.