• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.9
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• pp.775-780
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• 2016

In this paper, a computational algorithm of an improved and versatile structural analysis applicable for large-size flexible nonlinear structures is developed. In more detail, nonlinear finite element based on the co-rotational (CR) framework is developed. Then, a finite element tearing and interconnecting method using local Lagrange multipliers (FETI-local) is combined with the nonlinear CR finite element. The resulting computational algorithm is presented and applied for nonlinear static analyses, i.e., cantilevered beam and multibody structure. Finally, the proposed analysis is evaluated with regard to its parallel computation performance, and it is compared with those obtained by serial computation using the sparse matrix linear solver, PARDISO.

• ETRI Journal
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• v.45 no.3
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• pp.404-417
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• 2023

This paper proposed a novel method for constructing quasi-cyclic low-density parity-check (QC-LDPC) codes of medium to high code rates that can be applied in cloud data storage systems, requiring better error correction capabilities. The novelty of this method lies in the construction of sparse base matrices, using a girth greater than 4 that can then be expanded with a lift factor to produce high code rate QC-LDPC codes. Investigations revealed that the proposed large-sized QC-LDPC codes with high code rates displayed low encoding complexities and provided a low bit error rate (BER) of 10^-10 at 3.5 dB E_b/N₀ than conventional LDPC codes, which showed a BER of 10^-7 at 3 dB E_b/N₀. Subsequently, implementation of the proposed QC-LDPC code in a softwaredefined radio, using the NI USRP 2920 hardware platform, was conducted. As a result, a BER of 10^-6 at 4.2 dB E_b/N₀ was achieved. Then, the performance of the proposed codes based on their encoding-decoding speeds and storage overhead was investigated when applied to a cloud data storage (GCP). Our results revealed that the proposed codes required much less time for encoding and decoding (of data files having a 10 MB size) and produced less storage overhead than the conventional LDPC and Reed-Solomon codes.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1267-1276
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• 2020

To quantitatively predict the impacts of large-scale volcanic eruptions of Mt. Baekdu on air quality and damage around the Korean Peninsula, a three-dimensional chemistry-transport modeling system (Weather Research & Forecasting - Sparse Matrix Operation Kernel Emission - Comunity Multi-scale Air Quality) was adopted. A worst-case meteorology scenario was selected to estimate the direct impact on Korea. This study applied the typical worst-case scenarios that are likely to cause significant damage to Korea among worst-case volcanic eruptions of Mt. Baekdu in the past decade (2005~2014) and assumed a massive VEI 4 volcanic eruption on May 16, 2012, to analyze the concentration of PM_2.5 caused by the volcanic eruption. The effects of air quality in each region-cities, counties, boroughs-were estimated, and vulnerable areas were derived by conducting an exposure assessment reflecting vulnerable groups. Moreover, the effects of cities, counties, and boroughs were analyzed with a high-resolution scale (9 km × 9 km) to derive vulnerable areas within the regions. As a result of analyzing the typical worst-case volcanic eruptions of Mt. Baekdu, a discrepancy was shown in areas between high PM_2.5 concentration, high population density, and where vulnerable groups are concentrated. From the result, PM_2.5 peak concentration was about 24,547 ㎍/㎥, which is estimated to be a more serious situation than the eruption of Mt. St. Helensin 1980, which is known for 540 million tons of volcanic ash. Paju, Gimpo, Goyang, Ganghwa, Sancheong, Hadong showed to have a high PM_2.5 concentration. Paju appeared to be the most vulnerable area from the exposure assessment. While areas estimated with a high concentration of air pollutants are important, it is also necessary to develop plans and measures considering densely populated areas or areas with high concentrations of susceptible population or vulnerable groups. Also, establishing measures for each vulnerable area by selecting high concentration areas within cities, counties, and boroughs rather than establishing uniform measures for all regions is needed. This study will provide the foundation for developing the standards for disaster declaration and preemptive response systems for volcanic eruptions.

• Geophysics and Geophysical Exploration
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• v.16 no.3
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• pp.119-130
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• 2013

We developed a method for inverting magnetic data to recover the 3D susceptibility models. The major difficulty in the inversion of the potential data is the non-uniqueness and the vast computing time. The insufficient number of data compared with that of inversion blocks intensifies the non-uniqueness problem. Furthermore, there is poor depth resolution inherent in magnetic data. To overcome this non-uniqueness problem, we propose a resolution model constraint that imposes large penalty on the model parameter with good resolution; on the other hand, small penalty on the model parameter with poor resolution. Using this model constraint, the model parameter with a poor resolution can be effectively resolved. Moreover, the wavelet transform and parallel solving were introduced to save the computing time. Through the wavelet transform, a large system matrix was transformed to a sparse matrix and solved by a parallel linear equation solver. This procedure is able to enormously save the computing time for the 3D inversion of magnetic data. The developed inversion algorithm is applied to the inversion of the synthetic data for typical models of magnetic anomalies and real airborne data obtained at the Geumsan area of Korea.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.889-898
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• 2022

In this paper, parallel computing method on the three-dimensional electromagnetic field is proposed. The present electromagnetic scattering analysis is conducted based on the time-harmonic vector wave equation and the finite element method. The edge-based element and 2^nd -order absorbing boundary condition are used. Parallelization of the elemental numerical integration and the matrix assemblage is accomplished by allocating the partitioned finite element subdomain for each processor. The graph partitioning library, METIS, is employed for the subdomain generation. The large sparse matrix computation is conducted by MUMPS, which is the parallel computing library based on the multi-frontal method. The accuracy of the present program is validated by the comparison against the Mie-series analytical solution and the results by ANSYS HFSS. In addition, the scalability is verified by measuring the speed-up in terms of the number of processors used. The present electromagnetic scattering analysis is performed for a perfect electric conductor sphere, isotropic/anisotropic dielectric sphere, and the missile configuration. The algorithm of the present program will be applied to the finite element and tearing method, aiming for the further extended parallel computing performance.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Parasites, Hosts and Diseases
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• v.30 no.2
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• pp.65-74
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• 1992

The tegumental ultrastructure of juvenile and adult Echinostoma cinetorchis (Trematoda: Echinostomatidae) was observed by scanning electron microscopy. Three-day (juvenile) and 16-day (adult) worms were harvested from rats (Sprague-Dawley) experimentally fed the metacercariae from the laboratory-infected fresh water snail, Hippeutis cantori. The worms were fifed with 2.5% glutaraldehyde, processed routinely, and observed by an ISI Korea DS-130 scanning electron microscope. The 3-day old juvenile worms were elongated and ventrally curved, with their ventral sucker near the anterior two-fifths of the body. The head crown was bearing 37∼38 collar spines arranged in a zigzag pattern. The lips of the oral and ventral suckers had 8 and 5 type II sensory papillae respectively, and bewteen the spines, a few type III papillae were observed. Tongue or spade-shape spines were distributed anteriorly to the ventral sucker, whereas peg-like spines were distributed posteriorly and became sparse toward the posterior body. The spines of the dorsal surface were similar to those of the ventral surface. The 16-day old adults were leaf-like, and their oral and ventral suckers were located very closely. Aspinous head crown, oral and ventral suckers had type II and type III sensory papillae, and numerous type I papillae were distributed on the tegument anterior to the ventral sucker. Scale-like spines, with broad base and round tip, were distributed densely on the tegument anterior to the ventral sucker but they became sparse posteriorly. At the dorsal surface, spines were observed at times only at the anterior body. The results showed that the tegument of E. cinetorchis is similar to that of other echinostomes, but differs in the number and arrangement of collar spines, shape and distribution of tegumenal spines, and type and distribution of sensory papillae.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.19-28
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• 2017

Collaborative filtering (CF) is a system that interprets the relationship between a user and a product and recommends the product to a specific user. The CF model is advantageous in that it can recommend products to users with only rating data without any additional information such as contents. However, there are many cases where a user does not give a rating even after consuming the product as well as consuming only a small portion of the total product. This means that the number of ratings observed is very small and the user rating matrix is very sparse. The sparsity of this rating data poses a problem in raising CF performance. In this paper, we concentrate on raising the performance of latent factor model (especially SVD). We propose a new model that includes product similarity information and co occurrence information in SVD. The similarity and concurrence information obtained from the rating data increased the expressiveness of the latent space in terms of latent factors. Thus, Recall increased by 16% and Precision and NDCG increased by 8% and 7%, respectively. The proposed method of the paper will show better performance than the existing method when combined with other recommender systems in the future.

• Parasites, Hosts and Diseases
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• v.22 no.1
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• pp.21-29
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• 1984

A scanning eletron microscopic study was performed to observe the tegumental surface of adult Fibricola seoulensis. The adult worms were collected from the small intestine of mice 5 days to 3 weeks after experimental infection with the metacercariae. The metacercariae were obtained from the viscera of the snakes, Matrix tigrina lateralis, by artificial digestion technique. The results were as follows: 1. The tegument of anterior body was covered with cobblestone-like cytoplasmic processes and that of posterior body showed finger-like processes. The posterior body had 4-5 large transverse wrinklings which formed many discontinued shallow rugae. 2. The entire surface of anterior body was regularly arranged with the spines of which tips diverged into 3 to 4 points. They were densely packed in anterior mid-median portion of dorsal surface where appeared a few spines indented upto 5 points. Farther laterally and posteriorly from this portion, the pointed spines were more sparse and became single tipped and extended to anterior one-third of posterior body, 3. The posterior surface of oral sucker was armed with 50-60 spines having 2-3 tips and ventral sucker also covered with such spines. On anteriormost dorsal surface arranged 60-70 spade-shaped spines. The tribocytic organ was armed with many stout recurved pile-like spines arranged radially. 4. There were 3 types of sensory papillae. The ciliated knob-like (Type I) papillae were almost bilaterally symmetrical in ventral and dorsal surfaces of anterior body, and abundant especially aroundbases of oral and ventral suckers, tribocytic organ, and in lateral margins of anterior body. About 24 non-ciliated round swellings (Type II) were observed around each lip of oral and ventral suckers. The plate-like elevated papilla without cilium (Type III) was found to distribute only in posterior body. These 3 types of papillae seem to be tangoreceptive and/or rheoreceptive in function when their morphology and distributions are considered.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.497-514
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• 2017

This study quantitatively analyzes the effects of emission inventory choices on the simulated particulate matter (PM) concentrations and the domestic/foreign contributions in the Seoul Metropolitan Area (SMA) with an air quality forecasting system. The forecasting system is composed of Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Community Multi-Scale Air Quality (CMAQ). Different domestic and foreign emission inventories were selectively adopted to set up four sets of emissions inputs for air quality simulations in this study. All modeling cases showed that model performance statistics satisfied the criteria levels (correlation coefficient >0.7, fractional error <50%) suggested by previous studies. Notwithstanding the apparently good model performance of total PM concentrations by all emission cases, annual average concentrations of simulated total PM concentrations varied up to $20{\mu}g/m^3$ (160%) depending on the combination of emission inventories. In detail, the difference in simulated annual average concentrations of the primary PM coarse (PMC) was up to $25.2{\mu}g/m^3$ (6.5 times) compared with other cases. Furthermore, model performance analyses on PM species showed that the difference in the simulated primary PMC led to gross model overestimation in general, which indicates that the primary PMC emissions need to be improved. The contribution analysis using model direct outputs indicated that the domestic contributions to the annual average PM concentrations in the SMA vary from 44% to 67%. To account for the uncertainty of the simulated concentration, the contribution correction factor method proposed by Bae et al. (2017) was applied, which resulted in converged contributions(from 48% to 57%). We believe this study shows that it is necessary to improve the simulated concentrations of PM components in order to enhance the accuracy of the forecasting model. It is deemed that these improvements will provide more accurate contribution results.