• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of the Korean Wood Science and Technology
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• v.18 no.3
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• pp.53-68
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• 1990

This research has been executed for maximization of lumber yield and more efficient use of small diameter logs. Sample logs from thinnings carne from densed artificial stands at the Kwangnung Experimental Forests situated in the central region of Korean peninsula. Species of sample logs were obtained to execute sawing and strength test for larch, and lumber strength test in full size for pitch pine and Korean pine. A survey on sawmills consuming domestic logs was carried out to know sawmill production, costs and utilization structure of lumber as a guide to business analysis. Results showed that sawing pattern from small logs less than 15cm in diameter was necessary to cut 9cm by 9cm square per one log in order to obtain high lumber recovery and provide for wide market needs. The total lumber yield of squares plus side boards was 56 percent to 58 percent from small logs and the yield for log sweep in 30 percent decreased by 24.5 percent in sawing production, compared to yield for straight logs. In sawing efficiency, production of lumber by twin band saw could be improved 238 percent higher than lumber of the same species produced by conventional sawmilling methods, and sawing accuracy with twin band saw was much higher at the lumber production than band saw. Lumber from the small larch logs has shown 70 knots per $m^2$ on its faces and also lumber showed lots of face checkings by air drying on the yard, compared to other species. MOR in bending of lumber in full size from small logs of larch was found ranging from 380kg/$cm^2$ to 460kg/$cm^2$, resulting in 40 percent less than the strength from clear small specimens. In lumber containing knots, cross grain, etc, longitudinal stress wave speed was delayed about 48 percent by defects in lumber from both larch and pitch pine logs. The surveyed sample sawmills consumed the domestic logs at the rate of 54 percent to 84 percent in the total timber consumption, showing high consumption at mills located in the mountains.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.1
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• pp.79-89
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• 1997

In order to reduce the outbreaks of short-term high concentrations and its impacts, we developed the models which predicted tomorrow's maximum hourly concentrations of $O_3$, TSP, SO$_2$, NO$_2$ and CO. Statistical methods like multi regressions were used because it must be operated easily under the present conditions. 47 independent variables were used, which included observed concentrations of air pollutants, observed and forcasted meteorological data in 1994 at Seoul and its surrounding areas. We subdivided Seoul into 4 areas coinciding with the present ozone warning areas. 4 kinds of seasonal models were developed due to the seasonal variations of observed concentrations, and 2 kinds of data models for the unavailable case of forecasted meteorological data. By comparing the $R^2$and root mean square error(hearafter 'RMSE') of each model, we confirmed that the models including forecasted data showed higher accuracy than ones using observed only. It was also shown that the higher the seasonal mean concentrations, the larger the RMSE. There was no distinct difference between the results of 4 areal models. In case of test run using 1995's data, the models predicted well the trends of daily variation of concentrations and the days when the possibility of outbreak of high concentarion was high. This study showed that it was reasonable to use those models as operational ones, because the $R^2$ and RMSE of models were smaller than those of operational/research models such as in South Coast Air Basin, CA, USA.

• Computers and Concrete
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• v.26 no.2
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• pp.185-201
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• 2020

This research is devoted to investigate the bending and free vibration behaviour of laminated composite/sandwich plates and shells, by applying an analytical model based on a generalized and simple refined higher-order shear deformation theory (RHSDT) with four independent unknown variables. The kinematics of the proposed theoretical model is defined by an undetermined integral component and uses the hyperbolic shape function to include the effects of the transverse shear stresses through the plate/shell thickness; hence a shear correction factor is not required. The governing differential equations and associated boundary conditions are derived by employing the principle of virtual work and solved via Navier-type analytical procedure. To verify the validity and applicability of the present refined theory, some numerical results related to displacements, stresses and fundamental frequencies of simply supported laminated composite/sandwich plates and shells are presented and compared with those obtained by other shear deformation models considered in this paper. From the analysis, it can be concluded that the kinematics based on the undetermined integral component is very efficient, and its use leads to reach higher accuracy than conventional models in the study of laminated plates and shells.

• The Journal of Information Systems
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• v.26 no.3
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• Journal of the Korean Home Economics Association
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• v.25 no.2
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• pp.55-68
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• 1987

This study was conducted to assess the knowledge and attitudes toward nutrition and behavior of mothers by using 30-item nutrition knowledge test and questionnaire. Results were summarized as follows; 1. Nutrition knowledge 1) The average score of nutrition knowledge and perceived knowledge were respectively 18.0, 26.0(the highest marks 30) and the accuracy of the knowledge was 68.4%. Knowledge about energy and nutrients scored lower marks than food composition and disease. 2) Nutrition knowledge had significant correlation with age, education level and total income. With increasing education level, total income and decreasing age, nutrition knowledge score were getting higher. 2. Attitudes about nutrition 1) Most important sources of nutrition information were by order of radio, T.V., newspapers, megazines and neighbors. 2) 56.2 percent of mothers said that they do meal planning and the greatest mian concern which had influence on meal planning was their hauband.(62.1%) 3) Among the mothers who responded 43.8 percent reported that they bring shopping list with them. 4) 72.6 percent of them wanted to participate re-education. 3. Food behavior 1) Most of mothers(93.1%) used instant food, regarding the reason for using instant food, 67.3 percent of them responded that is is convinient for cooking and 27.8 percent responded that it is for their familys' perference. 2) Mothers who had higher education level, tend to regard nutrition as the most important thing to cook, and with lower education level, they care more about taste. 3) Supper was the most main meal among three males of day.(75.9%) 4) 53.4 percent of mothers said they eat bread as a meal. This study provided baseline data for planning nutrition education programming for mothers.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1993.05a
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• pp.90-90
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• 1993

When illustrating the therapeutical plan of laryngeal cancer, there are difficulties in obtaining the three dimensional volume of tumor, submucosal extension of tumor, and particularly whether or not invasion on laryngeal cartilage has occurred. In particular clinical significance is the invasion to the laryngeal framework, which correlates with poor prognosis due to high frequency of local recurrence and cervical metastasis. Therefore the purposes of histopathological evaluation according to serial section study after laryngectomy are firstly, apprehension of the spread of laryngeal cancer and the pattern of invasion to laryngeal cartilage and secondly, obtaining an aid to establish direction of management to make higher the validity of preoperative clinical diagnosis. The following results were obtained : 1. The pattern of tumor invasion in cartilage 1) The tumor invades ossified cartilage chiefly and invades nonossified cartilage in extensive lesion only. 2) The tumor spread through intramarrow space at invaded ossified cartilage with intact perichondrium. 3) The perichondrium is strong barrier. 2. The incidence of cartilage invasion in order of frequency is as follow thyroid, arytenoid, cricoid, epiglottic cartilage. 3. The transglottic cancer has higher incidence(811.8%)of cartilage invasion. 4. The sensitivity, specificity, and accuracy rate of preoperative CT scan was 100%, 62.5%, 82.3% respectively.

• Journal of the Korean Society of Propulsion Engineers
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• v.22 no.5
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• pp.40-48
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• 2018

This paper presents a simulation-based design reliability estimation method of a low-energy exploding foil initiator (LEEFI) using a meta-model and describes the design reliability estimation results. The flyer velocity of the LEEFI is critical to initiate the explosive. Evaluation of the flyer velocity from mechanistic models in open literature requires a long computation time due to the multi-physical phenomena that generate the velocity. Moreover, the higher levels of confidence required for an initiator with high reliability incur higher computation costs. Thus, a meta-model of the flyer velocity over time was constructed in order to increase the computational efficiency for a reliable estimation. For different distributions and sigma levels of the design variables, the design reliability estimation results using the meta-model are provided. Additionally, the computational efficiency and accuracy of the estimation method are analyzed.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.2
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• pp.79-85
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• 2019

The mission tasks of polar exploration utilizing unmanned systems such as glacier monitoring, ecosystem research, and inland exploration have been expanded. To facilitate unmanned exploration mission tasks, precise and robust navigation systems are required. However, limitations on the utilization of satellite navigation system are present due to satellite orbital characteristics at the polar region located in a high latitude. The orbital inclination of global positioning system (GPS), which was developed to be utilized in mid-latitude sites, was designed at $55^{\circ}$. This means that as the user is located in higher latitudes, the satellite visibility and vertical precision become worse. In addition, the use of satellite-based wide-area augmentation system (SBAS) is also limited in higher latitude regions than the maximum latitude of signal reception by stationary satellites, which is $70^{\circ}$. This study proposes a local-area augmentation system that additionally utilizes Global Navigation Satellite System (GLONASS) considering satellite navigation system environment in Polar Regions. The orbital inclination of GLONASS is $64.8^{\circ}$, which is suitable in order to ensure satellite visibility in high-latitude regions. In contrast, GLONASS has different system operation elements such as configuration elements of navigation message and update cycle and has a statistically different signal error level around 4 m, which is larger than that of GPS. Thus, such system characteristics must be taken into consideration to ensure data integrity and monitor GLONASS signal fault. This study took GLONASS system characteristics and performance into consideration to improve previously developed fault detection algorithm in the local-area augmentation system based on GPS. In addition, real GNSS observation data were acquired from the receivers installed at the Antarctic King Sejong Station to analyze positioning accuracy and calculate test statistics of the fault monitors. Finally, this study analyzed the satellite visibility of GPS/GLONASS-based local-area augmentation system in Polar Regions and conducted performance evaluations through simulations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.65-75
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• 2021

This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.