• Journal of Environmental Science International
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• v.20 no.9
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• pp.1183-1190
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• 2011

This study was aimed to establish the evaluating protocol and standard assessment for genetically modified (GM) hot pepper and to find out a proper statistic method to analyze for equality of agricultural characters between GM and non-GM pepper lines. GM and non-GM hot pepper lines were cultivated in two GMO fields in the middle region of Korea and total of 52 agricultural characters were collected during the plant growing season for 4 years, 2007 to 2010. Levene's test was conducted to confirm the homogeneity of raw data before statistic analysis. Two-way ANOVA in the multivariate tests and t-test were conducted to analyze 52 agricultural characters in order to find out the equality between H15 and P2377. From the statistical analysis through two-way ANOVA, 16 out of 16 plant growth traits, 9 out of 18 green fruit traits and 7 out of 18 red fruit traits among 4 years and 9 out of 16 plant growth traits, 4 out of 18 green fruit traits and 3 out of 18 red fruit traits between H15 and P2377 have shown the statistic differences. With the same raw data of 52 agricultural characters, t-test was also conducted. Based on the result from t-test, only 1 out of 16 plant growth traits, 2 out of 18 green fruit traits and 1 out of 18 red fruit traits have shown the differences between H15 and P2377, so that it was concluded that there is no statistic difference between H15 and P2377 in terms of agricultural characters. Also, the t-test is a proper statistic method to analyze each trait between GM and its control lines in order to evaluate agricultural characters.

• Journal of Gastric Cancer
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• v.14 no.1
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• pp.39-46
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• 2014

Purpose: According to current guidelines, perioperative chemotherapy is an integral part of the treatment strategy for advanced gastric cancer. Randomized controlled studies have been conducted in order to determine whether perioperative chemotherapy leads to improved R0 resection rates, fewer recurrences, and prolonged survival. The aim of our project was to critically appraise three major studies to establish whether perioperative chemotherapy for advanced, potentially resectable gastric cancer can be recommended on the basis of their findings. Materials and Methods: We analyzed the validity of the three most important studies (MAGIC, ACCORD, and EORTC) using a standardized questionnaire. Each study was evaluated for the study design, patient selection, randomization, changes in protocol, participating clinics, preoperative staging, chemotherapy, homogeneity of subjects, surgical quality, analysis of the results, and recruitment period. Results: All three studies had serious shortcomings with respect to patient selection, homogeneity of subjects, changes in protocol, surgical quality, and analysis of the results. The protocols of the MAGIC and ACCORD-studies were changed during the study period because of insufficient recruitment, such that carcinomas of the lower esophagus and the stomach were examined collectively. In neither the MAGIC study nor the ACCORD study did patients undergo adequate lymphadenectomy, and only about half of the patients in the chemotherapy group could undergo the treatment specified in the protocol. The EORTC study had insufficient statistical power. Conclusions: We concluded that none of the three studies was sufficiently robust to justify an unrestrained recommendation for perioperative chemotherapy in cases of advanced gastric cancer.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.3-9
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• 1997

EEG(electroencephalogram) is attempted to determination of human emotion. Ten university students were participated in this study. Ten auditory stimuli were presented for a subject to evoke emotion. Data homogeneity according to brain local area and basic mechanism of relative variation for combinational delta, theta, alpha and beta waves were analyzed. As the result, the local area characterized by factor analysis and the relative variation of alpha-delta wave can be considered as the determinants of human emotion.

• Language and Information
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• v.13 no.1
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• pp.21-38
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• 2009

Since countability is a grammatical notion, the distinction between count and mass nouns may not reflect countability in the real world. Based on this, Chierchia (1998a; 1998b) provides a typological study of plurality and genericity, which does not account for countability in Korean. Nemoto (2005) revises Chierchia's analysis to deal with count and mass nouns in Korean and Japanese. This study discusses problems with the previous analyses and proposes that the semantic feature of humanness is the main criterion for countability in Korean.

• Communications for Statistical Applications and Methods
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• v.21 no.4
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• pp.275-284
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• 2014

Matched pairs are twice continuously measured data with the same categories. They can be represented as the square contingency tables. We can also consider symmetry and marginal homogeneity. Moreover, we can infer the matched pairs models; the symmetry model, the quasi-symmetry model, and the ordinal quasi-symmetry model. These inferences are involved in assumptions for special distributions. In this study, we visualize matched pairs models using modified correspondence analysis. Modified correspondence analysis can be used when square contingency tables are given; consequently, it is involved in the square and asymmetric correspondence matrix. This technique does not need assumptions for special distributions and is more helpful than the correspondence analysis to visualize matched pairs models.

• Radiation Oncology Journal
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• v.28 no.1
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• pp.39-49
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• 2010

Purpose: This aim of this study is to analyze the dosimetric difference between intensity-modulated radiation therapy (IMRT) using 3 or 5 beams and MSF in the radiotherapy of the left breast. Materials and Methods: We performed a comparative analysis of two radiotherapy modalities that can achieve improved dose homogeneity. First is the multistatic fields technique that simultaneously uses both major and minor irradiation fields. The other is IMRT, which employs 3 or 5 beams using a fixed multileaf collimator. We designed treatment plans for 16 early left breast cancer patients who had taken breast conservation surgery and radiotherapy, and analyzed them from a dosimetric standpoint. Results: For the mean values of $V_{95}$ and dose homogeneity index, no statistically significant difference was observed among the three therapies. Extreme hot spots receiving over 110% of the prescribed dose were not found in any of the three methods. A Tukey test performed on IMRT showed a significantly larger increase in exposure dose to the ipsilateral lung and heart than multistatic fields technique (MSF) in the low-dose area, but in the high-dose area, MSF showed a slight increase. Conclusion: In order to improve dose homogeneity, the application of MSF, which can be easily planned and applied more widely, is considered an optimal alternative to IMRT for radiotherapy of early left breast cancer.

• Analytical Science and Technology
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• v.11 no.4
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• pp.271-280
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• 1998

Rice flour reference materials were prepared from the unpolished rice grown in Korea and certified for elemental composition. The reference materials consist of two samples containing normal and high level. The reference material at elevated level was prepared by spiking to the normal rice flour six toxic elements of As, Cd, Cu, Cr, Hg, Pb with $1.0{\mu}g/g$ on a dry weight basis. Homogeneity of the prepared materials was evaluated through the determination of Ca, Cu, Fe, Mn, Zn by instrumental neutron activation analysis (INAA) and atomic absorption spectrometry (AAS). Small variance of elemental composition among interbottled samples assured homogeneity of the prepared materials. The materials were decomposed by high pressure digestion and microwave digestion method. INAA, AAS, inductively coupled plasma-atomic absorption spectrometry (ICP-AES), ICP-mass spectrometry (MS) and vapour generation techniques were employed to analyze the reference materials. From this independent analytical results, the certified or reference values are determined for As, Ca, Cd, Cr, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, P, Pb, Se, Zn.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.20 no.1
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• pp.29-35
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• 2015

Dissolved nutrients in seawater are recognized as an essential biogeochemical factor for detecting global environmental changes. The importance of nutrient reference material for seawater has been increased greatly for the comparison of nutrient data, measured in different time and space in global ocean by various researchers with different levels in nutrient analysis skill. In this study, we described the homogeneity and stability of nutrient reference material for seawater using natural seawater, collected at a station of Shihwa Lake, at a coastal station near Uljin (surface water), and at a station over the Ulleung Basin (surface water and 1500 m depth water) and sterilized. Based on the homogeneity data, the nutrient reference materials has similar homogeneity compared to other nutrient reference materials. During 3-13 month period, there was no unidirectional trend of increase or decrease in nutrient concentration of newly developed nutrient reference material for seawater. However, a sustained measurement is required to check stability for longer period.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.891-904
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• 2006

The estimation of the probability precipitation is essential for the design of hydrologic projects. The techniques to calculate the probability precipitation can be determined by the point frequency analysis and the regional frequency analysis. The regional frequency analysis includes index-flood technique and L-moment technique. In the regional frequency analysis, even if the rainfall data passed homogeneity, suitable distributions can be different at each point. However, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to parametric point frequency analysis because of suppositions about probability distributions. Therefore, this paper applies kernel density function to precipitation data so that homogeneity is defined. In this paper, The data from 16 rainfall observatories were collected and managed by the Korea Meteorological Administration to achieve the point frequency analysis and the regional frequency analysis. The point frequency analysis applies parametric technique and nonparametric technique, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function.