• Journal of Elementary Mathematics Education in Korea
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• v.10 no.1
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• pp.67-87
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• 2006

This study is to recognize a problem in the practice of performance assessment in elementary school, and to find out some suggestive points for improvement of teaching·learning method in elementary mathematics through assessment by reducing time restriction according to assessment through the practice of self-assessment, peer-assessment and observation, and then by reflecting the results of assessment on teaching learning plan. For that, the questions of study set up are as follows ; 1. How should self-assessment and peer-assessment be applied to in elementary mathematics assessment? 2. How should the time for 'let's play an interesting game' be managed for assessment of elementary mathematics? 3. How should the results of assessment be reflected on the Process of teaching and learning of mathematics? To solve these problems, a researcher of this thesis performed self-assessment, peer-assessment on 40 students of second grade under her charge as a class teacher, and applied observation in the time management process for 'let's play an interesting game' for a semester. self-assessment was made by mathematics journal, self-assessment chart, peer-assessment was by the analysis of conversation record among students in the situations of assessment, and observation was by observation of activity when playing with the results data of play analyzed. the concrete methods of application as follows ; First, mathematics journal was applied $1{\sim}2$ times by each unit with reconstruction into the level of second grade on the basis of the preceding-study models. Second, peer-assessment was applied to the unit-assessment time and the play-activities time by the method of recording·analyzing the contents of conversation among students in the process of assessment. Third, mathematical attitude & dispositions of students making use of the self- assessment table were examined referring to the teaching learning plan. Fourth, the time management for 'let's play an interesting game' was made through the prior recognition of play method and the joyful play-activities by use of the play-plate. Assessment depended on analysis of play-activities results of students making use of an observation form. Fifth, the results of self-assessment, peer-assessment, and observation were analyzed, and then they were made use of as self-observation data, of teacher her/his self, or teaching·learning improvement data. Students' self-assessment datum (mathematics diary, self-assessment sheets, conversation contents in the process of assessment) and observation materials (check lists, Play-activity result materials, conversation contents in the process of play) obtained in the process of application was analyzed as follows ; 1. From the practice of self-assessment in form of mathematics journal, I could obtain not only datum showing how much students was understanding the learning aims by unit time and to any degree they reached but also information about their response to learning datum and favorable type of learning. 2. Assessment by self-assessment chart was useful in planning the mathematics teaching learning process because it helps ascertain mathematical attitude & dispositions of students. 3. Through the application of peer-assessment, students had the opportunity of communicating with other students looking back on his/her explaining process, and teachers could obtain basic materials for assessment of students. 4, In case of time management for 'let's play an interesting game', there was natural extension of play made through time-security by prior looking into the method of play-activity, and then, for a remained time, by making children play a new game. 5, I could easily record the activities of students by use of the observation. form, and make use of it as basic data for descriptive assessment. 6, Each kinds of data obtained from the results of assessment was helpful for securing self-observation materials in the process of teaching learning and for their betterment in mathematics subject. However, because they were in the second grade of elementary school and there was an individual difference, some students could not make use of mathematics diary or self-assessment form properly. In case of these students, assessment data would be obtained through interview or observation. And for effective operation of play, its purpose & method and matters that demand special attention when play-acting should be clearly guided. Also, when applying an effective play in addition to play activities in textbook, to lessons, interesting mathematics lessons could be guided.

• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.11-21
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• 2019

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the SN explosion. To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes around the world and monitors the images of 60 nearby galaxies at distances D < 50 Mpc to a cadence as short as a few hours. The target galaxies are bright in near-ultraviolet (NUV) with $M_{NUV}$ < -18.4 AB mag and have high probabilities of hosting SNe ($0.06SN\;yr^{-1}$ per galaxy). With this strategy, we expect to detect the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling us to detect the shock-heated emission from a progenitor star with a radius as small as $0.1R_{\odot}$. The accumulated data will be also useful for studying faint features around the target galaxies and other science projects. So far, 18 SNe have occurred in our target fields (16 in IMSNG galaxies) over 5 years, confirming our SN rate estimate of $0.06SN\;yr^{-1}$ per galaxy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.91-104
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• 2023

The records system is believed to have started in Italy in the 14th century in line with trade developments in Europe. In 1491, Luca Pacioli, a mathematician, and an Italian Franciscan monk wrote the first book that described double-entry accounting processes. In many countries, including Korea, the government accounting standards used single-entry bookkeeping rather than double-entry bookkeeping that can be aggregated by account subject. The cash-based and single-entry bookkeeping used by the government in the past had limitations in providing clear information on financial status and establishing a performance-oriented financial management system. Accordingly, the National Accounting Act (promulgated in October 2007) stipulated the introduction of double-entry bookkeeping and accrual accounting systems in the government sector from January 1, 2009. Furthermore, the Korean government has also introduced International Financial Reporting Standards (IFRS), and the System of National Accounts (SNA). Since 2014, Korea owned five national accounts. In Korea, valuation began with the 1968 National Wealth Statistics Survey. The academic origins of the valuation of national wealth statistics which had been investigated by due diligence every 10 years since 1968 are based on the 'Engineering Valuation' of professor Marston in the Department of Industrial Engineering at Iowa State University in the 1930s. This field has spread to economics, etc. In economics, it became the basis of capital stock estimation for positive economics such as econometrics. The valuation by the National Wealth Statistics Survey contributed greatly to converting the book value of accounting data into vintage data. And in 2000 National Statistical Office collected actual disposal data for the 1-digit asset class and obtained the ASL(average service life) by Iowa curve. Then, with the data on fixed capital formation centered on the National B/S Team of the Bank of Korea, the national wealth statistics were prepared by the Permanent Inventory Method(PIM). The asset classification was also classified into 59 types, including 2 types of residential buildings, 4 types of non-residential buildings, 14 types of structures, 9 types of transportation equipment, 28 types of machinery, and 2 types of intangible fixed assets. Tables of useful lives of tangible fixed assets published by the Korea Appraisal Board in 1999 and 2013 were made by the Iowa curve method. In Korea, the Iowa curve method has been adopted as a method of ASL estimation. There are three types of the Iowa curve method. The retirement rate method of the three types is the best because it is based on the collection and compilation of the data of all properties in service during a period of recent years, both properties retired and that are still in service. We hope the retirement rate method instead of the individual unit method is used in the estimation of ASL. Recently Korean government's accounting system has been developed. When revenue expenditure and capital expenditure were mixed in the past single-entry bookkeeping we would like to suggest that BOK and National Statistical Office have accumulated knowledge of a rational difference between revenue expenditure and capital expenditure. In particular, it is important when it is estimated capital stock by PIM. Korea also needs an empirical study on economic depreciation like Hulten & Wykoff Catalog A of the US BEA.

• Tuberculosis and Respiratory Diseases
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• v.44 no.1
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• pp.44-51
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• 1997

Background : The changes of the composition in the T-lymphocyte are important as an immunological abnormality in the pathogenesis of tuberculosis. Previously, the second type of TCR dimer(${\gamma}{\delta}$ T lymphocyte) that did not express CD4 or CD8 molecules was found. In other reports the presence of this type of lymphocytes was increased in the initial stage of tuberculous infections. Method : To determine whether there are some differences in the T-lymphocyte subsets in the peripheral blood or pleural effusion between pleural tuberculosis and other pleurisy. Thirty patients with pleural effusion among the forty-nine patients were examined T-lymphocyte subset analysis(CD4+T-cell,CD8+ T-cell,${\gamma}{\delta}$ T-lymphocytes) with anti- Leu4, anti-Leu3a, anti-Lea2a, anti HLA-DR and anti-TCR-${\gamma}{\delta}$-1(Becton & Dickinson Co.). Results : The average age of the patients was 50 years old(17-81year). There were 33 males and 16 female patients. Patiensts with tuberculosis are 30cases(tuberculous pleurisy 15), lung cancer 12cases(malignant effusion 9) and pneumonia 7cases(parapneumonic effusion 6cases) In T lymphocyte subsets of pleural effusion, helper T lymphocyte(54.6 + 13.8 %) of tuberculous pleurisy was higher than that(36.2 + 25.3 %) of non-tuberculous pleurisy(p=0.04). The peripheral blood ${\gamma}{\delta}$ T-lymphocytes in tuberculousis was insignificantly higher than non-tuberculous patients(p= 0.24). The peripheral blood ${\gamma}{\delta}$ T-lymphocytes and pleural ${\gamma}{\delta}$ T-Iymphocytes in tuberculous pleurisy was insignificantly higher than in non-tuberculous pleurisy(p= 0.16, p= 0.12). Conclusion : The percentage of -${\gamma}{\delta}$ T lymphocytes among the total T-lymphocytes is not significantly increased in the peripheral blood or pleural effusion of the pleural tuberculosis. ${\gamma}{\delta}$ T lymphocytes is less useful as a diagnostic method of pleural tuberculosis.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Progress in Medical Physics
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• v.22 no.1
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• pp.42-51
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• 2011

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.