• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.9
• /
• pp.596-603
• /
• 2020

'Electro-Mechanical Brake (EMB) is a novel braking system for automobiles and railway vehicles, and research in this area is actively underway. The current braking system for railway vehicles generates a braking force using a pneumatic cylinder, but the EMB system generates the force through a combination of an electric motor and gears. In this study, the design of an EMB system that meets the domestic standards was conducted through the finite element modeling and fatigue analysis of an eccentric rotating shaft-based EMB system capable of generating a high clamping force. At this time, to improve the accuracy of fatigue analysis, three types of fatigue test specimens, which were subjected to the same heat treatment as the materials used in the prototype, were produced, and the fatigue tests were performed for each material. The fatigue properties (S-N curves) were obtained from the fatigue test results for each material and reflected in the analysis model. The results of fatigue analysis confirmed that the design of the EMB prototype could satisfy the maximum commercial braking/relaxation of 530,000 times, which was the endurance life condition for domestic railway vehicles. In addition, based on this design, a prototype will be manufactured, and endurance testing will be completed to demonstrate the durability characteristics of the developed prototype.

• Journal of Broadcast Engineering
• /
• v.22 no.3
• /
• pp.282-294
• /
• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Journal of the Korean Society for information Management
• /
• v.28 no.3
• /
• pp.103-121
• /
• 2011

This study is to seek to apply resource types of RDA to KCR4. It is difficult to choose appropriate term and to embody FRBR model because GMD of KCR4 is the mixture of content-based vocabularies and carrier-based vocabularies. SMD is to need to reflect the current technological terms. Resource type of RDA was already developed to overcome limitation of AACR2's GMD, and would affect the world cataloging environment, therefore it is need to apply resource type of RDA to Korean cataloging rule. For this study, case study and survey were used. In case study, it was to scan all GMD term for one university library to build by programming and to grape librarian and users' potential need. In the survey by cataloging librarian, it was to figure out the current description of resource type in university library and to test RDA resource type. As a result, it was needed to revise the vocabulary to the obvious and user-understandable list. Also it was different in correction rate in RDA testing by resource type. Based on the case study and the survey, RDA resource type was applied to KCR4 resource list by adding term such as computer game in content type, and by inserting terms such as DVD, CD-ROM, Blu-Ray, computer file in carrier type. It also applied RDA description method and display means to KCR4. This study would apply RDA resource type to KCR4 and contribute to revise KCR4 resource type.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.11
• /
• pp.61-69
• /
• 2019

In this paper, we propose a multisensory(i.e., visual-auditory-tactile) based AR system for the education of cultural heritage. The proposed system provides a multisensory interaction by designing a user to experience with a 3D printed artifact which is mapped by a virtual 3D content of digital heritage. Compared with the existing systems of cultural heritage education based on augmented reality(AR) technology, this system focused on not only providing learning experience via a sense of visual and auditory, but also a sense of tactile. Furthermore, since this systems mainly provided the direct interactions using a 3D printed model, it gives a higher degree of realism than existing system that use touch or click motions on a 2D display of mobile phones and tablets. According to a result of user testing, we concluded that the proposed system delivered the excellent presence and learning flow to users. Particularly, from the usability evaluation, a 3D printed target artifact which is similar in shape to original heritage artifact, achieved the highest scores among the various tested targets.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.39-55
• /
• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Korean Journal of Ecology and Environment
• /
• v.56 no.1
• /
• pp.45-56
• /
• 2023

In stream ecosystem assessment, RIVPACS, which makes a simple but clear evaluation based on macroinvertebrate community, is widely used. In this study, a preliminary study was conducted to develop a RIVPACS-type model suitable for Korean streams nationwide. Reference streams were classified into two types(upstream and downstream), and a prediction model for macroinvertebrates was developed based on each family. A model for upstream was divided into 7 (train): 3 (test), and that for downstream was made using a leave-one-out method. Variables for the models were selected by non-metric multidimensional scaling, and seven variables were chosen, including elevation, slope, annual average temperature, stream width, forest ratio in land use, riffle ratio in hydrological characteristics, and boulder ratio in substrate composition. Stream order classified 3,224 sites as upstream and downstream, and community compositions of sites were predicted. The prediction was conducted for 30 macroinvertebrate families. Expected (E) and observed fauna (O) were compared using an ASPT biotic index, which is computed by dividing the BMWPK score into the number of families in a community. EQR values (i.e. O/E) for ASPT were used to assess stream condition. Lastly, we compared EQR to BMI, an index that is commonly used in the assessment. In the results, the average observed ASPT was 4.82 (±2.04 SD) and the expected one was 6.30 (±0.79 SD), and the expected ASPT was higher than the observed one. In the comparison between EQR and BMI index, EQR generally showed a higher value than the BMI index.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.123-139
• /
• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of The Korean Association For Science Education
• /
• v.36 no.1
• /
• pp.177-190
• /
• 2016

The purpose of this study is to validate learning progressions for Earth's motion and solar system from two different perspectives of validity. One is construct validity, that is whether a hypothetical pathway derived from our study of LPs is supported by empirical evidence of children's substantive development. The other is consequential validity, which refers to the impact of LP-based adaptive instruction on children's improved learning outcomes. For this purpose, 373 fifth-grade students and 17 teachers from six elementary schools in Seoul, Kangwon province, and Gwangju participated. We designed LP-based adaptive instruction modules delving into the unit of 'Solar system and stars.' We also employed 13 ordered multiple-choice items and analyzed the transitions of children's achievement levels based on the results of pre-test and post-test. For testing construct validity, 64 % of children in the experimental group showed improvement according to the hypothetical pathways. Rasch analysis also supports this results. For testing consequential validity, the analysis of covariance between experimental and control groups revealed that the improvement of experimental group is significantly higher than the control group (F=30.819, p=0.000), and positive transitions of children's achievement level in the experimental group are more dominant than in the control group. In addition, the findings of applying Rasch model reveal that the improvement of students' ability in the experimental group is significantly higher than that of the control group (F=11.632, p=0.001).

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.27 no.4
• /
• pp.340-360
• /
• 1982

Because of the continuing rapid increase in pesticide usage in Taiwan, much attention has been focus on pesticide contamination of food and effect of pesticides on human and environmental health. The Plant Protection Center (PPC) conducts safety evaluation of pesticides usee! in Taiwan. The pesticides are classified into different groups based on their acute toxicities. Pesticides which are classified into extremely toxic group are not allow to used on short term crops or the continuously harvest crops. The acute toxicity of pesticides to the beneficial insects are also studied, special attention has been paid to the two predators of rice brown planthopper. 60% of cultivated land in Taiwan are paddy field; therefore, acute fish toxicity was taken into consideration when a pesticide was applied for registration to be used in the paddy. Fish toxicities were evaluated by the dangerous rating value which is the amount of pesticide residue in the field water over the TLM value. Mutagenicity of pesticides was continuously evaluated by using Arne's microbial testing method. Island wide survey of residual levels of pesticides of known pollutants such as chlorinated hydrocarbon . insecticides, mercurial compounds in soil, water and biological samples were carried out constantly. The potential of a new1y Imported esticides to pollute the environment were studied by using model ecosystem. Ecological magnification (EM) of a chemical was calculated from model ecosystem. A chemical was considered as a pollutant when its EM value over 5000. In order to ensure the levels of pesticides residue of the crop within the safety limit. The 'tolerance' of pesticides on different crop groupings were established base on 1) acceptable daily intake value of individual pesticides, 2) average daily consumption of each crop groupings by Chinese person, 3) Actual residues of pesticides. on different crops obtained from supervised trials. Total about 79 pesticides for which the tolerances have been established on different crop groupings. Because the intensive agricultural system was adopted in Taiwan. The phytotoxicity of pesticides to the non-target crops was therefore become one of the important factor in the safety evaluation of pesticide usage. These will include 1) direct injury, 2) injury caused by pesticide polluted irrigation water, 3) injury caused by the pesticide polluted soil, 4) reduction of growth caused by the effect of pesticide on the soil microorganisms. This paper will reviewed all the aspects mentioned in the previous .paragraphs. Most the works have done in Taiwan by the PPC.y the PPC.

• Journal of Gifted/Talented Education
• /
• v.17 no.1
• /
• pp.1-26
• /
• 2007

The purpose of this study was to develop a math test for identification of the mathematically gifted on the basis of their math creative problem solving ability and to evaluate the goodness of the test. Especially, testing reliability and validity of scoring method on the basis of fluency only for evaluation of math creative problem solving ability was one of the main purposes. Ten closed math problems and 5 open math problems were developed requiring math thinking abilities such as intuitive insight, organization of information, inductive and deductive reasoning, generalization and application, and reflective thinking. The 10 closed math test items of Type I and the 5 open math test items of Type II were administered to 1,032 Grade 7 students who were recommended by their teachers as candidates for gifted education programs. Students' responses were scored by math teachers. Their responses were analyzed by BIGSTEPS and 1 parameter model of item analyses technique. The item analyses revealed that the problems were good in reliability, validity, item difficulty and item discriminating power even when creativity was scored based on the single criteria of fluency. This also confirmed that the open problems which are less-defined, less-structured and non-entrenched were good in measuring math creative problem solving ability of the candidates for math gifted education programs. In addition, it was found that the math creative problem solving tests discriminated applicants for the two different gifted educational institutions.