• 대한공업교육학회지
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• v.43 no.1
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• pp.134-157
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• 2018

This study surveyed and analyzed satisfaction and issues about an intellectual property education system, and educational needs for intellectual property NCS (intellectual property management, intellectual property information survey analysis, intellectual property assessment trade), in order to introduce and operate NCS-based education system that trains practical manpower in the field. The results of this study are as follows. First, satisfaction for intellectual property education system showed education contents (M=3.86), followed by lecture (M=3.79), teaching method and environment (M=3.66) and education assessment (M=3.50). The issues to be improved are low application in the current occupation due to no reflection of demands of industrial fields, as well as insufficient education contents system, lectures who fall short of education capability and interactions with students tend to stress theoretical knowledge more than practical ability, teaching method lacks application of educational medium, insufficient interest and motivation, assessment methods that fall short of theoretical knowledge and practical ability achievement, and that is theory-centered. Second, educational needs for intellectual property NCS showed intellectual property assessment trade (4.33), followed by intellectual property management (3.68), and intellectual property information survey analysis (2.99), which should be reviewed to reform or newly develop NCS-based education course. Conclusively, intellectual property education showed satisfaction above the average, but a job-centered education is demanded to elevate application in the industrial field, which puts emphasis more on practical ability than theory. For this, it is necessary to introduce intellectual property NCS reflecting demands of industrial field, and to reform or newly develop into NCS-based education course. In addition, intellectual property education needs to be operated by changed education paradigm, such as user-centered teaching method, not provided-centered, and performance and course-centered assessment method, not theoretical knowledge-centered.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.107-116
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• 2013

In the implementation of a P300 speller, rows and columns paradigm (RCP) is most commonly used. However, the RCP remains subject to adjacency-distraction error and double-flash problems. This study suggests a novel P300 speller stimuli presentation-the sub-block paradigm (SBP) that is likely to solve the problems effectively. Fifteen subjects participated in this experiment where both SBP and RCP were used to implement the P300 speller. Electroencephalography (EEG) activity was recorded from Fz, Cz, Pz, Oz, P3, P4, PO7, and PO8. Each paradigm consisted of a training phase to train a classifier and a testing phase to evaluate the speller. Eighteen characters were used for the target stimuli in the training phase. Additionally, 5 subjects were required to spell 50 characters and the rest of the subjects were to spell 25 characters in the testing phase. Classification accuracy results show that average accuracy was significantly higher in SBP as of 83.73% than that of RCP as of 66.40%. Grand mean event-related potentials (ERPs) at Pz show that positive peak amplitude for the target stimuli was greater in SBP compared to that of RCP. It was found that subjects tended to attend more to the characters in SBP. According to the participants' ratings on how comfortable they were with using each type of paradigm on 7-point Likert scale, most subjects responded 'very difficult' in RCP while responding 'medium' and 'easy' in SBP. The result showed that SBP was felt more comfortable than RCP by the subjects. In sum, the SBP was more correct in P300 speller performance as well as more convenient for users than the RCP. The actual limitations in the study were discussed in the last part of this paper.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.219-231
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• 1996

The aim here is to analyse the system of description of GIS in all of the high school textbooks passed with the official approval, to find the degree to which teachers understand about GIS, and to consider the present condition of GIS instruction. Most of the authors of textbooks generally underestimate importance of GIS, and there is difference among their awareness. In the system of description of GIS, there are only a few kinds of textbooks in which explanation of GIS is made coherently from the purpose of instruction aim through the chapter summary and to overall test in both of the Korean Geography and the World Geography. This trend is due to the degree of distribution of the GIS specialists in writing a textbook while the other texts books shows just a brief introduction of GIS concept. Although there is the limit for teachers to study how to teach GIS due to its very technological aspect as well as few previous training and teacher's guide. Thus it is evident that about a half of teachers who responded taught high school students without a knowledge on GIS, and a few of them even never referred to that concept. These facts may negatively affect the status of a geography in the society of information. For the solution of these issues, it is considered how to repair the description system and its contents. Besides, the variation among textbooks is reduced at the further revision of the 7th curriculum. And the printed matters of GIS are sufficiently provided for the teachers to use as their teaching aids. It is desirable that the GIS instruction models should be further developed for college education, and the programs for the on-the-job teachers training should be arranged. Besides, the previous training for the on-the-job teachers should be achieved more practically with enough time before the revision of curriculum.

• Korean Security Journal
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• no.52
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• pp.73-91
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• 2017

This study is based on the political and economic standpoint of each country, Use advanced equipment to prevent new terrorism from causing widespread damage, In order to establish a countermeasures against terrorism in accordance with the reality of Korea, which is effective in responding to terrorist attacks, Korea conducted a SWOT analysis of the terrorist environment and terrorist environment through specialists. First, internal strengths of Korea 's terrorist environment include stable security situation, weakness of religious and ethnic conflicts, strong regulation and control of firearms, and counter terrorism capabilities and know - how accumulated during major international events. Second, the internal weaknesses of the terrorist environment in Korea include the insecurity of the people, the instability caused by the military confrontation with North Korea, the absence of anti-terrorism law system, the difficulty of terrorism control and management by the development of the Internet and IT technology. Third, the external opportunities for Korea 's terrorist environment are as follows: ease of supplementation and learning through cases of foreign terrorism failure, ease of increase of terrorist budget and support with higher terrorism issues, strengthening of counterterrorism through military cooperation with allied nationsRespectively. Fourth, the external threats to the terrorist environment in Korea are the increase of social dissatisfaction due to the continuous influx of defectors and foreign workers, the goal of terrorism from international terrorist organizations through alliance with the United States,Increased frequency of incidents, and increased IS coverage of terrorism around the world. In addition, the SWOT in - depth interviews on the terrorist environment of the expert group were conducted to diagnose and analyze the problems, terrorism awareness and legal system in the Korean terror environment. The results of the study are summarized as follows.First, the basic law on terrorism should be enacted.Second, the establishment of an integrated anti-terrorism organization.Third, securing and nurturing specialized personnel in response to terrorism.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.259-270
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• 2020

Extreme weather events, such as heat and drought, have occurred frequently over the past two decades. This has led to continuous reports of cases of forest damage due to physiological stress, not pest damage. In 2014, pine trees were collectively damaged in the forest genetic resources reserve of Sogwang-ri, Uljin, South Korea. An investigation was launched to determine the causes of the dieback, so that a forest management plan could be prepared to deal with the current dieback, and to prevent future damage. This study aimedto 1) understand the topographic and structural characteristics of the area which experienced pine tree dieback, 2) identify the main causes of the dieback, and 3) predict future risk areas through the use of machine-learning techniques. A model for identifying risk areas was developed using 14 explanatory variables, including location, elevation, slope, and age class. When three machine-learning techniques-Decision Tree, Random Forest (RF), and Support Vector Machine (SVM) were applied to the model, RF and SVM showed higher predictability scores, with accuracies over 93%. Our analysis of the variable set showed that the topographical areas most vulnerable to pine dieback were those with high altitudes, high daily solar radiation, and limited water availability. We also found that, when it came to forest stand characteristics, pine trees with high vertical stand densities (5-15 m high) and higher age classes experienced a higher risk of dieback. The RF and SVM models predicted that 9.5% or 115 ha of the Geumgang Pine Forest are at high risk for pine dieback. Our study suggests the need for further investigation into the vulnerable areas of the Geumgang Pine Forest, and also for climate change adaptive forest management steps to protect those areas which remain undamaged.

• Journal of The Korean Association For Science Education
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• v.18 no.4
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• pp.463-472
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• 1998

Biotechnology is the process of using biological system for the production of materials. Genetic engineering, a subset of biotechnology, is the process of altering biological systems by the purposeful manipulation of DNA It is a new field in biology and no topic in biology is more likely to impact our personal lives and is therefore more worthy of our attention and understanding. The purpose of this study was to investigate students' understanding of the concepts of biotechnology, and a test tool which is made up of 20 basic questions was developed for the study. The subject of this study was high school students and the sample size was 486. In order to find out the source of students' misunderstanding, we also analysed high school textbooks and teachers were given the same tool applied to students. Two-way ANOVA was used for the analysis. Major findings of this study are as following; 1. Mean score of students was 41, and there was a significant difference between the scores of boys and girls(p<0.05). Female students scored higher than male students. The variables "region" and "major" had no significant influence. 2. Students' the most misunderstood concepts were "monoclonal antibody" and "gene cloning". Many students thought that a plamid DNA originally has a useful DNA in it, which is apparently wrong. 3. Mean score of teachers was 82, and the variabes of gender and career did not have statistically significant influence on the result(p>0.05). 4. Teachers got the lowest scores on the concepts of "gene therapy", "the accomplishment of biotechnology in agriculture and medicine", and "plasmid DNA". The results of item analysis implied that teachers' misunderstanding might be a part of the sources of students' misunderstaning. 5. Out of 18 basic concepts selected in the study, only 10 concepts were explained well enough in most textbooks. The results of item analysis indicated that textbooks also could be a part of the source of students' misunderstanding.

• 대한공업교육학회지
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• v.40 no.2
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• pp.111-129
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• 2015

This study tried to investigate the possibility and expectation effect to organize and operate NCS(national competency standards)-based vocational education curriculum in technical specialized high schools and meister high schools and the perceptions of specialty subject teachers about support plans for effective operation of the NCS-based curriculum. For this, the survey was conducted targeting 286 specialty subject teachers in technical specialized high schools and meister high schools. And the results are as follow: First, the specialty subject teachers in the technical specialized high schools and meister high schools recognized that the positive expectation effect can be obtained through the NCS-based vocational education curriculum and the NCS-based vocational education curriculum should very much be applied to the school curriculum but it is impractical to organize and operate the NCS-based vocational education curriculum as the school curriculum from 2016. Second, the specialty subject teachers in the technical specialized high schools and meister high schools recognized that industrial education needs can be analyzed, industry duties-based educational objectives and contents can be set up, industrial duties-based education can be done, the capability to develop and operate teachers' curriculum can be improved, and the NCS-based curriculum will be effective for industrial and academic cooperation and connection with communities by applying it but the realistic possibility will relatively be low. Third, the specialty subject teachers in the technical specialized high schools and meister high schools recognized that tools for practice should be reorganized and expanded, the number of students targeting practical classes should be reduced by 15 to 20 persons, teachers' field education capability should be strengthened, supply and demand of teachers should be supported, industrial and academic cooperation-based field-centered education should be reinforced, and support of the NCS-based teaching materials to be textbooks should be required in terms of operating schools to operate the NCS-based vocational curriculum effectively. Support of finding jobs and field education which correspond with the NCS-based vocational curriculum should be provided, field instruction by ability of the national competency standards should be supported, field practice education projects about the NCS-based vocational curriculum should be provided and introduction and operation of the industrial employee performance evaluation system should be required in terms of the support plans of relevant organizations.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5
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• pp.64-79
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• 2010

Students with intellectual disabilities typically have great difficulties communicating their needs and wants and may get frustrated, anxious or show signs of aggressive behaviour. They are often unable to understand the concept of relationships with other people as well. This lack of social communication and interaction leads to poor motivation which increases other areas of difficulty in their lives. Therefore, to teach students with intellectual disabilities, it is essential to find special teaching methods to support their positive behavior. This paper proposes that special educational curriculum for students with intellectual impairments utilize natural environments(forests) and materials. The purpose of this study was to investigate the effects of Educational Programs Utilizing Forests on maladjusted behavior of students with mental retardation and to examine the positive effects of such planning practices. The subjects were middle school students who attended a special school for mentally-retarded students. They were divided into two separate groups- an experimental group and a control group. All subjects received the pre and post test using the same method. This program was applied to the formal educational process of middle school from March 1st to October 30th, 2009. In this experiment the results indicate that the effect of using a natural environment(forest) and the materials within a formal educational curriculum was positive as a type of horticultural therapy and that it supports positive behavior strategies in students with intellectual impairments. The usage of various natural materials including plants and flowers within the natural environments provide students with increased opportunities to participate. Teaching methods including natural materials help teachers engage with their students more easily during routine activities as their interest is already stimulated. This project will help students with intellectual impairments to build skills which enable effective participation and increase independence throughout their lives. This should be embedded into both routine and planned activities of the classroom Also, it offers a needed interior plan for the treatment space through an analysis of psychological factors of how the environment affects students.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.