• Title/Summary/Keyword: Competition-Based Learning

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Analyzing the Effect of Argumentation Program for Improving Teachers' Conceptions of Evolution (교사들의 진화 개념 이해 향상을 위한 논변활동 프로그램 효과 분석)

  • Kwon, Jieun;Cha, Heeyoung
    • Journal of The Korean Association For Science Education
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    • v.35 no.4
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    • pp.691-707
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    • 2015
  • This study aims to develop biology teachers' education program based on argumentation activity about core concepts of evolution and to analyze the characteristics of core concepts of evolution learned during the program. The eight core concepts of evolution in this study were variation, heritability of variation, competition, natural selection, adaptation, differential reproductive rate of individuals, changes in genetic pool within a population, and macroevolution. The performances of teachers participating in the program were compared before and after argumentation activities; consisting of seven sessions on the eight core concepts of evolution. The process of the program was specially designed by learning cycle model for teacher education, consisting of seven phases: identification of the task, production of a tentative argument, small group's written argument, share arguments with the other groups, reflective discussion, final written argument, and organization by an instructor. Participants in the study were two pre-service biology teachers and four in-service biology teachers. The results suggest that biology teachers reduced the teleological explanation for biological evolution and improve its adequacy after the intervention. Teachers lacked the opportunity to discuss variation, heritability of variation, competition, and macroevolution because science textbooks lack information on the concepts of biological evolution. The results of this study suggest that because the argumentation program developed for teachers helps to improve understanding the concepts of evolution and to reduce inadequate conceptions in biology, teacher education programs using argumentation activity and eight core concepts of evolution will play a role for efficient evolution education for biology teachers.

A biota research and analysis for Close-to-nature stream restoration planning (자연형 하천복원계획 수립을 위한 생물상 조사 및 분석)

  • SaGong, Jung-Hee;Ryu, Yeon-Su;Ra, Jung-Hwa
    • Current Research on Agriculture and Life Sciences
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    • v.24
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    • pp.37-42
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    • 2006
  • The purpose of this study was a biota research and analysis for Close-to-nature stream restoration planning of Shinchun. The summary of this study is as follows; 1) The vascular plants in research area recorded of 45 species and insect fauna recorded of 34 species of 8 orders. As a result of table of community classification, the communities were two group; Quercus variabilis community(I), Pinus densiflora-Quercus variabilis-Quercus dentata community(II). 2) As a result of analysis on correlation of tree species, the level of significance in positive correlation between Quercus dentata and Corylus heterophyll aindicated 1% and between Pinus densiflora and Lespedeza bicolor also indicated 1%. 3) As a result of DBH analysis, it is expected that Quercus variabilis and Quercus dentata will dominateover other species in competition and its succession continuously maintains from now on in community I. In community II, it is assumed that there is a high possibility of changing into community of Quercus such as Quercus mongolica, Quercus dentata, and Quercus variabilis. 4) As a result of analysis on insect fauna, insect fauna consists of 94% of whole species as 32 species, 23 families, 8 orders. And 7 species, 7 families 4 orders was found in highly urbanized area, the vicinity of Sang-Dong bridge. 5) As mentioned above, Based on A biota fundamental research, Close-to-nature stream restoration planning were full of suggestions: i) Designating ecosystem preservation area, ii) Making Close-to-nature stream revetments, iii) Making pool-and-riffle, vi) Making decks for observation and walks for nature experience, v) Creating wetland biotope. Through these methods, it is necessary to promote bio-diversity and lead people to the space for eco-learning.

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Development of Key Performance Indicators to Implement Balanced Scorecard to Small and Medium Size Dental Clinic (중소 규모의 치과의원에 균형성과표를 적용하기 위한 핵심성과지표 개발)

  • Kim, Sangsuk;Kim, Myeng Ki;Choi, Hyungkil
    • Korea Journal of Hospital Management
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    • v.22 no.1
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    • pp.40-50
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    • 2017
  • The purpose of this study is to develop the KPIs(Key Performance Indices) needed to improve management and strategy in the dental clinic based on the four perspectives of BSC(Balanced Scorecard). The questionnaire was conducted on 52 dentists approved by Dental Managment Research Committee in Seoul National University as a panel. Using the Delphi technique, the top five KPIs for each point of perspective in BSC were extracted from KPI pools. In the third survey, the top five KPIs of all points were compared with each other through AHP(Analytic Hierarchy Process) method, and priority and overall importance rankings were calculated. The biggest difference in the three level AHP results was the customer perspective took priority to others. In the second survey, the financial perspective, which was number one, was pushed back. The overall significance of KPIs was in the order of customer, internal process, finance, learning and growth perspective, with the exception of medical profits (5th of 20) and new patient growth (10th of 20). We were able to overcome the limitations of the Delphi Technique with the AHP method. In general, the financial perspective in BSC is known to be the most important, but we conclude that the customer perspective is more important through the pairwise comparison survey. In the current dental service market, which is a long-term recession, excessive competition, customer satisfaction and customer relationship management seem to be the first goal to pursue in dental clinic.

The Effect of Online Entrepreneurship Education on the Global Start-up Entrepreneurship (온라인 창업교육이 글로벌 창업 기업가정신에 미치는 영향 연구)

  • Choi, Ju-Choel
    • International Commerce and Information Review
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    • v.17 no.3
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    • pp.59-70
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    • 2015
  • The recent global economic crisis and intensifying competition among Northeast Asian neighbors, China and Japan are changing in the foreign policy coarse of growth uncertainty, the domestic enterprise's growth power is faced serious limitations, Therefore, it's increasing that making new growth engines for the creative economy in order to achieve sustainable growth and continue to lead the Global Trade and human resources development and training needs for social entrepreneurship through the creation usually related to human resources. However, the creation of institutional entrepreneurship support system based on the fusion construct and cultured creativity through entrepreneurship education, such as mental challenges proactively apply the various ordinary area and several temporal spatial constraints can be utilized. There follows are in this study and time to entrepreneurship education without restrictions in place were the impact of the most important elements are enterpreneurship in the online entrepreneurship education and entrepreneurship. As the result of analysis, online learning environment have a positive impact on entrepreneurship. I hope that a global powerhouse through youth entrepreneurship would like to contribute IT power nation.

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Capacity Building Measures of SMEs Employee for Spreading the Creative Economy : For focus on Excavation of Convergence Project (창조경제 확산을 위한 중소기업 임직원의 역량강화방안 : 융합과제발굴을 중심으로)

  • Han, Ji-Won;Park, Ki-Nam;Lim, Heui-Seok
    • Journal of Digital Convergence
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    • v.12 no.6
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    • pp.607-614
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    • 2014
  • The need for integration of knowledge and technology among SMEs has been acknowledged, and lacks ways of convergence in practical education. Therefore contents of convergence in practical education of high quality are needed. In this study, a case-oriented curriculum and contents were developed to enhance employee's skills of SMEs. The curriculum consists of 3 steps. The first step is analysis of trends and current status of convergence of SMEs in the domestic and foreign areas. Thus drawing up measures of standards to analyze a successful case. The second step is collection of materials, and development of models through successful cases of convergence. The third step is the analysis of a curriculum to enhance employees' of SMEs and the development of an education program. This study may lead to strengthening competition of SMEs through knowledge and technology convergence based on developed curriculum.

A semi-supervised interpretable machine learning framework for sensor fault detection

  • Martakis, Panagiotis;Movsessian, Artur;Reuland, Yves;Pai, Sai G.S.;Quqa, Said;Cava, David Garcia;Tcherniak, Dmitri;Chatzi, Eleni
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.251-266
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    • 2022
  • Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

Summative Evaluation of 1993, 1994 Discussion Contest of Scientific Investigation (제 1, 2회 학생 과학 공동탐구 토론대회의 종합적 평가)

  • Kim, Eun-Sook;Yoon, Hye-Gyoung
    • Journal of The Korean Association For Science Education
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    • v.16 no.4
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    • pp.376-388
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    • 1996
  • The first and the second "Discussion Contest of Scientific Investigation" was evaluated in this study. This contest was a part of 'Korean Youth Science Festival' held in 1993 and 1994. The evaluation was based on the data collected from the middle school students of final teams, their teachers, a large number of middle school students and college students who were audience of the final competition. Questionnaires, interviews, reports of final teams, and video tape of final competition were used to collect data. The study focussed on three research questions. The first was about the preparation and the research process of students of final teams. The second was about the format and the proceeding of the Contest. The third was whether participating the Contest was useful experience for the students and the teachers of the final teams. The first area, the preparation and the research process of students, were investigated in three aspects. One was the level of cooperation, participation, support and the role of teachers. The second was the information search and experiment, and the third was the report writing. The students of the final teams from both years, had positive opinion about the cooperation, students' active involvement, and support from family and school. Students considered their teachers to be a guide or a counsellor, showing their level of active participation. On the other hand, the interview of 1993 participants showed that there were times that teachers took strong leading role. Therefore one can conclude that students took active roles most of the time while the room for improvement still exists. To search the information they need during the period of the preparation, student visited various places such as libraries, bookstores, universities, and research institutes. Their search was not limited to reading the books, although the books were primary source of information. Students also learned how to organize the information they found and considered leaning of organizing skill useful and fun. Variety of experiments was an important part of preparation and students had positive opinion about it. Understanding related theory was considered most difficult and important, while designing and building proper equipments was considered difficult but not important. This reflects the students' school experience where the equipments were all set in advance and students were asked to confirm the theories presented in the previous class hours. About the reports recording the research process, students recognize the importance and the necessity of the report but had difficulty in writing it. Their reports showed tendency to list everything they did without clear connection to the problem to be solved. Most of the reports did not record the references and some of them confused report writing with story telling. Therefore most of them need training in writing the reports. It is also desirable to describe the process of student learning when theory or mathematics that are beyond the level of middle school curriculum were used because it is part of their investigation. The second area of evaluation was about the format and the proceeding of the Contest, the problems given to students, and the process of student discussion. The format of the Contests, which consisted of four parts, presentation, refutation, debate and review, received good evaluation from students because it made students think more and gave more difficult time but was meaningful and helped to remember longer time according to students. On the other hand, students said the time given to each part of the contest was too short. The problems given to students were short and open ended to stimulate students' imagination and to offer various possible routes to the solution. This type of problem was very unfamiliar and gave a lot of difficulty to students. Student had positive opinion about the research process they experienced but did not recognize the fact that such a process was possible because of the oneness of the task. The level of the problems was rated as too difficult by teachers and college students but as appropriate by the middle school students in audience and participating students. This suggests that it is possible for student to convert the problems to be challengeable and intellectually satisfactory appropriate for their level of understanding even when the problems were difficult for middle school students. During the process of student discussion, a few problems were observed. Some problems were related to the technics of the discussion, such as inappropriate behavior for the role he/she was taking, mismatching answers to the questions. Some problems were related to thinking. For example, students thinking was off balanced toward deductive reasoning, and reasoning based on experimental data was weak. The last area of evaluation was the effect of the Contest. It was measured through the change of the attitude toward science and science classes, and willingness to attend the next Contest. According to the result of the questionnaire, no meaningful change in attitude was observed. However, through the interview several students were observed to have significant positive change in attitude while no student with negative change was observed. Most of the students participated in Contest said they would participate again or recommend their friend to participate. Most of the teachers agreed that the Contest should continue and they would recommend their colleagues or students to participate. As described above, the "Discussion Contest of Scientific Investigation", which was developed and tried as a new science contest, had positive response from participating students and teachers, and the audience. Two among the list of results especially demonstrated that the goal of the Contest, "active and cooperative science learning experience", was reached. One is the fact that students recognized the experience of cooperation, discussion, information search, variety of experiments to be fun and valuable. The other is the fact that the students recognized the format of the contest consisting of presentation, refutation, discussion and review, required more thinking and was challenging, but was more meaningful. Despite a few problems such as, unfamiliarity with the technics of discussion, weakness in inductive and/or experiment based reasoning, and difficulty in report writing, The Contest demonstrated the possibility of new science learning environment and science contest by offering the chance to challenge open tasks by utilizing student science knowledge and ability to inquire and to discuss rationally and critically with other students.

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A Case Study on Credit Analysis System in P2P: 8Percent, Lendit, Honest Fund (P2P 플랫폼에서의 대출자 신용분석 사례연구: 8퍼센트, 렌딧, 어니스트 펀드)

  • Choi, Su Man;Jun, Dong Hwa;Oh, Kyong Joo
    • Knowledge Management Research
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    • v.21 no.3
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    • pp.229-247
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    • 2020
  • In the remarkable growth of P2P financial platform in the field of knowledge management, only companies with big data and machine learning technologies are surviving in fierce competition. The ability to analyze borrowers' credit is most important, and platform companies are also recognizing this capability as the most important business asset, so they are building a credit evaluation system based on artificial intelligence. Nonetheless, online P2P platform providers that offer related services only act as intermediaries to apply for investors and borrowers, and all the risks associated with the investments are attributable to investors. For investors, the only way to verify the safety of investment products depends on the reputation of P2P companies from newspaper and online website. Time series information such as delinquency rate is not enough to evaluate the early stage of Korean P2P makers' credit analysis capability. This study examines the credit analysis procedure of P2P loan platform using artificial intelligence through the case analysis method for well known the top three companies that are focusing on the credit lending market and the kinds of information data to use. Through this, we will improve the understanding of credit analysis techniques through artificial intelligence, and try to examine limitations of credit analysis methods through artificial intelligence.

A Study on Webtoon Background Image Generation Using CartoonGAN Algorithm (CartoonGAN 알고리즘을 이용한 웹툰(Webtoon) 배경 이미지 생성에 관한 연구)

  • Saekyu Oh;Juyoung Kang
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.173-185
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    • 2022
  • Nowadays, Korean webtoons are leading the global digital comic market. Webtoons are being serviced in various languages around the world, and dramas or movies produced with Webtoons' IP (Intellectual Property Rights) have become a big hit, and more and more webtoons are being visualized. However, with the success of these webtoons, the working environment of webtoon creators is emerging as an important issue. According to the 2021 Cartoon User Survey, webtoon creators spend 10.5 hours a day on creative activities on average. Creators have to draw large amount of pictures every week, and competition among webtoons is getting fiercer, and the amount of paintings that creators have to draw per episode is increasing. Therefore, this study proposes to generate webtoon background images using deep learning algorithms and use them for webtoon production. The main character in webtoon is an area that needs much of the originality of the creator, but the background picture is relatively repetitive and does not require originality, so it can be useful for webtoon production if it can create a background picture similar to the creator's drawing style. Background generation uses CycleGAN, which shows good performance in image-to-image translation, and CartoonGAN, which is specialized in the Cartoon style image generation. This deep learning-based image generation is expected to shorten the working hours of creators in an excessive work environment and contribute to the convergence of webtoons and technologies.

Customer Behavior Prediction of Binary Classification Model Using Unstructured Information and Convolution Neural Network: The Case of Online Storefront (비정형 정보와 CNN 기법을 활용한 이진 분류 모델의 고객 행태 예측: 전자상거래 사례를 중심으로)

  • Kim, Seungsoo;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.221-241
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    • 2018
  • Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.