• Journal of the HCI Society of Korea
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• v.13 no.2
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• pp.31-44
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• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.135-141
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• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.

• Journal of The Korean Association For Science Education
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• v.38 no.4
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• pp.587-598
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• 2018

In this study, we investigated the characteristics of pre-service science teachers' curriculum design for lessons using self-generated analogy. Three pre-service science teachers at a college of education in Seoul participated in this study. After a workshop on lessons using self-generated analogy, they planned and demonstrated lessons. All of the teaching-learning materials were collected, and their lessons were observed and videotaped. Semi-structured interviews were also conducted before and after their lessons. The characteristics of lessons using self-generated analogy were analyzed in the perspectives of PCK. The analyses of the results revealed that they used various strategies to promote students' generating analogies. They lacked understanding of the stages of the lessons and the role of teachers. Although all of them considered assessment, they used limited assessment methods and assessment dimensions. Some actively considered students' misconceptions, and specifically anticipated analogies that students could generate. They determined topics for lessons considering various aspects such as the level of self-generated analogy and the characteristics of scientific conceptions. On the bases of the results, we suggest some educational implications for pre-service science teacher education.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.51-58
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• 2020

This study redesigned the Korean speaking classes to foreign undergraduate students as flipped learning classes and verified their effect on speaking-related emotional variables. In addition, international students' perceptions of what experiences are needed to improve speaking efficacy in Korean were examined. For this purpose, the 'Creative speaking' subject for freshmen was redesigned to flipped learning class and operated for one semester. To analyze the effect of speech-related emotions, a paired t-test was conducted on 26 foreign students' pre-post scores of speech efficacy and anxiety. Also awareness of experiences needed to improve speech efficacy was surveyed and content analysis was conducted. As the result, the speaking efficacy of students after flipped-learning has been significantly improved. This means that flipped learning classes for the Korean speaking are effective for the positive emotions of foreign students speaking Korean. In addition, international students perceived that Korean speaking efficacy can be improved by practicing speaking in Korean, learning with Korean colleagues. Based on these results, several discussions and suggestions were presented.

• Journal of the Korean School Mathematics Society
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• v.16 no.2
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• pp.383-407
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• 2013

As an alternative of making students active and independent under the passive learning conditions in school math classes, many researchers have paid much attention to problem posing and done a lot of research on it. Above all, Brown and Walter proposed What I f Not strategy as a means of problem posing. In this strategy, during the process of posing problems, the transformation of their attributes is inevitably made, and so after problem posing, the process is finished by explaining the problem. But only the simple transformation of attributes could pose wrong problems. It suggests that it is very important to recognize the relationship which leads to organic connection between attributes in order to pose the right problem. However, many other studies of problem posing haven't focused on this fact. Thus, this study tried to design a model of problem posing to help recognize inherent knowledge in the problem and then pose the right problem by adding an activity of meaning analysis. We concretely showed a model of problem posing emphasizing the analysis of meaning by means of an example, thereby examining the meaning of the model. This study expects students to have the chance to understand the true meaning of problem posing and to be active learners after all.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.139-143
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• 2002

1990 년대 후반부터 다양한 디지털 통신망을 이용하여 멀티미디어 컨텐츠 서비스가 가능하게 되었다. 하지만, 멀티미디어 컨텐츠의 전달 및 이용을 위한 기반 구조들의 독자적 발전 및 다양한 통합적 관리 체계 시스템으로 인해, 멀티미디어 컨텐츠 표현 방식의 호환성 문제, 혼재하는 네트워크 전달 방식과 단말 방식의 호환성 문제 등의 잠재적인 문제점이 발생한다. 이런 문제의 대안으로 현재 존재하는 기술 및 기반 구조들 사이의 연동을 통한 큰 프레임워크인 MPEG-21이 진행 중이다. MPEG-21 의 목표는 표준화 목표를 구체화하는 것부터 진행하여, 최종적으로 “다양한 네트워크 환경과 단말기에 있어서, 투명하고 통합적으로 멀티미디어 자원의 이용을 가능하게 하는 것”이다. 본 논문에서는 현재 표준화 작업이 진행 중인 MPEG-21 을 기반으로 하는 Testbed를 제안한다. Testbed는 server, client, DIA(Digital Item Adaptation) 의 세 모듈로 구성된다. Server 의 역할은 멀티미디어 컨텐츠를 Digital Item(DI)으로 생성하고, client 가 DI를 요구할 경우 DIA 모듈을 통해서 변환된 DI를 client 에게 제공한다. DIA 모듈은 server 에서 동작되며 client로부터 요청된 DI를 분석하고 client로부터 전송된 환경 정보를 이용하여 client 환경에 적합하게 변환된 (adapted) DI를 생성하는 것이 주 기능이다. Client 는 server 에 저장되어 있는 DI를 선택하고 user preference, terminal capability 등의 필요한 정보를 server로 전송한다. Testbed 에서는 스포츠 경기의 동영상, 정지 영상, 경기 내용 역사를 기록한 파일 등의 DI를 이용한다. 표현 언어는 XML이며, HTTP 기반의 Web 환경에서 구동되도록 설계된다.스템 사이에 의미 있는 데이터 전송, 지식 획득을 위해 정보 기술 분야에서 활용해야 할 영역으로 XML Web Services, Multi-agent Systems, 전문가 컴뮤니티를 위한 그룹웨어 연구 개발에 관해 사례 중심으로 발표한다.다 신선한 공기를 넣어 주었을 때는 배의 발달이 많이 늦어져 배양 3주째에 다른 처리보다 배의 수가 훨씬 적었다. 체세포배가 발달하는 동안에는 산소를 많이 요구하지 않으나 성숙하는 동안에는 산소를 많이 요구하는 것으로 생각된다.적인 것으로 나타났다. 다만, 곡선형은 물론 직선형에서도 열교환 튜브의 배치밀도, 튜브 길이 및 두께 등의 변화에 따른 최적화 연구가 수반되어야 할 것으로 판단된다.에서 제공된 API는 객체기반 제작/편집 도구에 응용되어 다양한 멀티미디어 컨텐츠 제작에 사용되었다.x factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.0$\mu$M이 적당하며, 초기배발달을 유기할 때의 효과적인 cysteamine의 농도는 25~50$\mu$M인 것으로 판단된다.N)A(N)/N을 제시하였다(A(N)=N에 대한 A값). 위의 실험식을 사용하여 헝가리산 Zempleni 시료(15%$S_{XRD}$)의 기본입자분포로부터 %$S_{XRD}$를 계산한 결과, 16%$S_{XRD}$의 결과값을 얻을 수 있었다. 따라서, 본 연구에서 도출한 관계식들이 유효함을 확인할 수 있었다.계식들이 유효함을 확인할 수 있었다.할 때 약간의 증가

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.38-49
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• 2018

The nursing education with evidence-based practice(EBP) should set a differentiated education strategy according to the level of the learner, so that the students experience it step by step and it leads them to be skilled. The purpose of this study was to integrate and operate the EBP in the fundamental nursing classes of the second grade students and to verify the effectiveness on improvement of EBP basic competency of them. A non-equivalent control group pretest-posttest design was used. The subjects were 108 students in the second year of nursing at the two universities. The experimental group participated in the class for 8 weeks and 24 hours during the 15-weeks, second semester 2016 and the control group participated in general fundamental nursing class. Data were collected proactivity in problem solving, future use of EBP, and critical thinking disposition instrument and analyzed using SPSS/WIN 23.0 program with Chi-square test, independent t-test. The experimental group had a significant increase in proactivity in problem solving and future use of EBP compared to the control group. However, there was no significant difference in critical thinking disposition between the two groups. Findings indicate that the fundamental nursing class used EBP was an effective lesson to improve proactivity in problem solving and future use of EBP, which is the EBP basic competency for the lower grader. Long-term efforts are needed to improve the EBP competence and critical thinking of nursing students by curriculum appropriate to grade-based goals of EBP.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.970-976
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• 2007

In this study, Polynomial Network Pattern Classifier(PNC) based on Fuzzy Inference Mechanism is designed and its parameters such as learning rate, momentum coefficient and fuzzification coefficient are optimized by means of Particle Swarm Optimization. The proposed PNC employes a partition function created by Fuzzy C-means(FCM) clustering as an activation function in hidden layer and polynomials weights between hidden layer and output layer. Using polynomials weights can help to improve the characteristic of the linear classification of basic neural networks classifier. In the viewpoint of linguistic analysis, the proposed classifier is expressed as a collection of "If-then" fuzzy rules. Namely, architecture of networks is constructed by three functional modules that are condition part, conclusion part and inference part. The condition part relates to the partition function of input space using FCM clustering. In the conclusion part, a polynomial function caries out the presentation of a partitioned local space. Lastly, the output of networks is gotten by fuzzy inference in the inference part. The proposed PNC generates a nonlinear discernment function in the output space and has the better performance of pattern classification as a classifier, because of the characteristic of polynomial based fuzzy inference of PNC.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.11-20
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• 2020

As the manufacturing environment becomes more complex, traditional simulation models alone are having a lot of difficulties in reflecting real-time manufacturing situations. Although the Digital Twin concept is actively discussed as an alternative to overcome theses issues, many studies are being carried out only in the product design phase. This research presents a Digital Twin-based manufacturing environment framework for applying the Digital Twin concept to the manufacturing process. Twin model that is operated in virtual space, physical system and databases describing the actual manufacturing environment, are proposed as detailed components that make up the framework. To check the applicability of proposed framework, a simple Digital Twin-based manufacturing system was simulated in a conveyor system using Arena software and Excel VBA. Experiment results have shown that the twin model is transmitted real time data from the physical system via DB and were operating in the same time unit. The Excel VBA fitted parameters defined by cycle time based on historical data that real-time and training data are being accumulated together. This study proposes operating method of digital twin model through the simple experiment examples. The results lead to the applicability of Digital twin model.