• 한국정보교육학회:학술대회논문집
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• 2004.08a
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• pp.20-27
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• 2004

현재의 정보통신기술교육은 정보 활용적인 측면과 다른 교과에 대한 도구적인 성격이 짙다. 정보통신기술교육에 새로운 활력을 불어넣기 위하여 ACM과 IEEE의 공동보고서인 Computing Curricula 2003을 통하여 컴퓨터 교과에 대한 관점을 조명해 볼 필요가 있다. 컴퓨터 과학에 대한 내용학적인 접근을 통하여 교과에 대한 정체성이 확립되는 밑거름이 될 수 있다. 미래 사회의 주역인 학생들의 정보화 마인드 형성을 위하여 정보교육은 내용선정부터 체계적으로 시도되어져야 한다. 여러 분야 중에서도 컴퓨터 구조교육의 내용을 단순화, 정교화시키는 과정을 통해 정보에 쉽게 접근할 수 있고, 정보적인 사고가 가능할 수 있도록 프로토타입(Prototype)을 구성하고자 한다. 기존의 구조교육의 형태와 내용을 분석하여 학습 내용을 선정하여 요소를 추출하는데 그 목적이 있다.

• Spatial Information Research
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• v.22 no.6
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• pp.55-65
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• 2014

By combining the role of current GIS technology and design behaviors from the cognitive perspective, spatial conceptualization can be extended efficiently and creatively for ill-structured problems. This study elaborates the model of a conceptualization-oriented SDSS(Spatial Decision Support System) for a landscape design problem. Current information-oriented GIS technology plays a minor role in planning and design. The three attributes in planning and design problems describe how the deficiencies of current GIS technology can be seen as a failure of the technology. These are summarized: (1) Information Explosion/Information Ignorance (2) Dilemma of Rigor and Relevance (3) Ill-structured Nature of planning and Design. In order to implement the conceptualization idea in the current GIS environment, it will be necessary to shift from traditional, information-oriented GISs to conceptualization-oriented SDSSs. The conceptualization-oriented SDSS model reflects the key elements of six important theories and techniques. The six useful theories and techniques are as follows; (1) Human Information Processing (2) Tool/Theory Interaction (3) The Sciences of the Artificial and Epistemology of Practice (4) Decision Support Systems (DSSs) (5) Human-Computer Interaction (HCI) (6) Creative Thinking. The future conceptualization-oriented SDSS can provide capabilities for planners and designers to figure out some "hidden organizations" in spatial planning and design, and develop new ideas through its conceptualization capability. The facilitation of conceptualization has been demonstrated by presenting three key ideas for the framework of the SDSS model: (1) bubble-oriented design support system (2) prototypes as an extension of semantic memory, and (3) scripts as an extension of episodic memory in a cognitive pschology perspective. The three ideas can provide a direction for the future GIS technology in planning and design.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1293-1301
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• 2017

Recent changes in social structure, such as nuclear family and personalization, are leading to personal and social problems, which may cause various problems due to negative emotional amplification. The absence of a family member who gives a sense of psychological stability in the past can be considered as a representative cause of the emotional difficulties of modern people. This personal and social problem is solved through the empathic interaction of the companion robot communication with users in daily life. In this study, we developed sophisticated empathic interaction design through prototyping of emotional robots. As a result, it was confirmed that the face interaction greatly affects the emotional interaction of the emotional robot and the interaction of the robot improves the emotional sense of the robot. This study has the theoretical and practical significance in that the emotional robot is made more sophisticated interaction and the guideline of the sympathetic interaction design is presented based on the experimental results.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.243-250
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• 2021

In the medical field, applications of plasma are applied sterilize instruments mainly but with the advent of bio-plasma technology, the scope of application is expanding. Recently, In addition, high-density miniaturization with handheld is required for sophisticated procedures when irradiated directly or treated with non-standard conditions. Rosen-type PZT is a device with a structure that generates high voltage plasma by achieving voltage transformation through electro-mechanical coupling using piezoelectric effect.and is used in portable plasma generating devices as an advantage to increase energy density relatively. In this paper, Rosen-type PZT was modeled using equivalent circuits and was carried out and a plasma generating device for medical application was designed and prototype tested. Prototype plasma generating device generates an output voltage of 5.8 kV with 12V input power and is designed to operate at high voltage by applying the half-bridge topology power converter. The results of the study confirmed the availability of various medical devices, such as plasma jets or direct exposure equipment.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.