• Journal of The Korean Association of Information Education
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• v.17 no.4
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• pp.409-419
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• 2013

The aims of this paper were to review the usable possibility of the educational App Inventor Program in the field of programming education and to develop programming teaching materials that can overcome limitations of the established programming instruction. The study showed that the learners' motivations were strengthened through smart device programs. Containing the elements of STEAM, the teaching materials were developed for the logical and systematic learning that deals with elementary students' real-life situations, and that helps children follow the procedures of software development. By introducing the Waterfall Model to the process of programming, students are able to follow the software developers' thinking process. In addition, beyond the simplistic programming language and simply acquiring related knowledge, the App Inventor programming was designed to enhance students' higher-order thinking skills such as creativity, problem solving ability, collaborative thinking, and so forth.

• Korean Journal of Computational Design and Engineering
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• v.11 no.4
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• pp.289-302
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• 2006

It is becoming a common trend that many designers work on a very complex assembly together in a collaborative environment. In this environment, every designer should be able to see the whole assembly in a full detail or in a rough shape at least. Even though the hardware technology is being improved very rapidly, it is very difficult to display a very complex assembly at a speed to allow smooth interactions for designers. This problem could be solved if a designer could manipulate his portion of the assembly in a full resolution while the remaining portion of the assembly is displayed in a rough resolution. It is also desired that the remaining portion is converted to the full resolution when needed. To realize this environment, the capabilities to simplify the portions of an assembly and to reset to the original resolution should be added to the current CAD systems. Thus operators realizing multi-resolution on B-rep are proposed in this paper. They are: wrap-around, smooth-out, and thinning operator. Through appropriately applying these operators sequentially, an assembly model of any desired resolution can be easily generated. Of course, the assembly can go back to the finer resolution. In this paper, the data structures and the processes to realize these operators are described and a prototype modeling system with these operators is also demonstrated.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.739-748
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• 2014

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1306-1313
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• 1999

본 연구는 인터넷 기반 공유가상공간에서 시스템의 확장성을 유지하기 위하여 이동객체를 대상으로 하는 이벤트 필터링 기법을 제안하고자 한다. 제안된 다중격자 모델 기법은 이동객체의 경로 상에서 대표적인 이벤트를 샘플링하는 방식을 사용한다. 이 방식은 메시지 트래픽의 양을 동적으로 조절하기 위하여 이동객체 간의 관심정도 정보를 수치적으로 변환하여 이벤트 갱신빈도에 반영한다. 대량의 이동객체를 생성하여 제안된 기법을 적용한 성능평가 실험에서 기존의 방식에 비하여 평균 메시지 전송량이 50%이상 감소하는 것으로 확인할 수 있었다. 다중격자 모델은 참여자의 수와 메시지 트래픽 상황에 따라 가상환경의 공유 QoS를 동적으로 조절할 수 있으며, 인터넷 상에서 다수 사용자를 위한 3차원 가상사회 구축 및 온라인 네트워크 게임 개발 등에 활용될 수 있을 것이다.Abstract This paper proposes an event filtering technique that can dynamically control a large amount of event messages produced by moving objects like avatars or autonomous objects in a distributed virtual environment. The proposed multi-level grid model technique uses the method that extracts the representative events from the paths of moving objects. For dynamic control of message traffics, this technique digitizes the DOIs of the avatars and reflects the interest information controlling the frequency of message transmission. For the performance evaluation, a large number of moving objects were created and the model was applied to these avatar groups. In the experiments, more than 50% of messages have been reduced in comparison with the existing AOI-based filtering techniques. The proposed technique can dynamically control the QoS in proportion to the number of users and the amount of messages where a large number of users share a virtual space. This model can be applied to the development of 3D collaborative virtual societies and multi-user online games in the Internet.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.141-151
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• 2023

Traditional ODA to North Korea (NK) has been unsustainable and politically contentious. This study proposes the design of appropriate technology (AT) as an alternative. We identified NK residents' urgent needs and global AT instances, and classified data by Maslow's hierarchy of needs. As electricity and potable water were identified as primary needs, suitable AT cases were selected. Given NK's extreme isolation, collaborative AT practices with local residents are unfeasible. Therefore we propose a new AT adoption model customized to NK, which emphasizes community-level adoption. We proposed a solar charging station for cooperative farms, a re-design of an AT previously utilized in Africa, and tailored it to fit our proposed model. The study's significance lies in its novel AT adoption model for NK's unique social fabric and the proposition of a specific design case, thus transcending previous relevant studies exploring AT's potential for NK.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.43-48
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• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Journal of the Korean Society for Library and Information Science
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• v.47 no.1
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• pp.377-398
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• 2013

The research has provided elementary and junior high school students at Children's Center in Incheon district and analyzed its effective factors in both educational and operational aspects. The educational factors in reading discussion include reading, writing, presenting, listening, and rethinking. In the result, the influential factors are as follows: the respondents' emotional intelligence, the level of reading completion, the level of sympathy with class participants, and the level of advance preference on reading. There are additional factors that have influences on the result, including suitability of topics, capabilities of leaders, selection of books, and combination of basic educational training, like speaking and writing.

• Electronics and Telecommunications Trends
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• v.20 no.1 s.91
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• pp.139-146
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• 2005

폭발적인 정보의 흐름 속에 놓여 있는 지식정보화 시대에서는 필요한 정보를 선택하고 가공하여 새로운지식의 창조, 전달 및 확대 재생산 할 수 있는 능력이 요구되고 있다. 지식정보화 시대가 필요로 하는 창의적 인재 육성을 위한 새로운 교육 형태와 패러다임으로 e-러닝이 유력한 솔루션으로 부각되고 있다.e-러닝은 교수자 중심의 일방향 교육이 아닌 학습자가 시간과 장소에 구애받지 않고 필요한 학습을 하는 양방향 교육 방식이나, 현재까지는 학습 콘텐츠의 단순 반복 학습에 그치고 있어 기존 교실 수업 방식에 비해 학습효율이 떨어지는 점이 이 분야 발전의 장애요소가 되고 있다. 이에 대한 해결책으로 온라인상에서 학습 과제를 여러 명의 학생들이 상호 의존하여 공동으로 해결함으로써 학습 목표를 달성하는 형태의 협력 학습에 대한 연구가 활발히 진행되고 있다. e-러닝 협력학습에는 단순히 학생들을 그룹화하여 함께 학습하도록 하는 것은 교육 효과면 에서 비효율적일 수 있으며, 학생들의 자발적인 참여와 협력을 유도할 수 있는 교수모형을 적용하여야 하며, 개인의 책임감을 근간으로 한 상호 의존적 과제 해결 활동이 이루어져야 한다. 본 고에서는 협력 e-러닝 학습을 위한 연구사례와 기술 동향들에 대해 살펴본다.