• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 1부
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• pp.281-286
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• 2006

본 논문에서는 홈 환경에서의 사용자의 컨텍스트에 따라 지능적으로 반응하는 미디어 콘텐츠인 vrFlora 을 소개한다. 이는 사용자의 정적인 프로파일 및 간단한 조작 정보 등을 이용하여 사용자의 명시적인 컨텍스트를 인지한다. 그리고 인지된 컨텍스트에 따라 vrFlora 의 자체적인 동기, 즉 감정과 욕구을 자율적으로 변화시키며 이에 따라 자발적인 반응을 표현한다. 더 나아가 사용자에 따라 동기의 변화 정도를 차별화 함으로써, 사용자에 따른 개인화된 반응을 나타낸다. 제안한 시스템의 유용성을 평가하기 위하여 스마트홈 환경을 위한 테스트 베드인 ubiHome 에 vrFlora 를 구현하였다. 그리고 사용자로 하여금 이를 자연스럽게 경험해 볼 수 있도록 하였다. 이를 통해 미래형 홈 환경에서의 지능형 미디어 콘텐츠에 대한 응용 가능성을 제시한다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2006년도 춘계 종합학술대회 논문집
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• pp.367-369
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• 2006

본 논문에서는 캐릭터 에이전트를 활용하여 학습콘텐츠를 개발할 시 적용할 수 있는 입출력 모달리티의 협력방식을 제안하고자 한다. 시각적 효과, 개인화된 스토리 전개, 상호 작용성이라는 세 가지 요소를 유기적으로 결합하여 3D의 화면 구성 및 캐릭터의 독특한 동작언어를 개발함으로써 학습자의 학습동기를 유발하고, 집중도를 향상시킬 수 있다. 이러한 캐릭터 에이전트 환경에서 입출력간의 동기화와 협력방식을 설정은 학습의 효율성과 전체적인 시스템의 성능을 결정하는 중요한 요소가 된다. 마이크로소프트 에이전트 프레임웍을 기반으로 하여 이러한 입출력방식을 제어하는 접근법을 제시하고자 한다.

• 한국컴퓨터정보학회논문지
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• 제21권3호
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• pp.73-81
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• 2016

With the increasing popularity of social network services (SNSs), there have been many attempts to analyze the users of SNSs. By doing so, the characteristics and preferences of the users can be understood, which can help companies provide personalized information and services that they need or are relevant for them. This study aimed to analyze the usage behavior of Korean Twitter users from various perspectives to deepen the understanding of it. For this research goal, an online survey was conducted for the users of Twitter and the data about their actual usage were collected using the open API of Twitter. Factor analysis of the data revealed five factors that explain about 69.3% of the usage variables. It was also investigated how the factors are related to gender, age, and brand preferences. The results showed that the usage behavior of Twitter is largely affected by age (p<0.001), and also by gender through an interaction effect (p<0.05). Also, the factors showed significant statistical correlations with the brand preferences of the users.

• International Journal of Internet, Broadcasting and Communication
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• 제4권2호
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• pp.12-16
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• 2012

This paper presents a learning framework that fits the digital age - an e-Friendly PLE. The learning framework is based on the theory of connectivism which asserts that knowledge and the learning of knowledge is distributive and is not located in any given place but rather consists of the network of connections formed from experiences and interactions with a knowing community, thus, the newly empowered learner is thinking and interacting in new ways. The framework's approach to learning is based on conversation and interaction, on sharing, creation and participation, on learning not as a separate activity, but rather as embedded in meaningful activities such as games or workflows. It sees learning as an active, personal inquiry, interpretation, and construction of meaning from prior knowledge and experience with one's actual environment.

• Biomolecules & Therapeutics
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• 제26권1호
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• pp.69-80
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• 2018

Cancer cells reprogram cellular metabolism to support the malignant features of tumors, such as rapid growth and proliferation. The cancer promoting effects of metabolic reprogramming are found in many aspects: generating additional energy, providing more anabolic molecules for biosynthesis, and rebalancing cellular redox states in cancer cells. Metabolic pathways are considered the pipelines to supply metabolic cofactors of epigenetic modifiers. In this regard, cancer metabolism, whereby cellular metabolite levels are greatly altered compared to normal levels, is closely associated with cancer epigenetics, which is implicated in many stages of tumorigenesis. In this review, we provide an overview of cancer metabolism and its involvement in epigenetic modifications and suggest that the metabolic adaptation leading to epigenetic changes in cancer cells is an important non-genetic factor for tumor progression, which cooperates with genetic causes. Understanding the interaction of metabolic reprogramming with epigenetics in cancers may help to develop novel or highly improved therapeutic strategies that target cancer metabolism.

• 한국멀티미디어학회논문지
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• 제17권11호
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• pp.1374-1381
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• 2014

Digital technology With the popularization of computers and IT technology development is causing a dramatic change across the human life. Increase of profit in fashion industry has a significant impact on the overall industry. It has been studied to develop consumer oriented higher value-added fashion products of including clothes using digital technology abroad. In this paper, we propose a system that when user stand in front of display, user can show body captured depth camera look the coordination of a variety of costume and fashion concept through a magic mirror. Using the system, we will satisfy the convenience of user and be used as a way appropriate to clothing shopping in the shortest time. The system will develop personalized fashion content industry enhanced interaction.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2006년도 추계학술대회 발표논문집
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• pp.120-123
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• 2006

The provision of personalized user interfaces for mobile devices is expected to be used for different devices with a wide variety of capabilities and interaction modalities. In this paper, we implemented a multimodal context-aware middleware incorporating XML-based languages such as XHTML, VoiceXML. SCXML uses parallel states to invoke both XHTML and VoiceXML contents as well as to gather composite multimodal inputs or synchronize inter-modalities through man-machine I/Os. We developed home networking service named "HomeN" based on our middleware framework. It demonstrates that users could maintain multimodal scenarios in a clear, concise and consistent manner under various user's interactions.

• 대한음성학회지:말소리
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• 제60호
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• pp.125-144
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• 2006

W3C announced a standard software architecture for multimodal context-aware middleware that emphasizes modularity and separates structure, contents, and presentation. We implemented a distributed multimodal interface system followed the W3C architecture, based on SCXML. SCXML uses parallel states to invoke both XHTML and VoiceXML contents as well as to gather composite or sequential multimodal inputs through man-machine interactions. We also hire Delivery Context Interface(DCI) module and an external service bundle enabling middleware to support context-awareness services for real world environments. The provision of personalized user interfaces for mobile devices is expected to be used for different devices with a wide variety of capabilities and interaction modalities. We demonstrated the implemented middleware could maintain multimodal scenarios in a clear, concise and consistent manner by some experiments.

• 로봇학회논문지
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• 제18권2호
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• pp.216-224
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• 2023

Guide robots that provide services in public places have recently emerged as a non-face-to-face solution with the spread of COVID-19 and are growing. However, most guide robots provide only the same level of intelligence and the same interaction in different and changing environments. Therefore, its usefulness is limited and customers' interest is quickly lost. To solve this problem, it is necessary to develop social intelligence that can improve the robot's environment and situational awareness performance, and to continuously maintain customer interest by providing personalized and situational services. In this study, we developed guide robot services based on social HRI components that provides multi-modal context-aware. We evaluated service usefulness by measuring user satisfaction and frequency of use of the service through the survey. We analyzed the service quality attributes to identify the differentiating factors of guide robot based on social HRI components.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 춘계학술발표대회
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• pp.523-525
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• 2020

In recent years, deep learning has been widely used in news recommendation systems. In the previous personalized news recommendation, a large number of CF-based methods, content-based or hybrid methods have been proposed. But most of the works are only modeling the user's interaction history, ignoring the hidden meaning of the user's continuous behaviors. In this paper, we propose to adopt the powerful Transformer model in order to understand the hidden meaning of the user's continuous behaviors in news recommendations. The experimental results prove the superiority of the transformer, and the AUC has been significantly improved as compared to the original model.