• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.97-104
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• 2017

This study explored the potential associations among older adults' online community uses, socialization, and social isolation. Results from the hierarchical regression analysis indicated that the quality and size of personal networks composed of online community members positively influences older adults' socialization and reduces social isolation. However, the frequency of meeting with online community members in offline settings was not significantly associated with socialization. Moreover, the amount of time using online communities indirectly and significantly affected social isolation, mediated by socialization. Results from this study address the positive roles of online community uses in overcoming psychological difficulties among elderly people.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.61-72
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• 2020

Social problems, such as economic instability, aging population, heightened competition, and changes in personal values, might become more serious in the near future. Affective computing has received much attention in the scholarly community as a possible solution to potential social problems. Accordingly, we examined domestic and global knowledge structure, major keywords, current research status, international research collaboration, and network for each major keyword, focusing on keywords related to affective computing. We searched for articles on a specialized academic database (Scopus) using major keywords and carried out bibliometric and network analyses. We found that China and the United States (U.S.) have been active in producing knowledge on affective computing, whereas South Korea lags well behind at around 10%. Major keywords surrounding affective computing include computing, processing, affective analysis, research, user modeling categorizing recognitions, and psychological analysis. In terms of international research collaboration structure, China and the U.S. form the largest cluster, whereas other countries like the United Kingdom, Germany, Switzerland, Spain, and Canada have been strong collaborators as well. Contrastingly, South Korea's research has not been diverse and has not been very successful in producing research outcomes. For the advancement of affective computing research in South Korea, the present study suggests strengthening international collaboration with major countries, including the U.S. and China and diversifying its research partners.

• Journal of Internet Computing and Services
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• v.18 no.2
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• pp.75-85
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• 2017

Open innovation, a new paradigm which utilizes customer ideas for organizational innovation directly, is evaluated as a useful method to innovate the organization itself. In this research, we analyze the case of Starbucks' online community, MyStarbucksIdea.com to examine how collective intelligence is formed out of mass customers in the community and how open innovation is to be implemented successfully. We review various challenges in implementing open innovation and then suggest practical approaches to the challenges, including customer relationship management, utilization of opinion leaders, application of engineering techniques, etc.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.118-120
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• 2006

커뮤니티 컴퓨팅 시스템은 3단계 모델(CCM, CIM-PI, CIM-PS)로 이루어져 있다. 모델은 이 전의 모델을 기반으로 툴의 지원을 받아 코드를 상세화하면서 실제 구현단계에 이르게 된다. 3가지 모델 중 가장 먼저 기술해야 하는 CCM(Community Computing Model)은 커뮤니티 컴퓨팅 시스템에 대한 가장 놓은 수준의 추상화 모델로서, 시스템의 환경과 요구사항을 기술하는 부분이다. 기술된 CCM을 기반으로 생성되는 CIM-PI(Platform Independent Community Implementation Model)에서는 시스템의 구현을 고려하여 컴퓨팅 요소들과 또 이들 간에 생길 수 있는 협업관계를 자세히 기술한다. 이렇게 기술된 CIM-PI를 멀티에이전트 플랫폼 위에서 작동할 수 있도록 CDTK를 이용해 변환해 농은 것이 CIM-PS(Platform Specific Community Implementation Model)이다. 본 논문에서는 커뮤니티 컴퓨팅 시스템 개발을 더욱 쉽고 체계적으로 개발하기 위해 만든 CDTK와 이 개발 툴을 통해 얻을 수 있을 수 있었던 여러 장점들에 대해 소개한다. CDTK를 이용한 적용사례로 유비쿼터스 환경내에서 발생할 수 있는 가상시나리오에 적용하여 CDTK의 실현성과 효율성을 검증해 보았다.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.1-11
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• 2023

Federated learning (FL) is a ground breaking machine learning paradigm that allow smultiple participants to collaboratively train models in a cloud environment, all while maintaining the privacy of their raw data. This approach is in valuable in applications involving sensitive or geographically distributed data. However, one of the challenges in FL is dealing with heterogeneous and non-independent and identically distributed (non-IID) data across participants, which can result in suboptimal model performance compared to traditionalmachine learning methods. To tackle this, we introduce FedGCD, a novel FL algorithm that employs Graph Neural Network (GNN)-based community detection to enhance model convergence in federated settings. In our experiments, FedGCD consistently outperformed existing FL algorithms in various scenarios: for instance, in a non-IID environment, it achieved an accuracy of 0.9113, a precision of 0.8798,and an F1-Score of 0.8972. In a semi-IID setting, it demonstrated the highest accuracy at 0.9315 and an impressive F1-Score of 0.9312. We also introduce a new metric, nonIIDness, to quantitatively measure the degree of data heterogeneity. Our results indicate that FedGCD not only addresses the challenges of data heterogeneity and non-IIDness but also sets new benchmarks for FL algorithms. The community detection approach adopted in FedGCD has broader implications, suggesting that it could be adapted for other distributed machine learning scenarios, thereby improving model performance and convergence across a range of applications.

• Journal of Information Science Theory and Practice
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• v.12 no.1
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• pp.1-20
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• 2024

This research aims to study and confirm enabling factors affecting the knowledge transfer and business process of community enterprise groups in Pattani province, Thailand. Key informants were community enterprise entrepreneurs; 30 people were selected purposively with criteria. This study used a mixed-methods approach and conducted semi-structured interviews to collect data. Qualitative data were analyzed using content analysis and classification, while quantitative data were analyzed using descriptive statistics with frequency, percentage, mean, and standard deviation. Moreover, inferential statistics chi-square value, Phi Cramer's V, and multiple regression analysis with the R program for statistical computing were employed to analyze the relationship between the variables, test the research hypothesis, and create forecasting equations. The research results revealed that the overview of enabling factors had a very high relationship (Cramer's V=0.965). Regarding community enterprise, it was found that enabling factors related to the knowledge transfer and business process consisted of four factors: regulations and administrative guidelines, business plan, reinforcement, and brainstorming. Reinforcement was the factor with the highest degree of correlation (Cramer's V=0.873) and predictor of influence on the knowledge transfer and business process (R₂=0.670, p<0.05). This study's findings can lead to the developing of guidelines for promoting community enterprises properly and timely. These guidelines are expected to be used to develop knowledge about business models for community enterprises, which will help to improve their competency and competitiveness.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.75-86
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• 2015

Internet of Thing (IoT) computing is an environment where various devices with sensors and actuators are connect, and interact together to acquire contexts and provide useful services. With the advances of IoT technologies, its usability becomes an in important issue. However, there exist various types of faults in IoT computing which are not conventionally addressed in software research community. Providing reliable IoT services is challenging. In this paper, we present a hierarchy of IoT faults and analyze causes and symptoms of the faults. Based on the analysis, we define effective methods for managing IoT faults. We believe that our proposed framework for managing IoT faults can be utilized in reducing the development cost of IoT applications and enhancing the quality of the applications.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.50-58
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• 2006

The mutual exclusion (MX) paradigm can be used as a building block in many practical problems such as group communication, atomic commitment and replicated data management where the exclusive use of an object might be useful. The problem has been widely studied in the research community since one reason for this wide interest is that many distributed protocols need a mutual exclusion protocol. However, despite its usefulness, to our knowledge there is no work that has been devoted to this problem in a mobile computing environment. In this paper, we describe a solution to the mutual exclusion problem from mobile computing systems. This solution is based on the token-based mutual exclusion algorithm.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.97-108
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• 2001

Frauds detection is a difficult problem, requiring huge computer resources and complicated search activities Researchers have struggled with the problem. Even though a fee research approaches have claimed that their solution is much better than others, research community has not found 'the best solution'well fitting every fraud. Because of the evolving nature of the frauds. a novel and self-adapting method should be devised. In this research a new approach is suggested to solving frauds in insurance claims credit card transaction. Based on evolutionary computing approach, the method is itself self-adjusting and evolving enough to generate a new self of decision-makin rules. We believe that this new approach will provide a promising alternative to conventional ones, in terms of computation performance and classification accuracy.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.163-170
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• 2005

컴퓨팅 환경이 점점 분산되고 협업의 필요성이 점점 증대되고 시스템간에 상호작용(interaction)이 동적이고 복잡해지면서 기존의 협업 시스템 패러다임을 벗어난 커뮤니티 컴퓨팅을 구성하는 요소를 정의하고 커뮤니티 모델의 에이전트들의 상호작용 유형을 프로토콜의 형식으로 모델링 하는 방법과 지정된 프로토콜들을 실행하기 위한 방법으로소 에이전트 플랜(plan)을 이용하는 방안을 제안한다. 커뮤니티를 구성하는 요소들은 역할(role), 정책(policy), 구성원(member), 프로토콜(protocol)등이며 각각의 요소는 BDI 구조를 가지는 에이전트와 플랜, 목적(goal), 사실(fact)등의 결합으로 표현이 가능하다. 에이전트들은 프로토콜에 나타나는 유형을 서술한 플랜을 통해서 상호작용을 하게 된다. 본 논문에서는 이러한 프로토콜을 실행 가능한 플랜으로 변환하기 위한 4가지 유형을 파악하여 각각의 유형을 플랜으로 변환하는 방법을 제안한다. 제안된 방법은 시뮬레이션을 통하여 완전성과 유효성을 보인다.