• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.31-53
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• 2007

This paper presents a model of Task-Ontology for small unit operations(SUO) such as nongovernment organizations Despite the rapid development and extension of NGO in domestic area, most have insufficient structural domain resources in existence and underestimate the importance of information management. To improve the citizen's participation and to activate the conjoint actions among the NGO, which are critical to its social role-playing in global society, the modeling Task-Ontology is ultimately intended to implement the knowledge management system of NGO. In the perspective of ontology competency, not only the analysis of resources in vary, but also in-depth Interviews with the NGO practicing personnels and subject experts, and also the intensive observations of task-processing are required for the knowledge acquisition.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2010.05a
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• pp.248-262
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• 2010

국가의 산업 발전이 성장에 한계에 다다르고 그 성장 수준이 고도화 된 국가일수록, 서비스 산업은 그 중요성이 부각되고 있다. 우리나라 역시 서비스 산업의 국내 GDP의 60%이상을 점유하는 만큼 고도의 서비스 산업국가로 분류될 수 있겠으나, 서비스 산업의 경쟁력이 주요 선진국들과 차이가 나는 것이 사실이며, 부가가치가 높은 핵심 지식서비스 산업 분야에서의 격차는 더 크다. 이에 국내 서비스 산업의 경쟁력 강화가 제시되고 있으며, 그에 일환으로 서비스 사이언스(Service Science)에 대한 논의가 활발히 이루어지고 있다. 본 논문에서는 미래성장동력인 서비스 산업의 급부상과 관련하여 서비스 분야에서도 기존의 제조업과 같은 생산성과 효율성을 증가시키기 위해서 더욱 과학적이고, 체계적인 방법론을 연구해야하는 필요성이 제기되고 있다. 이러한 서비스 혁신의 개념은 서비스의 생산성, 품질, 평가, 지속 가능성, 혁신 등에 대하여 연구하는 서비스 사이언스(Service Science)에 대한 논의로 귀결되고 있다. 본 논문은 서비스 혁신사례로써 기술을 도입하여 기업의 성과를 크게 끌어올린 월마트 사례와 최첨단 기술이 융합 접목된 복합 산업적 공간으로 다양한 경제적 활동이 수반되는 인천국제공항공사를 중심으로 서비스 산업에서의 과학기술의 역할에 대해서 살펴보고, 그에 관련된 개념과 시사점을 제기하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.245-254
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• 2022

Proteins are the basic unit of all life activities, and understanding them is essential for studying life phenomena. Since the emergence of the machine learning methodology using artificial neural networks, many researchers have tried to predict the function of proteins using only protein sequences. Many combinations of deep learning models have been reported to academia, but the methods are different and there is no formal methodology, and they are tailored to different data, so there has never been a direct comparative analysis of which algorithms are more suitable for handling protein data. In this paper, the single model performance of each algorithm was compared and evaluated based on accuracy and speed by applying the same data to CNN, LSTM, and GRU models, which are the most frequently used representative algorithms in the convergence research field of predicting protein functions, and the final evaluation scale is presented as Micro Precision, Recall, and F1-score. The combined models CNN-LSTM and CNN-GRU models also were evaluated in the same way. Through this study, it was confirmed that the performance of LSTM as a single model is good in simple classification problems, overlapping CNN was suitable as a single model in complex classification problems, and the CNN-LSTM was relatively better as a combination model.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.129-138
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• 2017

The aim of this paper is to suggest methodology for local governments when discovering locally customized future promising industries with regard to policies of central government, regional competencies, and industrial promising. Firstly, key industries by region specified in '5-years regional industrial development master plan(2014)' were utilized. Secondly, science and technology competency by region was calculated with analyzing patent data in each key industries. Thirdly, industrial promising was verified by calculating Knowledge Stock and Activity Index based on measuring industry-IPC linkage. Based on the methodology proposed above, case study(case of Busan city) was done. Finally, 7 core industries and 94 candidates of future promising industries were extracted on the basis of 5 digit of KSIC subdivision. The methodology is expected to contribute local governments to establish evidence-based, efficient, and future-oriented local R&D roadmapping.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.352-352
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• 2021

가뭄은 강수량의 부족으로 인한 기상학적 가뭄과 지표수 및 지하수의 부족으로 인한 수문학적 가뭄, 토양의 건조 상태로 인한 농업적 가뭄, 용수 및 전력공급의 제한으로 인한 사회·경제적 가뭄으로 분류될 수 있으며, 일반적으로는 어느 지역의 인간생활 및 사회 경제 활동이나 동식물 생육에 피해를 가져올 정도로 강수량 부족이 장기화되는 비정상적인 현상으로 정의할 수 있다. 메가가뭄의 선제적인 대비를 위한 메가가뭄의 사전감지를 위해 본 연구에서는 매년 가뭄 발생 및 확산 여부 판단을 통해 메가가뭄 예방/대비 목적의 년 단위 가뭄 전주기 분석을 위한 메가가뭄상태 판단 절차 방법론을 제시하였다. 메가가뭄 상태 판단 절차 방법론은 메가가뭄 확산 유무에 따라 6단계의 절차로 진행된다. 1단계로 전년도의 가뭄상태(Carry over의 유무)와 가뭄피해 실적자료(통합가뭄위험도 활용 )를 분석하여 확산여부를 판단하며, 2단계로 당해연도에 가뭄이 발생할 것인지를 장기예보와 더불어 MODIS 위성자료를 이용한 평년대비 토양건조상태로 감지한다. 3단계로 1개월 및 10일 예보자료를 이용해 기상학적 가뭄의 발생 여부를 가뭄지수로 판단하고, 4단계로 기상학적 가뭄 하에서 농업 및 수문학적 가뭄의 진행여부를 저수율, 지하수위, 현장대응 정보의 신속한 수집을 통해 확산여부를 판단한다. 5단계는 가뭄 관련 인터넷 뉴스데이터기반의 농작물 피해, 식수제한, 녹조발생 등의 피해상황을 통해 가뭄 피해발생지역을 도출하여 확산여부를 판단하며, 6단계는 기상, 농업, 수문, 사회 경제적 가뭄을 평가함과 더불어 다음년도 가뭄확산에 대비하는 순으로 메가가뭄 상태 판단 절차 방법론이 진행된다.

• 한국노년학
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• v.38 no.3
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• pp.725-744
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• 2018

The purpose of this study is to review selected research articles on Social Welfare in Journal of the Korean Gerontological Society from 2008 to 2017 during 10 years periods, and suggest directions and implications for future research in the field of Gerontological Social Welfare. A total of 273 research articles were selected out of all published 655 articles in Journal of the Korean Gerontological Society in last 10 years. And relevant review articles were selected on the basis of cross checking among authors who majored in social welfare. Selected articles were analyzed for ecological system perspective, research subjects, and research methods. The major findings of this study were as follows. First, ecological system were classified into three categories: 1) macro system(52 articles); 2) mezzo system(120 articles); 3) micro system(101 articles). Second, the research subjects were classified into five categories: 1) social problem of the elderly(151 articles); 2) laws and policies(38 articles); 3) social welfare service for the elderly(28 articles); 4) day service and residential service(39 articles), 5) social participation for the elderly(31 articles). Third, the research methods were classified into 5 categories: 1) qualitative research(213 articles); 2) qualitative research(39 articles); 3) literature review(14 articles); 4) meta research(4 articles); 5) mixed research(3 articles). Finally, there are some important research directions and implications in the field of social welfare for the elderly. First, there should be more balance researches related to the ecological system perspectives in the field of social welfare for the elderly. Second, there should be more systematic researches to analyze critical problems and social issues related to the aging and senior citizens, and developing better interventions and social welfare policies for the elderly. Third, there should be more researches related to evidence based approaches, and utilizing various research methods to examine social problems and major issues for the elderly persons.

• Management & Information Systems Review
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• v.28 no.3
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• pp.117-140
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• 2009

The purpose of this study is to investigate the effects of corporate mecenat activities, ultimately making more firmly established the theory of mecenat activities from the perspective of marketing. For the purpose, this researcher examined the motives of such activities and analyzed the current state and problems of those activities in Korea. In this study, the motives of corporate mecenat activities are largely classified into the improvement of corporate image, which is identified from the view of cultural investment, and direct corporate profits like tax favor, from the view of marketing. Regarding the effects of corporate mecenat activities, P. Kotler and J. Scheff suggested that in future, corporate supports to art would be the most remarkable part of marketing. In association, the Australian Foundation for Culture & Humanities and Arthur Andersen described the effects of corporate mecenat activities in form of cultural investment largely in terms of business, market and employees. In a similar vein, the Korea Business Council for the Arts classifies the effects of corporate mecenat activities largely into three, corporate legitimacy, market advantage and benefit to employees. In relation to corporate mecenat activities, now, the theory of mecenat which is established from the perspective of marketing is considered more persuasive than that which is provided from the perspective of philanthropy. For more corporate efficiency and effectiveness, in conclusion, it's needed to orient the theory of mecenat from the perspective of marketing.

• Knowledge Management Research
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• v.24 no.2
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• pp.137-159
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• 2023

This study focuses on consumers' perceptions of virtual influencers, which many companies recently used for marketing. This study uses the Q methodology to derive what kind of perception consumers have about virtual influencers who work with various appearances, background stories, and worldviews as components. In addition, we want to see how the expected value of virtual influencers differs by age group. To this end, 34 statements were produced through preliminary interviews and literature reviews. This study showed that some consumers preferred appearances similar to humans, despite recognizing that virtual influencers are fictional characters. Some other consumers preferred to feel like a fictional character by maintaining virtuality, confirming that there are both opposite consumers. In addition, consumers expect virtual influencers to have consistency and expertise in the content field covered, and some consumers do not prefer to show an overly commercial appearance. This study will likely provide implications for companies that want to utilize virtual influencers in considering which ones to use for target customers in marketing activities.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.141-166
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• 2018

Information technology improves the efficiency of humanities research. In humanities research, information technology can be used to analyze a given topic or document automatically, facilitate connections to other ideas, and increase our understanding of intellectual history. We suggest a method to identify and automatically analyze the relationships between arguments contained in unstructured data collected from humanities writings such as books, papers, and articles. Our method, which is called history mining, reveals influential relationships between arguments and the philosophers who present them. We utilize several classification algorithms, including a deep learning method. To verify the performance of the methodology proposed in this paper, empiricists and rationalism - related philosophers were collected from among the philosophical specimens and collected related writings or articles accessible on the internet. The performance of the classification algorithm was measured by Recall, Precision, F-Score and Elapsed Time. DNN, Random Forest, and Ensemble showed better performance than other algorithms. Using the selected classification algorithm, we classified rationalism or empiricism into the writings of specific philosophers, and generated the history map considering the philosopher's year of activity.

• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.219-228
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• 2014

The purpose of this study was to determine the trends of research on the effects of psychosocial intervention related to children with epilepsy. 454 articles were retrieved from databases (Ovid-MEDLINE, EMBASE, PubMed, CINAHL, The Cochrane library, KMbase, and Koreamed), and 7 articles met our criterias. Interventions were classified into four categories: education; counseling; cognitive-behavioral therapy; and physical activity. The target outcomes of the interventions were quite diverse. Each intervention showed some benefits for epilepsy-related health outcomes, but each study had methodological weaknesses, including incomplete information, poorly defined or validated outcome measures, small sample sizes, and design limitations.