• 디지털융복합연구
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• 제11권1호
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• pp.165-172
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• 2013

다양한 운영 체제 및 모바일 장치와 같은 끊임없이 변화하는 모바일 환경으로 인해 웹 사이트 개발 및 갱신과정이 복잡해졌다. HTML5는 다양한 개발 및 이용환경을 고려한 웹 사이트를 개발의 대안이 될 수 있다. 사용자가 다양한 OS 또는 장치 유형을 통해 접근 할 경우에도 HTML5를 사용하여 모바일 웹 사이트는 일관된 내용과 서비스를 제공할 수 있다. 본 논문은 부산에 있는 사립대학의 HTML5 기반 웹 사이트의 기반지도 서비스와 의미론적 자동 다이얼링 양식 서비스를 소개한다. HTML5를 이용한 웹사이트 구축이후 학생 및 직원은 로딩 시간과 콘텐츠 서비스의 속도의 향상에 만족했다. 향후 HTML5의 나머지 기능은 순차적으로 구현될 예정이다.

• 대한산업공학회지
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• 제39권6호
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• pp.577-586
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• 2013

In a shipyard, it is hard to predict block movement due to the uncertainty caused during the long period of shipbuilding operations. For this reason, block movement is rarely scheduled, while main operations such as assembly, outfitting and painting are scheduled properly. Nonetheless, the high operating costs of block movement compel task managers to attempt its management. To resolve this dilemma, this paper proposes a new block movement analysis framework consisting of the following operations: understanding the entire process, log clustering to obtain manageable processes, discovering the process model and detecting exceptional processes. The proposed framework applies fuzzy mining and trace clustering among the process mining technologies to find main process and define process models easily. We also propose additional methodologies including adjustment of the semantic expression level for process instances to obtain an interpretable process model, definition of each cluster's process model, detection of exceptional processes, and others. The effectiveness of the proposed framework was verified in a case study using real-world event logs generated from the Block Process Monitoring System (BPMS).

• 한국가스학회지
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• 제8권2호
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• pp.28-34
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• 2004

Enhanced methodologies for process diagnosis and abnormal situation management have been developed for the last two decades. However, there is no single method that always shows better performance over all kinds of diagnostic problems. In this paper, a framework of message-passing, cooperative, intelligent diagnostic agents is presented for improved on-line fault diagnosis through cooperative problem solving of different expertise. A group of diagnostic agents in charge of different process functional perform local diagnoses in parallel; exchange related information with other diagnostic agents; and cooperatively solve the global diagnostic problem of the whole process plant or business units just like human experts would do. For their better understanding, sharing and exchanging of process knowledge and information, we also suggest a way of remodeling processes and protocols, taking into account semantic abstracts of process information and data. The benefits of the suggested multi-agents-based approach are demonstrated by the implementations for solving the diagnostic problems of various chemical processes.

• Child Health Nursing Research
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• 제27권3호
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• pp.201-210
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• 2021

Purpose: This study analyzed research trends related to childhood and adolescent cancer survivors (CACS) using word co-occurrence network analysis on studies registered in the Korean Citation Index (KCI). Methods: This word co-occurrence network analysis study explored major research trends by constructing a network based on relationships between keywords (semantic morphemes) in the abstracts of published articles. Research articles published in the KCI over the past 10 years were collected using the Biblio Data Collector tool included in the NetMiner Program (version 4), using "cancer survivors", "adolescent", and "child" as the main search terms. After pre-processing, analyses were conducted on centrality (degree and eigenvector), cohesion (community), and topic modeling. Results: For centrality, the top 10 keywords included "treatment", "factor", "intervention", "group", "radiotherapy", "health", "risk", "measurement", "outcome", and "quality of life". In terms of cohesion and topic analysis, three categories were identified as the major research trends: "treatment and complications", "adaptation and support needs", and "management and quality of life". Conclusion: The keywords from the three main categories reflected interdisciplinary identification. Many studies on adaptation and support needs were identified in our analysis of nursing literature. Further research on managing and evaluating the quality of life among CACS must also be conducted.

• 한국컴퓨터정보학회논문지
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• 제24권3호
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• pp.159-166
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• 2019

The collection and manipulation of Internet of Things (IoT) data is increasing at a fast pace and its importance is recognized in every sector of our society. For efficient utilization of IoT data, the vast and varied IoT data needs to be reliable and meaningful. In this paper, we propose an IoT framework to realize this need. The IoT framework is based on a four layer IoT architecture onto which context aware computing technology is applied. If the collected IoT data is unreliable it cannot be used for its intended purpose and the whole service using the data must be abandoned. In this paper, we include techniques to remove uncertainty in the early stage of IoT data capture and collection resulting in reliable data. Since the data coming out of the various IoT devices have different formats, it is important to convert them into a standard format before further processing, We propose the RDF format to be the standard format for all IoT data. In addition, it is not feasible to process all captured Iot data from the sensor devices. In order to decide which data to process and understand, we propose to use contexts and reasoning based on these contexts. For reasoning, we propose to use standard AI and statistical techniques. We also propose an experiment environment that can be used to develop an IoT application to realize the IoT framework.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2162-2179
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• 2019

The performance of text classification is highly related to the feature selection methods. Usually, two tasks are performed when a feature selection method is applied to construct a feature set; 1) assign score to each feature and 2) select the top-N features. The selection of top-N features in the existing filter-based feature selection methods is biased by their discriminative power and the empirical process which is followed to determine the value of N. In order to improve the text classification performance by presenting a more illustrative feature set, we present an approach via a potent representation learning technique, namely DBN (Deep Belief Network). This algorithm learns via the semantic illustration of documents and uses feature vectors for their formulation. The nodes, iteration, and a number of hidden layers are the main parameters of DBN, which can tune to improve the classifier's performance. The results of experiments indicate the effectiveness of the proposed method to increase the classification performance and aid developers to make effective decisions in certain domains.

• 디지털융복합연구
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• 제17권2호
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• pp.303-312
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• 2019

본 연구의 목적은 동료자살 이후 소방공무원이 경험하는 외상 후 성장의 의미체계와 과정을 기술하기 위함이다. 이를 위하여 상징적 상호작용주의에 바탕을 둔 근거이론 방법을 적용하여 분석하였다. 연구 참여자는 동료의 자살사망을 경험한 소방공무원 7명이며, 자료 수집은 2015년 10월 1일부터 11월 30일까지 심층인터뷰를 통해 이루어졌다. 연구 결과 동료자살 이후 소방공무원의 외상 후 성장 경험은 '조금씩 단단해져 감'이 핵심범주로 분석되었고 4개의 범주와 9개의 하위 범주가 도출되었다. 본 연구의 결과를 토대로 다양한 외상사건에 노출되는 소방공무원의 외상 후 성장을 도모하기 위한 융복합 중재 프로그램 개발이 필요하다.

• 융합보안논문지
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• 제19권1호
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• pp.31-40
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• 2019

정보보호(Information Security)는 최근 사이버공간의 출현과 확장으로 인해 그 중요성이 점차 증가하고 있다. 1998년 미국 국방부 정보작전 교리에서 유래된 '정보보증(Information Assurance)'은 기존의 정보보호 개념에 대응과 복구를 포함한 광의의 적극적 보호, 정보체계 전 수명주기에서 보안관리, 위험분석 과정에서의 신뢰성 등을 추가한 개념으로서 현재 널리 사용중이다. 그러나 국내에서는 정보보증 개념을 잘못 이해하거나 정보보호와 혼용하여 사용하는 경우가 종종 발생하고 있다. 본 논문에서는 정보보증 개념의 명확한 이해를 위해 정보보증 관련 기존 문헌들을 고찰하여 정보보증 개념을 정의하고자 하였다. 본 논문에서 제안한 정보보증 용어 정의의 주요 표현들에 대한 구문 분석을 수행함으로써, 용어 정의의 타당성을 제시하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권4호
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• pp.66-71
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• 2021

The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

• 디지털융복합연구
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• 제17권11호
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• pp.517-522
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• 2019

많은 비즈니스에서 챗봇은 사용자의 질문에 가장 즉각적이고 직접적인 피드백으로 제공함으로써 사용자 경험을 높여가고 있으며 그 활용 영역이 커져가고 있다. 본 연구에서는 챗봇의 정의를 비롯해 명령방식, 기능, 플랫폼에 따른 세 가지 유형을 구분되는 요소에 따라 분류해 보았다. 그 과정에서 기능적 구분 요소는 패턴인식, 자연어처리, 시멘틱 웹, 텍스트 마이닝, 상황인식 컴퓨팅의 기능적 부분의 핵심 기술 요소가 챗봇 UX를 위해 필요하지만 현재 단계에서의 한계도 알 수 있었다. 이를 바탕으로 더 나은 사용자 경험을 위한 챗봇의 UX요소를 페이스북, 스카이프, 텔레그램, 구글어이스턴트를 대상으로 분석하였으며 카드와 같은 기본 UI요소와 빠른 응답, 명령, 영구 메뉴의 적용이 사용자 경험요소로 필요함을 알 수 있었다.