• Title/Summary/Keyword: use case diagram

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Model-Based Design of Operational Management System for Integrated Wireless Communication Network of Korean Railway Systems (철도 통합무선망 운영관리 시스템의 모델기반 설계에 관한 연구)

  • Kim, Changwon;Kim, Kyung-Hee;Lee, Young-Hoon;Lee, Jae-Chon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.5
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    • pp.3071-3080
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    • 2015
  • The increased demand on the transport of both passengers and goods through rail systems implies higher traffic intensity and congestion on the railways, resulting in greater likelihood of accidents and also degraded passenger services. To cope with the issues, development of an integrated communication network for rails has attracted great deal of attention lately. GSM-R is such an example developed in Europe, which seems to have restrictions in providing various communication services due to network speed limit. For the reason, an LTE-based approach is under study in Korea. After the network development, operation management of the network is necessary. Design of operation management systems has been studied little and thus is the objective of this paper. To do so, a conceptual design has been carried out based on model-based approach. Specifically, a context model has first been created using the use case diagram. Then, SysML models of operational scenarios were developed for the management system. The SysML models have alternatively been expressed as EFFBD models to simulate and verify them. Consequently, the result of the conceptual system design for the operation management of the integrated wireless network is expected to be used as a basis for the detailed design later.

Occupational Therapy for Community Mobility in Stroke Patients : Systematic review (뇌졸중 환자의 지역사회이동을 위한 작업치료 중재: 체계적 고찰)

  • Jo, Eun-Ju;Kam, Kyung-Yoon;Chang, Moon-Young
    • The Journal of Korean society of community based occupational therapy
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    • v.8 no.3
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    • pp.77-89
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    • 2018
  • Objective : The purpose of this study was to analyze occupational therapy intervention on the community mobility for stroke patients, and to provide evidence of intervention in the clinical fields. Methods : A systematic review was executed according to the PRISMA checklist. The accessed database was PubMed, EMBASE, Cochrane Library (CENTRAL), ProQuest Dissertations & thesis (PQDT), RISS, and KoreaMed. We included the articles published from 2005 to September 2018. RoBANS checklist was used to evaluate the quality of the articles. Included articles, totally eight, were categorized according to the type of intervention. Results : The study design of the literature was varied from two-group randomized trial, quasi-experimental study, case-control trial, one group pre-post comparison study, and cross-sectional study. In the evidence level, 6 articles were included in level II (75%). The percentage of low risk of bias in each article ranged from 52.5%~87.5%. Four studies (50%) provided intervention based on virtual reality or virtual environment. The three (37.5%) provided intervention based on the protocol, and the other (12.5%) did wheelchair training. All studies reported significant effects of the intervention. Conclusion : This systematic review provided evidences to use proper intervention in the clinical fields. Various type of studies should be conducted to prove the effect of occupational therapy intervention for community mobility.

Recommending Core and Connecting Keywords of Research Area Using Social Network and Data Mining Techniques (소셜 네트워크와 데이터 마이닝 기법을 활용한 학문 분야 중심 및 융합 키워드 추천 서비스)

  • Cho, In-Dong;Kim, Nam-Gyu
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.127-138
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    • 2011
  • The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

Knowledge graph-based knowledge map for efficient expression and inference of associated knowledge (연관지식의 효율적인 표현 및 추론이 가능한 지식그래프 기반 지식지도)

  • Yoo, Keedong
    • Journal of Intelligence and Information Systems
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    • v.27 no.4
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    • pp.49-71
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    • 2021
  • Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.