• Title/Summary/Keyword: 진화엔진

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System Visibility of Universal Middleware Pervasive Memorial Engine (시스템 가시성평가를 위한 유니버설미들웨어기반 Pervasive Memorial Engine 연구)

  • Lee, Hae-Jun;Hwang, Chi-Gon;Yoon, Chang-Pyo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.11
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    • pp.2115-2120
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    • 2017
  • Presently, It is required to change convergence the role of hardware system and software technology that promoted trust of In-Vehicle for integrated complex system visibility evaluation. There is possibility for the period system can invoke unpredictable confusing blank state. The blank state systems have ecosystem characteristics that are supplied, maintained and operated through the complex interactions of technology and culture. Using universal middleware can support the life-cycle model and increase the visibility of complex systems and prepare for confusing situations. In this study, based on universal middleware, data and service dynamic standardized modules were evaluated to support stable system visibility platform. The system visibility module consists of Intelligent Pervasive Cloud module, Memorial Service module and Life Cycler connection module. In addition, the analysis results are supported by various network application service standards through platform independent system and architecture.

시맨틱 웹 기술에 의한 표준 정보 검색 서비스의 진화

  • Jeong, Han-Min;Lee, Mi-Gyeong;Kim, Pyeong;Lee, Seung-U;Seong, Won-Gyeong;Kim, Tae-Wan;Lee, Jong-Seop
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2008.10b
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    • pp.575-582
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    • 2008
  • 본 논문은 시맨틱 웹 기술이 어떻게 국가 표준(KS) 정보 검색 서비스 내 정보들을 연계시키고 사용자 접근성을 향상시키는 데 도움을 줄 수 있는지를 실증적으로 보여준다. 기존 표준 정보 검색 서비스는 용어 검색의 유연성이 부족하여 표준 정보에서 사용된 용어와 사용자 용어 간의 괴리를 해소하지 못했으며 표준, 기관, 인력 등 상호 관련성을 가진 개체 정보들을 개별적으로 서비스하였다. 이러한 상황은 사용자의 표준 정보 검색 서비스 접근성을 떨어뜨리는 요인으로 작용한다. 본 연구에서는 유의어, 관련어를 중심으로 한 표준 용어 사전 구축을 통해 사용자 용어와 표준 정보 내 용어 간의 원활한 매칭을 지원하며, 표준 관련 개체들을 온톨로지와 추론을 통해 연계시키는 방안을 제시한다. 개선된 표준 정보 검색 서비스는 개선된 표준 정보 검색 서비스는 개체 중심적 통합 검색 결과 제공 방식으로 관련 정보들을 단일 웹 페이지 내에서 확인할 수 있도록 해준다. 예를 들어, 특정 KS 표준 검색 결과 페이지에서는 기존에 DB 접근이나 검색 엔진을 통해 바로 획득할 수 없었던 정부 표준들, 기관들의 해당 KS 표준 인용 현황, 해당 KS 표준 전문가들, 부합화를 위해 참조된 국제 표준들, 해당 KS 표준 전문가들, 부합화를 위해 참조된 국제 표준들, 해당 KS 표준 전문가 네트워크, 해당 KS 표준 내 표준 용어 사전 정보 등 다양한 관련 정보들을 조합하여 서비스한다. 본 연구를 위해 모델링된 온톨로지와 시맨틱 웹기반 서비스 프레임워크인 OntoFrame 상에서 추론 작업이 표준 정보 적재 시에 전방 추론 (Forward-chaining) 방식으로 수행되었으며, 표준 온톨로지 질의 언어인 SPARQL (SPARQL Protocol and RDF Query Language)을 이용해 일반 검색 서비스 수준의 속도로 서비스될 수 있었다.

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A Study on Content Marketing for Travel Brand Focus on Youtube Vlog Formed Travel Video - (여행 브랜드를 위한 콘텐츠 마케팅 연구 -여행 영상 형태의 유튜브 Vlog를 중심으로-)

  • Jo, Jang-Hwan;Park, Bo-ram
    • Journal of Digital Convergence
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    • v.17 no.12
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    • pp.445-450
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    • 2019
  • lock in effect This study aims to examine the viewing pattern of travel vlog on video-sharing platform YouTube. Preliminary survey was conducted with in-depth interviews on the usability and sensibility aspects of creating pleasurable interfaces model. As a result, first, viewers obtains general information on travel using travel vlog. Second, there were difficulties from the informational quantity. Third, the contents marketing using travel vlog could have limitation when it comes to the consistency of product's exposure which common mass media advertisement format have. Improvements driven from this study may provide insight in contents marketing strategy to travel-related companies and provide practical help to creators in contents production.

Development of Social Data Collection and Loading Engine-based Reliability analysis System Against Infectious Disease Pandemic (감염병 위기 대응을 위한 소셜 데이터 수집 및 적재 엔진 기반 신뢰도 분석 시스템 개발)

  • Doo Young Jung;Sang-Jun Lee;MIN KYUNG IL;Seogsong Jeong;HyunWook Han
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.103-111
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    • 2022
  • There are many institutions, organizations, and sites related to responding to infectious diseases, but as the pandemic situation such as COVID-19 continues for years, there are many changes in the initial and current aspects, and accordingly, policies and response systems are evolving. As a result, regional gaps arise, and various problems are scattered due to trust, distrust, and implementation of policies. Therefore, in the process of analyzing social data including information transmission, Twitter data, one of the major social media platforms containing inaccurate information from unknown sources, was developed to prevent facts in advance. Based on social data, which is unstructured data, an algorithm that can automatically detect infectious disease threats is developed to create an objective basis for responding to the infectious disease crisis to solidify international competitiveness in related fields.

An Event-Driven Dynamic Monitor for Efficient Service Monitoring (효율적인 서비스 모니터링을 위한 이벤트 주도 동적 모니터)

  • Kum, Deuk-Kyu;Kim, Soo-Dong
    • Journal of KIISE:Software and Applications
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    • v.37 no.12
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    • pp.892-908
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    • 2010
  • Services in SOA are typically perceived as black-box to service consumers, and can be dynamically evolved at runtime, and run on a number of unknown and heterogeneous environments. Because of these characteristics of the services, effective and efficient monitoring of various aspects on services is an essential functionality for autonomous management of service. But the problem with or limitation in conventional or existing approaches is, that they focus on services themselves, ignoring the effects by business processes. Consequently, there is a room for service monitoring which provides more useful information of business level by acquisition of only external monitoring data that depend on specific BPEL engine and middleware. Moreover, there is a strong demand to present effective methods to reduce monitoring overhead which can degrade quality of services. EDA can cope with such limitations in SOA by collecting and analyzing events efficiently. In this paper, we first describe EDA benefits in service monitoring, and classify monitorring target, and present an appropriate monitoring method for each monitoring target. Also to provide the applicability of our approach, an event meta-model is defined, and event processing model and architecture based on the meta-model are proposed. And, with the proposed architecture and method, we implement a prototype of an event-driven dynamic monitoring framework which can collect and process internal and external data at runtime. Finally, we present the result of a case study to demonstrate the effectiveness and applicability of the proposed approach.

Study on Development of Digital Ocean Information Contents for Climate Change and Environmental Education : Focusing on the 3D Simulator Experiencing Sea Level Rise (기후변화 환경교육을 위한 디지털 해양정보 콘텐츠 개발 방안 연구 - 해수면 상승 체험 3D 시뮬레이터를 중심으로 -)

  • Jin-Hwa Doo;Hong-Joo Yoon;Cheol-Young Lee
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.5
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    • pp.953-964
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    • 2023
  • Climate change is undeniably the most urgent challenge that humanity faces today. Despite this, the level of public awareness and understanding of climate change remains insufficient, indicating a need for more proactive education and the development of supportive content. In particular, it is crucial to intensify climate change education during elementary and secondary schooling when values and ethical consciousness begin to form. However, there is a significant lack of age-appropriate, experiential educational content. To address this, our study has developed an innovative 3D simulator, enabling learners to indirectly experience the effects of climate change, specifically sea-level rise. This simulator considers not only sea-level rise caused by climate change but also storm surges, which is a design based on the analysis of long-term wave observation big data. To make the simulator accessible and engaging for students, we utilized the 'Unity' game engine. We further propose using this simulator as a part of a comprehensive educational program on climate change.

Prediction of field failure rate using data mining in the Automotive semiconductor (데이터 마이닝 기법을 이용한 차량용 반도체의 불량률 예측 연구)

  • Yun, Gyungsik;Jung, Hee-Won;Park, Seungbum
    • Journal of Technology Innovation
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    • v.26 no.3
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    • pp.37-68
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    • 2018
  • Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.