• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.517-519
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• 2022

In 5G network environment, proactive mobility management is essential as 5G mobile networks provide new services with ultra-low latency through dense deployment of small cells. The importance of a system that actively controls device handover is emerging and it is essential to predict mobile trajectory during handover. Sequence-to-sequence model is a kind of deep learning model where it converts sequences from one domain to sequences in another domain, and mainly used in natural language processing. In this paper, we developed a system for predicting mobile trajectory in a wireless network environment using sequence-to-sequence model. Handover speed can be increased by utilize our sequence-to-sequence model in actual mobile network environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.43-44
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• 2020

최근 케이팝 문화의 확산으로 한류라는 브랜드가 구축되고, 이에 관심이 급증함에 따라 관련 콘텐츠 시장의 혁신이 요구되고 있다. 본 논문은 한류문화 전수를 위한 수퍼인텔리전스 기반의 확장현실(XR) 소프트웨어 플랫폼에 관한 것으로, 본 플랫폼을 통하여 한류 문화 체험 및 전수가 가능하다. 세부적으로는 한류 콘텐츠 전수를 위한 확장현실 기반 공간을 바탕으로 딥러닝 기반 영상 생성 및 동작 분석기술, 자동 음악생성 기술, 한류 문화 데이터 보안 기술을 포함한 통합적인 플랫폼 환경을 설계하여 제안한다. 또한 이 플랫폼의 3차원 동작 분류 및 예측을 향상 시킬 수 있는 방법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.652-654
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• 2023

The accurate prediction of User Equipment (UE) paths in wireless networks is crucial for improving handover mechanisms and optimizing network performance, particularly in the context of Beyond 5G and 6G networks. This paper presents a comprehensive evaluation of unidirectional and bidirectional recurrent neural network (RNN) architectures for UE path prediction. The study employs a sequence-to-sequence model designed to forecast user paths in a wireless network environment, comparing the performance of unidirectional and bidirectional RNNs. Through extensive experimentation, the paper highlights the strengths and weaknesses of each RNN architecture in terms of prediction accuracy and computational efficiency. These insights contribute to the development of more effective predictive path-based mobility management strategies, capable of addressing the challenges posed by ultra-dense cell deployments and complex network dynamics.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.263-270
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• 2014

In cloud environment, business intelligence data warehouse is used for decision making and enterprise policy. But if new system is added in cloud environment, much cost and time is needed due to heterogenous characteristics in data integration. This paper suggests a data cleaning system for business intelligence in cloud environment. The proposed system minimizes the effect of local system when it integrates distributed system using XMDR-DAI. And this system provides standardized information to generate information of data warehouse in real time. Also the proposed system saves cost and time by integrating the data without a change of existed system. And it can improve quality of information by generating coherent information through data extraction and cleaning work in real time.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.465-467
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• 2022

Mobile phones have become an essential item nowadays since it provides access to online platform and service fast and easy. Coming to these platforms such as Social Network Service (SNS) for shopping have been a go-to option for many people. However, searching for a specific fashion item in the picture is challenging, where users need to try multiple searches by combining appropriate search keywords. To tackle this problem, we propose a system that could provide immediate access to websites related to fashion items. In the framework, we also propose a deep learning model for an automatic analysis of image contexts using instance segmentation. We use transfer learning by utilizing Deep fashion 2 to maximize our model accuracy. After segmenting all the fashion item objects in the image, the related search information is retrieved when the object is clicked. Furthermore, we successfully deploy our system so that it could be assessable using any web browser. We prove that deep learning could be a promising tool not only for scientific purpose but also applicable to commercial shopping.

• Digital Contents
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• no.6 s.61
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• pp.60-66
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• 1998

OLAP은 데이터 마이닝, 데이터 비주얼라이제이션, 데이터웨어 하우징 등의 최신 의사결정지원 기술과 마찬가지로 전반적인 비즈니스 인텔리전스 프레임웍의 핵심 컴포넌트중 하나이다. 하지만 시스템 환경이 복잡해지고, 사용자들의 요구가 다양해짐에 따라 하나의 제품군이 모든 사용자 업무를 지원한다는 것은 무리이다. 이를 위해 각 제품들은 상호 통합 및 연계를 그 해결책으로 제시하고 있다.

• Digital Contents
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• no.10 s.137
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• pp.162-163
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• 2004

지난해 기업용 솔루션 업계의 최대 이슈로 급부상했던 BI(비즈니스인텔리전스)가 올해는 DW(데이터웨어하우스)라는 오랜 둥지에서 벗어나 독자적인 애플리케이션 영역으로 빠르게 성장하고 있다. 반면 ETL(데이터 추출 변환 로딩)툴을 중심으로 하는 데이터 통합 솔루션의 영역은 BI를 벗어난 영역으로의 확장을 강조하고 있고 그 부분이 경쟁력을 결정하는 핵심 포인트가 되고 있다. 최근 데이터통합 전문업체로 위상을 강화하고 있는 한국어센셜소프트웨어를 들러봤다.

• TTA Journal
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• s.89
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• pp.146-148
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• 2003

TTA(한국정보통신기술협회)는 2003년 8월 6일 품질인증 제품으로 한진정보통신㈜(대표 고원용 http://www.hist.co.kr)의 ''InfoMatrix v 1.0'', ㈜인텔리전스웨어(대표 은재형 www.intelligenceware.com/)의 ''Bizpus v 1.0'' 등 2건에 대하여 Good Software 마크를 발급하였다. 본 고에서는 상위의 인증획득한 제품에 대하여 소개하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.647-650
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• 2018

With the advent of advanced technologies in the real world, the cyber domain has become wider and cyber threats are increasing. A cyber threat intelligence sharing system is needed to more effectively defend and respond to such cyber threats. Through the definition of cyber threat information expression standard, it enables rapid sharing, consistent analysis, and automated interpretation of cyber threat information possessed by individual security control providers or organizations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.1-9
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• 2014

This study deals with development of Integrated Transportation Analysis System for Large-scale event. Based on case studies, the requirements of the system were defined and the direction of development was established. The large-scale events that require fast and accurate transportation policy were selected. The data warehouse and data mart were developed by integrating the large-scale event data and the traffic data. Business intelligence system was designed and developed users to allow timely decisions.