• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2005년도 춘계학술발표대회
• /
• pp.55-58
• /
• 2005

In multi-level storage system with snapshot data, some snapshots which are from selection portions of the base tables are kept in main memory. So how to efficiently refresh snapshots in response to changes on their base tables for preserving consistency which requires snapshots reflect the current state of the base tables referenced by the snapshot query is a very import research issue. In this paper, a method for efficiently refreshing snapshots is proposed. In this method, it uses a data structure to store metadata which contains some necessary information of every snapshot and an updating log that records the history of changes on its base tables. Synchronization process scans the metadata and refreshing process is executed using appropriate logs after it finds anyone of the snapshot need to be refreshed.

• Journal of Information Processing Systems
• /
• 제12권4호
• /
• pp.724-740
• /
• 2016

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

• International Journal of Internet, Broadcasting and Communication
• /
• 제14권2호
• /
• pp.63-69
• /
• 2022

We develop a smart tourism information system that provides smart tourism services to free independent tourists (FITs) through various content distribution channels such as mobile apps, Instagram, YouTube, and chatbots. The smart tourism information system provides location and storytelling-based tourism information, accommodation, restaurant information, and recommended travel products so that tourists can create a travel itinerary based on personalized situation awareness. The smart tourism information system also provides smart tourism services using commercial maps, navigation, and weather forecast APIs from the Korea Meteorological Administration to provide smart tour guide services to tourists who travel according to the travel itinerary. In this paper, we develop the React Native app that provides smart tourism services provided by the smart tourism information system. The smart tourism React Native app has implemented two methods: a method that directly connects to the smart tourism information system, and a method that provides services by interworking through the GraphQL Query Language developed by META (Facebook). The smart tourism React Native app implements OSMU (One Source Multi-use) by providing tourism information from mobile apps, photos from Instagram, and drone videos from YouTube as an integrated UI.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권9호
• /
• pp.3680-3692
• /
• 2020

The purpose of this study is to orient users' touchpoints in co-design experience, to identify their need via visualized experience map, to recommend valid design information in online e-customization services. A user-centered co-design experience map (UCEM) is adopted to analyze the relation between users' desire and time spent, so as to evaluate the online co-design experiences. Based on evolutionary algorithm and fuzzy theory, data of this study is collected from 30 participants. The data was analyzed by descriptive analysis in SPSS, and frequency query and word cloud in NVivo. Employing design category and evaluating users' time spent, the findings are that (a) vamp color matching is consistent with interview data; (b) supported by qualitative feedback, the virtual experience map played an important role in the co-design process and the visualized interaction process; and (c) participants prefer to get more information and professional help on color matching and exterior design. Based on the findings in design category, future work should be focused on developing a better understanding of design resource recommendations and multi-stakeholder communication.

• 한국정보과학회논문지:데이타베이스
• /
• 제37권1호
• /
• pp.44-49
• /
• 2010

본 논문에서는 각도 성분 근사와 차원 그룹화 기법을 이용한 차원 축소 기법에 의해 변환된 축소 데이터를 색인하고 검색하기 위해서 해결되어야 하는 문제들을 분석하고 이를 해결하기 위한 방법을 제안한다. 또한 다양한 실험에 의한 성능 평가를 통하여 제안하는 방법의 우수성을 규명한다.

• 정보처리학회논문지A
• /
• 제15A권3호
• /
• pp.155-160
• /
• 2008

RFID의 태그의 적용 범위는 첨차 그 영역을 확대되고 있으며, 동종 및 이종 태그들이 제한된 공간에서 리더에 동시에 식별되는 과정에서 충돌이 발생할 수 있다. 따라서, 하나의 RFID 리더 영역 내에 다수의 태그 상호간에 충돌이 없이 인식하는 다중태그식별 기술은 매우 중요한 기술로 RFID 시스템의 성능과 안정성을 결정하는 핵심 기술이다. 본 논문에서는 차등식별법을 이용한 Depth-First 충돌방지 기법을 제안한다. 시뮬레이션을 통해 검증결과 기존 쿼리트리 알고리즘에 비해 17%의 식별단계 개선과 150%의 성능 개선을 확인할 수 있었다.

• 한국산학기술학회:학술대회논문집
• /
• 한국산학기술학회 2009년도 추계학술발표논문집
• /
• pp.445-448
• /
• 2009

DSS 응용들의 대용량 집계 데이터 집중 시스템에서는 효율적이고 즉각적인 의사결정 지원을 위한 근사 질의응답의 연구가 필요하다. 따라서 본 연구에서는 FCM 클러스터링 기법과 ANFIS을 이용한 기법을 제안한다. 제안된 기법은 다차원 데이터 큐브의 데이터 특성을 가지며 질의에 대한 근사적인 응답을 제공할 수 있는 모델을 생성한다. 제안된 기법을 통해 학습된 모델은 기존의 기법보다 근사 질의응답의 정확성이 향상되었음을 비교 실험을 통하여 확인한다. 따라서 제안된 기법은 기존의 기법보다 저장 공간과 시간을 줄일 수 있으며 또한 근사 응답의 정확도를 향상시킬 수 있다.

• International Journal of Contents
• /
• 제11권1호
• /
• pp.69-72
• /
• 2015

Generally, existing parallel main-memory spatial index structures to avoid the trade-off between query freshness and CPU cost uses light-weight locking techniques. However, still, the lock based methods have some limits such as thrashing which is a well-known problem in lock based methods. In this paper, we propose a distributed index structure for moving objects exploiting the parallelism in multiple machines. The proposed index is a lock free multi-version concurrency technique based on the D-Stream model of Spark Stream. The proposed method exploits the multiversion nature of D-Stream of Spark Streaming.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
• /
• pp.367-370
• /
• 2004

We model a moving object as a sizable physical entity equipped with GPS, wireless communication capability, and a computer such as a PDA and mobile phone. Furthermore, we have observed that a real trajectory of a moving object is the result of interactions among moving objects in the system yielding Multi-points instead of a line segment. In this paper, the new types and operations are integrated seamlessly into the moving object framework to achieve a relatively simple, consistent and powerful overall model and query language for constrained and unconstrained movement.

• 한국공간정보시스템학회:학술대회논문집
• /
• 한국공간정보시스템학회 2004년도 국내 LBS 기술개발 및 표준화 동향세미나
• /
• pp.69-74
• /
• 2004

Selectivity estimation for spatial query is very important process in finding the most efficient execution plan. Many works have been performed to estimate accurately selectivity. Although they deal with some problems such as false-count, multi-count, they require a large amount of memory to retain accurate selectivity, so they can not get good results in little memory environments such as mobile-based small database. In order to solve this problem, we propose a new technique called MW histogram which is able to compress summary data and get reasonable results. It also has a flexible structure to react dynamic update. The experimental results showed that the MW histogram has lower relative error than MinSkew histogram and gets a good selectivity in little memory.