• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1143-1148
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• 2004

To develop multi-tier model or distributed architecture based distributed application needs to consider various aspects such as division of role between web-designer and software developer, defining entity and its usage, database connection and transaction processing etc. This paper presents DONSL(Data Server of Non SQL-Query) architecture that provides solution to above aspects through web-tier object modeling. This is the architecture that guarantees the transaction processing and performance between web-tier and DBMS through simplified usage of query logic property. This new conceptual framework also solves enterprise site implementation problems simplifying tier, and removing DAO(Data Access Object) and entity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8A
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• pp.847-857
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• 2007

For the implementation of a RFID system, an anti-collision algorithm is required to identify multiple tags within the range of a RFID Reader. A Bit-by-Bit algorithm is defined by Auto ID Class 0. In this paper, we propose a SBBB(Stack Bit-by-Bit) algorithm. The SBBB algorithm save the collision position and makes a query using the saved data. SBBB improve the efficiency of collision resolution. We show the performance of the SBBB algorithm by simulation. The performance of the proposed algorithm is higher than that of BBB algorithm. Especially, the more each tag bit streams are the duplicate, the higher performance is.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.209-212
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• 2015

본 논문에서는 지식베이스와 다중 소스 레이블 문서를 동시에 활용한 다중소스 기반 오픈 도메인 질의 응답 시스템에 대해 소개한다. 제안하는 질의 응답 시스템은 자연어처리를 기반으로 한 질의 분석 모듈, SPARQL (Simple protocol and RDF Query Language) query 생성 및 검색 부분, 다중 소스 레이블 문서 검색 부분으로 이루어져 있다. 정확도가 높은 지식베이스 기반의 질의 응답 시스템으로 정답을 우선 탐색한다. 지식베이스 기반 질의 응답 시스템으로 정답을 찾는 데 실패하거나, SPARQL query 생성에 실패하면, 다중 소스가 레이블된 문서 검색을 통해 정답을 찾는다. 제안하는 질의 응답 시스템은 지식베이스만 사용한 질의 응답 시스템보다 높은 성능을 보인다.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.663-673
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• 1999

WWW에 있어서 데이타베이스 통로는 필수적이다. 데이타베이스를 이용한 대부분의 웹 서비스는 CGI를 통해서 이루어지고 있는데 본 논문에서는 CGI가 갖는 문제점을 근본적으로 해결하기 위한 프레임웍으로서 JAQS(JAva Query Stub)를 제안하고 있다. JAQS를 통하여 이루어지는 서비스는 HTTP의 비연결성(connectionless) 및 무상태성(stateless)을 극복함으로써 상태 및 트랜잭션 관리를 지원할 수 있음은 물론 자바언어로 구현되어 플랫폼 독립적인 구조와 다중쓰레드를 최대한 활용하고 있다. 또한 JAQS와 함께 제안하고 있는 JAQS 관리자를 이용하면 데이타베이스가 분산되어 있는 환경에서도 효율적으로 동작할 수 있는 구조로 이루어져있다.Abstract Database gateway is absolutely vital to web-based services. Most web-based services with DBMS are implemented using CGI(Common Gateway Interface). This paper proposes a framework, dubbed JAQS(JAva Query Stub), as a solution for problems of CGI. JAQS not only supports state/transaction management by overcoming the connectionless and stateless nature of HTTP, but also effectively guarantees platform/DBMS-independence and multi-threading abilities because JAQS is implemented using Java. Also, using the JAQS Manager additionally proposed in this paper, JAQS can operate efficiently even in distributed database environments.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.49-54
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• 2021

Indoor positioning system becomes of increasing interests due to the demands for accurate indoor location information where Global Navigation Satellite System signal does not approach. Wi-Fi access points (APs) built in many construction in advance helps developing a Wi-Fi Received Signal Strength Indicator (RSSI) based indoor localization. This localization method first collects pairs of position and RSSI measurement set, which is called fingerprint database, and then estimates a user's position when given a query measurement set by comparing the fingerprint database. The challenge arises from nonlinearity and noise on Wi-Fi RSSI measurements and complexity of handling a large amount of the fingerprint data. In this paper, machine learning techniques have been applied to implement Wi-Fi based localization. However, most of existing indoor localizations focus on single position estimation. The main contribution of this paper is to develop multi-target localization by using deep neural, which is beneficial when a massive crowd requests positioning service. This paper evaluates the proposed multilocalization based on deep learning from a multi-story building, and analyses its learning effect as increasing number of target positions.

• Journal of the Korean Association of Geographic Information Studies
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• v.1 no.2
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• pp.67-79
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• 1998

Most GIS applications are read-intensive on a large number of spatial objects and when the spatial objects are composite objects, the contained objects within the composite objects are also accessed. In GIS applications, creation, deletion, and update operations on spatial objects occur very rarely, but once they occur they deal with a large number of spatial objects. This paper proposes the concept of the multi-level pre-fetch query to retrieve a large number of spatial objects efficiently, and the functionality of the deferred-flush on the newly created persistent objects into the database with the optimal performance, and presents the design and implementation details of those ideas into an object-oriented DBMS BADA-III while considering these characteristics of GIS applications. The multi-level pre-fetch query retrieves the objects that satisfy the query and the objects that are contained within the objects up to the level specified by users, and registers the retrieved objects on the client cache. The deferred-flush flushes a large number of composite objects that are created by the application with a minimal overhead of the server and a minimal number of communications between the client and the server. These two functionality are suitable for the applications that search or create a large number of composite objects like GIS applications.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.729-734
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• 2005

In order to access XML data stored in object databases, an efficient index scheme is inevitable. There have been several index schemes that can be used to efficiently retrieve XML data stored In object databases, but they are all the single path indexes that support indexing along a single schema path. Henee, if a query contains an extended path which is denoted by wild character ('*'), a query processor has to examine multiple index objects, resulting in poor performance and inconsistent index management. In this paper, we propose MPI (Multi-Path Index) scheme as a new index scheme that provides the functionality of multiple path indexes more efficiently, while it uses only one index structure. The proposed scheme is easy to manage since it considers the extended path as a logically single schema path. It is also practical since it can be implemented by little modification of the B -tree index structure.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.766-768
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• 2003

Selectivity estimation for spatial query is curial in Spatial Database Management Systems(SDBMS). Many works have been performed to estimate accurate selectivity. Although they deal with some problems such as false-count, multi-count arising from properties of spatial dataset, they can not get such effects in little memory space.* Therefore, we need to compress spatial dataset into little memory. In this paper, we propose a new technique called MW Histogram which is able to compress summary data and get reasonable results. Our method is based on two techniques:(a)MinSkew partitioning algorithm which deal with skewed spatial datasets. efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. The experimental result shows that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.669-680
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• 2011

R-trees are widely used in various areas such as geographical information systems, CAD systems and spatial databases in order to efficiently index multi-dimensional data. As data sets used in these areas grow in size and complexity, however, range query operations on R-tree are needed to be further faster to meet the area-specific constraints. To address this problem, there have been various research efforts to develop strategies for acceleration query processing on R-tree by using the buffer mechanism or parallelizing the query processing on R-tree through multiple disks and processors. As a part of the strategies, approaches which parallelize query processing on R-tree through Graphics Processor Units(GPUs) have been explored. The use of GPUs may guarantee improved performances resulting from faster calculations and reduced disk accesses but may cause additional overhead costs caused by high memory access latencies and low data exchange rate between GPUs and the CPU. In this paper, to address the overhead problems and to adapt GPUs efficiently, we propose a novel approach which uses a GPU as a buffer to parallelize query processing on R-tree. The use of buffer algorithm can give improved performance by reducing the number of disk access and maximizing coalesced memory access resulting in minimizing GPU memory access latencies. Through the extensive performance studies, we observed that the proposed approach achieved up to 5 times higher query performance than the original CPU-based R-trees.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.701-708
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• 2004

Existing contents-based video retrieval systems search by using a single method such as annotation-based or feature-based retrieval. Hence, it not only shows low search efficiency, but also requires many efforts to provide system administrator or annotator with a perfect automatic processing. Tn this paper, we propose an agent-based, and automatic and unified semantics-based video retrieval system, which support various semantics-retrieval of the massive video data by integrating the feature-based retrieval and the annotation-based retrieval. The indexing agent embodies the semantics about annotation of extracted key frames by analyzing a fundamental query of a user and by selecting a key-frame image that is ed by a query. Also, a key frame selected by user takes a query image of the feature-based retrieval and the indexing agent searches and displays the most similar key-frame images after comparing query images with key frames in the database by using the color-multiple-partition histogram techniques. Furthermore, it is shown that the performance of the proposed system can be significantly improved.