• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.131-143
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• 2007

The current trends in information technology and intelligent systems use data mining techniques to discover patterns and extract rules from distributed databases. In distributed environment, the extracted rules from data mining techniques can be used in dynamic replications, adaptive load balancing and other schemes. However, transmission of large data through the system can cause errors and unreliable results. This paper proposes the intelligent distributed platform based on dynamic group binding using mobile agents which addresses the use of intelligence in distributed environment. The proposed grouping service implements classification scheme of objects. Data compressor agent and data miner agent extracts rules and compresses data, respectively, from the service node databases. The proposed algorithm performs preprocessing where it merges the less frequent dataset using neuro-fuzzy classifier before sending the data. Object group classification, data mining the service node database, data compression method, and rule extraction were simulated. Result of experiments in efficient data compression and reliable rule extraction shows that the proposed algorithm has better performance compared to other methods.

• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.13-24
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• 2005

Objects, which change their positions over time such as cars, are called moving objects. Trajectories of a moving object have large volumes because trajectories are accumulated. Efficient indexing techniques for searching these large volumes of trajectories are needed in the moving object databases. Especially the TB-tree which supports bundling trajectories is suitable for processing combined queries which have 2 steps: first step is selecting trajectories (range search), next is selecting the parts of each trajectory (trajectory search). But the TB-tree has unnecessary disk accesses cause of lack of spatial discrimination in range queries. In this paper, we propose and implement the splitting polity which can reduce dead spaces of non-leaf node in order to process range queries efficiently. The policy has better performance about range queries than the TB-tree as well as the advantages of the TB-tree, such as highly space utilization and efficient trajectory extraction. This paper shows that the newly proposed split policy has better performance in processing the range queries than that of the TB-tree by experimental evaluation.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.451-462
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• 2008

Recently, with the advent of applications using locations of moving objects, it becomes crucial to develop efficient index schemes for spatio-temporal databases. The $TPR^*$-tree is most popularly accepted as an index structure for processing future-time queries. In the $TPR^*$-tree, the future locations of moving objects are predicted based on the CBR(Conservative Bounding Rectangle). Since the areas predicted from CBRs tend to grow rapidly over time, CBRs thus enlarged lead to serious performance degradation in query processing. Against the problem, we propose a new method to adjust CBRs to be tight, thereby improving the performance of query processing. Our method examines whether the adjustment of a CBR is necessary when accessing a leaf node for processing a user query. Thus, it does not incur extra disk I/Os in this examination. Also, in order to make a correct decision, we devise a cost model that considers both the I/O overhead for the CBR adjustment and the performance gain in the future-time owing to the CBR adjustment. With the cost model, we can prevent unusual expansions of BRs even when updates on nodes are infrequent and also avoid unnecessary execution of the CBR adjustment. For performance evaluation, we conducted a variety of experiments. The results show that our method improves the performance of the original $TPR^*$-tree significantly.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.52-65
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• 1999

이미지나 비디오, 오디오와 같이 멀티미디어 데이터들은 기존의 단순한 텍스트 기반의 데이터에 비하여 대용량적인 특성과 비정형적인 특성을 가지고 있어서 검색시 많은 어려움이 따른다. 본 논문에서는 대규모의 이미지 데이터베이스에서 효율적이고 신속하게 사용자가 원하는 이미지를 검색할수 있는 내용 기반 검색 시스템을 제시한다. 이를 위해서 본 논문에서는 최근 여러 장점으로 인하여 신호 분석이나 이미지 압축 분야에 많이 사용되는 웨이브릿 변환을 이용하여 이미지 데이터로부터 내용 기반 검색에 사용되는 특징 벡터를 효율적으로 추출하는 기법과 유사성 측정 방법을 제안한다. 그리고, 이러한 특징 추출방법과 유사성 측정 방법을 이용하여 내용 기반 질의 및 검색을 수행할 경우, 검색 조건을 만족하는 객체인데 실수로 검색해내지 못하는 경우인 false dismissals 이 발생하지 않음을 보인다. 또한 대규모 이미지 데이터베이스에서 신속한 내용 기반 검색을 지원하기 위하여 고차원 데이터에 대한 효율적인 색인을 제공하는 X-tree를 이용한 이미지 색인 방법을 보이며 이것이 기존의 순차 검색이나 R*-tree를 이용한 색인 방법보다 신속하게 이미지 데이터들을 검색할 수 있다는 것을 다양한 실험을 통해 보인다. 마지막으로 QBIC에서 제안한 검색 적합성 측정 방법을 이용하여 본 논문에서 제안하는 내용 기반 이미지 검색시스템의 검색 적합성을 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.139-141
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• 2004

사용자를 중심으로 하는 주변환경과 사용자간 흑은 사용자와 장치간의 상호 운용성을 지능적, 자동적으로 선택하여 지원해 줌으로써 사용자로 하여금 정보 획득 및 실행을 보다 용이하게 하는 상황인식 기술은 유비쿼터스 컴퓨팅 환경에서 가장 중요한 핵심 기술이다. 따라서, 본 논문에서는 유비쿼터스 컴퓨팅을 위한 상황인식 기반의 미들웨어 및 컨텍스트 서버를 설계 및 구현한다. 먼저 미들웨어는 블루투스 (Bluetooth) 무선 통신 기술을 이용하여 이동성을 지닌 이동 노드를 발견하고, 컨텍스트 서버에 등록하여 해당 컨텍스트에 적합한 실행 모듈을 서비스하는 기능을 담당한다. 컨텍스트 서버는 주어진 원격 객체의 정보와 사용자의 현재 상태 물리적 환경의 상태 등의 상황 정보를 효율적으로 데이터베이스 서버에 저장하고 관리할 수 있는 기능을 수행한다. 마지막으로 응용 시스템을 통해 제안하는 미들웨어와 컨텍스트 서버의 유용성을 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.177-180
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• 2004

비디오 데이터베이스에서 움직임 정보를 가지고 있는 이동객체에 대한 모델링은 크게 두 가지 측면 즉, 공간적 혹은 시간적 관계성에 의해 다루어진다. 공간적 관계에서 위상 관계는 근접 그래프에 의한 모델링이 대부분이며, 이를 이용한 내용 기반 비디오 검색에서 자연어 형태의 질의어는 정형화된 위상 관계 표현으로 변환하는 과정을 거친다. 그러나 이 과정에서 위상 관계 표현이 인간이 사용하는 언어의 의미를 정확히 반영하는지는 알 수 없다. 이에 본 논문에서는 위상 관계 표현과 인간이 사용하는 움직임 동사간 의미의 차이를 줄이기 위해 위상 관계 표현과 실제 움직임 동사간의 매칭에 대해 연구했다.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.35-40
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• 2005

Recently, the location based service for moving customers is becoming one of the most important service in mobile communication area and for moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. The primary processing of LBS application is spatio-temporal range queries and to improve the throughput of spatio-temporal range queries, the time of disk I/O in query processing should be reduced. In this paper, we adopt non-uniform two-level grid index structure, which are designed to minimize update operations. We propose query scheduling technique using spatial relationship and time relationship and a combined spatio-temporal query processing method using time zone concepts to improve the throughput of query processing. Some experimental results are shown for range queries with different query range to show the performance tradeoffs of the proposed methods.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.179-186
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• 2008

The converge of location-aware devices, GIS functionalities and the increasing accuracy and availability of positioning technologies pave the way to a range of new types of location-based services. The field of spatiotemporal data mining where relationships are defined by spatial and temporal aspect of data is encountering big challenges since the increased search space of knowledge. Therefore, we aim to propose algorithms for mining spatiotemporal patterns in mobile environment in this paper. Moving patterns are generated utilizing two algorithms called All_MOP and Max_MOP. The first one mines all frequent patterns and the other discovers only maximal frequent patterns. Our proposed approach is able to reduce consuming time through comparison with DFS_MINE algorithm. In addition, our approach is applicable to location-based services such as tourist service, traffic service, and so on.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.23-39
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• 2005

As developing satellite communication, the tracking range of the moving objects which move in local area is expanded to the whole world. However previous logistics management system is able to monitor freight which transporting in local area using mobile communication system. In this paper, we propose the reefer container management system that manages the location information and other related information such as temperature, humidity of container using the satellite system. The proposed system consists of three parts; data collector, satellite communication manager, reefer container information manager. And the proposed system uses the moving object index for managing the trajectory of container and tracing the location of container or vessel that is transporting the container, and supports various services such as reefer container and vessel tracking, container control and container statistics to logistic companies like shipper and forwarding agent. And the system can be increasing the quality of container transportation service to the shipper, and it makes the efficient management of reefer container to the shipping company.

• The KIPS Transactions:PartC
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• v.14C no.1 s.111
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• pp.105-114
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• 2007

In sensor network processing environments, current location tracking methods have problems in accuracy on receiving the transmitted data and pinpointing the exact locations depending on the applied methods, and also have limitations on decision making and monitoring the situations because of the lack of considering context-awareness. In order to overcome such limitations, we proposed a method which utilized context-awareness in a data processing module which tracks a location of the magnetic object(Magnetic Line Tracer) and controlled introspection data based on magnetic sensor. Also, in order to prove its effectiveness we have built a wireless sensor network test-bed and conducted various location tracking experiments of line tracer using the data and resulted in processing of context-aware data. Using the new data, we have analyzed the effectiveness of the proposed method for locating the information database entries and for controlling the route of line tracer depending on context-awareness.