• Title/Summary/Keyword: 시간기반 위치갱신

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Unified Index for Managing of Current Data and Past Trajectory of Moving Object Information (과거 및 현재 정보의 통합 관리를 위한 이동체 색인 기법)

  • Lee, Yang-Koo;Lee, Eung-Jae;Nam, Kwang-Woo;Ryu, Keun-Ho
    • 한국공간정보시스템학회:학술대회논문집
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    • 2003.11a
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    • pp.153-158
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    • 2003
  • 최근 이동 통신 기술과 GPS 기술의 발달은 실시간으로 이동하는 차량이나 비행기 등과 같은 이동 객체의 위치 정보 서비스를 가능하게 하였고, 이로 인해 이동 객체의 정보를 빠르게 검색하고 저장하기 위한 기술에 대한 연구가 활발히 진행되고 있다. 지금까지의 연구는 이동 객체의 과거 궤적 정보, 현재 및 미래 정보를 다루기 위한 구조가 각각 분리되어 연구되어 왔다. 하지만 이동객체는 시간의 흐름에 따라 연속적으로 변화하기 때문에 과거 정보와 현재 정보를 별도로 관리할 경우, 빈번한 위치 갱신이 발생하는 이동 객체의 환경에서는 심각한 처리비용이 요구된다. 따라서 이 논문에서는 이동 객체의 위치 정보를 효과적으로 관리하기 위하여 이동 객체의 과거 궤적정보 뿐만 아니라 현재의 정보까지도 하나의 색인 내에 통합하여 관리하는 방법을 제안한다. 제안된 방법에서는 범위 질의와 같은 좌표 기반의 질의뿐만 아니라 이동 객체의 궤적과 관련된 질의까지도 처리 가능하도록 기존의 TB-tree를 확장한다 또한 기존의 이동 객체 관리 기법들에서 처리하던 이동 객체의 궤적 정보를 저장하기 위한 방법을 개선하여 이동 객체 위치 정보의 중복저장 문제를 해결하고, 전체 색인의 크기를 크게 줄일 수 있는 방법을 제안한다. 그리고 현재 정보의 관리를 통해 새로운 데이터 삽입 시 방문하는 node의 수를 줄이고, 삽입 시간을 단축하는 방법을 제시한다.

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Grid-based Semantic Cloaking Method for Continuous Moving Object Anonymization (이동 객체 정보 보호를 위한 그리드 기반 시멘틱 클로킹 기법)

  • Zhang, Xu;Shin, Soong-Sun;Kim, Gyoung-Bae;Bae, Hae-Young
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.3
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    • pp.47-57
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    • 2013
  • Location privacy has been a serious concern for mobile users who use location-based services to acquire geographical location continuously. Spatial cloaking technique is a well-known privacy preserving method, which blurs an exact user location into a cloaked area to meet privacy requirements. However, cloaking for continuous moving object suffers from cloaked area size problem as it is unlikely for all objects travel in the same direction. In this paper, we propose a grid-based privacy preservation method with an improved Earth Mover's Distance(EMD) metric weight update scheme for semantic cloaking. We also define a representative cloaking area which protects continuous location privacy for moving users. Experimental implementation and evaluation exhibit that our proposed method renders good efficiency and scalability in cloaking processing time and area size control. We also show that our proposed method outperforms the existing method by successfully protects location privacy of continuous moving objects against various adversaries.

Fault Localization Method by Utilizing Memory Update Information and Memory Partitioning based on Memory Map (메모리 맵 기반 메모리 영역 분할과 메모리 갱신 정보를 활용한 결함 후보 축소 기법)

  • Kim, Kwanhyo;Choi, Ki-Yong;Lee, Jung-Won
    • Journal of KIISE
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    • v.43 no.9
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    • pp.998-1007
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    • 2016
  • In recent years, the cost of automotive ECU (Electronic Control Unit) has accounted for more than 30% of total car production cost. However, the complexity of testing and debugging an automotive ECU is increasing because automobile manufacturers outsource automotive ECU production. Therefore, a large amount of cost and time are spent to localize faults during testing an automotive ECU. In order to solve these problems, we propose a fault localization method in memory for developers who run the integration testing of automotive ECU. In this method, memory is partitioned by utilizing memory map, and fault-suspiciousness for each partition is calculated by utilizing memory update information. Then, the fault-suspicious region for partitions is decided based on calculated fault-suspiciousness. The preliminary result indicated that the proposed method reduced the fault-suspicious region to 15.01(%) of memory size.

Continuous Spatio-Temporal Self-Join Queries over Stream Data of Moving Objects for Symbolic Space (기호공간에서 이동객체 스트림 데이터의 연속 시공간 셀프조인 질의)

  • Hwang, Byung-Ju;Li, Ki-Joune
    • Spatial Information Research
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    • v.18 no.1
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    • pp.77-87
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    • 2010
  • Spatio-temporal join operators are essential to the management of spatio-temporal data such as moving objects. For example, the join operators are parts of processing to analyze movement of objects and search similar patterns of moving objects. Various studies on spatio-temporal join queries in outdoor space have been done. Recently with advance of indoor positioning techniques, location based services are required in indoor space as well as outdoor space. Nevertheless there is no one about processing of spatio-temporal join query in indoor space. In this paper, we introduce continuous spatio-temporal self-join queries in indoor space and propose a method of processing of the join queries over stream data of moving objects. The continuous spatio-temporal self-join query is to update the joined result set satisfying spatio-temporal predicates continuously. We assume that positions of moving objects are represented by symbols such as a room or corridor. This paper proposes a data structure, called Candidate Pairs Buffer, to filter and maintain massive stream data efficiently and we also investigate performance of proposed method in experimental study.

Non-Prior Training Active Feature Model-Based Object Tracking for Real-Time Surveillance Systems (실시간 감시 시스템을 위한 사전 무학습 능동 특징점 모델 기반 객체 추적)

  • 김상진;신정호;이성원;백준기
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.23-34
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    • 2004
  • In this paper we propose a feature point tracking algorithm using optical flow under non-prior taming active feature model (NPT-AFM). The proposed algorithm mainly focuses on analysis non-rigid objects[1], and provides real-time, robust tracking by NPT-AFM. NPT-AFM algorithm can be divided into two steps: (i) localization of an object-of-interest and (ii) prediction and correction of the object position by utilizing the inter-frame information. The localization step was realized by using a modified Shi-Tomasi's feature tracking algoriam[2] after motion-based segmentation. In the prediction-correction step, given feature points are continuously tracked by using optical flow method[3] and if a feature point cannot be properly tracked, temporal and spatial prediction schemes can be employed for that point until it becomes uncovered again. Feature points inside an object are estimated instead of its shape boundary, and are updated an element of the training set for AFH Experimental results, show that the proposed NPT-AFM-based algerian can robustly track non-rigid objects in real-time.

Location Management & Message Delivery Protocol for Multi-region Mobile Agents in Multi-region Environment (다중 지역 환경에서 이동 에이전트를 위한 위치 관리 및 메시지 전달 기법)

  • Choi, Sung-Jin;Baik, Maeng-Soon;Song, Ui-Sung;Hwang, Chong-Sun
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.11
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    • pp.545-561
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    • 2007
  • Location management and message delivery protocol is fundamental to the further development of mobile agent systems in a multi-region mobile agent computing environment in order to control mobile agents and guarantee message delivery between them. However, previous works have some problems when they are applied to a multi-region mobile agent computing environment. First, the cost of location management and message delivery is increased relatively. Second, a tracking problem arises. finally, cloned mobile agents and parent-child mobile agents do not get dealt with respect to location management and message delivery. In this paper, we present a HB (Home-Blackboard) protocol, which is a new location management and message delivery protocol in a multi-region mobile agent computing environment. The HB protocol places a region server in each region and manages the location of mobile agents by using intra-region migration and inter-region migration. It also places a blackboard in each region server and delivers messages to mobile agents when a region server receives location update form them. The HB protocol can decrease the cost of location update and message passing and solve the tracking problem with low communication cost. Also, this protocol deals with the location management and message passing of cloned mobile agents and parent-child mobile agents, so that it can guarantee message delivery of these mobile agents and pass messages without passing duplicate messages.

Optimization of Position of Lightening Hole in 2D Structures through MLS basede Overset Metheod along with Genetic Algorithm (이동최소자승 중첩 격자 기법과 유전자 알고리듬을 이용한 2차원 구조물의 경감공 위치 최적 설계)

  • Oh, Min-Hwan;Woo, Dong-Ju;Cho, Jin-Yeon
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.10
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    • pp.979-987
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    • 2008
  • In aerospace structural design, the position of lightening hole is often required to be optimized from the initial design in order to avoid an excessive stress concentration. To remodel the updated configuration in optimization procedure, re-meshing procedure is conventionally adopted. However, this approach is time-consuming, and has limitations especially in handling hexahedral or quadrilateral meshes, which are preferred because of their good numerical performances. To attenuate these disadvantages, new optimization scheme is proposed by combining the MLS(Moving Least Squares) based overset method and the genetic algorithm in this work. To test the validity of the proposed optimization scheme, optimizations of positions of lightening holes in 2D structures have been carried out.

Context Ontology and Trigger Rule Design for Service Pattern Mining (서비스 패턴 마이닝을 위한 컨텍스트 온톨로지 및 트리거 규칙 설계)

  • Hwang, Jeong-Hee
    • Journal of Digital Contents Society
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    • v.13 no.3
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    • pp.291-299
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    • 2012
  • Ubiquitous computing is a technique to provide users with appropriate services, collecting the context information in somewhere by attached sensor. An intelligent system needs to automatically update services according to the user's various circumstances. To do this, in this paper, we propose a design of context ontology, trigger rule for mining service pattern related to users activity and an active mining architecture integrating trigger system. The proposed system is a framework for active mining user activity and service pattern by considering the relation between user context and object based on trigger system.

Vision-based Mobile Robot Localization and Mapping using fisheye Lens (어안렌즈를 이용한 비전 기반의 이동 로봇 위치 추정 및 매핑)

  • Lee Jong-Shill;Min Hong-Ki;Hong Seung-Hong
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.4
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    • pp.256-262
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    • 2004
  • A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

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A Space Partitioning Based Indexing Scheme Considering, the Mobility of Moving Objects (이동 객체의 이동성을 고려한 공간 분할 색인 기법)

  • Bok, Kyoung-Soo;Yoo, Jae-Soo
    • Journal of KIISE:Databases
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    • v.33 no.5
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    • pp.495-512
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    • 2006
  • Recently, researches on a future position prediction of moving objects have been progressed as the importance of the future position retrieval increases. New index structures are required to efficiently retrieve the consecutive positions of moving objects. Existing index structures significantly degrade the search performance of the moving objects because the search operation makes the unnecessary extension of the node in the index structure. To solve this problem, we propose a space partition based index structure considering the mobility of moving objects. To deal with the overflow of a node, our index structure first merges it and the sibling node. If it is impossible to merge them, our method splits the overflow node in which moving properties of objects are considered. Our index structure is always partitioned into overlap free subregions when a node is split. Our split strategy chooses the split position by considering the parameters such as velocities, the escape time of the objects, and the update time of a node. In the internal node, the split position Is determined from preventing the cascading split of the child node. We perform various experiments to show that our index structure outperforms the existing index structures in terms of retrieval performance. Our experimental results show that our proposed index structure achieves about $17%{\sim}264%$ performance gains on current position retrieval and about $107%{\sim}19l%$ on future position retrieval over the existing methods.