• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.141-152
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• 2004

In this paper, we propose the index structure supporting the future position retrievals with efficiently updating continuous positions of moving objects in location based services. For reducing update costs of moving objects, our index structure directly accesses to the leaf node with moving objects using secondary index structure and performs bottom up update when node information is changed. Positions of moving objects are stored in primary index structure. In primary index structure, the split information similar to kd-tree is stored to internal node for increasing node's fanout. And the proposed index structure supports the future position retrievals using velocity of moving objects in the child node.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.673-676
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• 2004

To manage and query moving objects efficiently in MMDBMS, a memory index structure should be used. The most popular index structure for storing trajectories of moving objects is 3DR-tree. The 3DR-tree also can be used for MMDBMS. However, the volume of data can exceed the capacity of physical memory since moving objects report their locations continuously. To accommodate new location reports, old trajectories should be migrated to disk or purged from memory. This paper focuses on migration policies of a main memory index structure. Migration policies consist of two steps: (i) node selection, (ii) node placement. The first step (node selection) selects nodes that should be migrated to disk. The criteria of selection are the performance of insertion or query. The second step (node placement) determines the order of nodes written to disk. This step can be thought as dynamic declustering policies.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.1-11
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• 2006

It is possible to track the moving vehicle as well as to develop the location based services actively according to the progress of wireless telecommunication and GPS, to the spread of network, and to the miniaturization of cellular phone. To provide these location based services, it is necessary for an index technique to store and search too much moving object data rapidly. However the existing indices require a lot of costs to insert the data because they store every position data into the index directly. To solve this problem in this paper, we propose a buffer node operation and design a GU-tree(Group Update tree). The proposed buffer node method reduces the input cost effectively since the operation stores the moving object location data in a group, the buffer node as the unit of a non-leaf node. hnd then we confirm the effect of the buffer node operation which reduces the insert cost and increase the search performance in a time slice query from the experiment to compare the operation with some existing indices. The proposed tufter node operation would be useful in the environment to update locations frequently such as a transportation vehicle management and a tour-guide system.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.545-550
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• 2011

Trilateration is a typical method to locate an object, which requires inherently at least three prerecognized reference points. In some cases, owing to out of reachability to communication facilities the target node cannot be reachable always to three base stations. This paper presents a predictive method, which can identify the location of a moving target node in real time even though the target node could not get in touch with all three base stations. The method is based on the PIDcontrolled Moving Objects Spatio-Temporal Model Algorithm. Simulation results verify that this method can predict the moving direction of a moving target, and then combine with its past position information to judge accurately the location.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1529-1541
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• 2006

Moving objects have been widely employed in traffic and logistic applications. Spatio-temporal aggregations mainly describe the moving object's behavior in the spatial data warehouse. The previous works usually express the object moving in some certain region, but ignore the object often moving along as the trajectory. Other researches focus on aggregation and comparison of trajectories. They divide the spatial region into units which records how many times the trajectories passed in the unit time. It not only makes the storage space quite ineffective, but also can not maintain spatial data property. In this paper, a spatio-temporal aggregation index structure for moving object trajectory in constrained network is proposed. An extended B-tree node contains the information of timestamp and the aggregation values of trajectories with two directions. The network is divided into segments and then the spatial index structure is constructed. There are the leaf node and the non leaf node. The leaf node contains the aggregation values of moving object's trajectory and the pointer to the extended B-tree. And the non leaf node contains the MBR(Minimum Bounding Rectangle), MSAV(Max Segment Aggregation Value) and its segment ID. The proposed technique overcomes previous problems efficiently and makes it practicable finding moving object trajectory in the time interval. It improves the shortcoming of R-tree, and makes some improvement to the spatio-temporal data in query processing and storage.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.23-31
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• 2010

With the advances in the information technology and mobile communications, we now face increasing demands for various services based on both of position tracking of moving objects and their efficient index scheme. Accordingly, the $TPR^*$-tree, which were proposed for efficiently tracking moving objects and predicting their positions in the future time, has drawn much intention. As the $TPR^*$-tree came from the R-tree that is suitable for indexing static objects, it does not support cheap update costs. Therefore, it seems to be very costly to index moving objects if there are frequent occurrences of node updates caused by continuously changing velocities and positions. If some moving objects with high velocities have node updates, in particular, then the $TPR^*$-tree may suffer from many unnecessary updates in the wide range of tree regions. To avoid such a problem, we propose a method that can keep fast-moving objects in the child nodes of the root node, thereby saving node update costs in the $TPR^*$-tree. To show our performance advantages and retaining $TPR^*$-tree features, we performed some performance experiments using a simulation technique.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.301-307
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• 2016

The location measurement technique of moving worker in dangerous areas, is necessary for safety in the mines, basements, warehouses, etc. There are various measurement techniques about moving node of position in a restricted environment. Trigonometric Method, one of measurement techniques, is commonly used because of its easiness. However, errors occur frequently when measuring distance and position due to radio interference and physical disability with measuring instruments. This paper proposed a method which is more accurate and shows reduced margin of error than existing trigonometric method by recalculating distance between Anchor and moving node with various measuring instruments. By adding Anchor when calculating distance and position of moving node's estimated point, suggested technique obtains at least 41% efficiency compared to existing method.

• Journal of Korea Spatial Information System Society
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• v.8 no.2 s.17
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• pp.53-73
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• 2006

Recently, the need for Location-Based Services (LBS) has increased due to the development of mobile devices, such as PDAs, cellular phones and GPS. As a moving object database that stores and manages the positions of moving objects is the core technology of LBS, the scheme for maintaining the main memory DBMS to the server is necessary to store and process frequent reported positions of moving objects efficiently. However, previous works on a moving object database have studied mostly a disk based moving object index that is not guaranteed to work efficiently in the main memory DBMS because these indexes did not consider characteristics of the main memory. It is necessary to study the main memory index scheme for a moving object database. In this paper, we propose the main memory index scheme based on the R-tree for storing and processing positions of moving objects efficiently in the main memory DBMS. The proposed index scheme, which uses a growing node structure, prevents the splitting cost from increasing by delaying the node splitting when a node overflows. The proposed scheme also improves the search performance by using a MergeAndSplit policy for reducing overlaps between nodes and a LargeDomainNodeSplit policy for reducing a ratio of a domain size occupied by node's MBRs. Our experiments show that the proposed index scheme outperforms the existing index scheme on the maximum 30% for range queries.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.2
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• pp.63-68
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• 2004

This paper presents an approach to optimum design of Moving Magnet Type Linear Oscillatory Actuator(MM-LOA). The Finite Element Method is applied to characteristic parameters for characteristic analysis and in order to reduce modeling time and efforts, the moving model node technique is used. In addition the neural network is used to reduce computational time of analysis according to changing design variable. To confirm the validity of this study, optimum design results are compared with results of analysis procedure that is verified by experiment.