• Journal of KIISE:Databases
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• v.34 no.3
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• pp.217-231
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• 2007

Frequent disconnection is connected directly to client's cache consistency problem in Mobile Computing environment. For solving cache consistency problem, research about Invalidation Report is studied. But, existent invalidation report structure comes with increase of size of invalidation report structure and decline of cache efficiency if quantity of data become much, or quantity of updated data increases. Also, while existent method confirms whole cache, invalidation report doesn't support selective listening. This paper proposes TTCI(Timestamp Tree-based Cache Invalidation scheme) as invalidation report structure that solve problem of these existing schemes and improve efficiency. We can make TTCI using timestamp of updated data, composing timestamp tree and list ID of data in updated order. If we utilize this, each client can confirm correct information in point that become own disconnecting and increase cache utilization ratio. Also, we can pare down client's resources consumption by selective listening using tree structure. We experimented in comparison with DRCI(Dual-Report Cache Invalidation) that is existent techniques to verify such efficiency of TTCI scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4531-4535
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• 2011

In this paper, USN(Ubiquitous Sensor Network) is used in the structure of the tree routing was implemented in embedded systems. Tree Routing in the USN to the sink node to transmit sensor data is one of the techniques. When routing, sensor data is transmitted based on pre-defined ID according hop number. In order to have optimal routing path, the current state of the wireless sector and the sensor node informations were used. Also, received sensor data and the results of the tree routing by implementing an embedded system. This embedded system can be applied to a portable sensor information collecting system.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.984-990
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• 2007

As the amount of electronic documents increases explosively, automatic text categorization methods are needed to identify those of interest. Most methods use machine learning techniques based on a word set. This paper introduces a new method, called FPTC (FP-Tree based Text Classifier). FP-Tree is a data structure used in data-mining. In this paper, a method of storing text sentence patterns in the FP-Tree structure and classifying text using the patterns is presented. In the experiments conducted, we use our algorithm with a #Mutual Information and Entropy# approach to improve performance. We also present an analysis of the algorithm via an ordinary differential categorization method.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.472-482
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• 1997

Multi-dimensional data play a crucial role in various fields, as like computer graphics, geographical information system, and multimedia applications. Indexing method fur multi-dimensional data Is a very Important factor in overall system performance. What is proposed in this paper is a new dynamic access method for spatial objects called HL-CIF(Hierarchically Layered Caltech Intermediate Form) tree which requires small amount of storage space and facilitates efficient query processing. HL-CIF tree is a combination of hierarchical management of spatial objects and CIF tree in which spatial objects and sub-regions are associated with representative points. HL-CIF tree adopts "centroid" of spatial objects as the representative point. By reflecting objects′sizes and positions in its structure, HL-CIF tree guarantees the high spatial locality of objects grouped in a sub-region rendering query processing more efficient.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.827-836
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• 2001

Data is represented by file structure in Computer System. But the file size is to be larger, it is hard to control and transmit. Therefore, in recent years, many researchers have developed new algorithms for the data compression. And now, we introduce a new Dynamic Compression Technique, making up for the weaknesses of huffman's. The huffman compression technique has two weaknesses. The first, it needs two steps of reading, one for acquiring character frequency and the other for real compression. The second, low compression rate caused by storing tree information. These weaknesses can be solved by our new Dynamic Relocatable Method, reducing the reading pass by relocating data file to dynamic form, and then storing tree information from pipeline structure. The first, it needs two steps of reading, one for acquiring character frequency and the other for real compression. The second, low compression rate caused by storing tree information. These weaknesses can be solved by our new Dynamic Relocatable Method, reducing the reading pass by relocating data file to dynamic form, and then storing tree information from pipeline structure.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.247-257
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• 2013

A narrative structure is essential for a story generator to create a story plot. In digital storytelling system, a narrative structure can be generally designed as a tree or a graph, and the story generator in the digital storytelling system creates continuous story plots based on the narrative structure. When a narrative structure is designed with a tree or a graph, it is hard for the story generator to create various kinds of story-plots due to the inflexible nature of a tree or graph structure. It may result in degrading the quality of story-plots to provide similar story-plot to various kind of user. In this paper, we proposed an approach to create a story-plot based on association analysis of data mining to overcome the disadvantage. In detail, we defined a narrative structure which consists of narrative patterns, and then implemented a story generator which creates a story-plot using the proposed narrative structure. As a result, we confirmed that implemented story generator was able to create a story-plot according to understanding level of user in case study.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.677-679
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• 2017

Data convergecast is an indispensable task for any WSN applications. Typically, scheduling in the WSN consists of two phases: tree construction and scheduling. The optimal tree structure and scheduling for the network is proven NP-hard. This paper focuses on the delay optimality while constructing the data convergecast tree. The algorithm can take any tree as the input, and by performing the switches (i.e. a node changes its parent), the expected aggregation delay is potentially reduced. Note that while constructing the tree, only the in-tree collisions between the child nodes sending data to their common parent is considered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.183-186
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• 2012

To process continuous queries on a sensor network, it is required to transfer query predicates and build a query index on each sensor node. However, if we transfer query predicates to all sensor nodes, it makes the number of messages for query predicates increase. In this paper, we propose the scheme to construct the tree based relationship structure using data region of the sensor node and select the target nodes to transfer query predicates. we also implement the tree based relationship structure and measure the number of messages for sending predicates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1266-1272
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• 2004

Location-Based Services(LBS) give rise to location-dependent queries of which results depend on the positions of moving objects. Because positions of moving objects change continuously, indexes of moving object must perform update operations frequently for keeping the changed position information. Existing spatial index (Grid File, R-Tree, KDB-tree etc.) proposed as index structure to search static data effectively. There are not suitable for index technique of moving object database that position data is changed continuously. In this paper, I propose a dynamic hashing index that insertion/delete costs are low. The dynamic hashing structure is that apply dynamic hashing techniques to combine a hash and a tree to a spatial index. The results of my extensive experiments show the dynamic hashing index outperforms the $R^$ $R^*$-tree and the fixed grid.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.69-77
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• 2017

This paper represents a novel framework for multi-scale image fusion. Multi-scale Kalman Smoothing (MKS) algorithm with quad-tree structure can provide a powerful multi-resolution image fusion scheme by employing Markov property. In general, such approach provides outstanding image fusion performance in terms of accuracy and efficiency, however, quad-tree based method is often limited to be applied in certain applications due to its stair-like covariance structure, resulting in unrealistic blocky artifacts at the fusion result where finest scale data are void or missed. To mitigate this structural artifact, in this paper, a new scheme of multi-scale fusion framework is proposed. By employing Super Resolution (SR) technique on MKS algorithm, fine resolved measurement is generated and blended through the tree structure such that missed detail information at data missing region in fine scale image is properly inferred and the blocky artifact can be successfully suppressed at fusion result. Simulation results show that the proposed method provides significantly improved fusion results in the senses of both Root Mean Square Error (RMSE) performance and visual improvement over conventional MKS algorithm.