• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.267-274
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• 2009

For the implementation of a RFID system, an anti-collision algorithm is required to identify multiple tags within the range of a RFID Reader. There are two methods of anti-collision algorithms for the identification of multiple tags, conclusive algorithms based on tree and stochastic algorithms based on slotted ALOHA. In this paper, we propose a Dynamic Framed Slotted ALOHA-Slot Congestion(DFSA-SC) Algorithm. The proposed algorithm improves the efficiency of collision resolution. The performance of the proposed DFSA-SC algorithm is showed by simulation. The identification time of the proposed algorithm is shorter than that of the existing DFSA algorithm. Furthermore, when the bit duplication of the tagID is higher, the proposed algorithm is more efficient than Query Tree algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.91-103
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• 2010

This paper introduces efficient rule-based semantic search techniques to ontology-based knowledge commerce services. Primarily, the search techniques presented in this paper define rules of reasoning that are required for users to search using the concept of ontology, multiple characteristics, relations among concepts and data type. In addition, based on the defined rules, the rule-based reasoning techniques search ontology for knowledge commerce services. This paper explains the conversion rules of query which convert user's query language into semantic search words, and transitivity rules which enable users to search related tags, knowledge products and users. Rule-based sematic search techniques are also presented; these techniques comprise knowledge search modules that search ontology using validity examination of queries, query conversion modules for standardization and expansion of search words and rule-based reasoning. The techniques described in this paper can be applied to sematic knowledge search systems using tags, since transitivity reasoning, which uses tags, knowledge products, and relations among people, is possible. In addition, as related users can be searched using related tags, the techniques can also be employed to establish collaboration models or semantic communities.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.63-70
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• 2015

In the environment that the complex conditions need to be satisfied, skyline query have been applied to various field. To processing a skyline query in centralized scheme, several techniques have been suggested and recently map/reduce platform based approaches has been proposed which divides data space into multiple partitions for the vast volume of multidimensional data. However, the performances of these approaches are fluctuated due to the uneven data loading between servers and redundant tasks. Motivated by these issues, this paper suggests a novel technique called MR-DEAP which solves the uneven data loading using the random sampling. The experimental result gains the proposed MR-DEAP outperforms MR-Angular and MR-BNL scheme.

• 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.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1277-1298
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• 2017

Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples, where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to the beach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in all dimensions and better in at least one dimension. Traditionally, skyline queries are defined upon single-instance data or upon objects each of which is associated with an instance. However, in some cases, an object is not associated with a single instance but rather by multiple instances. For example, on a review website, many users assign scores to a product or a service, and a user's score is an instance of the object representing the product or the service. Such data is an example of multi-instance data. Unlike most (if not all) others considering the traditional setting, we consider skyline queries defined upon multi-instance data. We define the dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic and real data to evaluate the proposed methods, and the results demonstrate their utility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2717-2738
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• 2024

Cloud computing has extensively grown in recent years. A large amount of data is stored in cloud servers. To ensure confidentiality, these data is often encrypted and then stored in cloud servers. However, encryption makes range queries difficult to perform. To solve this issue, we present a scheme that facilitates fast range queries on encrypted multi-dimensional data in scenarios involving multiple users. In our scheme, we construct a tree index on encrypted multi-dimensional data, and each node is linked to a secure enhanced multi-dimensional range (MDR). To support efficient range query on the tree index, we adopt bloom filter technique. Additionally, users' privileges are designed in a one-way calculation manner to support that different users can only perform range queries within their own privileges. Finally, we conduct extensive experiments which show the efficiency of our scheme, and also conduct a thorough analysis of its security.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1447-1458
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• 2020

This paper describes a structured overlay network scheme based on multiple different time intervals. Many types of data (e.g., sensor data) can be requested at specific time intervals that depend on the user and the system. These queries are referred to as "interval queries." A method for constructing an overlay network that efficiently processes interval queries based on multiple different time intervals is proposed herein. The proposed method assumes a ring topology and assigns nodes to a keyspace based on one-dimensional time information. To reduce the number of forwarded messages for queries, each node constructs shortcut links for each interval that users tend to request. This study confirmed that the proposed method reduces the number of messages needed to process interval queries. The contributions of this study include the clarification of interval queries with specific time intervals; establishment of a structured overlay network scheme based on multiple different time intervals; and experimental verification of the scheme in terms of communication load, delay, and maintenance cost.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.73-80
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• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• 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.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.812-817
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• 2006

This paper presents an image-space algorithm to real-time collision detection, which is run completely by GPU. For a single object or for multiple objects with no collision, the front and back faces appear alternately along the view direction. However, such alternation is violated when objects collide. Based on these observations, the algorithm has been devised, and the implementation utilizes the state-of-the-art functionalities of GPU such as framebuffer objects(FBO), vertex buffer object(VBO) and occlusion query. The experimental results show the feasibility of GPU-intensive collision detection and its performance gain in real-time applications such as 3D games.