• The KIPS Transactions:PartD
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• v.14D no.3 s.113
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• pp.273-284
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• 2007

RFID middleware systems collect and filter the RFID streaming data gathered continuously by numerous readers in order to process requests from applications. These requests are called continuous queries because they are kept on executing during certain periods. To enhance the performance of the middleware, it is required to build an index to process the continuous queries efficiently. Several approaches of building an index on not data records but queries, called Query Index, are proposed and widely used for evaluating continuous queries over streaming data. The EPCglobal proposed an Event Cycle Specification (ECSpec) model, which is a standard query interface for RFID applications. Continuous queries based on ECSpec consist of a large number of segments for representing the query conditions. The problem with using any of the existing query indexes on these continuous queries is that it takes a long time to build the index because it is necessary to insert a large number of segments into the index. To solve this problem, we propose an Aggregate Transformation that converts a group of segments into a compressed data which is representative of the segments. We compare the performance of a transformed index with the existing query indexes.

• Journal of KIISE:Databases
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• v.36 no.3
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• pp.226-234
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• 2009

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to the characteristics of a data stream, it is impossible to save all the data elements of a data stream. Therefore it is necessary to define a new synopsis structure to store the summary information of a data stream. For this purpose, this paper proposes a cuboid prefix tree that can be effectively employed in evaluating an iceberg query over data streams. A cuboid prefix tree only stores those itemsets that consist of grouping attributes used in GROUP BY query. In addition, a cuboid prefix tree can compute multiple iceberg queries simultaneously by sharing their common sub-expressions. A cuboid prefix tree evaluates an iceberg query over an infinitely generated data stream while efficiently reducing memory usage and processing time, which is verified by a series of experiments.

• Journal of KIISE:Databases
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• v.36 no.2
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• pp.112-122
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• 2009

The EPCglobal leading the development in RFID standards proposed Event Cycle Specification (ECSpec) and Event Cycle Reports (ECReports) for the standard about RFID middleware interface. ECSpec is a specification for filtering and collecting RFID tag data and is treated as a Continuous Query (CQ) processed during fixed time intervals repeatedly. ECReport is a specification for describing the results after ECSpec is processed. Thus, it is efficient to apply Query Indexing technique designed for the continuous query processing. This query index processes ECSpecs as data and tag events as queries for efficiency. In logistics environment, the similar or same products are transferred together. Also, when RFID tags attached to the products are acquired, the acquisition events occur massively for the short period. For these properties, it is inefficient to process the massive events one by one. In this paper, we propose a technique reducing similar search process by considering tag events which are collected by the report period in ECSpec, as a range query. For this group processing, we suggest a queuing method for collecting tag events efficiently and a structure for generating range queries in the queues. The experiments show that performance is enhanced by the proposed methods.

• Journal of Korea Multimedia Society
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• v.11 no.7
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• pp.914-927
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• 2008

Grid database management systems are used for large data processing, high availability and data integration in grid computing. Furthermore the grid database management systems are in the use of manipulating the queries that are sent to distributed nodes for efficient query processing. However, when the query processing is concentrated in a random node, it will be occurred with imbalance workload and decreased query processing. In this paper we propose a load balancing method for query processing based on cache Management in grid databases. This proposed method focuses on managing a cache in nodes by cache manager. The cache manager connects a node to area group and then the cache manager maintains a cached meta information in node. A node is used for caching the efficient meta information which is propagated to other node using cache manager. The workload of node is distributed by using caching meta information of node. This paper shows that there is an obvious improvement compared with existing methods, through adopting the proposed algorithm.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.515-524
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• 2017

In this paper, we design and implement an expert system for diagnosing ADHD. As a result of the analysis with DSM-IV-TR, the ADHD diagnostic criteria are changed according to the age group. With this analyzed diagnostic, objects and their values are set and rules are created. We design a diagnostic system consisting of 'ADHD diagnostic system engine' and 'user query response program'. The ADHD diagnostic system engine is a rule-based reasoning engine that is implemented in the Prolog language and receives INPUT from the user query response program. By INPUT, the rule is executed based on the ADHD diagnostic criteria and the OUTPUT is sent back to the 'user query response program' by inferring the diagnostic result. The 'user query response program' is implemented in the Python language and serves as an interface for handling conversation with the user. The bridge between 'ADHD diagnostic system engine' and 'user query response program' is performed through the Pyswip library. As a result, the ADHD Diagnostic Expert System will help you plan your treatment with reduced diagnostic costs and use-complexity.

• Journal of Internet Computing and Services
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• v.6 no.3
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• pp.55-70
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• 2005

In order to provide mobile hosts with multicast service in mobile communication environment, we proposed a multicast mechanism named HXcast++ which is an extended version of the existing Xcast++ with hierarchical architecture, We assured that mobile hosts could get multicast service through an optimal path regardless of their location by making DR(Designated Router) join a group on behalf of the mobile hosts, In this present research we introduced hierarchical architecture in order to reduce the maintenance cost resulting from frequent handoff. We also proposed a GMA (Group Management Agent) based group management mechanism which enables the mobile hosts to join the group without waiting for a new IGMP Membership Query. A fast handoff method with L2 Mobile Trigger was, in this work, employed in order to reduce the amount of the packet loss which occurs as a result of the handoff, We also managed to curtail the packet loss caused by the latency of the group join by using a buffering and forward mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1460-1478
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• 2020

This paper proposes a novel anti-collision protocol for large-scale RFID tags identification, named Bi-response Collision Tree Protocol (BCT). In BCT, two group of tags answer the reader's same query in two response-cycles respectively and independently according to the bi-response pattern. BCT improves the RFID tag identification performance significantly by decreasing the query cycles and the bits transmitted by the reader and tags during the identification. Computation and simulation results indicate that BCT improves the RFID tag identification performance effectively, e.g. the tag identification speed is improved more than 13.0%, 16.9%, and 22.9% compared to that of Collision Tree Protocol (CT), M-ary Collision Tree Protocol (MCT), and Dual Prefix Probe Scheme (DPPS) respectively when tags IDs are distributed uniformly.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.139-141
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• 2007

최근 멀티미디어를 검색하기 위해 메타데이터 기반의 검색 방법에서 컨텐츠 자체를 검색 하려는 연구들이 활발히 진행되고 있다. 특히 음악 검색의 경우 허밍 입력으로 검색을 하려는 QBH(Query By Humming)가 많은 관심을 끌고 있다. 하지만 허밍 데이터는 개인마다 음높이나 박자 정보들이 모두 다르고 숨소리 등의 내재된 오류 정보들이 많아 정확한 검색 결과를 얻기가 쉽지 않다. 허밍 검색의 정확도 향상을 위해서는 음 데이터 추출이나 허밍의 오류 보정, 유사도 측정과 관련된 연구들이 선행되어야 한다. 본 논문에서는 효과적인 멜로디 표현방법에 대해 다양한 실험을 통해 최적의 모델을 제시하려 한다. 방법으로 UDR을 다양한 범위로 나누고 가중치를 달리하는 방법으로 실험을 한 결과 허밍을 그룹으로 분류하는 방법이 정확도를 향상 시키는 것을 확인 하였다.

• Journal of KIISE
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• v.43 no.2
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• pp.256-268
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• 2016

Modern networks consisting of various heterogeneous equipment are often installed in a distributed manner. Thus the NETCONF standard was established to manage networks centrally and efficiently. In this paper, we present a method that integrates each NETCONF layer into a single system based on the results of previous studies. In the RPC Layer, an asynchronous communication channel and parallel processes are possible using multi-threading. In the Operation Layer, operational efficiency is increased by using a data group with dependencies between the equipment configuration data and by improving the data structure, enabling efficiently processing of XML queries even with multiple managers. The data modeling techniques and grouping methods in the Content Layer are presented in detail for interoperability between the Operation Layer and the Content Layer. Finally, the GUI program was implemented and its implementation is reported. We performed an experiment comparing the improved NETCONF with the standard NETCONF to measure factors, such as query processing ratio, query processing speed, and CPU utilization. The improved NETCONF demonstrated excellent query processing ratio and query processing speed, whereas the standard NETCONF had excellent CPU utilization.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.55-62
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• 2017

Recently, there has been an increasing need for the sharing of microdata containing information regarding an individual entity. As microdata usually contains sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, to avoid the privacy problems that occur through the release of microdata for public use, extensive studies have been conducted in the area of privacy-preserving data publishing (PPDP). The k-anonymity algorithm, which is the most popular method, guarantees that, for each record, there are at least k-1 other records included in the released data that have the same values for a set of quasi-identifier attributes. Given an original table, the corresponding k-anonymous table is obtained by generalizing each record in the table into an indistinguishable group, called the equivalent class, by replacing the specific values of the quasi-identifier attributes with more general values. However, query processing over the anonymized data is a very challenging task, due to generalized attribute values. In particular, the problem becomes more challenging with an equi-join query (which is the most common type of query in data analysis tasks) over k-anonymous tables, since with the generalized attribute values, it is hard to determine whether two records can be joinable. Thus, to address this challenge, in this paper, we develop a novel scheme that is able to effectively perform an equi-join between k-anonymous tables. The experiment results show that, through the proposed method, significant gains in accuracy over using a naive scheme can be achieved.