• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.316-327
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• 2007

RFID (Radio Frequency Identification) is one of the most promising air interface technologies in the future for object identification using radio wave. If there are multiple tags within the range of the RFID tag reader, all tags send their tag identifications to the reader at the same time in response to the reader's query. This causes collisions on the reader and no tag is identified. A multi-tag identification problem is a core issue in the RFID. It can be solved by anti-collision algorithm such as slot based ALHOA algorithms and tree based algorithms. This paper, proposes a collision tree based anti-collision algorithm using collision tree in RFID system. It is a memory-less algorithm and is an efficient RFID anti-collision mechanism. The collision tree is a mechanism that can solve multi-tag identification problem. It is created in the process of querying and responding between the reader and tags. If the reader broadcasts K bits of prefix to multiple tags, all tags with the identifications matching the prefix transmit the reader the identifications consisted of k+1 bit to last. According to the simulation result, a proposed collision tree based anti-collision algorithm shows a better performance compared to tree working algorithm and query tree algorithm.

• The KIPS Transactions:PartC
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• v.11C no.6 s.95
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• pp.851-862
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• 2004

RFID(Radio frequency IDentification) is a technology that automatically identifies objects containing the electronic tags by using radio wave. The multi-tag identification problem is the core issue in the RFID and could be resolved by the anti-collision algorithm. However, most of the existing anti-collision algorithms have a problem of heavy implementation cost and low performance. In this paper. we propose a new tree based memoryless anti-collision algorithm called a collision tracking tree algorithm and presents its performance evaluation results obtained by simulation. The Collision Tracking Tree algorithm proves itself the capability of an identification rate of 749 tags per second and the performance evaluation results also show that the proposed algorithm outperforms the other two existing tree-based memoryless algorithms, i.e., the tree-walking algorithm and the query tree algorithm about 49 and 2.4 times respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1B
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• pp.17-26
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• 2005

RFID(Radio Frequency IDentification) is a technology that automatically identifies objects attached with electronic tags by using radio wave. For the implementation of an RFID system, an anti-collision algorithm is required to identify several tags within the RFID reader's range. Few researches report the performance trade-off among anti-collision algorithms in terms of the communications traffic between the reader and tags, the identification speed, and so on. In this paper, we analyze both tree based memoryless algorithms and slot aloha based algorithms that comprise of almost every class of existing anti-collision algorithms. To compare the performance, we evaluated each class of anti-collision algorithms with respect to low-cost RFID system with 96-bit EPC(Electronic Product Code). The results show that the collision tracking tree algorithm outperforms current tree based and aloha based algorithms by at least 2 times to 50 times.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.160-171
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• 2017

US national research laboratories developed the first Vital Area Identification (VAI) method for the physical protection of nuclear power plants that is based on Event Tree Analysis (ETA) and Fault Tree Analysis (FTA) techniques in 1970s. Then, Korea Atomic Energy Research Institute proposed advanced VAI method that takes advantage of fire and flooding Probabilistic Safety Assessment (PSA) results. In this study, in order to minimize the burden and difficulty of VAI, (1) a set of streamlined VAI rules were developed, and (2) this set of rules was applied to PSA fault tree and event tree at the initial stage of VAI process. This new rule-based VAI method is explained, and its efficiency and correctness are demonstrated throughout this paper. This new rule-based VAI method drastically reduces problem size by (1) performing PSA event tree simplification by applying VAI rules to the PSA event tree, (2) calculating preliminary prevention sets with event tree headings, (3) converting the shortest preliminary prevention set into a sabotage fault tree, and (4) performing usual VAI procedure. Since this new rule-based VAI method drastically reduces VAI problem size, it provides very quick and economical VAI procedure. In spite of an extremely reduced sabotage fault tree, this method generates identical vital areas to those by traditional VAI method. It is strongly recommended that this new rule-based VAI method be applied to the physical protection of nuclear power plants and other complex safety-critical systems such as chemical and military systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4A
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• pp.358-364
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• 2007

RFID, Radio Frequency Identification, technology is a contactless automatic identification technology using radio frequency. For this RFID technology to be widely spread, the problem of multiple tag identification, which a reader identifies a multiple number of tags in a very short time, has to be solved. Up to the present, many anti-collision algorithms have been developed in order to solve this problem, and those can be largely divided into ALOHA based algorithm and tree based algorithm. In this paper, two new anti-collision algorithms combining the characteristics of these two categories are presented. And the performances of the two algorithms are compared and evaluated in comparison with those of typical anti-collision algorithms: 18000-6 Type A, Type B, Type C, and query tree algorithm.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.259-264
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• 2005

This paper presents a vital area identification (VAI) method based on the current fault tree analysis (FTA) and probabilistic safety assessment (PSA) techniques for the physical protection of nuclear power plants. A structured framework of a top event prevention set analysis (TEPA) application to the VAI of nuclear power plants is also delineated. One of the important processes for physical protection in a nuclear power plant is VAI that is a process for identifying areas containing nuclear materials, structures, systems or components (SSCs) to be protected from sabotage, which could directly or indirectly lead to core damage and unacceptable radiological consequences. A software VIP (Vital area Identification Package based on the PSA method) is being developed by KAERI for the VAI of nuclear power plants. Furthermore, the KAERI fault tree solver FTREX (Fault Tree Reliability Evaluation eXpert) is specialized for the VIP to generate the candidates of the vital areas. FTREX can generate numerous MCSs for a huge fault tree with the lowest truncation limit and all possible prevention sets.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.652-662
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• 2023

Identifying highly discriminating genes is a critical step in tumor recognition tasks based on microarray gene expression profile data and machine learning. Gene selection based on tree models has been the subject of several studies. However, these methods are based on a single-tree model, often not robust to ultra-highdimensional microarray datasets, resulting in the loss of useful information and unsatisfactory classification accuracy. Motivated by the limitations of single-tree-based gene selection, in this study, ensemble gene selection methods based on multiple-tree models were studied to improve the classification performance of tumor identification. Specifically, we selected the three most representative tree models: ID3, random forest, and gradient boosting decision tree. Each tree model selects top-n genes from the microarray dataset based on its intrinsic mechanism. Subsequently, three ensemble gene selection methods were investigated, namely multipletree model intersection, multiple-tree module union, and multiple-tree module cross-union, were investigated. Experimental results on five benchmark public microarray gene expression datasets proved that the multiple tree module union is significantly superior to gene selection based on a single tree model and other competitive gene selection methods in classification accuracy.

• The Journal of Korean Medicine
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• v.33 no.4
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• pp.1-8
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• 2012

Objectives: The purpose of this study was to specify major tongue diagnostic indicators and evaluate their significance in discriminating pattern identification subtypes in stroke patients. Methods: This study used a community based multi-center observational design. Participants (n=1,502) were stroke patients admitted to 11 oriental medical university hospitals between December 2006 and February 2010. To determine which tongue indicator affected each pattern identification, a decision tree analysis of the chi-square automatic interaction detector (CHAID) algorithm was performed. The chi-squared test was used as the criterion in splitting data with a p-value less than 0.05 for division, which is the main procedure for developing a decision tree. The minimum sample size for each node was specified as n =10, and branching was limited to two levels. Results: From the 9 tongue diagnostic indicators, 6 major tongue indicators (red tongue, pale tongue, yellow fur, white fur, thick fur, and teeth-marked tongue) were identified through the decision tree analysis. Furthermore, each pattern identification was composed of specific combinations of the 6 major tongue indicators. Conclusions: This study suggests that the 6 tongue indicators identified through the decision tree analysis can be used to discriminate pattern identification subtypes in stroke patients. However, it is still necessary to re-evaluate other pattern identification indicators to further the objectivity and reliability of traditional Korean medicine.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.1
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• pp.99-108
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• 2010

RFID(Radio Frequency IDentification) is a technology that automatically identifies objects containing the electronic tags by using radio wave. When there are some tags in the domain of the RFID reader, the mechanism that can solve a collision between the tags occurs is necessary. The multi tag identification problem is the core issue in the RFID and could be resolved by the anti-collision algorithm. However, RFID system has another problem. The problem id user information security. Tag response easily by query of reader, so the system happened user privacy violent problem by tag information exposure. In the case, RFID system id weak from sniffing by outside. In this paper, We study of security robustness for tree-walking algorithm, query tree algorithm and advanced query tree algorithm of tree based memoryless algorithm.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.247-249
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• 2007

Crown parameters are important roles in tree species identification, because the canopy is the aggregate of all the crowns. However, crown measurements with spaceborne image data have remained more difficult than on aerial photographs since trees show more structural detail at higher resolutions. This recognized problem led to the initiation of the research to determine if high resolution satellite image data could be used to identify and classify single tree species. In this paper, shape parameters derived from pixel-based crown area measurements and texture features derived from GLCM parameters in QuickBird image were tested and compared for individual tree species identification. As expected, initial studies have shown that the crown parameters and the canopy texture parameters provided a differentiating method between coniferous trees and broad-leaved trees within the compartment(less than forest stand) for single extraction from spaceborne high resolution image.