• Convergence Security Journal
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• v.1 no.1
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• pp.37-45
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• 2001

In this paper, separated and optimized pattern database model is proposed. In order to improve efficiency of Network-based IDS, pattern database is classified by proper basis. Classification basis is decided by the specific Intrusions validity on specific target. Using this model, IDS searches only valid patterns in pattern database on each captured packets. In result, IDS can reduce system resources for searching pattern database. So, IDS can analyze more packets on the network. In this paper, proper classification basis is proposed and pattern database classified by that basis is formed. And its performance is verified by experimental results.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.47 no.5
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• pp.335-340
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• 2002

To evaluate the efficiency of anther floating culture according to the maturing group, the varietal difference and classification of fifty varieties was conducted in N6 liquid medium containing 1mg $l^{-1}$ NAA, 0.25 mg $l^{-1}$ kinetin. The efficiency of callus induction was widely ranged from 0 to 113.4%, but the mean callus induction was not significantly different among maturing groups. The efficiency of anther floating culture showed the highest variation in early-maturing group among three maturing groups. The varieties with the best callus induction were Sambaegbyeo and Jinbuolbyeo, while the recalcitrant variety was Obongbyeo in early-maturing group. The efficiency of plant regeneration showed the highest trends in late-maturing group among three maturing groups. The fifty varieties were classified into three groups (distance=0.78) by cluster analysis based on the callus formation and plant regeneration. Group including only two varieties, Shinunbongbyeo and Sambaegbyeo had the excellent androgenic efficiency, and the medium efficiency of Group was included thirty-six varieties. Whereas twelve varieties, including three Tongil varieties were fell into the bad efficiency of Group. Especially, Tongil varieties containing Japonica rice, Obongbyeo were the recalcitrant genotypes for the anther floating culture.

• International Journal of Contents
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• v.14 no.1
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• pp.7-11
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• 2018

Digital technology has been changing everyday life of ordinary people let alone the structure of world industry. The elderly care service is also going through changes influenced by the unavoidable impact from torrents of digital technologies. There are numerous reports and news about the digital technologies increasing the efficiency and effectiveness of care service yet lacking systematic understanding of the sources of such improvement. This study aims to present a new classification framework for digital elderly care service innovation to fully utilize the power of digital technologies drawing on insights from innovation studies and service studies. First, 4 features of digital technologies are identified as sources of new value in service innovation. The co-creation of value by users and producers in service and technology development is discussed to illuminate users' contributions to service innovation. Communication of needs and ideas with producers and application of new technologies into everyday practice of life are identified as the source of new value which can be attributed to the elderly. Customization along with efficiency gains is the key to digital elderly care service innovation. The classification framework, thus, incorporates the needs of the elderly as one axis of criteria in the conventional technology-centered framework. The new classification framework would help give due weight to user-driven or demand-driven innovation in the elderly care service R&D activities.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.10 no.1
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• pp.243-268
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• 1999

The purpose of this study is to develop the classification scheme in subject-based directory search engine for educational research information on the web. Five classification systems. Yahoo Korea, Argus Clearinghouse, DDC, ERIC thesaurus and KEDI thesaurus were measured in terms of coverage of subject fields, system logic, accuracy of terminology and efficiency of searching. For the design of Classification Scheme, this study considered the content of subject areas, features of information resources and efficiency based on users. Finally, the Classification Scheme was established in terms of 16 main divisions and 47 sub-divisions in educational research information.

• Structural Engineering and Mechanics
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• v.75 no.6
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• pp.771-784
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• 2020

Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation. The efficiency, superiority and practicability of AGPC-IS are verified by three examples.

• Journal of Soil and Groundwater Environment
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• v.18 no.7
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• pp.41-53
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• 2013

The study is to propose the optimal separation technique of heavy metals (Pb and Zn) contaminated in soil for improving the removal efficiency by various applicable techniques. The heavy metal contaminated soil samples near abandoned mine X-1 and X-2 were used for the study. Firstly, the wet classification process was shown more than 80% of removal efficiency for lead and zinc. Meanwhile, the magnetic separation process was shown low removal efficiency for lead and zincs because those heavy metals were non-magnetic materials. For the next step, the flotation separation process was shown approximately 24.4% of removal efficiency for zinc, while the gravity concentration process was shown approximately 57% of removal efficiency for lead, and 19.9% of removal efficiency for zinc, respectively. Therefore, zinc contaminated in soil would be effectively treated by the combination technique of the wet classification and the flotation technique. Meanwhile, lead contaminated in soil would be effectively treated by the combination technique of the wet classification process and the flotation process. Furthermore, the extraction of organic matter was shown more effective with aeration, 3% of hydrogen peroxide and 3% of lime such as calcium hydroxide.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.2
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• pp.118-125
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• 2009

This paper reports the size classification of nanoparticles as well as electrical tuning techniques for the cut-off diameter and collection efficiency. Classifying particles < 100 nm in diameter is quite a technical challenge using a virtual impactor with the cut-off diameter being determined geometrically. However, the proposed virtual impactor can classify particles <100 nm and tune the cut-off diameter by electrically accelerating the particles. The cut-off diameter of the proposed device was tuned from 15 to 50nm.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.293-294
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• 2011

KISTI collects the scientific and technical articles published in Korea and builds the Korean STI database for scientists. The number of papers exceeds one million. To improve the search efficiency of the database additional processing is required. Abstracting, classification, indexing and extracting is a traditional processing method adding value to information. Indexing and classification are useful tool to assist efficient retrieval. In this paper, authors propose a method to improve information retrieval efficiency by assigning classification code and index terms to records of Korean STI database.

• Journal of KIBIM
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• v.13 no.4
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• pp.96-105
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• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• Journal of the Korea Safety Management & Science
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• v.2 no.3
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• pp.171-184
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• 2000

We may be given a set of observations with the classes or clusters. The aim of this article is to provide an up-to-date review of different approaches to classification, compare their performance on a wide range of challenging data-sets. In this paper, machine learning algorithm classifiers based on CART, C4.5, CAL5, FACT, QUEST and statistical discriminant analysis are compared on various datasets in classification error rate and algorithms.