• ETRI Journal
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• v.32 no.2
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• pp.184-194
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• 2010

Ethernet ring protection (ERP) technology, which is defined in ITU-T Recommendation G.8032, has been developed to provide carrier grade recovery for Ethernet ring networks. However, the filtering database (FDB) flush method adopted in the current ERP standard has the drawback of introducing a large amount of transient traffic overshoot caused by flooded Ethernet frames right after protection switching. This traffic overshooting is especially critical when a ring provides services to a large number of clients. According to our experimental results, the traditional FDB flush requires a link capacity about sixteen times greater than the steady state traffic bandwidth. This paper introduces four flush optimization schemes to resolve this issue and investigates how the proposed schemes deal with the transient traffic overshoot on a multi-ring network under failure conditions. With a network simulator, we evaluate the performance of the proposed schemes and compare them to the conventional FDB flush scheme. Among the proposed methods, the extended FDB advertisement method shows the fastest and most stable protection switching performance.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.939-947
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• 2016

As the number of legacy database systems and the size of data to manipulate have been vastly increased, it has become more difficult and complex to analyze characteristics of data. To improve the efficiency of data analysis and help administrators to make decisions in business life, BI(Business Intelligence) system is used. To construct data warehouse and cube from legacy database systems makes it easy and fast to transform raw data into integrated and categorized meaningful information. In this paper, we built a BI system for an University administration. Several source system databases were integrated to data warehouse to build data cubes. The implemented BI system shows much faster data analysis and reporting ability than the manipulation in legacy systems. It is especially efficient in multi dimensional data analysis, nonetheless in single dimensional analysis.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.129-136
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• 2015

We propose a hybrid face recognition to deal with illumination variation. For this, we extract discriminant features by using the different illumination invariant feature extraction methods. In order to utilize both advantages of each method, we evaluate the discriminant power of each feature by using the discriminant distance and then construct a composite feature with only the features that contain a large amount of discriminative information. The experimental results for the Multi-PIE, Yale B, AR and yale databases show that the proposed method outperforms an individual illumination invariant feature extraction method for all the databases.

• Computers and Concrete
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• v.21 no.5
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• pp.513-523
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• 2018

Time dependent strain due to creep is a significant factor in structural design. Multi-gene genetic programming (MGGP) and artificial neural network (ANN) are used to develop two models for prediction of creep compliance in concrete. The first model was developed by MGGP technique and the second model by hybridized MGGP-ANN. In the MGGP-ANN, the ANN is working in parallel with MGGP to predict errors in MGGP model. A total of 187 experimental data sets that contain 4242 data points are filtered from the NU-ITI database. These data are used in developing the MGGP and MGGP-ANN models. These models contain six input variables which are: average compressive strength at 28 days, relative humidity, volume to surface ratio, cement type, age at start of loading and age at the creep measurement. Practical equation based on MGGP was developed. A parametric study carried out with a group of hypothetical data generated among the range of data used to check the generalization ability of MGGP and MGGP-ANN models. To confirm validity of MGGP and MGGP-ANN models; two creep prediction code models (ACI209 and CEB), two empirical models (B3 and GL 2000) are used to compare their results with NU-ITI database.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.5
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• pp.526-538
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• 2007

Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.149-152
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• 1998

Nowadays, GIS, as multi-discipline information system, is closely linked with GPS application in conjunction with GIS-T or Logistics GIS. With this R&D trend. CPS/GIS application system for AVL is newly developed in this study. This AVL is designed and implemented by using pure Java computing technology towards com ing Car-equipped wireless Internet PC age, and main features of Java are included at this system: Platform independence, Multi-thread processing, and Object-oriented paradigm. While, because core modules of this AVL are based on GIS spatial engine, unlike other commercial AVLs, large spatial database problem handling digital image/spatial information and attribute information and direct access problem of GIS data is easily dealt with. this system can directly access external database by using JDBC: MS Access for desktop version and Oracle for W/S version. Finally, it is thought that Java-based AVL, one of CPS/CIS applications, can be easily extended into other prospective GIS applications: Land surveyor supporting system, Flight tracking system, 3D facility management system with CPS, and so forth.

• Archives of design research
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• v.20 no.2 s.70
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• pp.103-116
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• 2007

Art education in design has repeatedly stressed the importance of developing creativity. In the digital period, however, which shows rapid change in both forms and contents, it needs to be equipped with more flexible and systematic ways of approaching to the creativity development, especially involved with cultural diversity of the digital world. This paper primarily proposes a maximally efficient, productive creativity learning program in which the integration of expressive media and communication generates a comprehensive network of communicative information in the development of digital technologies, which, consequently, brings forth valuable cultural contents of art. The amalgamation of Won (2006)'s Prism Effect, with distinctive three devices, and the facilitator factors, with two different facilitators such as self-controlled and controlled plays, would function as a catalyst for cultural diversity in the digital forms and contents of art. And this will, consequently, result in producing a number of practices that can be classified and assorted for a later performance. This paper thus suggests a roadmap of how to develop the creativity learning program in which two categories of facilitators based on three thinking devices function to classify four activities. In addition, selected activities are shaped as a creativity learning program by generating learning practices with the formalizing instructional strategy that fit into a specialized educational environment and learners. The samples of loaming practice design show guidelines for practice and the results of learning activity. Therefore, the eventual goal of this paper would be to establish a creativity learning program that constitutes a highly systematized and modularized database to maximize the efficiency and productivity of the creativity development.

• Mycobiology
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• v.48 no.5
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• pp.373-382
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• 2020

Laccases (EC 1.10.3.2), a group of multi-copper oxidases (MCOs), play multiple biological functions and widely exist in many species. Fungal laccases have been extensively studied for their industrial applications, however, there was no database specially focused on fungal laccases. To provide a comparative genomics platform for fungal laccases, we have developed a comparative genomics platform for laccases and MCOs (http://laccase.riceblast.snu.ac. kr/). Based on protein domain profiles of characterized sequences, 3,571 laccases were predicted from 690 genomes including 253 fungi. The number of putative laccases and their properties exhibited dynamic distribution across the taxonomy. A total of 505 laccases from 68 genomes were selected and subjected to phylogenetic analysis. As a result, four clades comprised of nine subclades were phylogenetically grouped by their putative functions and analyzed at the sequence level. Our work would provide a workbench for putative laccases mainly focused on the fungal kingdom as well as a new perspective in the identification and classification of putative laccases and MCOs.

• Journal of IKEEE
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• v.22 no.4
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• pp.933-940
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• 2018

In this paper, we propose a multi-block deep learning structure for improving face recognition rate. The recognition structure of the proposed deep learning consists of three steps: multi-blocking of the input image, multi-block selection by facial feature numerical analysis, and perform deep learning of the selected multi-block. First, the input image is divided into 4 blocks by multi-block. Secondly, in the multi-block selection by feature analysis, the feature values of the quadruple multi-blocks are checked, and only the blocks with many features are selected. The third step is to perform deep learning with the selected multi-block, and the result is obtained as an efficient block with high feature value by performing recognition on the deep learning model in which the selected multi-block part is learned. To evaluate the performance of the proposed deep learning structure, we used CAS-PEAL face database. Experimental results show that the proposed multi-block deep learning structure shows 2.3% higher face recognition rate than the existing deep learning structure.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.684-698
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• 2004

The Hippocratic database model recently proposed by Agrawal et al. incorporates privacy protection capabilities into relational databases. Since the Hippocratic database is based on the relational database, it needs extensions to be adapted for XML databases. In this paper, we propose the Hippocratic XML database model, an extension of the Hippocratic database model for XML databases and present an efficient access control mechanism under this model. In contrast to relational data, XML data have tree-like hierarchies. Thus, in order to manage these hierarchies of XML data, we extend and formally define such concepts presented in the Hippocratic database model as privacy preferences, privacy policies, privacy authorizations, and usage purposes of data records. Next, we present a new mechanism, which we call the authorization index, that is used in the access control mechanism. This authorization index, which is Implemented using a multi-dimensional index, allows us to efficiently search authorizations implied by the authorization granted on the nearest ancestor using the nearest neighbor search technique. Using synthetic and real data, we have performed extensive experiments comparing query processing time with those of existing access control mechanisms. The results show that the proposed access control mechanism improves the wall clock time by up to 13.6 times over the top-down access control strategy and by up to 20.3 times over the bottom-up access control strategy The major contributions of our paper are 1) extending the Hippocratic database model into the Hippocratic XML database model and 2) proposing an efficient across control mechanism that uses the authorization index and nearest neighbor search technique under this model.