• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.41-51
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• 1996

In this paper, anew parallel processing system based on a cluster architecture which provides scalability of a parallel processing system while maintains shared memory multiprocessor characteristics is proposed. In recent days low cost, high performnce microprocessors have led to construction of large scale parallel processing systems. Such parallel processing systems provides large scalability but are mainly used for scientific applications which have large data parallelism. A shared memory multiprocessor system like TICOM is currently used as aserver for the commercial application, however, the shared memory multiprocessor system is known to have very limited scalability. The proposed architecture can support scalability and performance of the parallel processing system while it provides adaptability for the commerical application, hence it can overcome the limitation of the shared memory multiprocessor. The architecture and characteristics of the proposed system shall be described. A proprietary hierarchical crsossbar network is designed for this system, of which the protocol, routing and switching technique and the signal transfer technique are optimized for the proposed architecture. The design trade-offs for the network are described in this paper and with simulation usihng the SES/workbench, it is explored that the network fits to the proposed architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.405-414
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• 1999

The auger and screw piles have known an important evolution during the last decade. Besides the large success of augercast (CFA) piling systems, new systems have been developed combining, to a variable extent, the classical extraction auger with especially designed displacement tools in order to develop screw piles with partial or total lateral soil displacement. These last developments cover the whole range of lateral soil displacement and are more difficult than ever to compare. The authors present the latest evolutions in auger piling systems and compare them with respect to penetration performances, bearing capacities and amount of spoil generated. A special focus is given to a new efficient system: the OMEGA(H) pile in use in Korea since 1997. The results of the Hongcheon site are presented where this R system was applied for a new investment of the Korean National Housing Corporation (KNHC). This first important experience, with the execution of some 1,500 Omega piles with diameter 410 mm, is presented. The piles were installed through loose silty sands down to very dense sands and layers of gravel. The results of full-scale load tests are analysed and show the conformity with requirements of the clients.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1392-1403
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• 2015

The rapid development of both communication traffic and increasing optical network sizes has increased energy consumption. Traditional algorithms and strategies don't apply to controlling the expanded network. Immunization algorithms originated from the complex system theory are feasible for large-scale systems based on a scale-free network model. This paper proposes the immunization strategy for complex systems which includes random and targeted immunizations to solve energy consumption issues and uses traffic to judge the energy savings from the node immunization. The simulation results verify the effectiveness of the proposed strategy. Furthermore, this paper provides a possibility for saving energy with optical transmission networks.

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.137-144
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• 2005

Many reliable group communication algorithms were presented to satisfy predetermined message ordering properties in small or medium-scale distributed systems. However, the previous algorithms with their strong reliability properties may be unappropriate for large-scale systems. To address this issue, some epidemic-style group communication algorithms were proposed for considerably improving scalability while guaranteeing the reasonably weaker reliability property than the existing ones. The algorithms are all designed for ensuring the atomic order message delivery property. But, some distributed applications such as multimedia systems and collaborative work, may require only the weaker message ordering property, i.e., causal order delivery. This paper proposes an efficient epidemic-style group communication algorithm ensuring causal order delivery to provide the indigenous scalability of the epidemic-style approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1415-1419
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• 2008

In this paper, we investigate various Audio Transmission Systems to implement Audio Transmission System based on AoIP of Internet transmission technology TCP/IP Network and we design and implement a Audio transmission system based on AoIP by adopting the most efficient one. The implemented system can be applied for various professional audio systems with large-scale audio distribution network as well as small-scale PA systems. Moreover, this can be applied in various fields which need audio transmission.

• Earthquakes and Structures
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• v.16 no.5
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• pp.513-522
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• 2019

A long-span transmission tower-line system is indispensable for long-distance electricity transmission across a large river or valley; hence, the failure of this system, especially the collapse of the supporting towers, has serious impacts on power grids. To ensure the safety and reliability of transmission systems, this study experimentally and numerically investigates the collapse failure of a 220 kV long-span transmission tower-line system subjected to severe earthquakes. A 1:20 scale model of a transmission tower-line system is constructed in this research, and shaking table tests are carried out. Furthermore, numerical studies are conducted in ABAQUS by using the Tian-Ma-Qu material model, the results of which are compared with the experimental findings. Good agreement is found between the experimental and numerical results, showing that the numerical simulation based on the Tian-Ma-Qu material model is able to predict the weak points and collapse process of the long-span transmission tower-line system. The failure of diagonal members at weak points constitutes the collapse-inducing factor, and the ultimate capacity and weakest segment vary with different seismic wave excitations. This research can further enrich the database for the seismic performance of long-span transmission tower-line systems.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.673-687
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• 2023

Convolutional neural network-based deep learning technology is the most commonly used in image identification, but it requires large-scale data for training. Therefore, application in specific fields in which data acquisition is limited, such as in the military, may be challenging. In particular, the identification of ground weapon systems is a very important mission, and high identification accuracy is required. Accordingly, various studies have been conducted to achieve high performance using small-scale data. Among them, the ensemble method, which achieves excellent performance through the prediction average of the pre-trained models, is the most representative method; however, it requires considerable time and effort to find the optimal combination of ensemble models. In addition, there is a performance limitation in the prediction results obtained by using an ensemble method. Furthermore, it is difficult to obtain the ensemble effect using models with imbalanced classification accuracies. In this paper, we propose a transfer learning-based feature fusion technique for heterogeneous models that extracts and fuses features of pre-trained heterogeneous models and finally, fine-tunes hyperparameters of the fully connected layer to improve the classification accuracy. The experimental results of this study indicate that it is possible to overcome the limitations of the existing ensemble methods by improving the classification accuracy through feature fusion between heterogeneous models based on transfer learning.

• Journal of IKEEE
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• v.22 no.1
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• pp.136-142
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• 2018

Recently, as the development system has become larger, sequential simulation methods have become impossible to verify systems that take a long time or require real time results. Therefore, a study of a distributed simulation system that simulates several processes has been conducted. In order to simulate real-time systems, efficient data exchange between distributed systems is required. Data Distribution Service is a data-oriented communication middleware proposed by Object Management Group and provides efficient data exchange and various QoS. However, in a large-scale distributed simulation environment distributed over a wide area, there is a problem of Participant Discovery and QoS guarantee due to domain separation in data exchange. Therefore, in this paper, we propose a DDS/SDN architecture that can guaranteed QoS and effective Participant Discovery in an SDN-based network.

• Fire Science and Engineering
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• v.27 no.6
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• pp.115-121
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• 2013

Industrial facilities are becoming bigger and more up to date, And a kind of the hazardous material used in the industrial filed is diversified. Therefore, serious accidents such as leakage of toxic materials, fire and explosion, is continuously occurred. There is Process Safety Management (PSM) system of the several preventive systems, but it is supposed to be a limitation to ensure safety or huge PSM industrial sites where have potential to catastrophically invisible and unexpected risks because it is still being managed by instruction and inspection of authority having jurisdiction other than self-regulating management differing from the primarily aim of PSM system. To verify safety management system of work-place, supplementation of existing system is urgently required. In this study, it suggests that PSM self-audit be emphasized significantly analyzing problems of the current systems for enhancing self-audit be emphasized significantly analyzing problems of the current systems for enhancing self-control safety through efficient self-audit management and improving the existing system and improving the existing as verifying the system there of, as well as studying methods which can support institutionally.