• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.333-340
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• 2002

Embedding is a mapping an interconnection network G to another interconnection network H. If a network G can be embedded to another network H, algorithms developed on G can be simulated on H. In this paper, we first propose a method to embed between Hierarchical Cubic Network HCN(n, n) and Hierarchical Folded-hypercube Network HFN(n, n). HCN(n, n) and HFN(n, n) are graph topologies having desirable properties of hypercube while improving the network cost, defined as degree${\times}$diameter, of Hypercube. We prove that HCN(n, n) can be embedded into HFN(n, n) with dilation 3 and congestion 2, and the average dilation is less than 2. HFN(n, n) can be embedded into HCN(n, n) with dilation 0 (n), but the average dilation is less than 2. Finally, we analyze the fault tolerance of HCN(n, n) and prove that HCN(n, n) is maximally fault tolerant.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.108-121
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• 2004

In this paper, we propose an enhanced snapshot technique that solves performance degradation when snapshot is initiated for the storage cluster system. However, traditional snapshot technique has some limits adapted to large amount storage shared by multi-hosts in the following aspects. As volume size grows, (1) it deteriorates crucially the performance of write operations due to additional disk access to verify COW is performed. (2) Also it increases excessively the blocking time of write operation performed during the snapshot creation time. (3)Finally, it deteriorates the performance of write operations due to additional disk I/O for mapping block caused by the verification of COW. In this paper, we propose an efficient snapshot technique for large amount storage shared by multi-hosts in SAN Environments. We eliminate the blocking time of write operation caused by freezing while a snapshot creation is performing. Also to improve the performance of write operation when snapshot is taken, we introduce First Allocation Bit(FAB) and Snapshot Status Bit(SSB). It improves performance of write operation by reducing an additional disk access to volume disk for getting snapshot mapping block. We design and implement an efficient snapshot technique, while the snapshot deletion time, improve performance by deallocation of COW data block using SSB of original mapping entry without snapshot mapping entry obtained mapping block read from the shared disk.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1464-1479
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• 2018

In face recognition, sometimes the number of available training samples for single category is insufficient. Therefore, the performances of models trained by convolutional neural network are not ideal. The small sample face recognition algorithm based on novel Siamese network is proposed in this paper, which doesn't need rich samples for training. The algorithm designs and realizes a new Siamese network model, SiameseFacel, which uses pairs of face images as inputs and maps them to target space so that the $L_2$ norm distance in target space can represent the semantic distance in input space. The mapping is represented by the neural network in supervised learning. Moreover, a more lightweight Siamese network model, SiameseFace2, is designed to reduce the network parameters without losing accuracy. We also present a new method to generate training data and expand the number of training samples for single category in AR and labeled faces in the wild (LFW) datasets, which improves the recognition accuracy of the models. Four loss functions are adopted to carry out experiments on AR and LFW datasets. The results show that the contrastive loss function combined with new Siamese network model in this paper can effectively improve the accuracy of face recognition.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.69-74
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• 2003

This study is aimed to develop a system to position and manage object flow in real time. Logistics management system which position objects and vans using GPS is required to load, unload and keep freight effectively and in real time at sea or airport. In this study, a management system which is consisted of five sub-systems is developed; GPS position analysis system, GPS interface system, mapping system, network system and database management system.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.815-818
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• 2003

Ad Hoc 네트워크는 이동하는 노드들이 무선 환경에서 상호 연결되어 네트워크를 구성하는 기술이다. Ad Hoc 네트워크는 패킷 라우팅과 서비스 중에 노드들의 단절 현상이 발생한다. 각 노드들의 위치 정보를 파악하면 이러한 현상을 미리 예측하여 회피하거나 복구하기 쉽다. 일반적으로는 GPS를 이용하여 위치 정보를 파악하지만 본 논문에서는 CPS를 사용하지 않고 전체적인 노드들이 가지고 있는 상대적인 정보만을 이용하여 이동 노드들의 전체적인 위치 정보를 표현하는 방식을 제안한다. 제안하는 방법은 기존 시스템을 소프트웨어적으로 보완가능 하므로 구축이 간단하고 구축비용을 절감할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1028-1033
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• 1991

This paper describes the design of a neural network estimator to estimate weld pool sizes for on-line use of quality monitoring and control in GMA welding processes. The estimator utilizes surface temperatures measured at various points on the top surface of the weldment as its input. The main task of the neural net is to realize the mapping characteristics from the point temperatures to the weld pool sizes through training, A series of bead-on plate welding experiments were performed to assess the performance of the neural estimator.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1232-1235
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• 2002

An experiment on the automatic population measurement of brown Mealy Bugs is first reported in this article. Several image processing techniques are employed along with mapping function and neural network. Though brown Mealy Bugs are difficult to detect because of their camouflage, the experimental results showed that approximately 74% of them were correctly detected.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.484-489
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• 1992

The inference of fuzzy controller can be considered a mapping from the controller input to membership value. The membership value, a kind of weight, has a role to decide if the input is appropriate to the rule. The membership function is described by several values, which are decided by a learning method. The learning method is adopted from adaptive filtering theory. The simulation shows the proposed fuzzy controller can learn linear and nonlinear functions. the structure of the proposed fuzzy controller becomes a kind of neural network.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.271-273
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• 2004

소형, 저가, 저전력의 센서노드와 무선 네트워크가 접목된 센서 네트워크 기술에 대한 연구가 활발히 진행되고 있다. 그러나, 기존의 센서 네트워크는 인터넷에 접속되지 않으므로 센서 네트워크의 서비스를 원격으로 이용할 수 없다는 문제점이 있다. 이에 본 논문에서는 센서 네트워크와 인터넷 망을 연동하여 센서 네트워크 서비스를 제공하는 센서 네트워크 게이트웨이를 설계하고 구현하였다. 센서 네트워크 게이트웨이는 인터넷 망의 IT 주소 및 소켓 정보를 센서 노드들의 주소와 맵핑함으로써 외부의 인터넷 망에서도 센서 네트워크에 접근할 수 있게 한다.

• Journal of the Chungcheong Mathematical Society
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• v.34 no.3
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• pp.221-234
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• 2021

We introduce high-order Hopfield neural networks with Leakage delays. Furthermore, we study the uniqueness and existence of Hopfield artificial neural networks having the weighted pseudo almost periodic forcing terms on finite delay. Our analysis is based on the differential inequality techniques and the Banach contraction mapping principle.