• International Journal of Contents
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• v.5 no.2
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• pp.43-52
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• 2009

The article first presents a broad overview of the design and management for survivable network. We review the concept of network survivability, various protection and restoration schemes. Also we introduce design architectures of Quantitative model and a Survivable Ad hoc and Mesh Network Architecture. In the other side of study like these(traditional engineering approach), there is the concept of the survivable network systems based on an immune approach. There is one sample of the dynamic multi-routing algorithms in this paper.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.89-94
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• 2002

In this paper, a protection system using a Multi-Agent concept for power distribution networks is proposed. Every digital over current relay(OCR) is developed as an agent by adding its own intelligence, self-tuning and communication ability. The main advantage of the Multi-Agent concept is that a group of agents work together to achieve a global goal which is beyond the ability of each individual agent. In order to cope with frequent changes in the network operation condition and faults, an OCR agent, suggested in this paper, is able to detect a fault or a change in the network and find its optimal parameters for protection in an autonomous manner considering information of the whole network obtained by communication between other agents. Through this kind of coordination and information exchanges, not only a local but also a global protective scheme is completed. Simulations in a simple distribution network show the effectiveness of the suggested protection system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.179-182
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• 2008

웹의 방대한 데이터에서 사용자에게 유용한 정보를 제공하기 위하여 다양한 연구가 시도되고 있다. 웹 사용 마이닝은 웹 사용자의 로그 정보를 기반으로 웹페이지를 평가할 수 있는 유용한 방법이다. 하지만 웹 사용 마이닝을 이용한 웹 페이지 평가에는 사용자들의 다양한 성향 패턴을 무시한 일괄적인 모델을 생성하는데 주를 이루고 있다. 본 논문은 사용자 관심 키워드에 대한 웹 페이지 사용 정보를 수집하고 분석하여 멀티 컨셉 네트워크(Multi Concept Network : MC-Net)를 생성한다. MC-Net은 사용자 관심 키워드에 기반한 다양한 성향 정보에 따른 웹 페이지 연결망을 제공한다. 생성된 MC-Net은 웹 페이지 추천을 위하여 유용하게 사용할 수 있으며, 실험을 통하여 제안하는 방법의 유효함을 확인하였다.

• Journal of Industrial Technology
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• v.27 no.B
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• pp.43-51
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• 2007

In mobile multi-hop wireless networks, the authentication between a base station and a mobile multi-hop node, between multi-hop nodes, and between user a station and a multi-hop node is needed for the reliable and secure network operation. In this paper, we survey various authentication schemes which can be considered to be adopted in mobile multi-hop wireless networks and propose a concept of novel mutual authentication scheme applicable to mobile multi-hop network architecture. The scheme should resolve the initial trust gain problem of a multi-hop node at its entry to the network, the problem of rogue mobile multi-hop node and the problem of hop-by-hop authentication between multi-hop nodes. Effectively, the scheme is a hybrid scheme of the distributed authentication method and the centralized authentication method which are considered to be deployed in the wireless ad-hoc network and the wireless network connected to wired authentication servers, respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.10a
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• pp.175-184
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• 1993

Modeling the production process is a necessary and essential aspect of the production planning. This paper introduces a theoretical model of the multi-stage production process. A multi-stage production process is regarded as a network of interrelated production activities which use system exogenous inputs of goods in production and the intermediate products transfers between activities to produce final products. Our model is characterized by (1) a few of the production-related assumptions and (2) two types of elements "goods and activities" that are represented in terms of the network terminology. This model is different from the another multi-stage production models, so-called production network models in relation to the production-theoretical concept. It is not based on the concept of the production correspondence and the activity production functions, but the technology model of Koopmans. Koopmans.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.397-404
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• 2002

In this paper, it is proposed wavelet neural network using the fuzzy concept with the fuzzy and the multi-resolution analysis(MRA) of wavelet transform. Also, it wishes to improve any nonlinear function learning approximation using this system. Here, the fuzzy concept is used the bell type fuzzy membership function. And the composition of wavelet has a unit size. It is used the backpropagation algorithm for learning of wavelet neural network using the fuzzy concept. It is used the multi-resolution analysis of wavelet transform, the bell type fuzzy membership function and the backpropagation algorithm for learning. This structure is confirmed to be improved approximation performance than the conventional algorithms from one dimension and two dimensions function through simulation.

• International Journal of Knowledge Content Development & Technology
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• v.9 no.3
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• pp.23-41
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• 2019

This study combines the concept of degree centrality in complex network with the Term Frequency $^*$ Proportional Document Frequency ($TF^*PDF$) algorithm; the combined method, called PMCN (PDF-Modified similarity and Complex Network), constructs relationship networks among sentences for writing news summaries. The PMCN method is a multi-document summarization extension of the ideas of Bun and Ishizuka (2002), who first published the $TF^*PDF$ algorithm for detecting hot topics. In their $TF^*PDF$ algorithm, Bun and Ishizuka defined the publisher of a news item as its channel. If the PDF weight of a term is higher than the weights of other terms, then the term is hotter than the other terms. However, this study attempts to develop summaries for news items. Because the $TF^*PDF$ algorithm summarizes daily news, PMCN replaces the concept of "channel" with "the date of the news event", and uses the resulting chronicle ordering for a multi-document summarization algorithm, of which the F-measure scores were 0.042 and 0.051 higher than LexRank for the famous d30001t and d30003t tasks, respectively.

• Smart Structures and Systems
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• v.5 no.4
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• pp.415-426
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• 2009

This study focuses on the concept of multi-scale wireless sensor networks for damage detection in civil infrastructure systems by first over viewing the general network philosophy and attributes in the areas of data acquisition, data reduction, assessment and decision making. The data acquisition aspect includes a scalable wireless sensor network acquiring acceleration and strain data, triggered using a Restricted Input Network Activation scheme (RINAS) that extends network lifetime and reduces the size of the requisite undamaged reference pool. Major emphasis is given in this study to data reduction and assessment aspects that enable a decentralized approach operating within the hardware and power constraints of wireless sensor networks to avoid issues associated with packet loss, synchronization and latency. After over viewing various models for data reduction, the concept of a data-driven Bivariate Regressive Adaptive INdex (BRAIN) for damage detection is presented. Subsequent examples using experimental and simulated data verify two major hypotheses related to the BRAIN concept: (i) data-driven damage metrics are more robust and reliable than their counterparts and (ii) the use of heterogeneous sensing enhances overall detection capability of such data-driven damage metrics.

• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.33-38
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• 2018

Although deep neural network-based acoustic models have greatly improved the performance of automatic speech recognition (ASR), reverberation still degrades the performance of distant speech recognition in indoor environments. In this paper, we adopt the DenseNet, which has shown great performance results in image classification tasks, to improve the performance of reverberant speech recognition. The DenseNet enables the deep convolutional neural network (CNN) to be effectively trained by concatenating feature maps in each convolutional layer. In addition, we extend the concept of multi-resolution CNN to multi-resolution DenseNet for robust speech recognition in reverberant environments. We evaluate the performance of reverberant speech recognition on the single-channel ASR task in reverberant voice enhancement and recognition benchmark (REVERB) challenge 2014. According to the experimental results, the DenseNet-based acoustic models show better performance than do the conventional CNN-based ones, and the multi-resolution DenseNet provides additional performance improvement.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.299-301
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• 2003

In this paper, a protection system using Multi-Agent concept for power distribution network is proposed. Multi agent system consist of Feeder agent, OCR(Over Current Relay) agent, Recloser agent and Switch agent. An agent calculates and corrects its parameter by itself through communication with neighboring agents and its own intelligence algorithm. Simulations in a simple distribution network show the effectiveness of the suggested protection system. Multi-Agent System, protection of distribution network, Communication.