• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.394-400
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• 2002

Networks of Workstations(NOWs), that has features of flexibility and scalability, recently has emerged as an inexpensive alternative to massively parallel multicomputers. However it is not easier to perform deadlock-free multicast than regular topologies like mash or hypercube. Single phase differential multicast(SPDM) is a modified multicast algorithm with less burden of the root node. By applying quality of serviece(QoS), a specific node can have differentiated service and artificial change of message flow pattern is also available. As the results of performance evaluation experiments, SPDM has lower latency and lower packet concentration rate of the root node than the case of SPAM, and has ability to control network load distribution among switch nodes by controlling the assignment rate among nodes.

• Korean Journal of Labor Studies
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• v.24 no.2
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• pp.137-179
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• 2018

To reduce labor market discrimination, there are lively discussions about the role of extant labor regime based on labor unions. It includes both the critical perspective on extant labor movement and the necessity of new actors for resolving discriminations within labor market. Among new actors, the present study focuses on contingent labor centers. Specifically, we have investigated on the development and identity of contingent labor centers as coalition of local government-labor organization. The core content of this study is to reconstruct the activities and strategies of contingent labor centers throughout the longitudinal approach. From many evidences, we can confirm that contingent labor centers have evolved via three phases such as differentiation, de- politicizing, and networks. This finding also provides insights about inside relationships between contingent labor centers and outside tensions between contingent labor center and extant labor organizations. We finally discuss on the theoretical implications of contingent labor center as new actor for contingent worker movement.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.554-556
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• 2003

인터넷에서 널리 사용되는 HTML은 현재 데이터베이스 시스템과 같은 저장소 대신, 전형적인 파일 시스템에 저장되는 경우가 대부분이다. 마찬가지로 최근에 인터넷 상에서의 데이터 교환 및 표현의 표준으로 부각되는 XML 역시 파일 시스템에 저장되는 경우가 많다. 하지만, XML 문서의 비정규적인 구조와 장황성 때문에. 디스크 공간이나 네트워크 대역폭이 정규적인 구조의 데이터에 비해 비효율적이다. 따라서. 이를 해결하고자. XML 문서의 압축에 관한 연구가 진행되었다. 하지만. 최근에 연구된 XML 압축 기법들은 압축한 XML 문서에 대한 질의를 지원하지 않거나, 질의를 지원하더라도 XML 문서의 데이터 값들의 특성을 고려하지 않고 단순히 기존의 압축 방법을 통해 XML 문서를 압축한다. 그러므로 본 연구에서는 압축한 XML 문서에 대한 질의를 효율적으로 지원하는 XML 압축 기법을 제안한다. 본 연구에서는 태그를 Dictionary 압축으로 압축하며 태그 별로 데이터 값들의 타입을 추출하여 추출한 타입에 적절한 압축 방법으로 데이터 값을 압축한다. 또한, 제안하는 압축 기법의 구현 및 성능 평가를 통하여. 구현한 시스템이 실생활에 사용되는 XML 문서들을 효율적으로 압축하며 향상된 질의 성능을 제공하는 것을 보인다.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.561-566
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• 2018

최근 신경망 번역 모델에 주의 집중 네트워크가 제안되어 기존의 기계 번역 모델인 규칙 기반 번역 모델, 통계적 번역 모델에 비해 높은 번역 성능을 보이고 있다. 그러나 주의 집중 네트워크가 잘못 모델링되는 경우 과소 번역 현상이 나타난다. 신경망 번역 모델에 커버리지 메커니즘을 추가하여 과소 번역 현상을 완화하는 연구가 진행되었으나 이는 모델의 구조를 변경해야하는 불편함이 있다. 본 논문에서는 신경망 번역 모델의 구조를 변경하지 않고 새로운 손실 함수를 정의하여 과소 번역 현상을 완화하는 방법을 제안한다. 한-영 번역 실험을 통해 제안한 주의 집중 네트워크의 정규화 방법이 커버리지 메커니즘의 목적을 효율적으로 달성함을 보인다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.135-142
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• 2015

This paper analyzed the effects of changes in temporary workers on firm performances, and the effects of different workforce portions of business functions on corporate performances, respectively, using Korean venture business survey conduected in 2013. Results show that the performance of venture businesses decreases significantly, as the portion of temporary workers increases, which is more pronounced in small companies than in medium companies. In addition, the portions of workforce for administration, R&D, production, and sales don't have uniform effect on firm performance, where medium companies are affected significantly by the portions of production and sales, while small companies do not show significant relationship. This analysis implies that innovative firms, based on knowledge workers, need to use caution when they plan to increase temporary workers, which may lead to lower performance. However, we need further research for the basic causes of the possible lower performance.

• Journal of KIISE
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• v.44 no.7
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• pp.668-673
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• 2017

Deep neural networks have shown remarkable performance in various fields of pattern recognition such as voice recognition, image recognition and object detection. However, underlying mechanisms of the network have not been fully revealed. In this paper, we focused on empirical analysis of the network parameters. The Faster R-CNN(region-based convolutional neural network) was used as a baseline network of our work and three important parameters were analyzed: the dropout ratio which prevents the overfitting of the neural network, the size of the anchor boxes and the activation function. We also compared the performance of dropout and batch normalization. The network performed favorably when the dropout ratio was 0.3 and the size of the anchor box had not shown notable relation to the performance of the network. The result showed that batch normalization can't entirely substitute the dropout method. The used leaky ReLU(rectified linear unit) with a negative domain slope of 0.02 showed comparably good performance.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.583-588
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• 2009

Network intrusion detection system (NIDS) monitors all incoming packets in the network and detects packets that are malicious to internal system. The NIDS should also have ability to update detection rules because new attack patterns are unpredictable. Incorporating FPGAs into the NIDS is one of the best solutions that can provide both high performance and high flexibility comparing with other approaches such as software solutions. In this paper we propose and design a novel approach, prefix sharing parallel pattern matcher, that can not only minimize additional resources but also maximize the processing performance. Experimental results showed that the throughput for 16-bit input is twice larger than for 8-bit input but the used LEs/Char in FPGA increases only 1.07 times.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.387-395
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• 2006

홈 네트워크는 유비쿼터스의 여러 응용분야 중 활발하게 연구 구현되고 있는 분야 중의 하나로, 최근 아파트 건설업체, 가전기기 업체, 통신서비스 업체들이 지능성을 갖춘 스마트 홈을 목적으로 다양한 시험제품과 솔루션을 출시 흑은 제시하면서 이를 자사의 중요한 마케팅전략으로 활용하고 있다. 스마트 홈 네트워크를 구성하는 다양한 스마트 홈 기기의 제품 경쟁력은 제품이 얼마나 지능성을 갖추어 사용자에게 편리성과 유용성을 제공할 수 있는가의 여부가 중요한 관건이 되고 있다. 따라서 지능형 홈 기기의 지능에 대한 측정기준 마련이 필요한 시점이다. 본 연구에서는 스마트 홈 네트워크를 구성하는 여러 요소 중에서 정보가전기기를 지능성 측정 대상으로 하여 지능등급 부여모델을 개발하고자 한다. 지능형 홈 기기의 지능을 측정하기 위하여 로봇분야의 다양한 문헌 고찰을 토대로 지능성 측정에 필요한 핵심 구성요소를 도출 및 재 정의하여 등급모델을 설계하였다. 특히 설계된 등급부여모델의 실질적 이용을 위해서는 평가방식에 있어서 계량화 절차가 요구된다. 따라서 평가모델의 특성상 다차원적인 지능성의 속성을 총합적으로 나타내기 위하여 퍼지이론(Fuzzy Theory)을 사용하였으며, 이를 정규화하기 위해 퍼지적분(Fuzzy Integral)을 이용하였다. 산출된 적분값을 다시 비퍼지화하여 지능성 등급을 부여하는 모델을 개발하였다. 제시된 지능성 등급부여 모델은 스마트 홈 네트워크 산업의 발전을 촉진하는 계기가 될 수 있으리라 기대한다.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.379-388
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• 2007

Disordered streams may cause inaccurate or delayed results in window-based queries. Existing approaches usually leverage buffers to hand]e the streams. However, most of the approaches estimate the buffer size simply based on the maximum network delay in the streams, which tends to over-estimate the buffer size and result in high latency. In this paper, we propose a probabilistic approach to estimate the buffer size adaptively according to the fluctuated network delays. We first assume that intervals of tuple generations follow an exponential distribution and network delays have a normal distribution. Then, we derive an estimation function from the assumptions. The function takes a drop ratio as an input parameter, which denotes a percentage of tuple drops permissible during query execution. By describing the drop ratio in a query specification, users can control the quality of query results such as accuracy or latency according to application requirements. Our experimental results show that the proposed function has better adaptivity than the existing function based on the maximum network delay.

• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.52-61
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• 2013

In wireless sensor networks, the geographical positioning scheme is one of core technologies for sensor applications such as disaster monitoring and environment monitoring. For this reason, studies on range-free positioning schemes have been actively progressing. The density probability scheme based on central limit theorem and normal distribution was proposed to improve the location accuracy in non-uniform sensor network environments. The density probability scheme measures the final positions of unknown nodes by estimating distance through the sensor node communication. However, it has a problem that all of the neighboring nodes have the same 1-hop distance. In this paper, we propose an efficient sensor positioning scheme that overcomes this problem. The proposed scheme performs the second positioning step through the sensing range control after estimating the 1-hop distance of each node in order to minimize the estimation error. Our experimental results show that our proposed scheme improves the accuracy of sensor positioning by about 9% over the density probability scheme and by about 48% over the DV-HOP scheme.