• Journal of Computing Science and Engineering
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• 제6권3호
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• pp.179-192
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• 2012

This paper presents novel statistical algorithms for protecting the iTrust information retrieval network against malicious attacks. In iTrust, metadata describing documents, and requests containing keywords, are randomly distributed to multiple participating nodes. The nodes that receive the requests try to match the keywords in the requests with the metadata they hold. If a node finds a match, the matching node returns the URL of the associated information to the requesting node. The requesting node then uses the URL to retrieve the information from the source node. The novel detection algorithm determines empirically the probabilities of the specific number of matches based on the number of responses that the requesting node receives. It also calculates the analytical probabilities of the specific numbers of matches. It compares the observed and the analytical probabilities to estimate the proportion of subverted or non-operational nodes in the iTrust network using a window-based method and the chi-squared statistic. If the detection algorithm determines that some of the nodes in the iTrust network are subverted or non-operational, then the novel defensive adaptation algorithm increases the number of nodes to which the requests are distributed to maintain the same probability of a match when some of the nodes are subverted or non-operational as compared to when all of the nodes are operational. Experimental results substantiate the effectiveness of the detection and defensive adaptation algorithms for protecting the iTrust information retrieval network against malicious attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.626-648
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• 2011

Energy consumption of wireless access networks is in permanent increase, which necessitates development of more energy-efficient network management approaches. Such management schemes must result with adaptation of network energy consumption in accordance with daily variations in user activity. In this paper, we consider possible energy savings of wireless local area networks (WLANs) through development of a few integer linear programming (ILP) models. Effectiveness of ILP models providing energy-efficient management of network resources have been tested on several WLAN instances of different sizes. To cope with the problem of high computational time characteristic for some ILP models, we further develop several heuristic algorithms that are based on greedy methods and local search. Although heuristics obtains somewhat higher results of energy consumption in comparison with the ones of corresponding ILP models, heuristic algorithms ensures minimization of network energy consumption in an amount of time that is acceptable for practical implementations. This confirms that network management algorithms will play a significant role in practical realization of future energy-efficient network management systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.362-362
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• 2000

The purpose of this thesis is to reduce force ripple of linear pulse motor(LPM) using neural network and to enhance precision. In order to this, we propose a new controller using a neural network to compensate disturbances. The structure includes adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances. The proposed controller compensates an unmodeled dynamics in the LPM. The neural network changes a current command to reduce position error and force ripple of the LPM. We compare proposed controller with PI controller. Simulation result shows that the proposed controller has better performance than a PI controller without neural network.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.156-165
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• 2021

In this paper, we propose an histogram weighted centroid based Siamese region proposal network for object tracking. The original Siamese region proposal network uses two identical artificial neural networks which take two different images as the inputs and decide whether the same object exist in both input images based on a similarity measure. However, as the Siamese network is pre-trained offline, it experiences many difficulties in the adaptation to various online environments. Therefore, in this paper we propose to incorporate the histogram weighted centroid feature into the Siamese network method to enhance the accuracy of the object tracking. The proposed method uses both the histogram information and the weighted centroid location of the top 10 color regions to decide which of the proposed region should become the next predicted object region.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 춘계학술발표논문집 (중)
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• pp.1161-1164
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• 2003

본 논문은 ALAN(Application Level Active Network)상에서 GME(Generic Modeling Environment)라고 불리는 컴포지션 메커니즘을 이용하는 AWCS(Adaptive Web Caching Service)에 관하여 언급하였다. ALAN상의 웹 캐싱의 요구사항은 자치 구성성(self-configuration)과 자치 적응성(self-adaptation)이다 이러한 요구사항을 지원하기 위해서 본 논문에서는 친AN상에서 IN(Intelligent Inetwork)에서 유래된 SCE(Service Creation Environment)와 유사한 서비스 컴포지션 메커니즘인 GME를 이용하여 AWCS 의 설계 및 구현에 관하여 언급하였다

• 한국경제지리학회지
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• 제12권4호
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• pp.364-387
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• 2009

1990년대 중반 이후 결혼이주여성의 증가는 이들의 한국사회 적응에 대하여 지대한 사회적, 정책적 관심을 불러일으키고 있다. 따라서 이에 대한 그동안 많은 연구가 있었으나, 접근방법 등의 한계로 결혼이주여성의 지역사회 적응 요인에 대한 충분한 분석이 이루어지지 않고 있다. 본 연구는 이러한 문제의식에 따라 전국적으로 광범위한 결혼이주여성 대상의 설문조사 자료를 바탕으로 이들의 지역사회 적응에 미치는 유효한 요인들을 단계적 다중회귀모형으로 분석하였다. 이주여성의 연령과 본국에서의 직업 경력, 지역주민으로서의 정체성, 가정생활의 적응 정도, 배우자의 직업과 연령, 한국으로 결혼이주 전 한국에 대한 지식과 이미지, 국내의 한국인 및 출신국 친구, 주민모임에의 참여 여부 등이 결혼이주여성의 지역사회 적응에 유효한 영향을 미치는 중요한 변수로 추출되었다. 그러나 일반적으로 중요하다고 생각되는 한국어 구사능력은 유효하지 않았다. 또한 한국인으로서의 정체성 또는 본국인으로서의 정체성도 유효한 변수가 되지 못하였다. 전반적으로 이주 전 배경으로 보면, 한국에 대한 이미지와 지식 등이, 이주 후로 보면, 지역주민으로서의 정체성과 사회적 연결망이 지역사회 적응에 중요한 변수로 확인되었다.

• 정보처리학회논문지C
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• 제12C권3호
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• pp.457-464
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• 2005

본 논문은 유비쿼터스 컴퓨팅 환경에서 PARLAY X기반 서비스 전송 플랫폼상의 MDA(Model Driven Architecture)기반 SCE(Service Creation Environment)를 이용하는 ACS(Adaptive Conte저-aware Service)에 관하여 서술하였다. 유비쿼터스 컴퓨팅 환경에서는 망 수준에서 문맥인식성과 더불어 적응성이 요구된다. 그러나 기존의 문맥인식성 미들웨어는 적응성에 대한 고려가 부족하다. 그러므로 본 논문의 목적은 유비쿼터스 컴퓨팅 환경에서 문맥인식성과 적응성이 동시에 지원 가능한 PARLAY X기반의 신규 망 서비스 구조 및 PARLAY X API를 개발하고자 하는 것이다. 본 논문에서 제안한 ACS(Adaptive Context-aware Service)는 사용자 주변에 변화하는 문맥 제약조건을 감지하고, 변화하는 문맥 제약 조건에 따라서 적응성 있는 망 서비스를 제공하는 것을 의미하며, ACS를 이용하는 예로 위치와 속도 등의 문맥정보를 인식한 후, 사용자에게 망에서 문맥정보에 따라서 적합한 차별화된 QoS를 지원하는 경우를 보였다. An의 구조는 SCE, Adaptive Context Broker, 그리고 PARLAY G/W로 구성되어 있다. SCE는 기존 지능망의 망 서비스와 같은 망 서비스로서 문맥인식성과 적응성을 표현하고 지원하기 위한 망 서비스 개발 환경으로 본 논문에서는 CCL(Context-based Constraint Language)을 이용하였다. Adaptive Context Broker는 SCE의 문맥인식성 및 적응성 표현과 기존 PARLAY G/W사이의 브로커 역할을 한다. PARLAY G/W는 PARLAY X기반의 서비스 전송 플랫폼을 위한 API(Application Programming Interface)를 제공한다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (D)
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• pp.136-138
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• 2006

The high-rate Wireless Personal Area Networks (WPANs) which IEEE 802.15.3 standard support, foster the Digital Home Network (DHN) scenarios with high rate multimedia data transmission. Actually, there are a few routing protocols for ad-hoc networks which considered the terminal location information and routing metric to reduce the energy consumption and optimize the routing path in mobile system. Based on other routing protocols, this paper presents the reliable location-based routing algorithm which is an adaptation to these networks.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.166-172
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• 2020

Video streaming application such as YouTube is one of the most popular mobile applications. To adjust the quality of video for available network bandwidth, a streaming server provides multiple representations of video of which bit rate has different bandwidth requirements. A streaming client utilizes an adaptive bit rate scheme to select a proper video representation that the network can support. The download behavior of video streaming client player is governed by several parameters such as maximum buffer size. Especially, the size of the maximum playback buffer in the client player can greatly affect the user experience. To tackle this problem, in this paper, we propose the maximum buffer size optimization according to available network bandwidth and buffer status. Our simulation study shows that our proposed buffer size optimization scheme successfully mitigates playback stalls while preserving the similar quality of streaming video compared to existing ABR schemes.

• 대한기계학회논문집
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• 제18권8호
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• pp.1939-1951
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• 1994

This study introduces a new tool breakage detecting technology comprised of an unsupervised neural network combined with adaptive time series autoregressive(AR) model where parameters are estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(Recursive Least Square). Experiment indicates that AR parameters are good features for tool breakage, therefore it can be detected by tracking the evolution of the AR parameters during milling process. an ART 2(Adaptive Resonance Theory 2) neural network is used for clustering of tool states using these parameters and the network is capable of self organizing without supervised learning. This system operates successfully under the wide range of cutting conditions without a priori knowledge of the process, with fast monitoring time.