• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.272-277
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• 2001

In this paper, we describe a new method for selecting information sources in a distributed environment. Recently, there has been much research on distributed information retrieval, that is information retrieval (IR) based on a multi-database model in which the existence of multiple sources is modeled explicitly. In distributed IR, a method is needed that would enable selecting appropriate sources for users\` queries. Most existing methods use statistical data such as document frequency. These methods may select inappropriate ate sources if a query contains polysemous words. In this paper, we describe an information-source selection method using two types of thesaurus. One is a thesaurus automatically constructed from documents in a source. The other is a hand-crafted general-purpose thesaurus(e.g. WordNet). Terms used in documents in a source differ from one another and the meanings of a term differ depending on th situation in which the term is used. The difference is a characteristic of the source. In our method, the meanings of a term are distinguished between by the relationship between the term and other terms, and the relationship appear in the co-occurrence-based thesaurus. In this paper, we describe an algorithm for evaluating a usefulness of a source for a query based on a thesaurus. For a practical application of our method, we have developed Papits, a multi-agent-based in formation sharing system. An experiment of selection shows that our method is effective for selecting appropriate sources.

• 한국생활과학회지
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• 제17권3호
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• pp.485-492
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• 2008

The study is to provide the types of fashion consumption of male and female university students and to analyze fashion involvement to the types and students' source of fashion information. Then the correlations were examined between fashion involvement and source of fashion information. The data were analyzed by a factor analysis, one-way ANOVA, Duncan test, cluster analysis, cross-tabulation analysis. The results are as follows: 1. The awareness about fashion consumption is classified into five factors: "hedonic consumption", "impulsive consumption", "brand loyal consumption", "prudent consumption", and "independent consumption". The fashion involvement to the types is categorized into four factors; "pleasure", "trend", "image", and "risk awareness". The source of fashion information is categorized into "mass media", "product information", and "personal information". 2. The fashion consumption is classified into three types: "an independent consumer type", "a brand loyal/ prudent consumer type", and "an impulsive consumer type". 3. In the fashion involvement to the types and the source of fashion information, there is a high correlation between the factors of "mass media" and "trend", "product information" and "pleasure" and "personal information" and "trend".

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2534-2553
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• 2018

Source routing is the routing scheme that arranges the whole path from source to target at the origin node that may suit the requirements from the upper layer applications' perspective. The centralized control in SDN (Software-Defined Networking) networks enables the awareness of the global topology at the controller. Therefore, augmented source routing schemes can be designed to achieve various purposes. This paper proposes a source routing scheme that conducts the top-K QoS-aware paths discovery in SDN. First, the novel non-invasive QoS over LLDP scheme is designed to collect QoS information based on LLDP in a piggyback fashion. Then, variations of the KSP (K Shortest Paths) algorithm are derived to find the unconstrained/constrained top-K ranked paths with regard to individual/overall path costs, reflecting the Quality of Service. The experiment results show that the proposed scheme can efficiently collect the QoS information and find the top-K paths. Also, the performance of our scheme is applicable in QoS-sensitive application scenarios compared with previous works.

• 한국지리정보학회지
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• 제16권4호
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• pp.106-119
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• 2013

오픈소스는 비용을 절감하고 다양한 분야에 빠르게 적용가능하다는 장점 때문에 현재 많은 나라에서 활발하게 기술을 도입하고 있다. 그러나 우리나라에서는 유사한 인프라 환경을 갖춘 다른 국가들에 비해 아직 공간정보 분야에서의 오픈소스 이용이 활발하지 않은 상태이다. 이 연구는 공간정보 분야 전문 학회 회원을 대상으로 설문조사를 수행하고, 이를 바탕으로 공간정보 분야에서의 오픈소스에 대한 인식과 활용 현황, 발전 가능성과 방향을 분석하고자 하였다. 설문 결과를 요약하면, 다수의 사람들이 오픈소스를 사용해본 경험은 있으나 라이선스나 규정에 대한 이해가 부족하고 전문적인 교육을 받은 경우는 거의 없었다. 한편 오픈소스 활용을 저해하는 주요 요인은 참고자료의 부족, 유지보수의 어려움, 지원의 부족, 기술에 대한 신뢰도가 떨어진다는 것이었다. 현재 국내에서는 일부 분야에서 몇몇 오픈소스 소프트웨어나 라이브러리만 사용되고 있는 실정이지만, 많은 공간정보 연구자들이 앞으로 빠른 시일 내에 오픈소스를 사용할 계획이 있고 오픈소스의 발전 가능성이 높은 것으로 기대하고 있었다. 앞으로 사용 편의성, 참고자료를 보완하고 기술 신뢰성과 정책적 지원이 확보된다면 앞으로 공간정보를 다루는 오픈소스 분야가 크게 발전 할 수 있을 것이다.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2007년도 한국음성과학회 공동학술대회 발표논문집
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• pp.315-318
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• 2007

This paper proposes the methods to enhance the speech quality of source controlled variable bit-rate coder based on the waveform interpolation. The methods are to estimate and generate the parameters that are not transmitted from encoder to decoder by the repetition and extrapolation schemes. For the performance evaluation, the PESQ(Perceptual Evaluation of Speech Quality) scores are measured. The experimental results shows that our proposed method outperforms the conventional source controlled variable bit-rate coder. Especially, the performance of the extrapolation method is better than that of the repetition method.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

• Journal of Communications and Networks
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• 제17권5호
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• pp.482-490
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• 2015

This article exploits spatial diversity for jamming to prevent wiretapping in the extreme case in which an eavesdropper is located near the source and a common jamming signal is unavailable. To address this challenge, the jamming signal is allowed to carry a random binary message. Then, it is proposed that the active intermediate node transmits this jamming signal and the decoding of this signal at both source and destination is physically secured as result of using the physical-layer security method. If the source and the destination securely and correctly decode this jamming message, the source transmits another message which is created from combining its information message and the decoded message using the network-coding method. Therefore, this method prevents the transmissions from being eavesdropped upon by the source-wiretapping.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1999년도 가을 학술발표논문집 Vol.26 No.2 (2)
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• pp.467-469
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• 1999

Independent component analysis (ICA)는 주어진 데이터를 통계적으로 독립인 요소들의 선형 결합으로 표시하는 통계학적 방법이다. ICA의 주요한 적용분야중의 하나는 source들의 선형 mixture로부터 어떠한 서전 정보도 없는 상태에서 원래의 통계학적 독립변수인 source를 복원하는 blind separation이다. ICA와 source separation을 위한 다양한 신경 학습 알고리듬이 제시되어왔다. ICA의 학습 알고리듬에서는 비선형 함수가 중요한 역할을 한다. 이 논문에서는 generalized 가우시안 prior를 도입하여 다양한 확률분포를 갖는 source들의 mixture를 분리하는 효율적인 source separation 알고리즘을 제시한다. 모의실험을 통하여 제안된 방법의 우수성을 살펴본다.

• Journal of Information Processing Systems
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• 제12권2호
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• pp.322-331
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• 2016

Image compression is an essential technique for saving time and storage space for the gigantic amount of data generated by images. This paper introduces an adaptive source-mapping scheme that greatly improves bit-level lossless grayscale image compression. In the proposed mapping scheme, the frequency of occurrence of each symbol in the original image is computed. According to their corresponding frequencies, these symbols are sorted in descending order. Based on this order, each symbol is replaced by an 8-bit weighted fixed-length code. This replacement will generate an equivalent binary source with an increased length of successive identical symbols (0s or 1s). Different experiments using Lempel-Ziv lossless image compression algorithms have been conducted on the generated binary source. Results show that the newly proposed mapping scheme achieves some dramatic improvements in regards to compression ratios.