• Korean Journal of Human Ecology
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• v.17 no.3
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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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• v.12 no.7
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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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• v.12 no.6
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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.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.106-119
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• 2013

As open source can reduce costs and apply to various fields rapidly, many countries have actively adopted open source. However, geo-spatial open source in Korea is not actively promoted yet comparing to other countries having similar infra environments. In this study, we analyzed the perception of geo-spatial open source, utilization status, the development possibility and future direction using questionnaire survey completed by experts dealing with spatial information. The survey result shows that many experts have experiences of using geo-spatial open source but they got a lack of understanding about open source license or regulations and only a few people got professional training. Insufficient references, the difficulty of maintenance, lack of support and low technical reliability have hindered the adoption of geo-spatial open source. Only some part of geo-spatial open source software or libraries in some field have been used in the country. However, many researchers rate highly development potential and plan to use geo-spatial open source soon. If user's convenience, reference materials, technical trust and policy support are improved, open source field for spatial information will be developed greatly in the future.

• Proceedings of the KSPS conference
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• 2007.05a
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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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• v.55 no.8
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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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• v.17 no.5
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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.

• Journal of Information Processing Systems
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• v.12 no.2
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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.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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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 the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.147-155
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• 2010

It has been widely addressed that static analysis techniques can play important role in identifying potential security vulnerability reside in source code. This paper proposes the design and application of security metrics that use both vulnerability information extracted from the static analysis, and significant factors of information that software handles. The security metrics are useful for both developers and evaluators in that the metrics help them identity source code vulnerability in early stage of development. By effectively utilizing the security metrics, evaluators can check the level of source code security, and confirm the final code depending on the characteristics of the source code and the security level of information required.