• Journal of Digital Contents Society
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• v.18 no.2
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• pp.357-363
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• 2017

The Linux operating system, considered to be a subset of the UNIX operating system, is becoming the backbone of the enterprise server market and is seen as the key to building cloud computing and big data infrastructures. Linux has a variety of Linux distributions due to the fact that the source is open and anyone can freely modify and distribute it. First of all, Linux dominated the server market, the emergence of various distributions dominates the desktop and mobile operating system markets. In this paper, we examine the birth and history of Linux and classify and characterize various Linux distributions. The emergence of various Linux distributions will play a pivotal role in the Internet of Things and will further expand their power.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.145-150
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• 2019

We develop the system realization of whale sound reconstruction by inverse MFCC algorithm with the weighted L2-norm minimization techniques. The output products from this research will contribute to the whale tourism and multimedia content industry by combining whale sound contents with the prototype of 3D printing. First of all, we develop the softwares for generating whale sounds and install them into Raspberry Pi hardware and fasten them inside a 3D printed whale. The languages used in the development of this system are the C++ for whale-sounding classification, MATLAB and Python for whale-sounding playback algorithm, and Rhino 6 for 3D printing.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.195-204
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• 2004

Due to growth of diversified media, content screening is the definite procedures. The procedures of screening varies from country by country in various reasons. Therefore, reason of conducting such study is to compare & contrast screening process by countries. In order to clarify definition of terms that measures screening, "censorship" means "legislative filtering process prior to public appearance". In contrary "Rating and/or Classification" is defined opposite of it. After defining these terms, Screening is dignified into two distinctive measures, which are "legislative intereference" and "voluntary notification". Those two measures are again sub-categorized into eight distinctive operational definition. Utilizing those distinctive measures, our study has concluded as US, Japan and some laissez-faire countries use "voluntary notification" systems but in contrast China and Brunei use "legislative filtering" system.? Korea and Australia uses unique combination of both system. In order for Korea to adopt "voluntary notification system", legislative intereference must be weaken and develop strong "voluntary notification" system.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.227-235
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• 2005

Document filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. In this paper, we treat document filtering problem as binary document classification problem and we proposed the News Filtering system based on the Bayesian Classifier. For we perform filtering, we make an experiment to find out how many training documents, and how accurate relevance checks are needed.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.76-84
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• 2002

The conventional database evaluation method is carried out by the way in which the person in charge of each specialty database(DB manager) composes the evaluation sheets for corretionㆍrevision on the already-constructed database in a manual method and carries out the measurement and re-education of DB workers based upon it. As a result, that way consumes much time on career information and measurement works about DB workers, causing low time and cost efficiency and lack of systematic management of DB workers, resulting in becoming the hindrance factor of databases quality improvement. This research provides on-line, red-time results of measurements about the efficiency of DB production and DB workers by combining the static measurement with dynamic measurement by DB manager, both of which utilize the System. Therefore, the DB manager can contribute to the improvement of DB quality by determining the continuation of DB production by DB workers or carrying out the re-education of DB workers without being affected by time or spacial constraints.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.11-12
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• 2016

SVM (Support Vector machine) is powerful machine-learning method, and obtains better performance than traditional methods in the applications of muti-dimension nonlinear pattern classification. For the case of SVM model training and low efficiency in large samples, this paper proposes a combination of statistical parameters of the GMM-UBM (Universal Background Model) model. It is very effective to solve the problem of the large sample for the SVM training. The experiment is carried on four special dynamic hand gestures using the EPIC sensors. And the results show that the improved dynamic hand gesture recognition system has a high recognition rate up to 96.75%.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.77-78
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• 2016

이 논문에서는 대용량의 이메일을 분류하여 아카이빙하는 시스템을 설계하고 구현한다. 이 논문에서 개발하는 이메일 아카이빙 시스템은 업무영역 별로 이메일을 분류하여 업무 관련 이메일에 대해 업무영역 카테고리별로 아카이빙을 수행한다. 분류의 정확도를 위해 온톨로지를 이용한 텀벡터의 확장 방법을 사용하였으며, 빠른 분류 및 아카이빙을 수행하도록 인메모리 기반의 분산 및 병렬 처리 프레임워크인 Spark을 기반으로 구현한다.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.425-426
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• 2019

전통적인 마이닝 기법은 다양한 디지털 매체와 센서 등에서 생산되는 빅데이터를 처리하기 어려울 뿐 아니라 신규 데이터 누적시 전체 데이터를 재분석 해야하는 비효율성과 대용량의 문서를 학습함에 있어 메모리부족 문제, 학습 소요시간 문제 등이 있다. 이러한 문제를 해결하기 위하여 본 논문에서는 자질축소 기법에 의존하지 않고 대량의 문서를 자유롭게 학습하고 부분적인 자질 추가 변경 시에 변경요소만을 추가 반영할 수 있는 범용적이고 일반적인 분류기의 구조설계 방법을 설계 및 구현하였다. 점진적 학습 모듈은 일반적인 학습 방법이 데이터의 추가 및 변동시마다 모든 데이터를 재학습하는 데 반해, 기존의 학습 결과에 증분된 데이터만 재처리 없이 추가적으로 학습한다. 재학습을 위해 사용자는 작업 수행 중 자원 관리를 통해 기존에 처리된 데이터를 자유롭게 가져와서 새로운 데이터와 병합이 가능하다. 이러한 점직적 학습 효율성은 빅데이터 기반 데이터 처리에 주요한 특성인 데이터 생산 속도를 극복하기 위한 좋은 대안이 될 수 있음을 확인하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.187-190
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• 2001

Due to the recent proliferation of the internet, it is broadly granted that the necessity of the automatic document categorization has been on the rise. Since it is a heavy time-consuming work and takes too much manpower to process and classify manually, we need a system that categorizes them automatically as their contents. In this paper, we propose the automatic E-mail response system that is based on 2 hierarchical document clustering methods. One is to get the final result from the classifier trained seperatly within each class, after clustering the whole documents into 3 groups so that the first classifier categorize the input documents as the corresponding group. The other method is that the system classifies the most distinct classes first as their similarity, successively. Neural networks have been adopted as classifiers, we have used dendrograms to show the hierarchical aspect of similarities between classes. The comparison among the performances of hierarchical and non-hierarchical classifiers tells us clustering methods have provided the classification efficiency.

• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.516-523
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• 2008

Recently, the Web has been constructed based on collective intel1igence and growing up quickly. User created contents have been made the mainstream in this environments. So it's required to make an efficient technique of searching for the contents. The current searching technique mainly is achieved by key words. Semantic Web based on similarity and relationship of a language and using user tags in web2.0 also have been researched with activity. Generally, the web of the participation architecture has a lot of user created contents, various forms and classification. Therefore, it is necessary to classify and to efficiently search for a lot of user created contents. In this paper, we propose a depth searching technique considering the relationship among the tags that descript user contents. It is expected that the proposed depth searching techniques can reduce the time taken to search for the unwanted contents and the increase the efficiency of the contents searching using a service of suggestion words in tags groups.