• Journal of Multimedia Information System
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• 제2권3호
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• pp.287-294
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• 2015

We are living in epoch of information when Internet touches all aspects of our lives. Therefore, it provides a plenty of services each of which benefits people in different ways. Electronic Mail (E-mail), File Transfer Protocol (FTP), Voice/Video Communication, Search Engines are bright examples of Internet services. Between them Social Network Services (SNS) continuously gain its popularity over the past years. Most popular SNSs like Facebook, Weibo and Twitter generate millions of data every minute. Twitter is one of SNS which allows its users post short instant messages. They, 100 million, posted 340 million tweets per day (2012)[1]. Often big amount of data contains lots of noisy data which can be defined as uninteresting and unclassifiable data. However, researchers can take advantage of such huge information in order to analyze and extract meaningful and interesting features. The way to collect SNS data as well as tweets is handled by crawlers. Twitter crawler has recently emerged as a great tool to crawl Twitter data as well as tweets. In this project, we develop Twitter Crawler system which enables us to extract Twitter data. We implemented our system in Java language along with MySQL. We use Twitter4J which is a java library for communicating with Twitter API. The application, first, connects to Twitter API, then retrieves tweets, and stores them into database. We also develop crawling strategies to efficiently extract tweets in terms of time and amount.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3559-3571
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• 2015

This paper addresses the problem of signal acquisition with a sparse representation in a given orthonormal basis using fewer noisy measurements. The authors formulate the problem statement for randomly measuring with strong signal noise. The impact of white Gaussian signals noise on the recovery performance is analyzed to provide a theoretical basis for the reasonable design of the measurement matrix. With the idea that the measurement matrix can be adapted for noise suppression in the adaptive CS system, an adapted selective compressive sensing (ASCS) scheme is proposed whose measurement matrix can be updated according to the noise information fed back by the processing center. In terms of objective recovery quality, failure rate and mean-square error (MSE), a comparison is made with some nonadaptive methods and existing CS measurement approaches. Extensive numerical experiments show that the proposed scheme has better noise suppression performance and improves the support recovery of sparse signal. The proposed scheme should have a great potential and bright prospect of broadband signals such as biological signal measurement and radar signal detection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권5호
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• pp.2555-2575
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• 2017

This paper presents a dual exposure fusion method for image enhancement. Images taken with a short exposure time usually contain a sharp structure, but they are dark and are prone to be contaminated by noise. In contrast, long-exposure images are bright and noise-free, but usually suffer from blurring artifacts. Thus, we fuse the dual exposures to generate an enhanced image that is well-exposed, noise-free, and blur-free. To this end, we present a new scale-space patch-match method to find correspondences between the short and long exposures so that proper color components can be combined within a proposed dual non-local (DNL) means framework. We also present a residual filtering method that eliminates the structure component in the estimated noise image in order to obtain a sharper and further enhanced image. To this end, the entropy is utilized to determine the proper size of the filtering window. Experimental results show that our method generates ghost-free, noise-free, and blur-free enhanced images from the short and long exposure pairs for various dynamic scenes.

• International journal of advanced smart convergence
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• 제9권3호
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.735-744
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• 2005

The number of electronic mail(E-mail) has been increased dramatically as a result of expanding internet and information technology. Although there are many conveniences of E-mail in the bright side, some serious problems occur because of E-mail in its dark side. One of the problems is spam-mail which is unsolicited mail and also called bulk mail. This paper presents a set of patterns of spam-mail occurrences within a week using the correspondence analysis. The correspondence analysis is an exploratory multivariate technique that converts data into a particular type of graphical display in which the rows and columns are depicted as points. One of the meaningful patterns is a great increment of adult and phishing related spam-mails at weekends so any spam-mail filters should be designed to cope with this pattern.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.96-100
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• 2020

Soundtrack dissonance, which appears in the background music of a movie scene, is a phenomenon of using songs or compositions that contrast with the general sentiment of the situation. A sad scene usually uses a slow tempo of sad music to match the mood of the scene. However, sometimes, in order to play background music that follows a depressing, sad, or anxious scene, there is a case of inserting music with an opposite atmosphere such as bright music, exciting music, fast-tempo music, or magnificent music. The method of presenting music that is contrary to the mood of the scene is a kind of psychological technique that inflicts a kind of mental shock on the audience and makes them remember a particular situation. In this study, we have investigated the meaning coming from scenes and Soundtrack Dissonance in movies, in order to understand the role that music and images play.

• 융합보안논문지
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• 제20권4호
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• pp.169-176
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• 2020

최근 스마트 기기를 이용한 다양한 서비스들이 사용되는 시대를 소위 "스마트 시대"라 부르기도 한다. 이러한 가운데 스마트홈 서비스는 주거 환경과 문화에 큰 변화를 가져왔을 뿐만 아니라, 매우 빠르게 진화해 가고 있다. 그리고 스마트홈 서비스는 일반 가정에서 다양한 전자제품들 간의 통신을 통해 사용자에게 보다 편리한 서비스를 제공해주며, 향후 밝은 미래를 보이고 있다. 특히 '스마트홈 서비스'는 각종 기기들 간의 연결에 있어, IoT 기술과 유·무선 통신을 기반으로 결합된 다양한 서비스들을 제공하고 있다. 그러나 이와 같은 '스마트홈 서비스'는 사물 인터넷과 유·무선 통신기술 같은 기반 기술들의 보안 취약점들을 상속하고 있어, 개인정보의 유출이나 사생활침해 등으로 이어지는 사고가 지속적으로 발생하고 있다. 이에 기반기술의 취약요인에 대해 예방과 대응방안의 마련이 필요한 상황이다. 따라서 본 논문에서는 스마트홈 서비스의 다양한 보안취약요인들을 알아봄으로써, 향후 응용기술의 개발 및 대응기술의 기초 자료로 활용될 것으로 기대한다.

• 한국인터넷방송통신학회논문지
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• 제14권6호
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• pp.235-243
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• 2014

본 논문에서는 지능형 LED 실내조명을 위한 효율적인 제어 시스템을 제안한다. 제안된 지능형 LED 실내조명을 위한 효율적인 제어 시스템은 스케줄 정의에 의한 조명 스타일과 재실 감지에 의한 조명 스타일에 PIR 센서와 조도 센서에 의해 측정되는 주광강도와 같은 요소를 포함시켜 무선 센서 네트워크로 점등제어를 하고 에너지 절감을 할 수 있도록 설계하였다. 또한, 재실감지에 의한 실내조명 점등제어는 PIR 센서를 사용하여 미세 움직임을 감지하고, 창측과 내측의 불필요한 조명 밝기 제어는 조도센서를 이용하여 주광의 수준을 측정하여 제어하였으며, 주광 유입량이 많은 경우 창측 조명은 자동으로 어두워지고, 적으면 조명이 자동으로 밝아지도록 설계하였다. 제안하는 지능형 LED 실내조명을 위한 효율적인 제어 시스템의 효율성 검증 결과, 외부 조명이나 주광이 조금이라도 실내로 유입되면 실내조명의 밝기를 실시간으로 제어하여 에너지 절감 효과를 극대화할 수 있었다.

• 한국산학기술학회논문지
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• 제16권10호
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• pp.6708-6714
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• 2015

언제 어디서나 사용하기 편리한 인터넷을 통해서 다양한 종류의 멀티미디어 콘텐츠가 자유롭게 유통되고 있는 반면, 어린이나 청소년에게 유해할 수 있는 영상 콘텐츠도 쉽게 얻을 수 있는 환경이 마련되어서 사회적으로 문제가 되고 있다. 본 논문에서는 인공 신경망을 이용하여 입력 영상의 유해성 유무를 자동으로 결정하는 방법을 제안한다. 본 논문에서 제안된 방법에서는 먼저 입력 영상으로부터 MCT 특징을 기반으로 사람의 얼굴 영역을 검출한다. 그런 다음, 색상 특징을 활용하여 피부 색상 영역을 찾고, 유두의 후보 영역들을 추출한다. 마지막으로 계층적인 인공 신경망을 활용하여 유두의 후보 영역들 중에서 실제적인 유두 영역만을 필터링함으로써 입력 영상의 유해성 유무를 확인한다. 본 논문의 실험결과에서는 인공 신경망을 이용한 제안된 방법이 입력되는 영상에서 유두 영역을 보다 강건하게 검출함으로써 영상의 유해 정도를 효과적으로 결정한다는 것을 보여준다.

• International journal of advanced smart convergence
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• 제8권4호
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• pp.104-112
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.