• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1700-1721
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• 2017

The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts.

• 정보교육학회논문지
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• 제20권1호
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• pp.39-46
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• 2016

컴퓨터과학의 원리를 교육하기 위한 도구로서 언플러그드 교육은 널리 사용되고 있다. 본 연구에서는 초등학교에서 자연수를 이진체계로 표현하는 사전 학습이 이루어진 학생들을 대상으로 문자를 이진체계로 표현하는 교육자료 개발에 대해 제시하였다. 학습방법은 활동중심학습으로 구성하였으며, 학습내용은 생활 속의 문자를 이진체계로 표현하는 원리를 학습하기 위하여 문자를 수와 대응시킨 문자표를 사용하여 이진체계로 표현하기이다. 개발된 자료의 적합성 평가를 위하여 교육자료를 현장에 적용하였으며, 그 결과는 문자의 이진체계 표현에 대한 지식과 적용 및 확장은 효과적인 것으로 평가되었다.

• ETRI Journal
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• 제39권3호
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• pp.398-405
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• 2017

In this paper, an artificial stereo extension method that creates stereophonic sound from a mono sound source is proposed. The proposed method first trains deep neural networks (DNNs) that model the nonlinear relationship between the dominant and residual signals of the stereo channel. In the training stage, the band-wise log spectral magnitude and unwrapped phase of both the dominant and residual signals are utilized to model the nonlinearities of each sub-band through deep architecture. From that point, stereo extension is conducted by estimating the residual signal that corresponds to the input mono channel signal with the trained DNN model in a sub-band domain. The performance of the proposed method was evaluated using a log spectral distortion (LSD) measure and multiple stimuli with a hidden reference and anchor (MUSHRA) test. The results showed that the proposed method provided a lower LSD and higher MUSHRA score than conventional methods that use hidden Markov models and DNN with full-band processing.

• Asian Pacific Journal of Cancer Prevention
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• 제16권15호
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• pp.6719-6727
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• 2015

Background: The objective of this study was to assess the readability, suitability, and health content of cancer screening information in municipal newspapers in Japan. Materials and Methods: Suitability Assessment of Materials (SAM) and the framework of Health Belief Model (HBM) were used for assessment of municipal newspapers that were published in central Tokyo (23 wards) from January to December 2013. Results: The mean domain SAM scores of content, literacy demand, and layout/typography were considered superior. The SAM scores of interaction with readers, an indication of the models of desirable actions, and elaboration to enhance readers' self-efficacy were low. According to the HBM coding, messages of medical/clinical severity, of social severity, of social benefits, and of barriers of fear were scarce. Conclusions: The articles were generally well written and suitable. However, learning stimulation/motivation was scarce and the HBM constructs were not fully addressed. Practice implications: Articles can be improved to motivate readers to obtain cancer screening by increasing interaction with readers, introducing models of desirable actions and devices to raise readers' self-efficacy, and providing statements of perceived barriers of fear for pain and time constraints, perceived severity, and social benefits and losses.

• 수산해양교육연구
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• 제28권3호
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• pp.661-666
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• 2016

This study was to explore the living experiences of the disabled adults who were participating in public education Yahak program held at evening class. The study designed in-depth interviews with ten disabled people using a grounded theory approach. Through analyzing process, 34 concepts, 15 subcategories, and eight categories were deduced. In axial coding, casual condition, 'Suffering from unknown cause disabilities' and 'Isolated by social cause', context condition, 'Taking discriminative treat for disabilities' impacted on phenomenon, 'Overcoming their conditions by themselves'. Intervening conditions was 'Taking social supports' and action-interaction condition, 'Enjoying public programs' totally lead to consequence in 'Controlling daily life' and 'Exploring their own social roles'. The periods of process were divided three stages, reflecting disabled situation, formation phase of social relation, and self-developing phase. The core category, 'Trying to be recognized as a member of society' incorporated the relationship between and among all categories and explained the process. The study indicates that social education program for the disabled helped to develop themselves as a member of society. Therefore, we suggest there may be a need for training for professionals who work with disabled people to develop social adaptation.

• 한국멀티미디어학회논문지
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• 제20권11호
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• pp.1811-1819
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• 2017

As the induction motor is the core production equipment of the industry, it is necessary to construct a fault prediction and diagnosis system through continuous monitoring. Many researches have been conducted on motor fault diagnosis algorithm based on signal processing techniques using Fourier transform, neural networks, and fuzzy inference techniques. In this paper, we propose a fault diagnosis method of induction motor using LPC and DNN. To evaluate the performance of the proposed method, the fault diagnosis was carried out using the vibration data of the induction motor in steady state and simulated various fault conditions. Experimental results show that the learning time of our proposed method and the conventional spectrum+DNN method is 139 seconds and 974 seconds each executed on the experimental PC, and our method reduces execution time by 1/8 compared with conventional method. And the success rate of the proposed method is 98.08%, which is similar to 99.54% of the conventional method.

• 산업융합연구
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• 제18권1호
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• pp.53-58
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• 2020

2015 개정 교육과정은 창의 융합 인재를 키우고자 하는 데 그 목적이 있다. 이에 SW 교육은 컴퓨팅 사고력을 높이기 위한 다양한 융합교육 방법에 대한 연구가 필요하다. 이에 본 연구의 목적은 컴퓨팅 사고력 향상을 위한 독서교육과 로봇활용 교육 중심의 SW융합교육의 효과를 분석하는 것이다. 이를 위해 카드코딩 기반의 로봇을 이용한 SW 교육과 온작품읽기와 상호텍스트성을 토대로한 독서교육을 융합하여 SW 교육 교수학습을 설계하였다. 결국 이러한 독서와 SW의 융합교육은 컴퓨팅 사고력의 개념, 실습, 관점의 3가지 영역을 모두 향상시켰으며 학습자의 만족도를 높였다.

• 한국초등과학교육학회지:초등과학교육
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• 제27권2호
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• pp.158-169
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• 2008

The purpose of this study was to analyze the uses of the external representations in the $3{\sim}6th$ grade science textbooks developed under the 7th National Curriculum on the basis of the theories and the research results on learning with the multiple representations. The results showed that the frequencies of the macroscopic external representations were higher than those of the symbolic external representations. The external representations with drawing and/or writing, especially writing, were used more frequently than those without drawing and/or writing. However, the most of the external representations were rarely used according to the principles and/or the theories (e.g., personalization principle, dual coding theory, cognitive load theory, and social constructivism theory) for effective uses of the multiple external representations in the science textbooks. The present study provides the guideline to establish the effective uses of the external representations in the science textbooks that not only meet learners but also teachers.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.695-705
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• 2019

The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.

• ETRI Journal
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• 제41권4호
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• pp.415-425
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• 2019

Generative adversarial networks (GAN) have been successfully used in many image restoration tasks, including image denoising, super-resolution, and compression artifact reduction. By fully exploiting its characteristics, state-of-the-art image restoration techniques can be used to generate images with photorealistic details. However, there are many applications that require faithful rather than visually appealing image reconstruction, such as medical imaging, surveillance, and video coding. We found that previous GAN-training methods that used a loss function in the form of a weighted sum of fidelity and adversarial loss fails to reduce fidelity loss. This results in non-negligible degradation of the objective image quality, including peak signal-to-noise ratio. Our approach is to alternate between fidelity and adversarial loss in a way that the minimization of adversarial loss does not deteriorate the fidelity. Experimental results on compression-artifact reduction and super-resolution tasks show that the proposed method can perform faithful and photorealistic image restoration.