• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.571-575
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• 2015

This paper propose a temporal histogram -based behavior pattern analysis algorithm to analyze the movement features of moving objects from the image inputted in real-time. For the purpose of tracking and analysis of moving objects, it needs to be performed background learning which separated moving objects from the background. Moving object is extracted as a background learning after identifying the object by using the center of gravity and the coordinate correlation is performed by the object tracking. The start frame of each of the tracked object, the end frame, the coordinates information and size information are stored and managed by the linked list. Temporal histogram defines movement features pattern using x, y coordinates based on time axis, it compares each coordinates of objects for understanding its movement features and behavior pattern. Behavior pattern analysis system based on temporal histogram confirmed high tracking rate over 95% with sustaining high processing speed 45~50fps through the demo experiment.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.70-77
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• 2017

Recently, Internet of Things (IoT) and deep learning techniques have affected video surveillance systems in various ways. The surveillance features that perform detection, tracking, and classification of specific objects in Closed Circuit Television (CCTV) video are becoming more intelligent. This paper presents real-time algorithm that can run in a PC environment using only a low power CPU. Traditional tracking algorithms combine background modeling using the Gaussian Mixture Model (GMM), Hungarian algorithm, and a Kalman filter; they have relatively low complexity but high detection errors. To supplement this, deep learning technology was used, which can be trained from a large amounts of data. In particular, an SRGB(Sequential RGB)-3 Layer CNN was used on tracked objects to emphasize the features of moving people. Performance evaluation comparing the proposed algorithm with existing ones using HOG and SVM showed move-in and move-out error rate reductions by 7.6 % and 9.0 %, respectively.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1024-1034
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• 2019

Preference for music is determined by a variety of factors, and identifying characteristics that reflect specific factors is important for music recommendations. In this paper, we propose a method to extract the singing voice related music features reflecting various musical characteristics by using a model learned for singer identification. The model can be trained using a music source containing a background accompaniment, but it may provide degraded singer identification performance. In order to mitigate this problem, this study performs a preliminary work to separate the background accompaniment, and creates a data set composed of separated vocals by using the proven model structure that appeared in SiSEC, Signal Separation and Evaluation Campaign. Finally, we use the separated vocals to discover the singing voice related music features that reflect the singer's voice. We compare the effects of source separation against existing methods that use music source without source separation.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.439-451
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• 2021

We propose a deep learning-based beamformer combined with spectral subtraction for continuous speech recognition operating in noisy environments. Conventional beamforming systems were mostly evaluated by using pre-segmented audio signals which were typically generated by mixing speech and noise continuously on a computer. However, since speech utterances are sparsely uttered along the time axis in real environments, conventional beamforming systems degrade in case when noise-only signals without speech are input. To alleviate this drawback, we combine online beamforming algorithm and spectral subtraction. We construct a Continuous Speech Enhancement (CSE) evaluation set to evaluate the online beamforming algorithm in noisy environments. The evaluation set is built by mixing sparsely-occurring speech utterances of the CHiME3 evaluation set and continuously-played CHiME3 background noise and background music of MUSDB. Using a Kaldi-based toolkit and Google web speech recognizer as a speech recognition back-end, we confirm that the proposed online beamforming algorithm with spectral subtraction shows better performance than the baseline online algorithm.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.361-366
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• 2018

For each character constituting learning data, different fonts are added in pixel unit to create MASK, and then pixel values belonging to the MASK are divided into three groups. The experimental data are modified into skeletal forms, and then regional boundary operation is used to create a boundary that distinguishes the background region adjacent to the skeleton of the character from the background of the modified experimental data. Discordance values between the modified experimental data and the MASKs are calculated, and then the MASK with the minimum value is found. This MASK is selected as a finally recognized result for the given experiment data. The recognition algorithm using skeleton of the character and the regional boundary operation can easily extend the learning data set by adding new fonts to the given learning data, and also it is simple to implement, and high character recognition rate can be obtained.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.33-42
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• 2013

The study looks for keys to provide development direction of digital textbooks based on educational meaning and roles for increasing satisfaction of teacher and student uses in educational activities. In the paradigm shift toward learner-centered pedagogy, digital textbooks have been actively discussed in exploiting the pedagogical ideas, such as multimedia learning, self-regulated learning, deeper learning, and collaborative learning, offered by the technology. In the study, we discuss the concept and historical background of digital textbooks based on the changes of pedagogical paradigm, and then we discuss fundamental functionality, effectiveness, physical and psychological impact, and cognitive aspects to empower the use of digital textbooks in public education system.

• The Mathematical Education
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• v.48 no.4
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• pp.419-442
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• 2009

This study was to find the difficulties students faced in their mathematical learning and to identify the instructional dimensions a teacher provided for the students from multi-cultural background. Since the study was focused on the process of students' learning, the qualitative method was chosen through clinical interviews with 2 students in a total of 11 units which played a role of compensating their learning of mathematics as an extra curriculum. The students solved the computational problems relying on formal procedure without understanding of concepts and principles and solved the word problems based on own interpretation of certain words without semantic comprehension out of math sentences. As the instructional dimensions of teaching mathematics, tasks, a tool and classroom norm were found in the activities they performed. For the tasks, situated tasks, challenging tasks, tasks with lack of conditions, and open-ended exploratory tasks were used. As the tool, pictorial representations were very useful to describe their ideas. Finally, as the classroom norm, consider equity for everyone, and cooperate and encourage each other were found.

• Journal of Korean Elementary Science Education
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• v.33 no.4
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• pp.784-794
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• 2014

In this study, we operated science teacher learning community to enhance professionality of elementary science teachers. 8 participants with various background, which include their science content knowledge, teaching experience and beliefs about teaching, were involved in this study. Bales(1950)'s social interaction process framework was mainly used to understand the members' interaction, focusing particularly on process aspects not on contents aspects. The data analysis shows that the members in the science teacher learning community tried their best to maintain the positive reaction to other members in most occasions in the community meetings. On the other hand, there were also negative reaction process due to their different ideas and views, causing their emotional conflicts in some social relations and dialogical situations. Nevertheless, the results also imply that the dual reaction processes, which are positive and negative processes, are equally important to facilitate science teachers' professional knowledge and experience. The educational meanings are discussed in the aspects of science teacher education.

• Communications of Mathematical Education
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• v.25 no.3
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• pp.557-575
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• 2011

The purpose of this paper is to analyze the way of teaching and learning logarithm in high school mathematics and provide practical suggestions for teaching logarithms. For such purpose, it reviewed John Napier's life and his ideas, the effect of logarithms on seventeenth century science, and a logarithmic scale and its methods of calculation. With this reviews, introduction of logarithms with function concept, logarithmic calculation with common logarithms, and the formula of converting to other logarithmic bases were reviewed for finding a new perspective of teaching and learning logarithms in high school mathematics. Through such historical and pedagogical reviews, this paper presented practical suggestions and comments about the way of teaching and learning logarithms in high school mathematics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1442-1447
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• 2014

This study examined the effect of the cold-warm color contrast of the learning-item on the learner's performance. To do this, experimental conditions were divided into three conditions: control condition, cold-warm contrast condition of background and figure, and cold-warm contrast condition of distracter and target. In addition, the OSPAN (operation span) task was used as the learning task. As a result, the rate of word recognition was higher in cold-warm contrast condition of distractor and target than any other condition. These results could be interpreted as enhancing effect.