• School Mathematics
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• v.18 no.4
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• pp.857-880
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• 2016

The development of teacher's professionalism through teacher education is a key element in the improvement of school education. However, there has been criticism that the mathematics teacher education in Korea do not provide given enough opportunities for the classroom experience during preservice teacher education period. For development of inservice mathematics teachers and preservice teachers' teaching professionalism, this study develops a research community for mathematics classroom consisting of experts, inservice mathematics teachers, and preservice teachers. And the study explores the possibilities of the model as an educational space for inservice teachers and preservice teachers by participating in a series of courses such as task development and revision, and observation and analysis of classes. As results, inservice teachers and preservice teachers were able to enhance the practical experience and understanding necessary for the class, and they were also positively influenced in teacher efficacy and view of teaching on the model. Based on this, we suggest the possibility of the model as a teacher education system.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.119-127
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• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.84-92
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• 2011

The automated segmentation technique of cell region in Bio Images helps biologists understand complex functions of cells. It is mightly important in that it can process the analysis of cells automatically which has been done manually before. The conventional methods for segmentation of cell and nuclei from multi-channel images consist of two steps. In the first step nuclei are extracted from DNA channel, and used as initial contour for the second step. In the second step cytoplasm are segmented from Actin channel by using Active Contour model based on intensity. However, conventional studies have some limitation that they let the cell segmentation performance fall by not considering inhomogeneous intensity problem in cell images. Therefore, the paper consider correlation between DNA and Actin channel, and then proposes the preprocessing algorithm by which the brightness of cell inside in Actin channel can be compensated homogeneously by using DNA channel information. Experiment result show that the proposed preprocessing method improves the cell segmentation performance compared to the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.99-109
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• 2011

Ubiquitous computing technology makes an impact on the appearance of u-learning and presents an advanced direction of futuristic school education. In ubiquitous learning environments, various embedded computational devices will be pervasive and interoperable across the network for supporting the learning, so users may utilize these devices anytime anywhere. An important next step for ubiquitous learning is the introduction of context-aware learning service that employing knowledge and reasoning to understand the local context and share this information in support of intelligent learning services. However, the existing studies on design and application of ontology context model to support context-aware service in actual school environments are incomplete state. This paper, therefore, suggests a scheme of constructing ubiquitous learning space for existing school network by introducing USN to support context-aware ubiquitous learning services. This paper, also, designs an ontology based context model for ubiquitous school environments which describes context information through OWL. To determine the suitability of proposed ubiquitous learning space and ontology context model, we implement some of context-aware learning services in the ubiquitous learning environments.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.114-120
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• 2009

Rupture directivity is the important parameter in estimating damage due to earthquakes. However, the traditional moment tensor inversion technique cannot resolve the real fault plane or the rupture directivity. To overcome these limitations, we have developed a new inversion algorithm to determine the moment tensor solution and the rupture directivity for moderate earthquakes, using the waveform inversion technique in the frequency domain. Numerical experiments for unilateral and bilateral rupture models with various rupture velocities confirm that the method can resolve the ambiguity of the fault planes and the rupture directivity successfully. To verify the feasibility of the technique, we tested the sensitivity to velocity models, which must be the most critical factor in practice. The results of the sensitivity tests show that the method can be applied even though the velocity model is not perfect. If this method is applied in regions where the velocity model is well verified, we can estimate the rupture directivity of a moderate earthquake. This method makes a significant contribution to understanding the characteristics of earthquakes in those regions.

• Journal of the Korea Society of Computer and Information
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• v.15 no.3
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• pp.45-53
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• 2010

When the user's role is getting more important in contents communicated online, we must know that the cultural trait of content that is reflecting user's mental model, needs and tastes. An attempt to study about cross-cultural characteristics focused on contents of global website give us the best chance to understand user. This paper takes a look if there are any linkages between certain country and its preferable contents and analyze that whether this preference is result from the cultural differences or not. This analysis is based on Hofstede's and Schwartz's framework. So, this content analysis examines cultural influence on the contents of global website in Korea and U.S and Japan and China. The results provide CIC(Cultural Index of Content) which is extended framework adding interaction. We expect that it can help service providers and content creators to have some new ideas.

• Smart Media Journal
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• v.3 no.1
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• pp.9-15
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• 2014

In these days, along with the extreme popularity of online social network services, it becomes an important problem understanding the role of social network in the research of message dissemination. Past studies of message dissemination over online social network services mostly consider the coverage of message dissemination and the methods to maximize it. But, these works lack of the consideration of the impact of multi channel social network, which has multiple communication channel with distinct properties of message transfer and various users with distinct channel preferences. In this paper, the new message dissemination model over multi-modal multi-channel social network, the Delay Weighted Independent Cascade Model, is proposed. The proposed model considers various channels including online social network service, email, SMS messaging, phone and mouth-to-mouth and their distinct message transfer properties. In order to consider the various user properties, the different value of probability of forwarding a message and the different preference of communication channel is considered. Moreover, the proposed model considers the distribution of user location and allows to analyze the properties of message dissemination under various scenarios. Based on the proposed model, a message dissemination simulator is generated and the message disseminations on various scenarios are analyzed.

• The Journal of Korean Association of Computer Education
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• v.12 no.3
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• pp.31-40
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• 2009

English education taken with native English speakers is very effective, but it is hard to obtain English education with native English speakers in rural schools. In this study, therefore, we supported English education with on-line content and video conferencing with native English speakers. This study worked with one hundred fifty students from six elementary and middle schools equally distributed by city size over three months. This study performed experimental research by T-test comparing of pre- and post-tests of the hybrid model. In our results, the upper group showed greater improvement in understanding while the lower group showed more improvement in writing. In addition, the lower group showed more improvement than the upper group in overall English accomplishment.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.105-110
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• 2016

As smart devices have proliferated and network speed and accessibility of mobile have accelerated, mobile cloud services that can do the same tasks by various devices are promoted. This paper explores the analysis of use intention of mobile cloud services and influencing factors. We develop and apply a convergence technology acceptance model which combines TAM, VAM and UTAUT. The proposed model verifies some hypotheses to aware the significant factors of use intention of mobile cloud services with TAM, VAM and UTAUT including additional mobile cloud service characteristics such as mobility, high availability, easy accessibility and scalability. Eventually, this research can not only help users gain insights into mobile cloud service use intention, but also help mobile cloud service providers to develop more effective mobile cloud service and their business strategy in the future.