• Journal of Satellite, Information and Communications
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• v.6 no.2
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• pp.51-59
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• 2011

To support seamless IPTV services in IP-based wireless network, delay or interruption time must be minimized because noticeable interruption will make IPTV service users unhappy. A number of protocols have been proposed for solving mobility problem. However effective seamless handover mechanism to support mobile IPTV services yet to be solved. Mobile WiMAX offers a wireless solution in the access networks that can support IPTV services. Goal of this paper is to identify some reasons of delay time during handover process in an IPv6 capable Mobile WiMAX and to perform handover delay of some optimization scenarios given by existing standardization and proposed improvement.

• The KIPS Transactions:PartC
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• v.15C no.1
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• pp.69-78
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• 2008

In this paper, we propose the effective exchange-method of a user profile for adapted contents services in the contents adaptation system. The profiles continuously exchange among the devices of contents adaption system for providing the adapted contents to a user. The profile should be also exchanged according to periodic, aperiodic, event, request and response. Consequently, a lot of network traffic occur and computing power require. Solving theses problem, the profile exchange research needs. we analyze creation information, exchange information, and exchange form of the profile information in contents adaptation system for effective profile exchange and define exchange procedure of the profile using the analyzed profile information. we also propose providing method of the profile configured information for decreasing profile processing time and user setting method for decreasing the number of profile transmission. As a result of performance evaluation, providing method of the profile configured information reduce 7% processing time and user setting method decrease the number of profile transmission are effective to exchange the profile.

• Education of Primary School Mathematics
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• v.6 no.1
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• pp.11-28
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• 2002

The purposes of this study were to analyze elementary school mathematics textbooks developed in accordance with the 7th national amended curriculum and to find implications for the development of a new revised curriculum to meet the needs of the knowledge-based society. Elementary school mathematics textbooks and accompanying practice books were analyzed. Teacher's manuals were also studied to examine the intentions of the textbook developers. The two major questions were sought. First, to what degree do elementary school mathematics textbooks and practice books match with the intentions of the national curriculum\ulcorner Second, how do elementary school mathematics textbooks and practice books facilitate student's learning for understanding mathematics\ulcorner The findings were as follows. First textbooks, practice books, and teacher's manuals appeared not to reflect the intentions of the 7th amended curriculum to the full extent. Second, characteristics and roles of textbooks, practice books, and teacher's manuals were not clearly defined and therefore, they were not very feasible for teaming for understanding mathematics. The recommendations for a new revised curriculum were suggested. First, regarding the contents presented in the textbooks, the idea of structure of subject matter need to be considered in order to help students to understand connections of concepts and relationships between concepts and functions in mathematics. Second, more ill defined problems should be presented to develop problem solving ability in real life contexts in students. Third, contents for relearning and enrichment need to be reorganized to reflect students' real ability. Fourth, uses of the concrete and the manipulative need to be more realistically suggested. Fifth, more prototypes of performance assessment tasks, scoring rubrics, and portfolios need to be presented in a more teacher-friendly manner. Sixth, characteristics and roles of textbooks and practice books need to be more discernible.

• The KIPS Transactions:PartC
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• v.18C no.4
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• pp.243-250
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• 2011

Nowadays, the traffic type and behavior are extremely diverse due to the appearance of various services on Internet, which makes the need of traffic identification important for efficient operation and management of network. In recent years traffic identification methodology using statistical features of flow has been broadly studied. We also proposed a traffic identification methodology using payload size distribution in our previous work, which has a problem of low completeness. In this paper, we improved the completeness by solving the PSD conflict using IP and port. And we improved the accuracy by changing the distance measurement between flow and statistic signature from vector distance to per-packet distance. The feasibility of our methodology was proved via experimental evaluation on our campus network.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.775-784
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• 2019

Image stitching is a technique for solving the problem of narrow field of view of a camera by composing multiple images. Recently, as the use of content such as Panorama, Super Resolution, and 360 VR increases, the need for faster and more accurate image stitching technology is increasing. So far, many algorithms have been proposed to satisfy the required performance, but the objective evaluation method for measuring the accuracy has not been standardized. In this paper, we present the problems of PSNR and SSIM(Structural similarity index method) measurement methods and propose a Local Differential Pixel Mean method. The LDPM evaluation method that includes geometric similarity and brightness measurement information is proved through a test, and the advantages of the evaluation method are revealed through comparison with SSIM.

• The Journal of Korean Society for School & Community Health Education
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• v.18 no.2
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• pp.97-105
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• 2017

Objectives: The purpose of this study is to investigate the knowledge, confidence and coping ability about emergency treatment, and the impact of right knowledge and confidence in practice on coping ability in part of dental hygienists. In addition, we suggest emergency treatment knowledge for develop substantive education program applicable to clinical as required data. Methods: This subjects were 259 dental hygienists working in dental setting Seoul, Gyeonggi-do from June 5 to July 20, 2016. We analyzed the data with frequency analysis, descriptive statistics, t-test, one-way ANOVA, pearson correlation coefficient, regression analysis by using SPSS. Results: Emergencies experienced by a dental hygienist in dental practice were fainting, local anesthetic allergies, and seizures. As a result of comparing the first aid knowledge, self-confidence, coping ability according to general characteristics of the study subjects, university graduation was higher than college and 3~5 years of working experience showed higher self confidence(F=3.837, p=0.023). The performance of self confidence and coping ability according to the characteristics of first aid showed high results in first aid training and dental hygienist having CPR license. Based on multiple regression analysis, confidence about emergency treatment is the biggest impact on coping ability(p<0.05). Conclusions: Dental hygienists need to develop and provide programs that can improve the ability of dental hygienists to respond appropriately and promptly in case of emergencies by recognizing the importance of first aid through conservative education.

• Journal of Korea Game Society
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• v.21 no.5
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• pp.17-28
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• 2021

Reinforcement learning, in which artificial intelligence develops itself to find the best solution to problems, is a technology that is highly valuable in many fields. In particular, the game field has the advantage of providing a virtual environment for problem-solving to reinforcement learning artificial intelligence, and reinforcement learning agents solve problems about their environment by identifying information about their situation and environment using observations. In this experiment, the instant dungeon environment of the RPG game was simplified and produced and various observation variables related to the field of view were set to the agent. As a result of the experiment, it was possible to figure out how much each set variable affects the learning speed, and these results can be referred to in the study of game RPG reinforcement learning.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.85-110
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• 2018

A chatbot is an interactive assistant that utilizes many communication modes: voice, images, video, or text. It is an artificial intelligence-based application that responds to users' needs or solves problems during user-friendly conversation. However, the current version of the chatbot is focused on understanding and performing tasks requested by the user; its ability to generate personalized conversation suitable for relationship-building is limited. Recognizing the need to build a relationship and making suitable conversation is more important for social chatbots who require social skills similar to those of problem-solving chatbots like the intelligent personal assistant. The purpose of this study is to propose a text analysis method that evaluates relationships between chatbots and users based on content input by the user and adapted to the communication situation, enabling the chatbot to conduct suitable conversations. To evaluate the performance of this method, we examined learning and verified the results using actual SNS conversation records. The results of the analysis will aid in implementation of the social chatbot, as this method yields excellent results even when the private profile information of the user is excluded for privacy reasons.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1542-1550
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• 2019

Legacy studies for classifying arrhythmia have been studied to improve the accuracy of classification, Neural Network, Fuzzy, etc. Deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose optimal parameter extraction method based on a deep learning. For this purpose, R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 97.84% in PVC classification.