• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.114-116
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• 2016

Recently, SDN and NFV technology have been developed actively and provide enormous flexibility of network provisioning. The future network services would generally involve many different types of services such as hologram games, social network live streaming videos and cloud-computing services, which have dynamic service requirements. To provision networks for future services dynamically and efficiently, SDN/NFV orchestrators must clearly understand the service requirements. Currently, network provisioning relies heavily on QoS parameters such as bandwidth, delay, jitter and throughput, and those parameters are necessary to describe the network requirements of a service. However it is often difficult for users to understand and use them proficiently. Therefore, in order to maintain interoperability and homogeneity, it is required to have a service abstraction layer between users and orchestrators. The service abstraction layer analyzes ambiguous user's requirements for the desired services, and this layer generates corresponding refined services requirements. In this paper, we present our initial effort to design a Smart Service Abstraction Layer (SmSAL) for future network architecture, which takes advantage of machine learning method to analyze ambiguous and abstracted user-friendly input parameters and generate corresponding network parameters of the desired service for better network provisioning. As an initial proof-of-concept implementation for providing viability of the proposed idea, we implemented SmSAL with a decision tree model created by learning process with previous service requests in order to generate network parameters related to various audio and video services, and showed that the parameters are generated successfully.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.2
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• pp.149-158
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• 2005

In this paper, we have designed and implemented a portable e-tongue (electronic tongue) system using MACS (multi array chemical sensor) and PDA. The system embedded in PDA has merits such as comfortable user interface and data transfer by internet from on-site to remote computer. MACS was made up 7 electrodes (${NH_4}^+$, $Na^+$, $Cl^-$, ${NO_3}^-$, $K^+$, $Ca^{2+}$, $Na^+$, pH) and a reference electrode. For learning the system, we adapted the Levenberg-Marquardt algorithm based on the back-propagation, which could iteratively learned the pre-determined standard patterns, in e-tongue system. Conclusionally, the relationship between the standard patterns and unknown pattern can be easily analyzed. The e-tongue was applied to whiskeys and cognac (one high level whisky, one low level whiskey, two cognac) and 2 sample whiskeys for each standard patterns and unknown patterns. The relationship between the standard patterns and unknown patterns can be easily analyzed.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.455-460
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• 2016

Recently, with more severe types felonies such as robbery and sexual violence, the importance of crime prediction and prevention is emphasized. For accurate and prompt crime prediction and prevention, both a classification model of crime with high accuracy based on past criminal records and well-designed system interface are required. However previous studies on the analysis of crime factors have limitations in terms of accuracy due to the difficulty of data preprocessing. In addition, existing crime monitoring systems merely offer a vast amount of crime analysis results, thereby they fail to provide users with functions for more effective monitoring. In this paper, we propose a classification model for types of crime based on random-forest algorithms and system design factors for real-time crime prediction. From our experiments, we proved that our proposed classification model is superior to others that only use criminal records in terms of accuracy. Through the analysis of existing crime monitoring systems, we also designed and developed a system for real-time crime monitoring.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.3
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• pp.1515-1521
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• 2014

This study applies simulation-based education and care for acute myocardial infarction nursing students to investigate the effect of critical thinking, problem solving, and academic achievement of a single group before and after the raw experimental design. A total of 137 subjects were arbitration period September-October 2011, enforcement and arbitration were evaluated after simulation-based training six weeks total. Data analysis was performed using SPSS Win17.0, Paired t-test, the mean and standard deviation, Pearson's correlation coefficient was used. Research results of simulation-based training program to improve critical thinking, problem solving, and academic achievement were As increase critical thinking and problem solving ability was improved. whereas, Critical thinking skills and problem solving ability was no significant difference with academic achievement. Simulation-based training program to improve the practical skills of nursing students learning was found how useful it, that there is a need to take advantage of hands-on training in a variety of cases that can be common in the field of clinical scenarios developed by. To do this, It seems to be necessary to the development and operation more varied and appropriate hands-on training method.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.1027-1038
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• 2006

There are many technical problems in the recommendation system based on very large database(VLDB). So, it is necessary to study the recommendation system' structure and the data-mining technique suitable for the large scale Internet shopping mail. Thus we design and implement the product recommendation system using k-means clustering algorithm and sequential pattern technique which can be used in large scale Internet shopping mall. This paper processes user information by batch processing, defines the various categories by hierarchical structure, and uses a sequential pattern mining technique for the search engine. For predictive modeling and experiment, we use the real data(user's interest and preference of given category) extracted from log file of the major Internet shopping mall in Korea during 30 days. And we define PRP(Predictive Recommend Precision), PRR(Predictive Recommend Recall), and PF1(Predictive Factor One-measure) for evaluation. In the result of experiments, the best recommendation time and the best learning time of our system are much as O(N) and the values of measures are very excellent.

• Journal of KIISE
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• v.44 no.7
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• pp.668-673
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• 2017

Deep neural networks have shown remarkable performance in various fields of pattern recognition such as voice recognition, image recognition and object detection. However, underlying mechanisms of the network have not been fully revealed. In this paper, we focused on empirical analysis of the network parameters. The Faster R-CNN(region-based convolutional neural network) was used as a baseline network of our work and three important parameters were analyzed: the dropout ratio which prevents the overfitting of the neural network, the size of the anchor boxes and the activation function. We also compared the performance of dropout and batch normalization. The network performed favorably when the dropout ratio was 0.3 and the size of the anchor box had not shown notable relation to the performance of the network. The result showed that batch normalization can't entirely substitute the dropout method. The used leaky ReLU(rectified linear unit) with a negative domain slope of 0.02 showed comparably good performance.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.108-115
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• 2006

e-Learning contents are composed of compounding multimedia data. It requires many professionals in contents development stage. The process of e-learning contents development can be seen as a collaborative work. In the perspective of a collaborative work process, the whole process of e-learning contents development would be regarded as collaborative work process for each participant as well as for whole group members. Most of collaborative works in contents development field are widely distributed. Members of work groups require workspaces for sharing information and communicating each other. In addition to workspaces, it also needs to support collaborative reflection such as planning for collaborative work and monitoring for work process. This paper is intended to develop the reflective collaborative work system for e-Learning contents development in order to support the systemic process of e-learning contents development. The reflective collaborative work system is composed of four supportive parts: work flow management, personal workspace, collaborative workspace, and collaborative reflection.

• Journal of Engineering Education Research
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• v.11 no.1
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• pp.24-33
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• 2008

The purpose of the study was to analyze system of accreditation for mechanical engineering education between A university in Korea and M university in U.S.A. which were evaluated in 2007 under EC2000. Literature review through self-study report and homepage of two programs was used to accomplish objectives of the study. Strengths of U.S.A for accreditation evaluation system were systematic curriculum operation, design education with cooperation system, course-based evaluation system for program outcome, supportive circumstances for research of faculty and guidance to students. On the other hands, strengths of Korea were likely to use quantitative data for educational improvement and were able to systematic guide to students with portfolio. In the future, plan and research for design education, curriculum operation and program outcome evaluation are needed to establish ABEEK evaluation.

• Journal of Science Education
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• v.40 no.1
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• pp.17-30
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• 2016

The purpose of this study was to investigate the effects of problem solving activities of STEAM program on metacognition of middle school students. The subject was 63 middle school students. This study was designed single group pre-posttest. A single-group t-test was performed for analyzing difference between the pre-post test on metacognition. In the result of this study, there was significant difference between pretest and posttest on middle school students' metacognition. Also there was significant difference on metacognitive knowledge and metacognitive regulation. The analysis on the subelements of metacognition showed significant difference between pretest and posttest. The multiple regression analysis to investigate the relation of sub-elements of metacognition was performed in this study. The result of the analysis showed high explanatory power among metacognition subelements. This result suggests that the problem solving activities of STEAM program can have a positive effect in promoting metacognition. of the learner.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.257-266
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• 2012

R is a free software for statistical analysis that provides simple interfaces to other application programs. Many people are trying to learn R, but it is difficult to learn R compared to commercial software such as SPSS or SAS, and it is cumbersome to provide an environment to teach R. Thus, it is essential to provide a new web-based R environment for novice users or for laboratory use. We developedWebER (a web-based R environment) using PHP on the Linux apache server. WebER can be easily used by any R user because we implemented the same functions as the basic Rgui such as editing R program, generating the text, image outputs, errors and warnings. It is also possible for multi-users to access WebER.