• KNOM Review
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• v.23 no.2
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• pp.29-41
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• 2020

Networks are growing faster than ever before causing a multi-domain complexity. The diversity, variety and dynamic nature of network traffic and services require enhanced orchestration and management approaches. While many standard orchestrators and network operators are resulting in an increase of complexity for handling E2E slice orchestration. Besides, there are multiple domains involved in E2E slice orchestration including access, edge, transport and core network each having their specific challenges. Hence, handling of multi-domain, multi-platform and multi-operator based networking environments manually requires specified experts and using this approach it is impossible to handle the dynamic changes in the network at runtime. Also, the manual approaches towards handling such complexity is always error-prone and tedious. Hence, this work proposes an automated and abstracted solution for handling E2E slice orchestration using an intent-based approach. It abstracts the domains from the operators and enable them to provide their orchestration intention in the form of high-level intents. Besides, it actively monitors the orchestrated resources and based on current monitoring stats using the machine learning it predicts future utilization of resources for updating the system states. Resulting in a closed-loop automated E2E network orchestration and management system.

• Journal of The Korean Association of Information Education
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• v.17 no.2
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• pp.147-156
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• 2013

Computer Science has been developed thru the study of information processing, the study of what can be automated, the study of computation, and the study of information processes both natural and artificial. As developing the computer science, the aspect of informatics education was changed. Recently we focus on computational thinking education. In this paper, I review the progress of informatics education and research the applying of unplugged computing as a method of computational thinking education. I also research the considerations about applying of unplugged computing in aspects of teacher preparation, educational content, and teaching resources. As result I found that teachers change their perceptions about computer education, understand the computer science contents, and understand the promotion of students thinking skills in point of view at teacher preparation, that teachers can set the levels of abstraction and can enrich and integrate of contents, and that teacher can manage class time and educational resources preparation in point of view at educational resources.

• The Journal of Society for e-Business Studies
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• v.11 no.2
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• pp.71-91
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• 2006

Nowadays most enterprise want to organize all Information Technology elements for their vision and mission accomplishments by integration view Enterprise architecture is used by the solution. But IT is so more complex that it can't cover application development. This research defines software architecture framework by enterprise view and designs enterprise architecture framework for embracing application development. Software architecture framework consists of meta architecture, conceptual architecture, logical architecture, physical architecture. For enterprise architecture framework including enterprise software architecture framework, this research analyzes its perspectives and Views. After all, This research able to apply to systematic application development based on enterprise architecture and completely IT elements organization by enterprise view.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1455-1473
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• 2004

This paper suggests a technique, TELOR(Technique of Object Extraction Based on Legacy System Interface for Improvement of Object Reusability) for reuse and reengineering by analyzing the Legacy System interface to distill the meaningful information from them and disassemble them into object units which are to be integrated into the next generation systems. The TELOR method consists of a 4 steps procedure: 1) the interface use case analysis step, 2) the interface object dividing step, 3) the object structure modeling step, and 4) the object model integration step. In step 1, the interface structure and information about the interaction between the user and the Legacy System are obtained. In step 2, the interface information is divided into semantic fields. In step 3, studies and models the structural and collaborative relationship among interface objects. Finally, in step 4, object model integration step, integrates the models and improves the integrated model at a higher level. The objects integration model created through TELOR provides a more efficient understanding of the Legacy System and how to apply it to next generation systems.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.483-491
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• 2007

This paper proposes a Situation Simulation Framework for implementing computer game and describes the possibility of analyzing game with unfolding situation. In last few years game systems have been evolving from the performance of physical engine, network traffic in the on line game to the representation of rendering physical phenomena. In computer game, a situation hierarchy structure which allows the designer for simulating high-level specifications of game structure. Logically simulated environment is created by defining situations and events based on hierarchy structure of the situation. We classify events into explicit event is occurred by user and implicit event is occurred by system. Our study defines the existence of objects is the most prevalent factor applied to any event in game world. The advantages of this approach are able to allow for providing the conceptual design for simulation game and analyzing the situation in the game world. And this method allows us to decrease the complexity of system design and abstraction modeling for the simulation game. Specially, the introduction of the definition of events allows us to approach game design in a structural manner rather than by their classification. The proposed method was implemented in the "Shooting BaDuk" among games.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.614-618
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• 2016

As information on the internet and the data from smart devices are growing, the amount of stream data is also increasing in the real world. The stream data, which is a potentially large data, requires online learnable models and algorithms. In this paper, we propose a novel class of models: predictive convolutional neural networks to be able to perform online learning. These models are designed to deal with longer patterns as the layers become higher due to layering convolutional operations: detection and max-pooling on the time axis. As a preliminary check of the concept, we chose two-month gathered GPS data sequence as an observation sequence. On learning them with the proposed method, we compared the original sequence and the regenerated sequence from the abstract information of the models. The result shows that the models can encode long-range patterns, and can generate a raw observation sequence within a low error.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.113-121
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• 2018

Position encoding is a method of applying weights according to position of words that appear in a sentence. Pointer networks is a deep learning model that outputs corresponding index with an input sequence. This model can be applied to coreference resolution using attribute. However, the pointer networks has a problem in that its performance is degraded when the length of input sequence is long. To solve this problem, we proposed two contributions to resolve the coreference. First, we applied position encoding and dynamic position encoding to pointer networks. Second, we stack deeply layers of encoder to make high-level abstraction. As results, the position encoding based stacked pointer networks model proposed in this paper had a CoNLL F1 performance of 71.78%, which was improved by 6.01% compared to vanilla pointer networks.

• Journal of KIISE
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• v.43 no.9
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• pp.953-962
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• 2016

Model-based testing is a technique for performing the test by using a model that represents the behavior of the system as a system specification. Industrial domains such as automotive, military/aerospace, medical, railway and nuclear power generation require model-based testing and code coverage-based testing to improve the quality of software. Despite the fact that both model-based testing and code coverage-based testing are required, difficulty in achieving a high coverage using model-based testing caused by the abstraction level difference between the test model and the source code, results in the need for performing model-based testing separately. In this study, to overcome the limitations of the existing model-based testing, we proposed the state machine transformation method to effectively improve the code coverage using the protocol state machine, one of the typical modeling methods is used as the test model in model-based testing, as the test model. In addition, we performed a case study of both systems and analyzed the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.144-150
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• 2017

Recently, deep learning is used for intelligent processing and accuracy improvement of data. It is formed calculation model composed of multi data processing layer that train the data representation through an abstraction of the various levels. A category of deep learning, convolution neural network is utilized in various research fields, which are human pose estimation, face recognition, image classification, speech recognition. When using the deep layer and lots of class, CNN that show a good performance on image classification obtain higher classification rate but occur the overfitting problem, when using a few data. So, we design the training network based on convolution neural network and trained our image data set for object classification in few class problem. The experiment show the higher classification rate of 7.06% in average than the previous networks designed to classify the object in 1000 class problem.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.61-75
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• 2008

A script language, which represents and controls avatar behaviors in a natural language style, is especially remarkable, because it can provide a fast and easy way to develop an animation scenario script. However, the studies that consider avatar behavior interactions with various virtual objects and intuitive interface techniques to design scenario script have been lack. Therefore, we proposed a context-based avatar-object behavior model and layered script language. The model defines context-based elements to solve ambiguity problems that occur in abstract behavior interface and it provides user interface to control avatar in the object-based approach. Also, the proposed avatar behavior script language consisted of a layered structure that represents domain user interface, motion sequence, and implement environment information at each level. Using the proposed methods, the user can conveniently and quickly design an avatar-object behavior scenario script.