• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.75-80
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• 2009

In this study, a Web server was constructed using LabVIEW's DataSocket, which makes possible acquisition, analysis, and saving in real time. The output value of the optical current sensor at the web server PC was measured and the output value was displayed using the Web browser of the client PC. DataSocket by LabVIEW makes the construction of a Web server easier than other languages and is compatible with other application programs. An optical current sensor was composed using a 1310 [nm] laser diode, and 9/125 [${\mu}m$] standard single mode optical fiber and was created to be a close type sensor. Data measurement using Web servers has the advantage of monitoring electric power systems at a great distance and can fuse IT technology and electric power systems. Also, this measurement uses inexpensive mounting and programming when compared to existing measurement equipment allowing the construction of a measurement system in any situation or surrounding.

• ETRI Journal
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• v.41 no.2
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• pp.207-223
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• 2019

Network function virtualization can significantly improve the flexibility and effectiveness of network appliances via a mapping process called service function chaining. However, the failure of any single virtualized network function causes the breakdown of the entire chain, which results in resource wastage, delays, and significant data loss. Redundancy can be used to protect network appliances; however, when failures occur, it may significantly degrade network efficiency. In addition, it is difficult to efficiently map the primary and backups to optimize the management cost and service reliability without violating the capacity, delay, and reliability constraints, which is referred to as the reliability-aware service chaining mapping problem. In this paper, a mixed integer linear programming formulation is provided to address this problem along with a novel online algorithm that adopts the joint protection redundancy model and novel backup selection scheme. The results show that the proposed algorithm can significantly improve the request acceptance ratio and reduce the consumption of physical resources compared to existing backup algorithms.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.31-34
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• 2021

The classical HMM is defined by a parameter triple �� = (��, A, B), where each parameter represents a collection of probability distributions: initial state, state transition and output distributions in order. This paper proposes a new stationary parameter e = (e1, e2, …, eN) where N is the number of states and et = P(|xt = i, y) for describing how an input pattern y ends in state xt = i at time t followed by nothing. It is often said that all is well that ends well. We argue here that all should end well. The paper sets the framework for the theory and presents an efficient inference and training algorithms based on dynamic programming and expectation-maximization. The proposed model is applicable to analyzing any sequential data with two or more finite segmental patterns are concatenated, each forming a context to its neighbors. Experiments on online Hangul handwriting characters have proven the effect of the proposed augmentation in terms of highly intuitive segmentation as well as recognition performance and 13.2% error rate reduction.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.373-378
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• 2019

Since many programming sources are open online, problems with reckless plagiarism and copyrights are occurring. Among them, source codes produced by repeated authors may have unique fingerprints due to their programming characteristics. This paper identifies each author by learning from a Google Code Jam program source using deep neural network. In this case, the original creator's source is to be vectored using a pre-processing instrument such as predictive-based vector or frequency-based approach, TF-IDF, etc. and to identify the original program source by learning by using a deep neural network. In addition a language-independent learning system was constructed using a pre-processing machine and compared with other existing learning methods. Among them, models using TF-IDF and in-depth neural networks were found to perform better than those using other pre-processing or other learning methods.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.222-235
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• 2018

This study explores the factor which effects user's viewing on online in the situation of increasing viewing via OTT. After analyzing how the amount of news coverage and viewing rate affects user's active viewing, higher the number of views, In case of groundwave programs, if number of news coverage is high, hits of view and the number of comments is also high. While viewing rate, the number of views, the number of comments are independent of each other. In case of TV channels of comprehensive programming and cable TV, there is a interaction effect of viewing rate and the amount of news coverage. This study highlights the importance of the amount of news coverage when viewers is watching video on web.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.127-133
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• 2019

A callable product is one of service derivatives using options to generate demand and reduce risk. This paper compares two booking admission controls for callable products, the online and the batch admission controls. To this end, the paper computes the optimal booking policy by using the backward dynamic programming and the stochastic optimization method. Intuitively, the provider should outperform under the batch control by utilizing demand information. The contribution of the paper is to show that the two controls are equivalent in terms of the booking strategy and the expected profit, which enables the provider to keep its current control method. The paper develops the closed-form solutions for the three fare classes. The future work is to extend the result to the model with complicated fare structures.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.143-150
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• 2021

Process model is an integral part of software industry. Different process models are used now a days in the industry for different software projects. Process models need to be tailored to address some specific project needs. Agile models are considered as the most widely used process models nowadays. They have distinctive features and the ability to address the dynamic needs of today's software development. Extreme programming (XP) is one of the extensively used agile process model especially for small projects. Many researchers have tried to mold XP to overcome its shortcomings and for better working in specific scenarios. Therefore, many customized versions of XP process model are available today. In this paper, we are going to analyze the latest customizations of XP. For this purpose, a systematic literature review is conducted on studies published from 2012 till 2018 in renowned online search libraries. This comprehensive review highlights the purpose of customizations, along with the areas in which customizations are made, and phases & practices which are being customized. This work will serve the researchers to discover the modern versions of XP process model as well as will provide a baseline for future directions for customizations.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.193-198
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• 2023

This paper analyzed the validity of exercise problems for each unit in Python programming education. Practice questions presented for each unit are presented through an online learning system, and each student uploads an answer code and is automatically graded. Data such as students' mid-term exam scores, final exam scores, and practice questions scores for each unit are collected through Python lecture that lasts for one semester. Through the collected data, it is possible to improve the exercise problems for each unit by analyzing the validity of the automatic scoring exercise problems. In this paper, Orange machine learning tool was used to analyze the validity of automatic scoring exercises. The data collected in the Python subject are analyzed and compared comprehensively by total, top, and bottom groups. From the prediction accuracy of the machine learning model that predicts the student's final grade from the Python unit-by-unit practice problem scores, the validity of the automatic scoring exercises for each unit was analyzed.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.1-11
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• 2021

NC Soft will continue to dream of an entertainment innovation world where customers are connected through game and contents. NC Soft images an expansion in entertainment industry which open doors to the future of enjoy break through innovative online game and creative AI & IT technologies, focused on new business opportunities that are solely NC's own. This study starts with the implication on why focusing on exploration innovation and exploitation strategy at the same time in NC Soft is so challenging. NC Soft manages to their online & mobile gaming competencies in the long term and achieves their sustainable growth by incremental innovation (e.g. game planning, game programming, and graphic design). Also, for innovative success, pursuing exploration strategy is essential. NC Soft have built a strategic alliance spanning K-POP, digital contents platform, movie, and animation, sharing the connectivity of entertainment domains with major contents corporations. The findings of this study would also beneficial to entertainment and contents corporation executives and could provide some road-map on managing the dual challenges of exploration and exploitation implementations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.508-510
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• 2021

In this study, the difference in resilience was analyzed based on the results of a study of classes that practiced using Raspberry Pi, which had to cross school due to temporarily conducting online classes due to the COVID-19 pandemic. As a result of the study, in online classes, 14 people had resilience less than 150, 32 people who had 150 or more and less than 180, and 9 people who had 180 or more. On the other hand, in the school attendance class, there were 7 people with resilience less than 150, 29 people with resilience less than 150 and less than 180, and 20 people with more than 180. Therefore, in subjects where programming using Raspberry Pi and circuit manufacturing are taught at the same time, the laboratory and practice environment should be able to proceed properly as much as possible. should proceed mainly.