• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.9-20
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• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

• Journal of Internet Computing and Services
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• v.14 no.3
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• pp.23-33
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• 2013

Recently in the field of IT, cloud computing technology has been deployed rapidly in the current society because of its flexibility, efficiency and cost savings features. However, cloud computing system has a big problem of vulnerability in security. In order to solve the vulnerability of cloud computing systems security in this study, impact types of virtual machine about the vulnerability were determined and the priorities were determined according to the risk evaluation of virtual machine's vulnerability. For analyzing the vulnerability, risk measurement standards about the vulnerability were defined based on CVSS2.0, which is an open frame work; and the risk measurement was systematized by scoring for relevant vulnerabilities. Vulnerability risk standards are considered to suggest fundamental characteristics of vulnerability and to provide the degree of risks and consequently to be applicable to technical guides to minimize the vulnerability. Additionally, suggested risk standard of vulnerability is meaningful as the study content itself and could be used in technology policy project which is to be conducted in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5301-5323
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• 2017

Small cell deployment offers a low-cost solution for the boosted traffic demand in heterogeneous cellular networks (HCNs). Besides improved spatial spectrum efficiency and energy efficiency, future HCNs are also featured with the trend of network architecture convergence and feasibility for flexible mobile applications. To achieve these goals, dual connectivity (DC) is playing a more and more important role to support control/user-plane splitting, which enables maintaining fixed control channel connections for reliability. In this paper, we develop a tractable framework for the downlink SINR analysis of DC assisted HCN. Based on stochastic geometry model, the data-control joint coverage probabilities under multi-frequency and single-frequency tiering are derived, which involve quick integrals and admit simple closed-forms in special cases. Monte Carlo simulations confirm the accuracy of the expressions. It is observed that the increase in mobility robustness of DC is at the price of control channel SINR degradation. This degradation severely worsens the joint coverage performance under single-frequency tiering, proving multi-frequency tiering a more feasible networking scheme to utilize the advantage of DC effectively. Moreover, the joint coverage probability can be maximized by adjusting the density ratio of small cell and macro cell eNBs under multi-frequency tiering, though changing cell association bias has little impact on the level of the maximal coverage performance.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.119-127
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• 2019

This paper proposes a new authentication model to solve the problem of personal information takeover and personal information theft by service providers using centralized servers for user authentication and management of personal information. The centralization issue is resolved by providing user authentication and information storage space through a decentralize platform, blockchain, and ensuring confidentiality of information through user-specific symmetric key encryption. The proposed model was implemented using the public-blockchain Ethereum and the web-based wallet extension MetaMask, and users access the Ethereum main network through the MetaMask on their browser and store their encrypted personal information in the Smart Contract. In the future, users will provide their personal information to the service provider through their Ethereum Account for the use of the new service, which will provide user authentication and personal information without subscription or a new authentication process. Service providers can reduce the costs of storing personal information and separate authentication methods, and prevent problems caused by personal information leakage.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.55-63
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• 2017

One of the purposes of Information Technology (IT) is to support human response to natural and social problems such as natural disasters and spread of disease, and to improve the quality of human life. Recent climate change has happened worldwide, natural disasters threaten the quality of life, and human safety is no longer guaranteed. IT must be able to support tasks related to disaster response, and more importantly, it should be used to predict and minimize future damage. In South Korea, the data related to the damage is checked out by each local government and then federal government aggregates it. This data is included in disaster reports that the federal government discloses by disaster case, but it is difficult to obtain raw data of the damage even for research purposes. In order to obtain data, information extraction may be applied to disaster reports. In the field of information extraction, most of the extraction targets are web documents, commercial reports, SNS text, and so on. There is little research on information extraction for government disaster reports. They are mostly text, but the structure of each sentence is very different from that of news articles and commercial reports. The features of the government disaster report should be carefully considered. In this paper, information extraction method for South Korea government reports in the word format is presented. This method is based on patterns and dictionaries and provides some additional ideas for tokenizing the damage representation of the text. The experiment result is F1 score of 80.2 on the test set. This is close to cutting-edge information extraction performance before applying the recent deep learning algorithms.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.79-88
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• 2018

Major countries stay to expand invest in R&D to promote new growth engines in the future and to secure new technologies and Korea is also expanding to R&D investment. Quality of R&D investment is getting more Important than quantity of R&D investment because Korea's indicator related to R&D investment is already world class with other countries's investment scale by comparison with GDP. According to this trend, Korea's policy in R&D is focusing the R&D Innovation Plan and "Utilization of R&D Facility and Equipment(F&E)" has been getting important. In this research, it research on facility and equipment management plan through Defense R&D Equipment information System(DRES). It analyzes existing process F&E in Defense field and Nation. Furthermore, it explains major process, function, and menu reflecting Defense F&E management rule enacted recently. Lastly, it shows the development direction for Defense F&E management.

• 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.

• Korean journal of communication and information
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• v.66
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• pp.5-27
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• 2014

The past, present, and future of online journalism in Korea are inextricably bound up with the portal site news services. In traditional journalism, finite news media took hold on news consumption completely because of performing news production and distribution simultaneously. Since then, in the age of multi-media and multi-channel, the audience selection has become more important because of greatly increasing news media and then exploding news production. In online journalism, the news distribution have emerged as the most important field because of the intensive consuming the portal site news services making use of various news easier, the characteristic of news consumption focusing on not news media brands but news media contents, etc. Therefore, the news present landscape of Korean journalism oriented news distribution has been completed by that the portal site news services became the symbol of online journalism. That the portal site news services performing only news distribution have more influence than the paper based online newspapers and Internet based online newspapers producing news means the change of media power. By this, a conflict between news media and portal site news services appears at all times.

• Journal of Digital Convergence
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• v.13 no.3
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• pp.209-214
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• 2015

Social network services such as Facebook and Flickr is a very useful service that was the foundation of the Internet. If a state in which the Internet is connected, music, photos, and us to be able to share it freely post such as documents. However, even when the digital information posted in such social network services the user has died, and have been published, it is also used for people who do not intend the bad purposes some problems can occur. Facebook is trying to apply the findings Jed R. Brubaker of UC Irvine University in order to solve this problem. However, in Korea, such efforts, not much appears for now. Therefore, we proposed a method that can be managed by delegated Facebook, safely a Delegator digital information posted on social networking services such as Flickr. Our proposed system, as compared with Jed R. Brubaker and Jeong-Kyung Moon is executed previous studies, we studied a method proposed by the appropriate compensates points shortage is passed through the future research. And I consider to have been proposed a method to safely use posted digital assets in a social network service.

• Journal of Digital Convergence
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• v.14 no.6
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• pp.199-218
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• 2016

The purpose of this study is to investigate the determinants of consumer's repurchase intention in the foreign direct sales shopping malls, focusing on the Japanese customers. Research model of the study is composed of seven independent variables (price competitiveness, product diversity, reputation, country-of-origin image, ease of use, delivery service, after service), a mediating variable (trust) and a dependent variable (repurchase intention). The results of this study show that trust is an important factor affecting the repurchase intention of customers. Customers' trust is affected by the reputation, country-of-origin image, ease of use, delivery service, after service. However, price competitiveness and product diversity, which are hypothesized to affect the trust, are not statistically significant. This study will provide a basis for future research on the foreign direct sales area. In addition, it will provide practical information useful in launching and/or operating the foreign direct sales malls.