• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.222-235
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• 2008

This study looks at motivations of video UCC users as a member of creative class. A qualitative research method was used for analyzing data collected by interviews. Killing time users, active clickers and creators are distinguished as different types of UCC users and their differing motivations are explored. The findings of the study are as follows: First, information sharing, self presentation, communication needs, ease of use for self presentation, usefulness are expressed as motivating factors for both active clickers and creators, Pleasure motivates every type of users. However, content creators experience a specific type of pleasure which is the pleasure of creativity or flow, which this study highlights as a key driving factor for content creators. The study adds to the findings of UCC user research which applies the TAM and the PAD model by revealing what pleasure and flow specifically mean for different types of UCC users.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.138-154
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• 2008

Geo-special technologies are being adopted in variety fields since the 3rd NGIS plan that was started at 1996. However, the required system or structure to guarantee the up-to-date validity and accuracy of the geospatial data - the most fundamental elements of the technology - was not constructed yet. All the activities related to geospatial data, including topographical map and numerical base map, are all implemented in separate way; from change of geographical objects and features, data gathering, and database construction to distribution, transfer and sharing of these data. The data model that links all the activities are required that enables consistent data-flow and effective and systematic work-flow. In this study, economic data renewal and exchange method was proposed, and benefit-cost analysis was implemented by comparing the conventional work-flow to newly proposed work-flow. The case study was implemented using the model that was adopted in Daegu metropolitan city, and the model was developed by reflecting these results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1254-1260
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• 2009

This paper proposes history-aware random early detection (HRED), a modified version of RED, to lessen bandwidth monopoly by a few of stations employing multiple parallel TCP flows. Stations running peer-to-peer file sharing applications such as BitTorrent use multiple TCP flows. If those stations share a link with other stations with only a small number of TCP flows, the stations occupy most of link bandwidth leading to undesirable bandwidth monopoly. HRED like RED determines whether to drop incoming packets according to probability which changes based on queue length. However it adjusts the drop probability based on bandwidth occupying ratio of stations, thus able to impose harder drop penalty on monopoly stations. The results of simulations assuming various scenarios show that HRED is at least 60% more effective than RED in supporting the bandwidth fairness among stations and at least 4% in utilization.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.235-247
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• 2021

Today, the cloud computing has become a major demand of many organizations. The major reason behind this expansion is due to its cloud's sharing infrastructure with higher computing efficiency, lower cost and higher fle3xibility. But, still the security is being a hurdle that blocks the success of the cloud computing platform. Therefore, a novel Multi-tenant Decentralized Information Flow Control (MT-DIFC) model is introduced in this research work. The proposed system will encapsulate four types of entities: (1) The central authority (CA), (2) The encryption proxy (EP), (3) Cloud server CS and (4) Multi-tenant Cloud virtual machines. Our contribution resides within the encryption proxy (EP). Initially, the trust level of all the users within each of the cloud is computed using the proposed two-stage trust computational model, wherein the user is categorized bas primary and secondary users. The primary and secondary users vary based on the application and data owner's preference. Based on the computed trust level, the access privilege is provided to the cloud users. In EP, the cipher text information flow security strategy is implemented using the blowfish encryption model. For the data encryption as well as decryption, the key generation is the crucial as well as the challenging part. In this research work, a new optimal key generation is carried out within the blowfish encryption Algorithm. In the blowfish encryption Algorithm, both the data encryption as well as decryption is accomplishment using the newly proposed optimal key. The proposed optimal key has been selected using a new Self Improved Cat and Mouse Based Optimizer (SI-CMBO), which has been an advanced version of the standard Cat and Mouse Based Optimizer. The proposed model is validated in terms of encryption time, decryption time, KPA attacks as well.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.887-888
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• 2016

Internet data for IoT(Internet of Things) period was changed in such a way that the data is done by sharing information for the user. However, in the existing system IoT environment for the user to utilize the system it has a problem does not take into account the individual characteristics. And there must be an intermediate vectors are capable of controlling problems such as Dongle. In this paper, through the flow sensor control applications as a way to solve this problem to control the flow of the sensor according to the characteristics desired by the user. Due to this makes it possible to easily manage the sensor compared to conventional IoT environment. Accordingly, the user must manage the sensor through the application regardless of time and place. So it is believed to reduce the unnecessary power consumption is possible effective control sensor.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.751-760
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• 2003

One of the business in the future will be executed by Business to Business(B to B) model of E-Commerce. The concept of the B to B model composes the work process, people, and supporting environment. The work processes are related to the information process, technologies, and standards. Information process elements contains digital data exchange, data sharing, and collaboration. This paper designed and implemented the XML-based Business Flow Management System(BFMS) for B to B model of E-commerce in the Internet. BFMS in this paper automatically performs the information process for B to B model such as electronic bidding system including purchase order management, bidding management, delivery management to build E-Commerce in the Internet. XML can be used as document standard between business for skating and exchange of data and also provide platform independent environment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.8
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• pp.1145-1153
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• 2015

The paper analyzes reactive power flow characteristic in power system by reactive power tracing. In addition, virtual buses are inserted in the algorithm to consider losses of transmission lines, and shunt capacitor treated as a reactive power generator. The results of simulation are analyzed by two points of view. The one is load’s point of view and another is generator’s point of view. Classic purpose of the reactive power tracing consists in the reactive power pricing. However, it is significantly used to select vulnerable area about line outage in this paper. To find the vulnerable area, reactive power tracing variations between pre-contingency and post-contingency are calculated at all load buses. In heavily load area, buses which has highest variation become the most vulnerable bus. This method is applied to the IEEE 39-bus system. It is compared with voltage variation result and VQ-margin to verify its effect.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4B
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• pp.202-209
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• 2005

In this paper, a dynamic TCP-friendly rate control (TFRC) is proposed to adjust the coding rates according to the channel characteristics of the wireless-to-wired network consisting of wireless first-hop channel. To avoid the throughput degradation of multimedia flows traveling through wireless lint the proposed rate control system employs a new wireless loss differentiation algorithm (LDA) using packet loss statistics. This method can produce the TCP-friendly rates while sharing the backbone bandwidth with TCP flows over the wireless-to-wired network. Experimental results show that the proposed rate control system can eliminate the effect of wireless losses in flow control of TFRC and substantially reduce the abrupt quality degradation of the video streaming caused by the unreliable wireless link status.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.119-130
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• 2022

Crime is a common social problem that affects the quality of life. As the number of crimes increases, it is necessary to build a model to predict the number of crimes that may occur in a given period, identify the characteristics of a person who may commit a particular crime, and identify places where a particular crime may occur. Data privacy is the main challenge that organizations face when building this type of predictive models. Federated learning (FL) is a promising approach that overcomes data security and privacy challenges, as it enables organizations to build a machine learning model based on distributed datasets without sharing raw data or violating data privacy. In this paper, a federated long short- term memory (LSTM) model is proposed and compared with a traditional LSTM model. Proposed model is developed using TensorFlow Federated (TFF) and the Keras API to predict the number of crimes. The proposed model is applied on the Boston crime dataset. The proposed model's parameters are fine tuned to obtain minimum loss and maximum accuracy. The proposed federated LSTM model is compared with the traditional LSTM model and found that the federated LSTM model achieved lower loss, better accuracy, and higher training time than the traditional LSTM model.

• Transactions of Materials Processing
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• v.31 no.4
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• pp.200-206
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• 2022

The finite element analysis is one of the representative methods for predicting the materials behavior for experiments that are difficult to perform empirically. Constitutive equations are essential for reducing computation time and sharing data because they enable finite element analysis simulations through simple formulae. However, it is difficult to derive accurate flow curves for all materials as most constitutive equations are not formulated based on their physical meaning. Also, even if the constitutive equation is a good representation of the flow curve to the experimental results, some fundamental issues remain unresolved, such as the effect of mesh size on the calculation results. In this study, a new constitutive equation was proposed to predict various materials by modifying the combined Swift-Voce model, and the calculation results with various mesh sizes were compared to better simulate the experimental results.