• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.227-242
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• 2012

It is a daunting task to theorize the process effectiveness of IT convergence based service model. Despite the criticalness of investigating process enhancement impact of IT-convergence based service model, the theoretical research in this field is relatively scarce, possibly due to the too wide and comprehensiveness of research scope. In this vein, we conducted exploratory study to understand the contributional impact of IT convergence based service model on resolving service process limitations. We first identified five IT convergence based service models in the area of typical service industry, which include entertainment, learning, location based services, tourism, and healthcare. Our research model classified value creation factors of the IT convergence model in twofold. The one is defined as basic value creation factor of the IT convergence, which is treated as the second-order factor that consists of two first-order factors of mobile functionality and Internet with digital contents merging functionality. The other is defined as service process limitations resolving factor which are comprised with the two first-order factors of simultaneousity and perishability. Both the second-order factors are modeled, each respectively, with the two first-order factors in formative manner. Using PLS, empirical validation is executed to analyze each value creating factor's contribution impact on the relative advantage, as well as the mediating effect of basic value creation factor on resolving service process limitations. On the basis of the insights revealed from this paper, further theory building research could be elaborated in the area of IT convergence applications for service industry.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.4
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• pp.129-138
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• 2003

Role-Based Access Control(RBAC) model is becoming a promising model for enterprise environments with various organization structures. In terms of role hierarchy, each senior role inherits all the permissions of its junior roles in the role hierarchy, and a user who is a member of senior role is authorized to carry out the inherited permissions as well as his/her own ones. But there is a possibility for senior role members to abuse permissions. Since senior role members need not have all the authority of junior roles in the real world, enterprise environments require a restricted inheritance rather than a unconditional or blocked inheritance. In this paper, we propose a new role-based delegation model using the role hierarchy model with restricted inheritance functionality, in which security administrator can easily control permission inheritance behavior using sub-roles. Also, we describe how role-based user-to-user, role-to-role delegations are accomplished in the model and the characteristics of the proposed role-based delegation model.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.172-172
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• 2020

In recent years, soil erosion has come to be regarded as an essential environmental problem in human life. Soil erosion causes various on- and off-site problems such as ecosystem destruction, decreased agricultural productivity, increased riverbed deposition, and deterioration of water quality in streams. To solve these problems caused by soil erosion, it is necessary to quantify where, when, how much soil erosion occurs. Empirical erosion models such as the Universal Soil Loss Equation (USLE) family models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well by utilizing big data related to climate, geography, geology, land use, etc. within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models remain powerful tools to distinguish erosion-prone areas at the macro scale but physics-based models are necessary to better analyze soil erosion and deposition and eroded particle transport. In this study, the physics-based Surface Soil Erosion Model (SSEM) was upgraded based on field survey information to produce sediment yield at the watershed scale. The modified model (hereafter MoSE) adopted new algorithms on rainfall kinematic energy and surface flow transport capacity to simulate soil erosion more reliably. For model validation, we applied the model to the Doam dam watershed in Gangwon-do and compared the simulation results with the USLE outputs. The results showed that the revised physics-based soil erosion model provided more improved and reliable simulation results than the USLE in terms of the spatial distribution of soil erosion and deposition.

• Journal of People, Plants, and Environment
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• v.22 no.1
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• pp.65-73
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• 2019

The purpose of the study was to examine the effects of the Horticulture Job Skill course based on the employment practice model on personal performance indicator of vocational rehabilitation for university students with disabilities. In the first step of this study, an employment practice model was developed by a focus group composed of six specialists from the industry and academia. The second step consisted of selecting the items of personal performance indicator related to horticulture vocational rehabilitation among all items of vocational rehabilitation. The third step was selecting students to participate in the study. The next step was coming up with a pilot instructional design based on the employment practice model. The final step was examining the effects of pilot course (horticulture job skill) based on the employment practice model on personal performance indicator of vocational rehabilitation for university students with disabilities. As a result, there were significant improvements after treatment in the experimental group with indicator 1 (managing) from 1.8±0.155 to 4.2±0.267, indicator 2 (planting) from 1.5±0.114 to 4.45±0.153, indicator 3 (using tool) from 3.2±0.186 to 4.6±0.112, indicator 4 (packing) from 2.05±0.153 to 4.45±0.114, indicator 5 (decorating) from 2.65±0.150 to 5.5±0.114, indicator 6 (cleaning) from 2.85±0.131 to 4.45±0.114, indicator 7 (observing) from 2.4±0.112 to 4.45±0.112, and indicator 8 (laboring) from 2.35±0.109 to 4.1±0.180. However, the control group did not show any significant improvement after 15 weeks of the program. This study determined that the Horticulture Job Skill course based on the employment practice model has an effect on improving the individual performance of vocational rehabilitation for university students with disabilities. Finally, horticulture education-based on the employment practice model will contribute to vocational rehabilitation for university student with disabilities.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.139-155
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• 2024

This study performed a multi-classification task to classify mesial temporal lobe epilepsy with left hippocampal sclerosis patients (left mTLE), mesial temporal lobe epilepsy with right hippocampal sclerosis (right mTLE), and healthy controls (HC) using magnetoencephalography (MEG) data. We applied various artificial neural networks and compared the results. As a result of modeling with convolutional neural networks (CNN), recurrent neural networks (RNN), and graph neural networks (GNN), the average k-fold accuracy was excellent in the order of CNN-based model, GNN-based model, and RNN-based model. The wall time was excellent in the order of RNN-based model, GNN-based model, and CNN-based model. The graph neural network, which shows good figures in accuracy, performance, and time, and has excellent scalability of network data, is the most suitable model for brain research in the future.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.319-325
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• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.95-103
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• 2016

In a dynamic environment autonomous robots often encounter unexpected situations that the robots have to deal with in order to continue proceeding their mission. We propose an adaptive goal-based model that allows cyber-physical systems (CPS) to update their environmental model and helps them analyze for attainment of their goals from current state using the updated environmental model and its capabilities. Information exchange approach utilizes Human-Agent-Robot-Machine-Sensor (HARMS) model to exchange messages between CPS. Model validation method uses NuSMV, which is one of Model Checking tools, to check whether the system can continue its mission toward the goal in the given environment. We explain a practical set up of the model in a situation in which homogeneous robots that has the same capability work in the same environment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.7-14
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• 2011

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rate per fault (hazard function). This infinite non-homogeneous Poisson process is model which reflects the possibility of introducing new faults when correcting or modifying the software. In this paper, polynomial hazard function have been proposed, which can efficiency application for software reliability. Algorithm for estimating the parameters used to maximum likelihood estimator and bisection method. Model selection based on mean square error and the coefficient of determination for the sake of efficient model were employed. In numerical example, log power time model of the existing model in this area and the polynomial hazard function model were compared using failure interval time. Because polynomial hazard function model is more efficient in terms of reliability, polynomial hazard function model as an alternative to the existing model also were able to confirm that can use in this area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2142-2161
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• 2018

Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter ${\lambda}$, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.

• Structural Engineering and Mechanics
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• v.70 no.2
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• pp.209-219
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• 2019

By normalizing the internal hysteresis variable and eliminating the redundant parameter, the normalized Bouc-Wen model is considered to be an improved and more reasonable form of the Bouc-Wen model. In order to facilitate application and further research of the normalized Bouc-Wen model, some key aspects of the model need to be uncovered. In this paper, hysteresis characterization of the normalized Bouc-Wen model is first studied with respect to the model parameters, which reveals the influence of each model parameter to the shape of the hysteresis loops. The parameter identification scheme is then proposed based on an improved genetic algorithm (IGA), and verified by experimental test data. It is proved that the proposed method can be an efficacious tool for identification of the model parameters by matching the reconstructed hysteresis loops with the target hysteresis loops. Meanwhile, the IGA is shown to outperform the standard GA. Finally, a simplified identification method is proposed based on parameter sensitivity, which indicates that the efficiency of the identification process can be greatly enhanced while maintaining comparable accuracy if the low-sensitivity parameters are reasonably restricted to narrower ranges.