• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.13-39
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• 2006

The primary purpose of this study is to examine the interaction effects of organizational characteristics as contextual variables on the relationship between relational exchange characteristics and ASP service performance. The effect of relational exchange characteristics on ASP service performance has been also investigated. For this purposes, we developed a research model based on the literature reviews of ASP services, relational exchange theory, and contingency theory. A total of 106 usable survey responses from companies using ASP services has been analyzed in the study. The findings indicate that (1) flexibility and partnership had a positive influence upon noneconomic profit, (2) information sharing had a positive influence upon economic profit, (3) organizational size and IS maturity had a partial moderating effect on the relationship between relational exchange characteristics and ASP service performance, and (4) the subgroup analysis, conducted to determine the exact nature of interaction effect, reveals that the relationship between relational exchange characteristics and noneconomic profit is significantly stronger with a high level of organizational size than with a low level, and that the relationship between relational exchange characteristics and economic profit is significantly stronger with a low level of IS maturity than with a high level.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.584-590
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• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected Power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SYC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to IEEE 14 buses and 10 machines 39 buses model system.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.83-90
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• 2000

The chi-squared test statistic is usually employed for testing independence of two categorical variables in a two-way contingency table. It is well known that, under independence, the test statistic has an asymptotic chi-squared distribution under multinomial or product-multinomial models. For the case where both margins fixed, the sampling model of the contingency table is a multiple hypergeometric distribution and the chi-squared test statistic follows the same limiting distribution. In this paper, we study the difference between the small sample and large sample distributions of the chi-squared test statistic for the case with fixed margins. For a few small sample cases, the exact small sample distribution of the test statistic is directly computed. For a few large sample sizes, the small sample distribution of the statistic is generated via a Monte Carlo algorithm, and then is compared with the large sample distribution via chi-squared probability plots and Kolmogorov-Smirnov tests.

• Research in Plant Disease
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• v.22 no.3
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• pp.168-177
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• 2016

A forecast model for estimating the infection risk of bacterial canker caused by Pseudomonas syringae pv. actinidiae on kiwifruit leaves in Korea was developed using the generic infection model of Magarey et al. (2005). Two-way contingency table analysis was carried out to evaluate accuracy of forecast models including the model developed in this study for estimating the infection of bacterial canker on kiwifruit using the weather and disease data collected from three kiwifruit orchards at Seogwipo in 2015. All the tested models had more than 80% of probability of detection indicating that all the tested models could be effective to manage the disease. The model developed in this study showed the highest values in proportion of correct (51.1%), probability of detection (90.9%), and critical success index (47.6%). It indicated that the model developed in this study would be the best model for estimating the infection of bacterial wilt on kiwifruit leaves in Korea. The model developed in this study could be used for a part of decision support system for managing bacterial wilt on kiwifruit leaves and help growers to reduce the loss caused by the disease in Korea.

• The Transactions of the Korea Information Processing Society
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• v.4 no.5
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• pp.1358-1370
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• 1997

Client-Sever-Comptuing is now recognized as the most powerful and flexible computing mode of the future.Many companies have already commited significant amount of their corporate IS resources to building the cli-ent-server computing environment.Despite this active interst and commitment,however,results from such cli-ent-sever projects are far from being convincing Among the many factors,we suspect,we supect that the less than less than satisfac-tory client-server experiences are perhaps due to the company's lack of underxtanding its essertial information processing characteristics.We analyze five client-server archiedctures in temrs of seven IS-related crieria.We then develop a contin-gency model to match company's information processing chracteristics to the ideal client-server architecture for the firm.Based on the client-server architecture analysis from the previous step. we recommend specific im-plementation strategies for each-server architecture selected. Finally,on an exploratory level,we look into the three client-server implmentation cases to cases to check the validity of our contingency model.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.412-420
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• 2010

With increased complexity of product and market, the phenomenon that a consumer get paradoxical attitude toward marketing object has been increased. And this phenomenon eventually affects the relationship between consumer and product. In this study we tried to find more paradoxical phenomenon and understand consumer behavior confronting these situations when they buy agro-product based on ground theory methodology. According to the results, consumer's expectation and purchase experience can promote quality paradox experience during confronting various marketing activities such as price, product, promotion, place. Also these experience can cause quality paradox related interaction and communication even though there could be differences in their experience according to demographic characteristics, personal preference, and risk perception. Consumer will develop multiple strategies against quality paradox to manage the uncomfortable paradox experiences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3093-3115
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• 2020

Network anomaly detection system plays an essential role in detecting network anomaly and ensuring network security. Anomaly detection system based machine learning has become an increasingly popular solution. However, due to the unbalance and high-dimension characteristics of network traffic, the existing methods unable to achieve the excellent performance of high accuracy and low false alarm rate. To address this problem, a new network anomaly detection method based on data balancing and recursive feature addition is proposed. Firstly, data balancing algorithm based on improved KNN outlier detection is designed to select part respective data on each category. Combination optimization about parameters of improved KNN outlier detection is implemented by genetic algorithm. Next, recursive feature addition algorithm based on correlation analysis is proposed to select effective features, in which a cross contingency test is utilized to analyze correlation and obtain a features subset with a strong correlation. Then, random forests model is as the classification model to detection anomaly. Finally, the proposed algorithm is evaluated on benchmark datasets KDD Cup 1999 and UNSW_NB15. The result illustrates the proposed strategies enhance accuracy and recall, and decrease the false alarm rate. Compared with other algorithms, this algorithm still achieves significant effects, especially recall in the small category.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.191-199
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• 2014

This study was analyzed to relate between business performance and leadership types for global corporations practically. Also, in this study for research, Have developed a research model to analyze comprehensively using the business performance and leadership theory. One of the important things are leader's characteristics or contingency factors at global corporations, but leadership is being re-evaluated through how it enable to perceive and to evaluate at the organization. Therefore, this study had been analyzed to relationship with the type of global readers between the employee's perception and business performance focusing on research model The research results had shown that job satisfaction, performance variables like sales amount, and productivity to be impact on the leadership type of global enterprises. Therefore, this study concluded that the efficiency and performance of the Company may increase when assigned a leadership professional to be able to consider the nature of the global enterprise. Results of the study, will be expected to be a useful guide for control of business performance at global corporation in the future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.261-284
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• 2017

This paper describes the results of a low-frequency oscillation analysis using data measured in PMU installed in the KEPCO system, and the comparison with eigenvalues computed from the linear model. The dominant oscillation modes are estimated by applying various algorithms. The algorithms are: the extended Prony method; multiple time interval parameter estimation method; subspace system identification method; and spectral analysis. From the measurement data, modes of frequency 0.68[Hz] and 0.92[Hz] were estimated, and modes of frequency 0.63[Hz] and 0.80[Hz] were computed from the eigenvalue calculation. There was a difference between the mode estimated from measurement data and that from the linear model. This is possibly because of an error in the dynamic data of the KEPCO system used in eigenvalue calculation. Because wide area modes exist in the KEPCO system, these modes should be monitored continuously for the reliable operation of the system. In order to prevent total blackouts caused by wide area oscillation, moreover, contingency analysis should be performed in relation to this mode and appropriate measures should be established.

• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.105-115
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• 2007

It is essential to give a fatal damage to the enemy force by using prompt and accurate fire in order to overcome the lack of artillery force. During the artillery fire operations, minimizing the firing time will secure the adapt ability in tactical operation. In this paper, we developed a mathematical model to schedule the artillery fire on the multiple targets to decrease total fire operation time. To design a program to describe a real firing situation, we consider many possible circumstances of changes such as commander's intention, firing constraints, target priority, and contingency plan to make a fire plan in an artillery unit. In order to work out the target sequencing problem, MIP is developed and the optimum solution is obtained by using ILOG OPL. If this analytical model is applied to a field artillery unit, it will improve the efficiency of the artillery fire force operations.