• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.311-316
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• 2004

For the location estimation in the conventional LPMS(Loose Parts Monitoring System), it is popular to employ a group delay among the acoustic sensors installed within a 3 ft range from the impact source. However, there exists inherent error in determining the arrival time differences of the generated wave group among the neighboring sensors. To overcome this problem in this study, the two dimensional approach has been proposed and applied to effectively estimate the arrival time differences by using a continuous wavelet transform which is one of the linear time-frequency analysis methods. The experiment has been performed to both the plate model and the real steam generator in a nuclear power plant. It is expected that the reliability of the location estimation could be enhanced when the proposed time-frequency method is introduced into the LPMS system.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.97-100
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• 2000

Deadbeat property is well established in digital control system design in time domain. But in continuous time system, deadbeat is impossible because of it's ripples between sampling points. But several researchers suggested delay elements. From some specifications such as Internal model stability, physical realizations and finite time settling, unknown polynomials with delay elements in error transfer functions can be calculated. For the application to the real system, robustness property can be added. In this paper, error transfer function is specified with 1 delay element and unkown coefficients are calculated from the specs. Especially, by varying settling time and the user-specified poles, a deadbeat controller with lower order is obtained.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.67-73
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• 2010

This study began the study by instructing enterprises to change Batch Production into U-Line. This study suggested TPS U-Line building model process and applied it to some of their product line. By connecting concerned process elements into continuous operations. Outside orders were also switched to inside operations and executed in continuous operations, thereby about 100Km of transit distance became zero Km, Production lead Time was incredibly reduced. After all, 90% of Production Lead Time, 50% of handling fault, 3/4 of workers decreased and Productivity per Person enhanced which involves improving Batch Production into Continuous Production and applies it to the real world, so that small and medium enterprises can consult this study if the company is willing to make an improvement to their product line.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.97-113
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• 2012

In order to implement the real-time enterprise (RTE) and smart work effectively, many companies have introduced a mobile office. A mobile office improves employee productivity and increases ability to respond to business opportunities by helping employee manage their business anytime and anywhere. However, it also raises the user's stress level. We conducted in-depth interviews with users to assess user's perception of a mobile office according to Saaty's BOCR model. Based on the results of the interviews, we set variables affecting user's perception of the mobile office using factor analysis. This study revealed that support for real-time business, support for communication and collaboration, and information processing quality were positively related to continuous intention to use mobile office. Further study demonstrated that three variables have mediating effect between the psychological stress and continuous intention to use. This result implies that the system quality and function are the key elements of mobile office and may contribute to the continuous use.

• Knowledge Management Research
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• v.15 no.3
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• pp.37-66
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• 2014

Since social network service (SNS) has been widely used as a effective way for people to connect and communication with each other, the use of corporate SNS account also has increased. However, compared to a private SNS account, only few people have a continuous relationship with their corporate SNS account because the use of corporate SNS account tends to be one-time and temporary activity whenever the users just need events and information. Given the psychological side effects of using SNS, the relative lack of empirical studies on the impacts of emotional factor in SNS prevents the deeper understanding of the intention to continuous using corporate SNS account. Therefore, this study aims to explore key determinants of the intension to continuous using the corporate SNS account from a habit and emotional perspective. To bridge research gap, we attempt to divide emotional factor into the following 5 factors based on Mehrabian and Russell model (1974): intimacy, enjoyment (positive factor), privacy concern, anxiety (negative factor), arousal (arousal factor) and (dominant factor). The basic model is proposed to explore the effects of habit and emotional factors on the intension to continuous using the corporate SNS account. We then examine how the effects of habit and emotional factors differ depending on social media types (e.g., facebook and twitter). The results indicates that habit is related to emotional factors, and each emotional factor differently influences the intension to continuous using the corporate SNS account. The results also confirm that the effects of the habit and emotional factors on the intension to continuous using the corporate SNS account differ according to social media types. This study provides practical and useful guidance and the strategic marketing insight for managers in maintaining and improving the intension to continuous using the corporate SNS account.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.45-56
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• 2003

In the wireless environment, according to the development of technology, which is able to obtain location information of spatiotemporal moving object, the various application systems are developed such as vehicle tracking system, forest fire management system and digital battle field system. These application systems need the data model, which is able to represent and process the continuous change of moving object. However, if moving objects are expressed by a relational model, there is a problem which is not able to store all location information that changed per every time. Also, existing data models of moving object have a week point, which constrain the query time to the time that is managed in the database such as past or current and near future. Therefore, in this paper, we propose a data model, which is able to not only express the continuous movement of moving point and moving region but also process the operation at all query time by using shape-change process and location determination functions for past and future. In addition, we apply the proposed model to forest fire management system and evaluate the validity through the implementation result.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.4
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• pp.181-191
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• 2006

The most common kind of vehicular accident is the low-speed rear-end impact that result in high portion of insurance claims and Whiplash Associated Disorders(WAD). The low-speed collisions have specific characteristics that differ from high speed collisions and must be treated differently This paper presents a simple continuous contact force model for the low-speed rear-end impact to simulate the accelerations, velocities and the contact force as functions of time. A smoothed Coulomb friction force is used to represent the effect of braking, which was found to be significant in simulating low-speed rear end impact. The intervehicular contact force is modeled using nonlinear damping and spring elements with coefficients and exponents. This paper presents how to estimate analytically stiffness and damping coefficients. The exponent of the nonlinear contact force model was determined to match the overall acceleration pulse shape and magnitude. The model can be used to determine ${\Delta}Vs$ and peak accelerations for the purpose of accident reconstruction and for injury biomechanics studies.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.249-259
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• 2022

Project management and deployment has gone through a long journey from traditional and agile to continuous integration, continuous deployment and continuous monitoring. Software industry benefited with the latest buzzword in the development process, DevOps that not only escalates software productivity but at the same time enhances software quality. But the implementation and assessment of DevOps practices is expository as there are no guidelines to assess and improvise DevOps application in software industries. Hence, there was a need to develop a hybrid model to assist software practitioners in DevOps implementation. The intention behind this paper is to implement the already proposed DevOps hybrid model using suggested tool chains including Jenkins, Selenium, GitLab, Ansible and Nagios automation tools through Jenkins project management environment and plugins. To achieve this implementation objective, a java application is developed with a web-based graphical interface. Further, in this paper, different challenges and benefits of Jenkins implementation shall also be outlined. The paper also presents the effectiveness of DevOps based Model implementation in software organizations. The impact of considering other automation tools and models can also be considered as a part of further research.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.44-53
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• 2008

An interacting multiple model (IMM) estimation algorithm based on the mixing of the predicted state estimates is proposed in this paper for a right continuous jump-linear system model different from the left-continuous system model used to develop the existing IMM algorithm. The difference lies in the modeling of the mode switching time. Performance of the proposed algorithm is compared numerically with that of the existing IMM algorithm for noisy system identification. Based on the numerical analysis, the proposed algorithm is applied to target tracking with a large sampling period for performance comparison with the existing IMM.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.50-60
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• 1998

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.