• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.38-46
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• 2011

The OPRoS (Open Platform for Robotic Service) framework provides uniform operating environment for service robots. As an OPRoS-based service robot has to support real-time as well as non-real-time applications, application of Windows NT kernel based operating system can be restrictive. On the other hand, various benefits such as rich library and device support and abundant developer pool can be enjoyed when service robots are built on Windows NT. The paper presents a user-mode component scheduler of OPRoS, which can provide near real-time scheduling service on Windows NT based on the restricted real-time features of Windows NT kernel. The component scheduler thread with the highest real-time priority in Windows NT system acquires CPU control. And then the component scheduler suspends and resumes each periodic component executors based on its priority and precedence dependency so that the component executors are scheduled in the preemptive manner. We show experiment analysis on the performance limitations of the proposed scheduling technique. The analysis and experimental results show that the proposed scheduler guarantees highly reliable timing down to the resolution of 10ms.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.51-60
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• 1995

Given an $n \times p$ data matrix, if we add the $p_s$ variables somewhat different nature than the p variables to this matrix, we have a new $n \times (p+p_s)$ data matrix. Because of these $p_s$ variables, the traditional principal component analysis can't provide its efficient results. In this study, to improve this problem we review the supplementary principal component analysis putting $p_s$ variables to supplementary variable. This technique is based on the algebraic and geometric aspects of the traditional principal component analysis. So we provide a type of statistical data analysis for the records of eight teams and fourteen fields of the 1982-1992 Korean Pro Baseball Data based on the supplementary principal component analysis and the traditional principal component analysis. And we compare the their results.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.301-314
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• 2015

Aiming at accurately distinguishing modeless component and natural vibration mode terms from data series of nonlinear and non-stationary processes, such as Vortex-Induced Vibration (VIV), a new empirical mode decomposition method has been developed in this paper. The key innovation related to this technique concerns the method to decompose modeless component from non-stationary process, characterized by a predetermined 'maximum intrinsic time window' and cubic spline. The introduction of conceptual modeless component eliminates the requirement of using spurious harmonics to represent nonlinear and non-stationary signals and then makes subsequent modal identification more accurate and meaningful. It neither slacks the vibration power of natural modes nor aggrandizes spurious energy of modeless component. The scale of the maximum intrinsic time window has been well designed, avoiding energy aliasing in data processing. Finally, it has been applied to analyze data series of vortex-induced vibration processes. Taking advantage of this newly introduced empirical decomposition method and mode identification technique, the vibration analysis about vortex-induced vibration becomes more meaningful.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.699-704
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• 2001

Developing a component-based software requires verified and standardized software components. This paper presents a component quality management (CQM) process. The process was developed and applied to the government-sponsored trial projects that developed software components. The process is composed of four phases：quality specification, quality planning, quality control, and quality evaluation. With this process, we can establish quality goals and focus our efforts on the activities to achieve the goals. A component quality model is also suggested to transform the implicit quality requirements into the measurable quality goals and to be used for the basis when we evaluate the quality of software components against the quality goals.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.69-76
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• 2008

In this thesis, we implemented the prototype system for the class code generator based on consistent code generation process and standard type, the class to be component unit. Particularly, we proposed relationship rule to solve the difficult problem by the object-oriented language to association and aggregation between classes based on component, through this method we can make to consistent code generation standard. Also it is adopted to component model construction which is generated code using code generation, and it can be basic assembly and deployment of business components to reusable target in developing application system.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.12
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• pp.825-830
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• 2014

$[(Co_{1-x}Cu_x)_{0.2}(Ni_{0.3}Mn_{0.7})_{0.8}]_3O_4$ ($0{\leq}x{\leq}1$) thin films prepared by metal organic decomposition process were fabricated on SiN/Si substrate for infrared sensor application. Their structural and electrical properties were investigated with variation of Cu dopant. The $[(Co_{1-x}Cu_x)_{0.2}(Ni_{0.3}Mn_{0.7})_{0.8}]_3O_4$ (CCNMO) film annealed at $500^{\circ}C$ exhibited a dense microstructure and a homogeneous crystal structure with a cubic spinel phase. Their crystallinity was further enhanced with increasing doped Cu amount. The 120 nm-thick CCNMO (x=0.6) thin film had a low resistivity of $53{\Omega}{\cdot}cm$ at room temperature while the Co-free film (x=1) showed a significantly decreased resistivity of $5.9{\Omega}{\cdot}cm$. Furthermore, the negative temperature coefficient of resistance (NTCR) characteristics were lower than $-2%/^{\circ}C$ for all the specimens with $x{\geq}0.6$. These results imply that the CCNMO ($x{\geq}0.6$) thin films are a good candidate material for infrared sensor application.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.431-445
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• 2006

In this paper we review some methods for analyzing functional data and illustrate real application of functional data analysis. Representing methods for functional data by using basis function, analyzing functional variation by functional principal component analysis and functional linear models are reviewed. For a real application, we use temperature and precipitation data measured in Korea from the January of 1970 to the May of 2004. We apply functional principal component analysis for each data and test the significance of regional division done by using shining hours. We also estimate functional regression model for temperature and precipitation.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.134-143
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• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.814-823
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• 2012

Electric power transmission utilities make an effort to maximize profit by reducing their electricity supply and operation costs while maintaining their reliability. The development of maintenance strategies for aged components is one of the more effective ways to achieve this goal. The reliability centered approach is a key method in providing optimal maintenance strategies. It considers the tradeoffs between the upfront maintenance costs and the potential costs incurred by reliability losses. This paper discusses the application of the Particle Swarm Optimization (PSO) technique used to find the optimal maintenance strategy for a transmission component in order to achieve the minimum total expected cost composed of Generation Cost (GC), Maintenance Cost (MC), Repair Cost (RC) and Outage Cost (OC). Three components of a transmission system are considered: overhead lines, underground cables and insulators are considered. In regards to aged and aging component, a component state model that uses a modified Markov chain is proposed. A simulation has been performed on an IEEE 9-bus system. The results from this simulation are quite encouraging, and then the proposed approach will be useful in practical maintenance scheduling.

• Journal of KIISE:Software and Applications
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• v.29 no.10
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• pp.694-702
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• 2002

An application in Component-Based Software Development (CBSD) is built by 'composing'two kinds of components; One is a component that is made by current developer himself, and the other is a component that is from other developments. We define the former as a 'White-box component' and the latter as a 'Black-box component.' The error from the composition can be said to be caused by interactions of Black-box components and White-box components. This paper proposes a new testing technique for composition errors, and applies the technique to Enterprise Java Beans component architecture. Our technique selects test cases by injecting a fault only into the specific parts of a White-box component. This specific parts for injecting a fault are selected by analyzing composition patterns, and lead to make our test cases have a good effectiveness. We show the effectiveness of our test cases through an experiment. Moreover, we also mention an automation tool for our technique.