• Journal of Digital Convergence
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• v.11 no.10
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• pp.387-394
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• 2013

Data mining is the process of discovering hidden, non-trivial patterns in large amounts of data records in order to be used very effectively for analysis and forecasting. Because hundreds of variables give rise to a high level of redundancy and dimensionality with time complexity, they are more likely to have spurious relationships, and even the weakest relationships will be highly significant by any statistical test. Hence cluster analysis is a main task of data mining and is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. In this paper system implementation is of great significance, which defines a new definition based on information-theoretic entropy and analyse the analogue behaviors of objects at hand so as to address the measurement of uncertainties in the classification of categorical data. The sources were taken from a survey aimed to identify of job guidance from students in high school pyeongtaek. we show how variable precision information-entropy based rough set can be used to group student in each section. It is proved that the proposed method has the more exact classification than the conventional in attributes more than 10 and that is more effective in job guidance for students.

• Journal of Korea Foundry Society
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• v.35 no.4
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• pp.80-87
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• 2015

The Al die casting process has been widely used in the manufacturing of automotive parts when the process requires near-net shape casting and a high productive rate. However, porosity arises in the casting process, and this hampers the wider use of this method for the creation of high-durability automotive components. The porosity can be controlled by the shot condition, but, it is critical to set the shot condition in the sleeve, and it remains difficult to optimize the shot condition to avoid air entrapment efficiently. In this study, the 4.5 mm, 2.0 mm plate die castings were fabricated under various shot conditions, such as plunger velocities of 0.7 m/s ~ 3.0 m/s and fast shot set points of the cavity of -25%, 0%, 25%, and 50%. The mold filling behavior of Al melts in the cavity was analyzed by a numerical method. Also, according to the shot conditions, the results of numerical analyses were compared to those of die-casting experiments. The porosity levels of the plate castings were analyzed by X-ray CT images and by density and microstructural analyses. The effects of the porosity on the mechanical properties were analyzed by tensile tests and hardness tests. The simulation results are in good general agreements with the die-casting experimental results. When plunger velocity and fast shot set point are 1.0 m/s and cavity 25% position, castings had optimum condition for good mechanical properties and a low level of porosity.

• Korean Chemical Engineering Research
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• v.58 no.1
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• pp.106-112
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• 2020

Analyzing vitamin D levels is important for monitoring health conditions because vitamin D deficiency is associated with various diseases such as rickets, osteomalacia, cardiovascular disorders and some cancers. However, vitamin D concentration in the blood is very low with optimal level of 75 nmol/L, making quantitative analysis difficult. The objective of this study was to develop a highly sensitive analysis method for vitamin D using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-MS). 25-hydroxyvitamin D (25(OH)D), which has been used as an indicator of vitamin D metabolites in human biofluids was chemically derivatized using a secosteroid signal enhancing tag (SecoSET) with powerful dienophile and permanent positive charge. The SecoSET-derivatized 25(OH)D provided good linearity (R² > 0.99) and sensitivity (limit of quantitation: 11.3 fmol). Chemical derivatization of deuterated 25-hydroxyvitamin D₃ (d₆-25(OH)D3) with SecoSET enabled absolute quantitative analysis using MALDI-MS. The highly sensitive method could be successfully applied into monitoring of quantitative changes of bioactive vitamin D metabolites after treatment with ketoconazole to inhibit 1α-hydroxylase reaction related to vitamin D metabolism in human breast cancer cells. Taken together, we developed a MALDI-MS-based platform that could quantitatively analyze vitamin D metabolites from cell products, blood and other biofluids. This platform may be applied to monitor various diseases associated with vitamin D deficiency such as rickets, osteomalacia and breast cancer.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.133-142
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• 2012

This paper presents a salient region detection algorithm for auto-focusing based on the characteristics of a human's visual attention. To describe the saliency at the local, regional, and global levels, this paper proposes a set of novel features including multi-scale local contrast, variance, center-surround entropy, and closeness to the center. Those features are then prioritized to produce a saliency map. The major advantage of the proposed approach is twofold; i) robustness to changes in focus and ii) low computational complexity. The experimental results showed that the proposed method outperforms the existing low-level feature-based methods in the sense of both robustness and accuracy for auto-focusing.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.7-13
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• 1999

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input -output pair. First, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.2
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• pp.17-33
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• 2003

The explosive growth of the internet-based transactions requires not only a secure payment system but also an appropriate trust measuring methodology and secure transaction protocols to guarantee the minimal risk for the transacting entities involved in specific transactions. Especially, in internet auction systems where either buyers or sellers or both can be more than one in one transaction, providing those systems that make sure no one transacting entity takes a major risk becomes critical. In this paper, an improved trust measuring method using a relationship-based internet community for an auction system is proposed. The proposed system incorporates fuzzy set and calculation concepts to help build trust matrices and models, which is used to measure the level of risk involved in a specific auction trade concerned. Also, to optimize the auction trade process in terms of cost and time, the proposed system recommends a differentiated trade protocol according to the risk level involved in each auction trade. To test the appropriateness of the proposed trusted auction system, a prototype system has been developed under a Windows-NT environment.

• Journal of computational fluids engineering
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• v.20 no.2
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• pp.103-108
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• 2015

Fluid-body interaction analysis of floating body with six degree-of-freedom motion is presented. In this study, three-dimensional incompressible Navier-Stokes equations are employed as a governing equation. The numerical method is based on a finite-volume approach on a cartesian grid together with a fractional-step method. To represent the body motion, the immersed boundary method for direct forcing is employed. In order to simulate the coupled six degree-of-freedom motion, Euler's equations based on rigid body dynamics are utilized. To represent the complex body shape, level-set based algorithm is utilized. In order to describe the free surface motion, the volume of fluid method utilizing the tangent of hyperbola for interface capturing scheme is employed. This study showed three different continuums(air, water and body) are simultaneously simulated by newly developed code. To demonstrate the applicability of the current approach, two different problems(dam-breaking with stationary obstacle and water entry) are simulated and all results are validated.

• International Journal of Quality Innovation
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• v.9 no.3
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• pp.71-91
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• 2008

The definition of cycle time is the time from the wafer start to the wafer output. It usually takes one or two months to get the product since customer decides to produce it. The cycle time is a critical factor for customer satisfaction because it represents the response time to the market. Long cycle time reflects the ineffective investment for the capital. The cycle time is very important for foundry because long cycle time will cause customer unsatisfied and the order loss. Consequently, all of the foundries put lots of human source in the cycle time improvement. Usually, we make decisions based on the experience in the cycle time management. We have no mechanism or theory for cycle time management. We do work-in-process (WIP) management based on turn rate and standard WIP (STD WIP) set by experiences. But the experience didn't mean the optimal solution, when the situation changed, the cycle time or the standard WIP will also be changed. The experience will not always be applicable. If we only have the experience and no mechanism, management will not be work out. After interview several foundry fab managers, all of the fab can't reflect the situation. That is, all of them will have an impact period after product mix or utilization varied. In this study, we want to develop a formula for standard WIP and use statistical process control (SPC) concept to set WIP upper/lower limit level. When WIP exceed the limit level, it will trigger action plans to compensate WIP Profile. If WIP Profile balances, we don't need too much WIP. So WIP level could be reduced and cycle time also could be reduced.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.721-740
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• 2019

Noise reduction is an important field in image processing and requires a statistical approach. However, it is difficult to assume a specific distribution of noise, and a spatial filter that reflects regional characteristics is a small sample and cannot be accessed in a parametric manner. The first order image differential and the second order image differential show a clear difference according to the noise level included in the image and can be more clearly understood using the canyon edge detector. The Fligner-Killeen test was performed and the bootstrap method was used to statistically check the noise level. The estimated noise level was set between 0 and 1 using the cumulative distribution function of the beta distribution. In this paper, we propose a nonparametric noise reduction algorithm that accounts for the noise level included in the image.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.893-898
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• 2004

This research proposes an implementation method of linearized equations of motion for multibody systems with closed loops. The null space of the constraint Jacobian is first pre multiplied to the equations of motion to eliminate the Lagrange multiplier and the equations of motion are reduced down to a minimum set of ordinary differential equations. The resulting differential equations are functions of all relative coordinates, velocities, and accelerations. Since the coordinates, velocities, and accelerations are tightly coupled by the position, velocity, and acceleration level constraints, direct substitution of the relationships among these variables yields very complicated equations to be implemented. As a consequence, the reduced equations of motion are perturbed with respect to the variations of all coordinates, velocities, and accelerations, which are coupled by the constraints. The position, velocity and acceleration level constraints are also perturbed to obtain the relationships between the variations of all relative coordinates, velocities, and accelerations and variations of the independent ones. The perturbed constraint equations are then simultaneously solved for variations of all coordinates, velocities, and accelerations only in terms of the variations of the independent coordinates, velocities, and accelerations. Finally, the relationships between the variations of all coordinates, velocities, accelerations and these of the independent ones are substituted into the variational equations of motion to obtain the linearized equations of motion only in terms of the independent coordinate, velocity, and acceleration variations.