• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.203-209
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• 1999

In this paper, we present the methods to predict the milled surface shapes in profile milling process. In the cutting process, tools are deflected due to the cutting forces varying with the imposed depth of cut and feedrate. Thus, the final shapes of the milled surface, generated by the nominal tool trajectory, are different from the required profile. In order to predict the milled surface shapes, we present two methods based on: (1) the deflected tool profile and (2) the trace of contact point between the tool and the workpiece. In the first method, we make an assumption that the milled surface corresponds to the deflected tool profile. In another method, we make we make an assumption that the milled surface is generated by the trace of the contact point between the cutting edge of the tool and workpiece. We present the surface generation process by calculating the trajectory of the contact points on the workpiece. Several simulations and experiments are performed to verify the proposed milled surface prediction methods.

• Journal of KSNVE
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• v.6 no.5
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• pp.661-669
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• 1996

Proposed is an aero-acoustic performance prediction method of axial fan. The fan aerodynamic performance is predicted by combining pitch-averaged quasi 3-D flow analysis with pressure loss models for blade boundary layer and wake, secondary flow, endwall boundary layer and tip leakage flows. Fan noise is assumed to be radiated as dipole distribution type, and its generation is assumed to be mainly due to the vortex street shed from blade trailing edge. The fluctuating pressure and lift on the blade surface are analyzed by incorporating the wake vortex stree shed from blade trailing edge. The fluctuating pressure and lift on the blade surface are analyzed by incorporating the wake vortex street model with thin airfoil theory. The aero-acoustic performance prediction results by the present method are in good agreement with the measured results of several axial fans. With the present prediction method, parametric studies are carried out to investigate the effects of blade chord length and spacing on the efficiency and the noise level of fan. In the case of lightly loaded fan, both efficiency improvement and noise reduction can be achieved by decreasing chord length or by increasing blade specing. However, when fan is designed at highly loaded condition, the noise reduction by increasing blade spacing penalizes the attaninable efficiency of fan.

• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.45-48
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• 2013

The electronic device, such as flat panel display (FPD), is very important in our life as a means of communication between humans. Liquid crystal display (LCD), which is categorized as a flat panel display, has been used in many display products, especially in TV industry. An LED TV is composed of several electrical components, such as liquid critical module (LCM), analog to digital convertor (AD), power supplier, and inverter board. These modules are very vulnerable to particulate contamination, and causing malfunction or visibility degradation. In this study, we developed a test method for prediction of LCM's lifetime. The test system consists of carbon particle generation flame, dilution system, test chamber, and particle concentration monitoring instrument. Since the carbon particles are the most abundant in the atmosphere and easily absorb light, soot particles are used as a challenging material for this test. The concentration of generated soot particles is set around 4,000,000 #/cc, which is 400 times higher than that of usual atmospheric particles. Through this experiment, we deduced the relationship between the dust concentration and life time of the test specimen.

• Korean Journal of Human Ecology
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• v.24 no.6
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• pp.887-901
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• 2015

This study aims to identify limitations and pending problems after reviewing the overall policies and status of rural Newtown projects, and to seek solutions to its problems. This study targeted the villages of 5 districts, which were developed as rural new-towns after 2009 and included the basic status and progress of the pilot districts. This study conducted a literature review to examine the basic status and progress of the pilot districts, and based on this, analyzed the demand prediction, site selection, project implementation, and housing and amenity facilities of the pilot districts. The study methods included literature reviews, on-site surveys, interviews with village representatives, and consultations with experts. According to the analysis results, a low occupancy rate of the Newtown project districts is because the prediction of occupancy demand was incorrectly completed before implementing the projects. Also, the eligibility for occupancy, such as age restriction and mandatory farming was too strict. Other problems included an absence of income generation support policies for rural returnees, a housing supply policy in disregard of agricultural characteristics, and a lack of understanding of maintenance of communal space, etc.

• Journal of Korea Water Resources Association
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• v.34 no.4
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• pp.391-401
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• 2001

Several curvature parameters, solar radiation parameter and topographic flow generation parameters have been summarized and calculated to predict the spatial distribution of soil moisture content. The spatial distribution of soil moisture data can be obtained using Global Positioning System(GPS) and portable soil moisture monitoring equipment, Theta-Probe. Correlation analysis has been performed between the parameters of soil moisture prediction and measured data of soil moisture. Multiple regression analysis of soil moisture prediction shows the potential capability and limitations of existing methods of digital terrain analysis.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.79-92
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• 2020

As the number of systems increases and the network size increases, automated attack prediction systems are urgently needed to respond to cyber attacks. In this study, we developed four types of information gathering sensors for collecting asset and vulnerability information, and developed technology to automatically generate attack graphs and predict attack targets. To improve performance, the attack graph generation method is divided into the reachability calculation process and the vulnerability assignment process. It always keeps up to date by starting calculations whenever asset and vulnerability information changes. In order to improve the accuracy of the attack target prediction, the degree of asset risk and the degree of asset reference are reflected. We refer to CVSS(Common Vulnerability Scoring System) for asset risk, and Google's PageRank algorithm for asset reference. The results of attack target prediction is displayed on the web screen and CyCOP(Cyber Common Operation Picture) to help both analysts and decision makers.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.10-14
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• 2001

We studied the use of time-related information, with and without prediction, to support human operators performing moni-toring and control tasks in the process. Based on monitoring and control techniques used for Project Management we developed a display design for the process industries. A simulated power plant was used to test the hypothesis that availability of predictions along with information on past trends can improve the performances of the human operator handling faults. Several designs of dis-plays were tested in the experiment in which human operators had to detect and handle two types of faults(local and systems wide) in the simulated electricity generation process. Analysis of the results revealed that temporal data, with and without prediction, signifi-cantly reduced response time. Our results encourage the integration of temporal information and prediction in displays used for the control processes to enhance the capabilities of the human operators. Based on the analysis we proposed some guidelines for the de-signer of the human interface of a process control system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.6
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• pp.661-669
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• 2018

Engineering system problems consist of multi-objective optimisation and the performance analysis is generally time consuming. To optimise the system concerning its performance, many researchers perform the optimisation using an approximation model. The Response Surface Method (RSM) is usually used to predict the system performance in many research fields, but it shows prediction errors for highly nonlinear problems. To create an appropriate metamodel for marine systems, Lee (2015) compares the prediction accuracy of the approximation model, and multi-objective optimal design framework is proposed based on a confirmed approximation model. The proposed framework is composed of three parts: definition of geometry, generation of approximation model, and optimisation. The major objective of this paper is to confirm the applicability/usability of the proposed optimal design framework and evaluate the prediction accuracy based on sensitivity analysis. We have evaluated the proposed framework applicability in derrick structure optimisation considering its structural performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.425-428
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• 2005

This paper is made up Advanced Image Coding(AIC) that combines algorithms from next generation image coding standard, H.264/MPEG-4 Part 10 advanced video coding(AVC) and still image compression standard, JPEG(Joint Photographic Experts Group). AIC combines intra frame block prediction from H.264 with a JPEG style discrete cosine transform and quantization, followed by Context-based Adaptive Binary Arithmetic Coding(CABAC) as used in H.264. In this paper, we analyzes the efficiency of the AIC algorithm and JPEG and JPEG-2000, and it presents of result.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.201-211
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• 2021

Purpose: This paper proposes a density adaptive grid algorithm for the k-NN regression model to reduce the computation time for large datasets without significant prediction accuracy loss. Methods: The proposed method utilizes the concept of the grid with centroid to reduce the number of reference data points so that the required computation time is much reduced. Since the grid generation process in this paper is based on quantiles of original variables, the proposed method can fully reflect the density information of the original reference data set. Results: Using five real-life datasets, the proposed k-NN regression model is compared with the original k-NN regression model. The results show that the proposed density adaptive grid-based k-NN regression model is superior to the original k-NN regression in terms of data reduction ratio and time efficiency ratio, and provides a similar prediction error if the appropriate number of grids is selected. Conclusion: The proposed density adaptive grid algorithm for the k-NN regression model is a simple and effective model which can help avoid a large loss of prediction accuracy with faster execution speed and fewer memory requirements during the testing phase.