• Journal of the Korean Society of Industry Convergence
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• v.16 no.3
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• pp.85-93
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• 2013

The MCT has been most extensively used in the machining. In particular, the ball endmill has been mainly adopted for finishing on the free- form surface. The advancement of CAD/CAM software has made it possible to develop various cutting pattern methods and to create diverse tool routes. Therefore, the current research made an attempt to find the optimal cutting pattern among the seven cutting patterns (i.e., Follow Periphery, Zig, Zig Zag, Concentric Zig, Concentric Zig Zag, Radial Zig, Radial Zig Zag) when aluminium 6000 series were machined by the ball endmill. The optimal pattern was found by comparing different shapes and surface roughness produced by the seven patterns. The current research found that each cutting pattern produced its own unique geometric features on the machined surface. It was found that the Radial Zig cutting pattern produced the lowest roughness on the flat surfaces. The Radial Zig Zag cutting pattern was found to produce the most accurate free-form surface. Finally, the most efficient cutting pattern in terms of machining time turned out to be the Follow Periphery.

• Ocean and Polar Research
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• v.44 no.4
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• pp.287-296
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• 2022

High-frequency (HF) radar measures sea surface currents from the radio waves transmitted and received by antenna on land. Since the data quality of HF radar measurements sensitively depend on the radio wave environment around antenna, Antenna Pattern Measurements (APM) plays an important role in evaluating the accuracy of measured surface currents. In this study, APM was performed by selecting the times when the background noise level around antenna was high and low, and radial data were generated by applying the ideal pattern and measured pattern. The measured antenna pattern for each case was verified with the current velocity data collected by drifters. The radial velocity to which the ideal pattern was applied was not affected by the background noise level around antenna. However, the radial velocity obtained with APM in the period of high background noise was significantly lower in quality than the radial velocity in a low noise environment. It is recomended that APM be carried out in consideration of the radio wave environment around antenna, and that the applied result be compared and verified with the current velocity measurements by drifters. If it is difficult to re-measure APM, we suggest using radial velocity in generating total vector with the ideal pattern through comparative verification, rather than poorly measured patterns, for better data quality.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.293-300
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• 2014

This paper proposes a novel pattern recognition approach based on the radial basis function (RBF) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). Pattern recognition of PD is used for identifying defects causing the PD, such as internal discharge, external discharge, corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. Since an insulation defect, such as one resulting from PD, would have a corresponding particular pattern, pattern recognition of PD is significant means to discriminate insulation conditions of high-voltage electrical apparatus. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD pattern recognition of cast resin current transformer (CRCT) models. These tests used artificial defects created in order to produce the common PD activities of CRCTs by using feature vectors of field-test PD patterns. The significant features are extracted by using nonlinear principal component analysis (NLPCA) method. The experimental data are found to be in close agreement with the recognized data. The test results show that the proposed approach is efficient and reliable.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.161-172
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• 2016

The use of a chemical sensor array can help discriminate between chemicals when comparing one sample with another. The ability to classify pattern characteristics from relatively small pieces of information has led to growing interest in methods of sensor recognition. A variety of pattern recognition algorithms, including the adaptive radial basis function network (RBFN), may be applicable to gas and/ or odor classification. In this paper, we provide a broad review of approaches for various types of gas and/or odor identification techniques based on RBFN and drift compensation techniques caused by sensor poisoning and aging.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.272-273
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• 2013

Some living thingsuse micro- or nano- structures for living in nature. Scientists and engineers made efforts to mimic them, and they succeeded in making new types of applications. They used 'Namib desert beetle' to self-filling device by moisture harvesting and 'lotus leaf' to self-cleaning device by water repelling. 'Namib desert beetle' and lotus leaf have micro-patterns on their surface, which consists of hydrophobic or hydrophilic materials [1]. Moreover, micro-patterns on the surface make self-filling or self-cleaning property enhanced because of the surface roughness. Surface roughness enhances wettability [2]. Micro-pattern is a significant factor to make the surface be functional, so we want to make new types of functional surface by micro-patterning. In this work,we make several functional micro-patterns (radial, line, and dot arrays) using maskless lithography and analyze the characteristics of each micro-pattern. In order to analyze and understand surface characteristics, micro-patterns with varying sizes are investigated. All experiments are proceeded on mr-DWL5 photo resists coated on silicon wafers in same condition. All the experiments have demonstrated good performances about hydrophobic or hydrophilic property corresponding to their material and structural combinations. In radial micro-pattern, although the surface is flat, water drops on hydrophilic radial pattern can be convergent to a middle point and water drops on hydrophobic radial pattern can be divergent from the middle point. In line array micro-pattern, water drops can roll off along only one direction in parallel with the line arrays. Such phenomena might be mainly caused by the local change of surface roughness. From these results, controlling the movement and direction of water drops is made feasible without introducing a slope, which can potentially be used for new types of applications.

• Transactions of Materials Processing
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• v.16 no.1 s.91
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• pp.67-74
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• 2007

This study is aimed to find out the optimal forming conditions by comparing and analyzing material flow, deformation pattern, and a forming load through rigid-plastic FEM for a flange using pipe. Flanges are widely used for various purposes as connectors of industrial steel pipes which are manufactured by drawing process. The forming feature of flange was reviewed through both heading process and radial extrusion process in a cold working condition. As a result of simulation, the shape of flange can not be made by heading process, but made by radial extrusion process. The effects of design factors, such as gap-height, die-comer radius, and frictional factors on maximum forming load and deformation pattern are investigated for radial extrusion process.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2448-2450
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• 1998

For the exact classification of the arm motion this paper proposes EMG pattern recognition method with neural network. For this autoregressive coefficient, linear cepstrum coefficient, and adaptive cepstrum coefficient are selected for the feature parameter of EMG signal, and they are extracted from time series EMG signal. For the function recognition of the feature parameter a radial basis function network, a field of neural network is designed. For the improvement of recognition rate, a number of radial basis function network are combined in parallel, comparing with a backpropagation neural network an existing method.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.16 no.5
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• pp.516-524
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• 1987

This paper presents experimental data of fluctuation characteristics of local void fraction of air-water two-phase flow which are associated with the flow pattern, annular gap size and radial location in vertical concentric annuli with coefficient of skewness and kurtosis. The annular gap widths are 13mm, 11mm, and 9mm for a 38m inner diameter as the lucite outer tube. A electrical conductivity probe was used to measure the local void fraction and traversed diametrically from inner wall to outer wall using radial increments of 2mm. It was shown that distribution of the coefficient of skewness and kurtosis, which is related that the one is the asymmetry and the other peakness of local void fraction distribution was influenced by flow pattern, annular gap size and radial location.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.544-553
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• 2013

In this paper, we propose the pattern classifier of Radial Basis Function Neural Networks(RBFNNs) for diagnosis of 3-phase partial discharge. Conventional methods map the partial discharge/noise data on 3-PARD map, and decide whether the partial discharge occurs or not from 3-phase or neutral point. However, it is decided based on his own subjective knowledge of skilled experter. In order to solve these problems, the mapping of data as well as the classification of phases are considered by using the general 3-PARD map and PA method, and the identification of phases occurring partial discharge/noise discharge is done. In the sequel, the type of partial discharge occurring on arbitrary random phase is classified and identified by fuzzy clustering-based polynomial Radial Basis Function Neural Networks(RBFNN) classifier. And by identifying the learning rate, momentum coefficient, and fuzzification coefficient of FCM fuzzy clustering with the aid of PSO algorithm, the RBFNN classifier is optimized. The virtual simulated data and the experimental data acquired from practical field are used for performance estimation of 3-phase partial discharge pattern classifier.

• Transactions of Materials Processing
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• v.12 no.3
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• pp.228-235
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• 2003

In this paper, the workability of flange in the radial extrusion is analyzed in terms of the deformation pattern, the punch load and the forming limit by using simulation and experiment. A single action pressing is applied to both simulation and experiment. The analysis in this study is focused on the transient extrusion into the gap in radial direction with various gap heights and die corner radius. Based on the surface strains where surface cracking occurs, the forming patterns and strain-fracture relationships in producing radially extruded flange are obtained.