• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.807-812
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• 1997

For an equivalent uniform soil model to multiple-layered soil structure, ground depth, which is used in the calculation of equivalent resistivity, should be varied according to the size of grounding area. In case of 150 kV substation grounding design, 15 m of ground depth has been used and 25 m for 345 kV, But applying these ground depths can lead to errors in grounding resistance calculation, and these errors are coming from the poor representation of those depths to real soil resistivities. In this paper, the soil resistivity measurement techniques by Wenner method and grounding resistance calculation results by computer simulation were presented. Case studies contain the area from 3,000 to $30,000\;m^2$ and measuring space from of m to $100{\sim}250\;m$, Based of the computation results, 50 m, 60 m and 80 m of ground depth for less than 30, 40 and 70 m of equivalent hemispherical radius were proposed respectively.

• Journal of the Korean Ceramic Society
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• v.41 no.11
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• pp.793-796
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• 2004

Process Parameters were studied in synthesis of LiCoO$_2$ Powder by ultrasonic spray Pyrolysis. Concentration of the mixed solution influenced the size, shape, and yield of the synthesized powder. The yield was affected primarily by the height of the solution, and then by the flow rate of a carrier gas. The temperature of the reactor governed the crystallinity and morphology of the powder. LiCoO$_2$ powders were synthesized as a layered high temperature phase above 800$^{\circ}C$. The synthesized powders were sphere and secondary Particles consisted of primary particles of 55-70 nm. The secondary Particles became bigger from 0.28 to 1.43 $\mu\textrm{m}$ as the concentration of the solution was increased from 0.05 to 2.0 M. The 2.0 M solution provided the highest production rate.

• Journal of the Korea Safety Management & Science
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• v.6 no.4
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• pp.155-170
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• 2004

Among the semiconductor If-chips, unlike memory chips, a majority of Application Specific IC(ASIC) products are produced by customer orders, and meeting the customer specified due date is a critical issue for the case. However, to the one who understands the nature of semiconductor manufacturing, it does not take much effort to realize the difficulty of meeting the given specific production due dates. Due to its multi-layered feature of products, to be completed, a semiconductor product(called device) enters into the fabrication manufacturing process(FAB) repeatedly as many times as the number of the product specified layers, and fabrication processes of individual layers are composed with similar but not identical unit processes. The unit process called photo-lithography is the only process where every layer must pass through. This re-entrant feature of FAB makes predicting and planning of due date of an ordered batch of devices difficult. Parallel machines problem in the photo process, which is bottleneck process, is solved with restricted roll out algorithm. Roll out algorithm is a method of solving the problem by embedding it within a dynamic programming framework. Restricted roll out algorithm Is roll out algorithm that restricted alternative states to decrease the solving time and improve the result. Results of simulation test in condition as same as real FAB facilities show the effectiveness of the developed algorithm.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.2
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• pp.84-92
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• 1995

To understand how low-frequency sound waves propagate axially in drilling boreholes, the propagation modes and speeds including the effect of interaction among layers are obtained by analyzing an infinitely-long, uniform, and cylindrically multi-layered waveguide which is consisted of fluid layers and solid layers. Assuming low frequency(wave length considered is very long compared to the borehole diameter), axisymmetry, non-viscosity, and etc., analytical solutions are obtained. Also, sound reflection due to the changes in the cross section is analyzed. Results for typical drilling boreholes show the usefulness of the method developed in this research, and are compared with FEM results showing good agreements.

• The Research Journal of the Costume Culture
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• v.26 no.3
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• pp.296-312
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• 2018

In this study, we analyzed the whole design of the necklace in detail, which reflects the artistic sense of handicraft in couture. The purpose of the study was to identify the characteristics of the design based on the analysis findings and to provide basic data to help fashion designers. The research method entailed analyzing trends in necklace design - viewed in fashion magazines and on websites - by year, season, brand, kind, material, color, and image. The identified necklace design characteristics were as follows. First, artistry and originality are dramatically expressed through the use of a broad range of materials. Second, due to the necklace's role as an object of perfect beauty, in a number of images, the necklaces were presented in convergence and contrast with overall costumes. Third, the dramatic effects of layering revealed a strong presence and individualized styling. Necklaces are created with diverse sculptures by realizing the creative imagination of fashion designers. Even though they looked a little different every year, there were designs in the collections constantly. Round shape and princess length were preferred. In particular, the mix type was used to express dramatic effect by focusing neck part in entire styling which different length of necklaces were layered and worn. As a result, it meets the needs of consumers who emphasize brand differentiation and diversity, and it is believed that the role of necessities in fashion will continue and it creates economic demand in the fashion industry.

• Journal of the Korean Society of Combustion
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• v.14 no.4
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• pp.1-6
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• 2009

Analysis of the internal state of the blast furnace is necessary to predict and to control the operating conditions. Especially, it is important to develop models of the blast furnace to predict the cohesive zone because shape of the cohesive zone influences overall operating conditions of blast furnace such as gas flow, chemical reactions and temperature. Because many previous blast furnace models have assumed cohesive zone to be fixed, it was not possible to evaluate the shape change of cohesive zone in relation with operating conditions such as PCR, blast condition, and production rate. In this study, an axi-symmetric 2-dimensional steady state model is proposed to simulate blast furnace processes. In this model, cohesive zone is determined by the solid temperature. Finite volume method is employed for numerical simulation. To find location of the cohesive zone, entire calculation procedure is iterated until converged. Through this approach, shape of the cohesive zone, velocity and temperature within the furnace are predicted from the model.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.123-139
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• 2011

Context-awareness as a key technology of ubiquitous computing needs a context model that understands and processes situational information coming from diverse sensors and devices, and can be applied diversely in various domains. Semantic web based ontologies use structured standard format and express meaning of information, so it is possible to recognize effectively context-awareness situations, allowing the system to share information and understand situation by inference. In this paper, we propose a layered ontology model to support generality and scaleability of the context-awareness system, and applied the model to u-Convention domain. In addition, we propose a effective reasoning method to handle compound situation by combining OWL-DL and SWRL rules.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.263-270
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• 2004

Recently, wavelet transform have been applied to various kinds of problems in many fields. In this paper, we propose method of Daubechies wavelet to detect several kinds of important characteristic waves in tasks EEG that are needed to diagnose EEG. We show that our system could be attained higher performance in detecting characteristic waves than the other methods. In this system, the architecture of the neural network is a three layered feed-forward networks with one hidden layer which implements the error back propagation teaming algorithm. Applying the algorithms to 4 subjects show 92% classification rates. The proposed system shows a little more accurate diagnosis for task EEG by Wavelet and neural network. From the simulation results by the implemented system, we demonstrated this research can be reduce doctor's labors and quantitative diagnosis of task EEG.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.269-276
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• 2010

In this paper, we present the detection method of moving objects based on two background models. These background models support to understand multi layered environment belonged in images taken by shaking camera and each model is MBM(Multiple Background Model) and TMBM (Temporal Median Background Model). Because two background models are Pixel-based model, it must have noise by camera movement. Therefore correlation coefficient calculates the similarity between consecutive images and measures camera motion vector which indicates camera movement. For the calculation of correlation coefficient, we choose the selected region and searching area in the current and previous image respectively then we have a displacement vector by the correlation process. Every selected region must have its own displacement vector therefore the global maximum of a histogram of displacement vectors is the camera motion vector between consecutive images. The MBM classifies the intensity distribution of each pixel continuously related by camera motion vector to the multi clusters. However, MBM has weak sensitivity for temporal intensity variation thus we use TMBM to support the weakness of system. In the video-based experiment, we verify the presented algorithm needs around 49(ms) to generate two background models and detect moving objects.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.13-18
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• 2018

This paper is based on a simple approach that the most efficient learning of a multi-layered network is the process of finding the optimal set of weight vectors. To overcome the disadvantages of general learning problems, the proposed model uses a combination of features of EBP and OVSSA. In other words, the proposed method can construct a single model by taking advantage of each algorithm so that it can escape to the probability theory of OVSSA in order to reinforce the property that EBP falls into local minimum value. In the proposed algorithm, methods for reducing errors in EBP are used as energy functions and the energy is minimized to OVSSA. A simple experimental result confirms that two algorithms with different properties can be combined.