• Bulletin of the Korean Chemical Society
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• v.32 no.4
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• pp.1336-1340
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• 2011

Molecular dynamics simulations have been performed to investigate the transport properties of self-diffusion coefficients in the penetrable-sphere model system. The resulting simulation data for the product of the packing fraction and the self-diffusion coefficient exhibit a transition from an increasing function of density in lower repulsive systems, where the soft-type collisions are dominant, to a decreasing function in higher repulsive systems, where most particle collisions are the hard-type reflections due to the low-penetrability effects. A modified Enskog-like equation implemented by the effective packing fraction with the mean-field energy correction is also proposed, and this heuristic approximation yields a reasonably good result even in systems of high densities and high repulsive energy barriers.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.189-190
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• 2006

During cold compaction processes loose powder is pressed under tooling action in order to produce complex shaped engineering components. Here, the analysis of the plastic deformation of granular packings is of fundamental importance to the development of computer simulation models. Powders can be idealized by packing discrete particles, where each particle is a sphere meshed with finite elements. The pressing of a body centered cubic packing was compared with numerical prediction and experimental data. The global response was expressed in force-displacement curve, and the accuracy of the numerical models analyzed for high relative densities up to 0.95.

• Spatial Information Research
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• v.19 no.1
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• pp.107-116
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• 2011

Due to development of environment of wireless Internet, location based services on the basis of spatial data have been increased such as real time traffic information as well as CNS(Car Navigation System) to provide mobile user with route guidance to the destination. However, the current application adopting the file-based system has limitation of managing and storing the huge amount of spatial data. In order to supplement this challenge, research which is capable of managing large amounts of spatial data based on embedded database system is surely demanded. For this reason, this study aims to suggest the lossless compression technique by using the hybrid approach of BytePacking and Lempel-Ziv which can be applicable in DBMS so as to save a mass spatial data efficiently. We apply the proposed compression technique to actual the Seoul and Inchcon metropolitan area and compared the existing method with suggested one using the same data through analyzing the query processing duration until the reconstruction. As a result of comparison, we have come to the conclusion that suggested technique is far more performance on spatial data demanding high location accuracy than the previous techniques.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.31-39
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• 1998

This paper presents the design and implementation of a new multimedia fixed-point DSP (MDSP) core for portable multimedia applications. The MDSP instruction set is designed through the analysis of multimedia algorithms and DSP instruction sets. The MDSP architecture employs parallel processing techniques, such as SIMD and vector processing as well as DSP techniques. The instruction set can handle various data formats and MDSP can perform two MAC operations in parallel. The switching network and packing network can increase the performance by overlapping data rearrangement cycles with computation cycles. We have designed Verilog HDL models and the 0.6 $\mu\textrm{m}$ Samsung KG75000 SOG library is used. The total gate count is 68,831 and the clock frequency is 30 MHz.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Design & Manufacturing
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• v.14 no.3
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• pp.1-7
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• 2020

This paper predicts the mass and the length of injection-molded products through the Artificial Neural Network (ANN) method. The ANN was implemented with 5 input parameters and 2 output parameters(mass, length). The input parameters, such as injection time, melt temperature, mold temperature, packing pressure and packing time were selected. 44 experiments that are based on the mixed sampling method were performed to generate training data for the ANN model. The generated training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. A random search method was used to find the optimized hyper-parameter of the ANN model. After the ANN completed the training, the ANN model predicted the mass and the length of the injection-molded product. According to the result, average error of the ANN for mass was 0.3 %. In the case of length, the average deviation of ANN was 0.043 mm.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2294-2304
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• 1999

Our research purpose in this paper is to improve the performance of query processing in GIS(Geographic Information System) by enhancing the I/O performance exploiting parallel I/O and efficient disk access. By packing adjacent spatial data, which are very likely to be referenced concurrently, into one block or continuous disk blocks, the number of disk accesses and the disk access overhead for query processing can be decreased, and this eventually leads to the I/O time decrease. So, in this paper, we proposes EPR(Enhanced Parallel R-tree) indexing method which integrates the parallel I/O method of the previous Parallel R-tree method and a packing-based clustering method. The major characteristics of EPR method are as follows. First, EPR method arranges spatial data in the increasing order of proximity by using Hilbert space filling curve, and builds a packed R-tree by bottom-up manner. Second, with packing-based clustering in which arranged spatial data are clustered into continuous disk blocks, EPR method generates spatial data clusters. Third, EPR method distributes EPR index nodes and spatial data clusters on multiple disks through round-robin striping. Experimental results show that EPR method achieves up to 30% or more gains over PR method in query processing speed. In particular, the larger the size of disk blocks is and the smaller the size of spatial data objects is, the better the performance of query processing by EPR method is.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.518-526
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• 2017

This study analyzed the impact of family firms and their characteristics on how they use debts to analyze the decision-making process of Korean family firms. For analysis, we classified the characteristics of family firms into three categories, through the influence of the relationship between the lack of funds and net debt issuance, which was confirmed as the 'packing order theory' of family firms. There was a total of 4,503 enterprises in the Korean Exchange (KRX). The period of analysis was 10 years, between 2004 and 2014. To summarize, Shyam-Sunder and Myers (1999) validated the packing order theory by presenting a model of family businesses that showed greater applicable to higher packing order theory than a model of non-family businesses. Moreover, the results also confirmed the application of the packing order theory by the family stronger corporate governance and ownership structure. The ownership and governance characteristics of the ruling family has also shown the applicability of higher packing order theory.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.6
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• pp.483-489
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• 2019

For machine learning techniques, a large amount of high-quality material property data should be accumulated. In this study, several data for an alumina tape casting process were produced with the variables of slurry viscosity, gap size, and coating speed. The alumina tapes were manufactured in the range of 1,000~6,000 cps for slurry viscosity, $300{\sim}1,000{\mu}m$ for gap size, and 0.5~2.0 m/min for coating speed. As a result, the lower the viscosity, coating speed, and gap size, the more pore-free tapes could be manufactured. The viscosity of the slurry limited the minimum thickness of the tape. Green sheets with high packing density were manufactured from the slurry of 100~6,000 cps slurry viscosity, coating speed of 0.5 m/min, and a $300{\sim}500{\mu}m$ gap size.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.2
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• pp.289-301
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• 1998

The present study attempted to numerically simulate the process in detail by developing an appropriate physical modeling and the corresponding numerical analysis for precision injection and injection/compression molding process of center-gated disk. In part I, a physical modeling and associated numerical analysis of injection molding with a compressible viscoelastic fluid model are presented. In the distribution of birefringence, the packing procedure results in the inner peaks in addition to the outer peaks near the mold surface, and values of the inner peaks increase with the packing time. Also, values of the density in the core region increase with the packing time. From the numerical results, we also found that birefringence becomes smaller as the melt temperature gets higher and that it is insignificantly affected by the flow rate and the mold temperature. As far as the density distribution is concerned, mold temperature affected the distribution of density especially near the wall. But it was not significantly affected by flow rate and melt temperature. Numerical results of birefringence coincided with experimental data qualitatively but didn't quantitatively.