• Journal of Environmental Health Sciences
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• v.26 no.4
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• pp.97-104
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• 2000

The purpose of this is made an examination of phosphorus loading model for eutrophication response in the Yongsan lake. For the model, we measured the total amount of nutrients derived from the Yongsan river watershed, inflow rate to the Yongsan lake, water quality, and water budget from January to December in 1999. The total amount of precipitation in the Yongsan river watershed was 4,951.7$\times$10$^{6}$ ㎥/y and inflow amount was 2,569.7$\times$10$^{6}$ ㎥/y, therefore the outflow rate of the Yongsan river watershed was 51.9%. The develop loading of total nitrogen was 86,928.1kg/d and that of total phosphorus was 22,007.6kg/d at the Yongsan river watershed, But, as the inflow loading of total nitrogen was 33,962kg/d and the inflow loading of total phosphorus was 2,218kg/d to the Yongsan lake. so each infolw rate was 39.0% and 10.1%. The hydraulic residence time was 34days, total phosphorus loading [L(P)] on the surface area was 23.398g/㎥/y, the hydraulic load( $Q_{s}$) of inflow water was 74.269m/y, the reserve rate of phosphorus in the lake was 0.359, and the settinh velocity of phosphorus was 0.114m/d at the Yongsan lake. Mathematical model of phosphorus loading to estimate the responses of eutrophication at the Yongsan lake is [ $P_{j}$] = 0.838 [L(P)/Q.(1+√ $T_{w}$)$^{-1}$ ] . ] . .

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.1-12
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• 1999

This paper presents a DEA-AHP hybrid model to evaluate and select R&D projects. AHP collects and processes information on the weights of evaluation criteria. The processed information is used as an input for DEA/AR model. Only desirable number of projects are selected by the hybrid model. The model is examined by an example generated from a real data set.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• Journal of Applied Reliability
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• v.17 no.4
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• pp.296-304
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• 2017

Purpose: Recent weapon systems in defense have increased the complexity and importance of software when developing multifunctional equipment. In this study, we analyze the accuracy of the proposed software reliability model when applied to weapon systems. Methods: Determine the similarity between software reliability analysis results (prediction/estimation) utilizing data from developing weapon systems and system failures data during operation of weapon systems. Results: In case of a software reliability prediction model, the predicted failure rate was higher than the actual failure rate, and the estimation model was consistent with actual failure history data. Conclusion: The software prediction model needs to adjust the variables that are appropriate for the domestic weapon system environment. As the reliability of software is increasingly important in the defense industry, continuous efforts are needed to ensure accurate reliability analysis in the development of weapon systems.

• Journal of Fashion Business
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• v.8 no.4
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• pp.94-103
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• 2004

The purpose of this study was to make activated electronic business transaction of clothes. The subject used for this study was 19 - 24 aged 149 college women who most likely buying products through internet. By compare the 149 women's body shape with 3D model, 149 women could be judged their body shape objectively. We showed the average 3D model by the measurement of 19 - 24aged women's body shape. 19 - 24aged women are big customer of internet shopping mall. By understanding of the difference between real somatotype and perceptual somatotype, we can reduce the disadvantage such as returning clothes. Also, imaginary fitting model can be used for internet shopping mall, animation work, fashion show, and advertisement work. Therefore, we can expect the worth of this study to do.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3A
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• pp.353-361
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• 2000

The performance of a multi-carrier CDMA system is analyzed considering frequency selective multipath fading and Near/Far effects. The number of multicarrier, multiuser, and arms of RAKE receiver, and the decay ratio of frequency selective multipath fading are used as a parameter for the performance analysis. More over, the distribution and the strength of multiuser interference are also considered. To evaluated the Near/Far effects in a multi-carrier CDMA system, three distribution models are assumed. In the first model. interference to carrier Ratio, I/C, ranges form -4 dB to 4dB, and at each 2 dB interval 20 % of multiuser is assumed to be uniformly distributed. In the second one, I/C ranges from -2 dB to 2 dB, and 33.3% of multiuser is assumed to be equally dispersed at each 2dB interval. The third model is 0 dB of I/C, that is, with perfect power control, multiuser are assumed to be evenly located. In this paper, multi-carrier CDMA system adoption RAKE receiver is proposed to mitigate the frequency selective multipath fading. Form the results, the third model(i.e. perfect power control)shows the best performance, and the narrower range of I/C causes the less effects to the desired signal, which reads to the better performance.

• IE interfaces
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• v.24 no.4
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• pp.408-419
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• 2011

R&D is a foundation for new business chance and productivity improvement leading to enormous expense and a long-term multi-step process. During the R&D process, decision-makers are confused due to the various future uncertainties that influence economic and technical success of the R&D projects. For these reasons, several decision-making models for R&D project investment have been suggested; they are based on traditional methods such as Discounted Cash Flow (DCF), Decision Tree Analysis (DTA) and Real Option Analysis (ROA) or some fusion forms of the traditional methods. However, almost of the models have constraints in practical use owing to limits on application, procedural complexity and incomplete reflection of the uncertainties. In this study, to make the constraints minimized, we propose a new model named Real Option Decision Tree Model which is a conceptual combination form of ROA and DTA. With this model, it is possible for the decision-makers to simulate the project value applying the uncertainties onto the decision making nodes.

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.258-267
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• 2016

Three-dimensional integrated circuits (3D ICs) experience die-to-die variations in addition to the already challenging within-die variations. This adds an additional design complexity and makes variation estimation and full-chip optimization even more challenging. In this paper, we show that the industry standard on-chip variation (AOCV) tables cannot be applied directly to 3D paths that are spanning multiple dies. We develop a new machine learning-based model and methodology for an accurate variation estimation of logic paths in 3D designs. Our model makes use of key parameters extracted from existing GDSII 3D IC design and sign-off simulation database. Thus, it requires no runtime overhead when compared to AOCV analysis while achieving an average accuracy of 90% in variation evaluation. By using our model in a full-chip variation-aware 3D IC physical design flow, we obtain up to 16% improvement in critical path delay under variations, which is verified with detailed Monte Carlo simulations.

• Imaging Science in Dentistry
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• v.34 no.1
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• pp.13-18
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• 2004

Purpose : This study was to evaluate the influence of slice thickness of computed tomography (CT) and rapid protyping (RP) type on the accuracy of 3-dimensional medical model. Materials and Methods: Transaxial CT data of human dry skull were taken from multi-detector spiral CT. Slice thickness were 1, 2, 3 and 4 mm respectively. Three-dimensional image model reconstruction using 3-D visualization medical software (V-works /sup TM/ 3.0) and RP model fabrications were followed. 2-RP models were 3D printing (Z402, Z Corp., Burlington, USA) and Stereolithographic Apparatus model. Linear measurements of anatomical landmarks on dry skull, 3-D image model, and 2-RP models were done and compared according to slice thickness and RP model type. Results: There were relative error percentage in absolute value of 0.97, 1.98,3.83 between linear measurements of dry skull and image models of 1, 2, 3 mm slice thickness respectively. There was relative error percentage in absolute value of 0.79 between linear measurements of dry skull and SLA model. There was relative error difference in absolute value of 2.52 between linear measurements of dry skull and 3D printing model. Conclusion: These results indicated that 3-dimensional image model of thin slice thickness and stereolithographic RP model showed relative high accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.11-16
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• 2020

3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer's operations. Facet, which is a small triangle, represents a small surface of 3D model. Depending on the height or precision of the 3D model, the number of facets becomes very large and so the conversion time from 3D model to G-code takes longer. Apach Hadoop is a software framework to support distributed processing for large data set and its application range gets widening. In this paper, Hadoop is used to do the conversion works time-efficient way. 2-phase distributed algorithm is developed first. In the algorithm, all facets are sorted according to its lowest Z-value, divided into N parts, and converted on several nodes independently. The algorithm is implemented in four steps; preprocessing - Map - Shuffling - Reduce of Hadoop. Finally, to show the performance evaluation, Hadoop systems are set up and converts testing 3D model while changing the height or precision.