• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• Journal of Nutrition and Health
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• v.45 no.3
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• pp.218-228
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• 2012

The prevalence rate of thyroid dysfunction (hypothyroidism and hyperthyroidism) has increased within the Korean population and seems to be affected by iodine dietary habits. Some studies reported that the prevalence of thyroid dysfunction increase both in the area of iodine deficiency and excess. In this study, we tried to discover the difference in iodine intake, anthropometric measurements, and blood parameters between male subjects with or without subclinical thyroid dysfunction. A total of 5,249 subjects (Euthyroid: 4706, SubHypo: 454, SubHyper: 89) were used in this study. There were no significant differences in BMI, body fat, visceral fat, waist circumference, SBP, DBP, total cholesterol, HDL-cholesterol, LDL-cholesterol, TG, fasting serum glucose, HbA1c, alcohol intake, however significant differences were noticed in both age and smoking status. Through a food frequency questionnaire (FFQ), iodine intake per day was estimated. The average iodine intake was similar (SubHypo $392.9{\pm}279.0{\mu}g$, Euthyroid $376.5{\pm}281.7{\mu}g$, SubHyper $357.3{\pm}253.8 {\mu}g$) among groups. The main source of iodine intake was eggs (52.8%, 54.2%, 52.4%) followed by milk (16.3%, 15.8%, 17.8%), then sea mustard & sea tangle (12.4%, 11.9%, 11.6%). The prevalence of subclinical hypothyroidism and subclinical hyperthyroidism was higher in subjects whose intake was higher than the recommended nutrient intake (RNI). These results suggest that the excess consumption of iodine intake may act as one of the risk factors regarding thyroid dysfunction in Korea. Therefore, an adequate amount of iodine intake is necessary in order to prevent subclinical thyroid dysfunction and clinical thyroid dysfunction.

• Applied Microscopy
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• v.32 no.1
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• pp.31-37
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• 2002

As-cast microstructure of Mg-rich $Mg_{68}Zn_{28}Y_4$ has been investigated by a detailed transmission electron microscopy. The as-cast $Mg_{68}Zn_{28}Y_4$ alloy consisted of three different types of phases: $10{\sim}20{\mu}m$ size primary solidification phase, dendritic phase grown from the primary phase and a eutectic structure formed at the later stage of solidification. The primary solidification phase has an icosahedral structure with a large degree of phason strain. 1/1 rhombohedral approximant phase with lattice parameters: $a=27.2{\AA}\;and\;{\alpha}=63.43^{\circ}$ is first observed in Mg-Zn-Y system. The rhombohedral structure can be obtained by introducing phason strain in the six dimensional face centered hyper-cubic lattice. The decagonal phase nucleates with orientation relationship with the icosahedral phase, and $Mg_4Zn_7$ nucleates with orientation relationship with the decagonal phase, indicating a close structural similarity between the three phases. Gradual depletion of Y during solidification plays an important role in heterogeneous nucleation of decagonal and $Mg_4Zn_7$ phases from icosahedral and decagonal phases respectively.

• Coupled systems mechanics
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• v.4 no.4
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• pp.279-295
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• 2015

The article presents a theoretical-experimental approach developed for modeling the coefficient of sliding friction in the dynamic system tool-workpiece in slide diamond burnishing of low-alloy unhardened steels. The experimental setup, implemented on conventional lathe, includes a specially designed device, with a straight cantilever beam as body. The beam is simultaneously loaded by bending (from transverse slide friction force) and compression (from longitudinal burnishing force), which is a reason for geometrical nonlinearity. A method, based on the idea of separation of the variables (time and metric) before establishing the differential equation of motion, has been applied for dynamic modeling of the beam elastic curve. Between the longitudinal (burnishing force) and transverse (slide friction force) forces exists a correlation defined by Coulomb's law of sliding friction. On this basis, an analytical relationship between the beam deflection and the sought friction coefficient has been obtained. In order to measure the deflection of the beam, strain gauges connected in a "full bridge" type of circuit are used. A flexible adhesive is selected, which provides an opportunity for dynamic measurements through the constructed measuring system. The signal is proportional to the beam deflection and is fed to the analog input of USB DAQ board, from where the signal enters in a purposely created virtual instrument which is developed by means of Labview. The basic characteristic of the virtual instrument is the ability to record and visualize in a real time the measured deflection. The signal sampling frequency is chosen in accordance with Nyquist-Shannon sampling theorem. In order to obtain a regression model of the friction coefficient with the participation of the diamond burnishing process parameters, an experimental design with 55 experimental points is synthesized. A regression analysis and analysis of variance have been carried out. The influence of the factors on the friction coefficient is established using sections of the hyper-surface of the friction coefficient model with the hyper-planes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.14-24
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• 2018

Several typical hyper-elastic constitutive models that encompass both conventional and advanced ones were investigated for the application of instability problems, including the biaxial tension of a rubber patch and inflation of spherical or cylindrical balloons. The material models included the neo-Hookean model, Mooney-Rivlin model, Gent model, Arruda-Boyce model, Fung model, and Pucci-Saccomandi model. Analyses can be done using membrane equations with particular strain energy density functions. Among the typical strain energy density functions, Kearsley's bifurcation for the Treloar's patch occurs only with the Mooney-Rivlin model. The inflation equation is so generalized that a spherical balloon and tube balloons can be taken into account. From the analyses, the critical material parameters and limit points were identified for material models in terms of the non-dimensional pressure and inflation volume ratio. The bifurcation was then identified and found for each material model of a balloon. When the finite element method was used for the structural instability problems of rubber-like materials, some careful treatments required could be suggested. Overall, care must be taken not only with the analysis technique, but also in selecting constitutive models, particularly the instabilities.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.980-993
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• 2020

Deep-learning based style transfer has recently attracted great attention, because it provides high quality transfer results by appropriately reflecting the high level structural characteristics of images. This paper deals with the problem of providing more stable and more diverse style transfer results of such deep-learning based style transfer method. Based on the investigation of the experimental results from the wide range of hyper-parameter settings, this paper defines the problem of the stability and the diversity of the style transfer, and proposes a partial loss normalization method to solve the problem. The style transfer using the proposed normalization method not only gives the stability on the control of the degree of style reflection, regardless of the input image characteristics, but also presents the diversity of style transfer results, unlike the existing method, at controlling the weight of the partial style loss, and provides the stability on the difference in resolution of the input image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.749-756
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• 2021

Thanks to PLC and IoT Sensor, huge amounts of data has been accumulated onto the companies' databases. Machine Learning Algorithms for the predictive model with good performance have been widely utilized in the manufacturing process. We present how to improve the performance of machine learning predictive models. To improve the performance of the predictive model, typical techniques such as increasing the sample size, optimizing the hyper parameters for the algorithm, and selecting a proper machine learning algorithm for the predictive model would be shown. We suggest some new ways to make the model performance much better. With the proposed methods, we can build a better predictive model for predicting and controlling product qualities and save incredibly large amount of quality failure cost.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.374-376
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• 2021

For the diagnosis of cancer-related diseases in clinical practice, pathological examination using biopsy is essential after basic diagnosis using imaging equipment. In order to proceed with such a biopsy, the assistance of an oncologist, clinical pathologist, etc. with specialized knowledge and the minimum required time are essential for confirmation. In recent years, research related to the establishment of a system capable of automatic classification of cancer cells using artificial intelligence is being actively conducted. However, previous studies show limitations in the type and accuracy of cells based on a limited algorithm. In this study, we propose a method to identify a total of 4 cancer cells through a convolutional neural network, a kind of deep learning. The optical images obtained through cell culture were learned through EfficientNet after performing pre-processing such as identification of the location of cells and image segmentation using OpenCV. The model used various hyper parameters based on EfficientNet, and trained InceptionV3 to compare and analyze the performance. As a result, cells were classified with a high accuracy of 96.8%, and this analysis method is expected to be helpful in confirming cancer.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.1
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• pp.121-131
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• 1998

This paper applies the FE analysis procedure, developed in the Part I of the companion article, to the three-dimensional rubber pad deformation during rubber-pad forming process. Effects of different algorithms corresponding to incompressibility constraint and time integration methods on numerical solution responses are investigated. Laboratory scale experiments support the validity of the developed FE procedure an demonstrate the accuracy of the numerical models. Full scale model responses are also predicted using the reasonable method and parameters obtained in laboratory modeling.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.59-66
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• 2013

In this paper, we propose a probabilistic framework for model-based clustering of direction of arrival (DOA) data to obtain stable sound source localization (SSL) estimates. Model-based clustering has been shown capable of handling highly overlapped and noisy datasets, such as those involved in DOA detection. Although the Gaussian mixture model is commonly used for model-based clustering, we propose use of the von Mises mixture model as more befitting circular DOA data than a Gaussian distribution. The EM framework for the von Mises mixture model in a unit hyper sphere is degenerated for the 2D case and used as such in the proposed method. We also use a histogram of the dataset to initialize the number of clusters and the initial values of parameters, thereby saving calculation time and improving the efficiency. Experiments using simulated and real-world datasets demonstrate the performance of the proposed method.