• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Journal of Korea Water Resources Association
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• v.42 no.12
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• pp.1079-1089
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• 2009

The objective of this study is to develop the accurate, robust and high resolution two-dimensional numerical model that solves the computationally difficult hydraulic problems, including the wave front propagation over dry bed and abrupt change in bathymetry. The developed model in this study solves the conservative form of the two-dimensional shallow water equations using an unsplit finite volume scheme and HLLC approximate Riemann solvers to compute the interface fluxes. Bed-slope term is discretized by the divergence theorem in the framework of FVM for application of unsplit scheme. Accurate and stable SGM, in conjunction with the MUSCL which is second-order-accurate both in space and time, is adopted to balance with fluxes and source terms. The exact C-property is shown to be satisfied for balancing the fluxes and the source terms. Since the spurious oscillations in second-order schemes are inherent, an efficient slope limiting technique is used to supply TVD property. The accuracy, conservation property and application of developed model are verified by comparing numerical solution with analytical solution and experimental data through the simulations of one-dimensional dam break flow without bed slope, steady transcritical flow over a hump and two-dimensional dam break flow with a constriction.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.339-344
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• 2013

Water vapor isotopes can be excellent tools for understanding complex mechanisms in the water cycle and atmospheric hydrological cycle and they can be applied to various fields of paleoclimatology, atmospheric science, hydrogeology, oceanography, and ecohydrology. Thus, studies of global or local transport of water vapor may be able to provide a very useful clue to better understand the movements of water and energy in the atmosphere, hydrosphere and biosphere. In this study, the isotopic compositions of water vapor have been observed for moisture transport during the passage of Typhoon Bolaven at Korea Polar Research Institute (KOPRI), Incheon, in the western part of Korea, from August 27 to August 29, 2012. In the clear sky, the isotopic compositions of water vapor at KOPRI exhibited relatively higher isotopic ratios, which were near isotopic equilibrium with sea surface water (${\delta}^{18}O$=-14‰). On the other hand, a largely depleted isotopic ratios in surface water vapor were observed in association with the passage of Typhoon Bolaven (approximately 10‰ depleted compared to the clear sky). The fact that the isotopic minima in water vapor are encountered during the onset period of the Typhoon Bolaven with increases of relative humidity, which is consistent with, so called, "the amount effect".

• Journal of Korea Water Resources Association
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• v.44 no.10
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• pp.819-830
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• 2011

The multi-slope MUSCL, proposed by T. Buffard and S. Clain, determines slopes of conserved variables at each edge of a cell in the linear reconstructions of data. In this study, the second order accurate numerical model was developed according to the multi-slope MUSCL to solve the shallow water equations on the unstructured grids. The HLLL scheme of approximate Riemann solvers was used to calculate fluxes. For the review of the applicability of the developed model, the results of the model were compared to the 'isolated building test' and the 'model city flooding experiment' conducted as part of the IMPACT (Investigation of extreMe flood Processes And unCerTainty) project in Europe. There were limitations to predict abrupt rising of water depths by the resistance of model buildings and water depths at the specific locations among the buildings. But they were identified as the same problems also revealed in results of the other models to the same experiment. On the more refined meshes to the 'model city flooding experiment' simulated results showed good agreement with measurements. It was verified that the developed model simulated well the complex phenomena such as a dam-break problem and the urban inundation by flash floods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.4
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• pp.75-86
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• 1985

A beam with web opening may reduce the cost of steel and the height of multistory steel buildings. Bower's analysis based on the theory of elasticity and Vierendeel analysis had evaluated the normal stresses around the holes, but these analyses have difficulties for practical uses because of complexity and the limitation for their application. In this study, it is shown that the finite element method, using smaller number of isoparametric elements by taking only a part of the beam which includes the hole, can diminish defects of the above two methods and it may represent more satisfactorily the distribution of the local stress concentration around the hole than the other methods which employed linear elements such as in the analysis by Samuel or Redwood. This study presents the effects of moments, shears, and eccentricities of a hole on the distribution of the normal stresses calculated by using the proposed finite element method. Consequently, it is found that the variations of shear force and hole depth give significant effects on the normal stresses around a hole, while the variations of eccentricities of the hole provide a little effect on them. The regression coefficients resulted from the multiple linear regression may be used for estimating the normal stresses around any arbitrary hole in the web of a beam, since the normal stresses guessed by this regression coefficient equation match well the results by the finite element method except the case of large eccentricity.

• Korean Chemical Engineering Research
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• v.51 no.2
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• pp.226-232
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• 2013

To produce biobutanol, fermentation processes using clostridia that mainly produce acetone, butanol and ethanol are used. In this work, a dynamic model describing the metabolic reactions in an acetone-butanol-ethanol (ABE)-producing clostridium, Clostridium acetobutylicum ATCC824, was proposed. To estimate the 58 kinetic parameters of the metabolic network model with experimental data obtained from a batch fermentor, we used an efficient optimization method combining a genetic algorithm and the Levenberg-Marquardt method because of the complexity of the metabolism of the clostridium. For the verification of the determined parameters, the developed metabolic model was evaluated by experiments where genetically modified clostridium was used and the initial concentration of glucose was changed. Consequently, we found that the developed kinetic model for the metabolic network was considered to describe the dynamic metabolic state of the clostridium sufficiently. Thus, this dynamic model for the metabolic reactions will contribute to designing the clostridium as well as the fermentor for higher productivity.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.34-44
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• 2006

Simulation models allow researchers to model large hydrological catchment for comprehensive management of the water resources and explication of the diffuse pollution processes, such as land-use changes by development plan of the region. Recently, there have been reported many researches that examine water body quality using Geographic Information System (GIS) and dynamic watershed models such as AGNPS, HSPF, SWAT that necessitate handling large amounts of data. The aim of this study is to develop a watershed based water quality estimation system for the impact assessment on stream water quality. KBASIN-HSPF, proposed in this study, provides easy data compiling for HSPF by facilitating the setup and simulation process. It also assists the spatial interpretation of point and non-point pollutant information and thiessen rainfall creation and pre and post processing for large environmental data An integration methodology of GIS and water quality model for the preprocessing geo-morphologic data was designed by coupling the data model KBASIN-HSPF interface comprises four modules: registration and modification of basic environmental information, watershed delineation generator, watershed geo-morphologic index calculator and model input file processor. KBASIN-HSPF was applied to simulate the water quality impact by variation of subbasin pollution discharge structure.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.5 s.39
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• pp.35-43
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• 2004

Small-scale models have been frequently used for seismic performance tests because of limited testing facilities and economic reasons. However, there are not enough studies on similitude law for analogizing prototype structures accurately with small-scale models, although conventional similitude law based on geometry is not well consistent in the inelastic seismic behavior. When fabricating prototype and small-scale model of reinforced concrete structures by using the same material, added mass is demanded from a volumetric change and scale factor could be limited due to aggregate size. Therefore, it is desirable that different material is used for small-scale models. Thus, a modified similitude law could be derived depending on geometric scale factor, equivalent modulus ratio and ultimate strain ratio. In this study, compressive strength tests are conducted to analyze the equivalent modulus ratio of micro-concrete to normal-concrete. Then, equivalent modulus ratios are divided into multi-phase damage levels, which are basically dependent on ultimate strain level. Therefore, an algorithm adaptable to the pseudodynamic test, considering equivalent multi-phase similitude law based on seismic damage levels, is developed. Test specimens, consisted of prototype structures and 1/5 scaled models as a reinforced concrete column, were designed and fabricated based on the equivalent modulus ratios already defined. Finally quasistatic and pseudodynamic tests on the specimens are carried out using constant and variable modulus ratios, and correlation between prototype and small-scale model is investigated based on their test results. It is confirmed that the equivalent multi-phase similitude law proposed in this study could be suitable for seismic performance tests on small-scale models.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.21-26
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• 2011

Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.