• Journal of Korean society of Dental Hygiene
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• v.24 no.1
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• pp.9-16
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• 2024

Objectives: The demand for dental care is expected to increase as the population ages. This study aimed to predict the utilization of dental implant care following the expansion of national health insurance benefits for dental implants. Methods: Multiple linear regression analysis was performed on HIRA big data open portal data and DNN-based artificial intelligence models to forecast the utilization of dental care in relation to the national health insurance coverage for dental implants. Results: National health insurance coverage of dental implants was found to be associated with the number of patients using dental implant services and demonstrated a statistical significance. The dental implant services utilization increased with the increased dental implant health insurance benefits for the elderly population, increased mean by region, increased number of dental institutions by region, and increased health insurance coverage rate for dental implants. However, the dental implant services utilization decreased with the increased number of older people living alone and increased size of dental institutions. Conclusions: With the expansion of the national health insurance coverage for dental implants, it is predicted that the utilization of dental implant medical services will increase in the future.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.745-751
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• 2011

This study proposes finite element modeling of dislocation punching at cooling after consolidation in order to calculate the strength of particle-reinforced aluminum composites. The Taylor dislocation model combined with strain gradient plasticity around the reinforced particle is adopted to take into account the size-dependency of different volume fractions of the particle. The strain gradients were obtained from the equivalent plastic strain calculated during the cooling of the spherical unit cell, when the dislocation punching due to CTE (Coefficient of Thermal Expansion) mismatch is activated. The enhanced yield stress was observed by including the strain gradients, in an average sense, over the punched zone. The tensile strength of the SiCp/Al 356-T6 composite was predicted through the finite element analysis of an axisymmetric unit cell for various sizes and volume fractions of the particle. The predicted strengths were found to be in good agreement with the experimental data. Further, the particle-size dependency was clearly established.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.474-481
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• 2017

When designing photovoltaic power plants in Korea, the prediction of photovoltaic power generation at the design phase is carried out using PVSyst, PVWatts (Overseas power generation prediction software), and overseas weather data even if the test site is a domestic site. In this paper, for a comparative study to predict power generation using weather information, domestic photovoltaic power plants in two regions were selected as target sites. PVsyst, which is a commercial power generation forecasting program, was used to compare the accuracy between the predicted value of power generation (obtained using overseas weather information (Meteonorm 7.1, NASA-SSE)) and the predicted value of power generation obtained by the Korea Meteorological Administration (KMA). In addition, we have studied ways to improve the prediction of power generation through comparative analysis of meteorological data. Finally, we proposed a revised solar power generation prediction model that considers climatic factors by considering the actual generation amount.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.35-40
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• 2022

In this paper, we propose a method of constructing clinical knowledge with clinical concept relations and predicting diseases based on a deep learning model to support clinical decision-making. Clinical terms in UMLS(Unified Medical Language System) and cancer-related medical knowledge are classified into five categories. Medical related documents in Wikipedia are extracted using the classified clinical terms. Clinical concept relations are established by matching the extracted medical related documents with the extracted clinical terms. After deep learning using clinical knowledge, a disease is predicted based on medical terms expressed in a query. Thereafter, medical terms related to the predicted disease are selected as an extended query for clinical document retrieval. To validate our method, we have experimented on TREC Clinical Decision Support (CDS) and TREC Precision Medicine (PM) test collections.

• Journal of Ecology and Environment
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• v.48 no.1
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• pp.96-109
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• 2024

Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled. Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041-2060 and 2081-2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041-2060 and 2081-2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

• Journal of the Korean Geosynthetics Society
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• v.12 no.4
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• pp.87-98
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• 2013

This study was performed a series of the isotropic compression-expansion tests and the drained triaxial tests with various the relative densities 40%, 60%, 80% and 95% for bottom ash. Using the tests results the characteristic of the parameters of Lade's single hardening constitutive model were investigated. The soil parameters Kur and n representing elastic behavior are not much affected by the change of the relative density. The other parameters such as failure criterion(m, ${\eta}_1$), hardening function(c, p) and plastic potential(${\psi}_2$, ${\mu}$) are in a positive linear relationship with the relative density. Since the soil parameters h and ${\alpha}$ representing yield function do not change much to the change of relative density and also closely related to failure criterion, they can be replaced by failure criterion ${\eta}_1$. We also observed that predicted values from the Lade's single hardening constitutive model were well consistent with the observed data.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.433-443
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• 2009

For the better understanding of the temporal characteristics of soil water, this study is to suggest a stochastic soil water model and to apply it for impact assessment of climate change. The loss function is divided into 3 stages for more specified comprehension of the probabilistic behavior of soil water, and especially, the soil water model considering the stochastic characteristics of precipitation is developed in order to consider the variation of climatic factors. The simulation result of soil water model confirms that the proposed soil water model can re-generate the observation properly, and it also proves that the soil water behaves with consistent cycle based on the precipitation pattern. Moreover, with the simulation results with a climate change scenario, it can be predicted that the future soil water will have higher variations than present soil water.

• Journal of the Korean Geosynthetics Society
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• v.10 no.4
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• pp.29-36
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• 2011

In this study, a series of the isotropic compression-expansion tests and the drained triaxial tests were performed on Pocheon granite soil with various the dry densities of $16.67kN/m^3$, $17.26kN/m^3$ and $17.65kN/m^3$. Using the tests results the characteristic of the parameters of Lade's single hardening constitutive model were investigated. The soil parameters such as kur and n related to elastic behavior, m and ${\eta}_1$ related to failure criterion, c and p related to hardening function and ${\psi}_2$ and ${\mu}$ related to plastic potential show in a positive linear relationship with the dry density. Since the soil parameters h and representing yield function do not change much to relative density and also are closely related to failure criterion, they can be replaced by failure criterion. We also observed that predicted values from the Lade's single hardening constitutive model were well consistent with the observed data.

• Nuclear Engineering and Technology
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• v.41 no.7
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• pp.875-884
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• 2009

We present three nuclear/hydrogen-related R&D activities being performed at KAIST: air-ingressed LOCA analysis code development, gas turbine analysis tool development, and hydrogen-production system analysis model development. The ICE numerical technique widely used for the safety analysis of water-reactors is successfully implemented into GAMMA, with which we solve the basic equations for continuity, momentum conservation, energy conservation of the gas mixture, and mass conservation of 6 species (He, N2, O2, CO, CO2, and H2O). GAMMA has been extensively validated using data from 14 test facilities. We developed a tool to predict the characteristics of HTGR helium turbines based on the throughflow calculation with a Newton-Raphson method that overcomes the weakness of the conventional method based on the successive iteration scheme. It is found that the current method reaches stable and quick convergence even under the off-normal condition with the same degree of accuracy. The dynamic equations for the distillation column of HI process are described with 4 material components involved in the HI process: H2O, HI, I2, H2. For the HI process we improved the Neumann model based on the NRTL (Non-Random Two-Liquid) model. The improved Neumann model predicted a total pressure with 8.6% maximum relative deviation from the data and 2.5% mean relative deviation, and liquid-liquid-separation with 9.52% maximum relative deviation from the data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1C
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• pp.11-17
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• 2011

This study was performed a series of the isotropic compression-expansion tests and the drained triaxial tests with various the relative densities 25%, 50%, 80% and 100% for Baekma river sand. Using the tests results the characteristic of the parameters of Lade's single hardening constitutive model were investigated. The soil parameters Kur and n representing elastic behavior are not much affected by the change of the relative density. The other parameters such as failure criterion (m, ${\eta}_1$), hardening function (C, p) and plastic potential (${\Psi}_2$, ${\mu}$) are in a positive linear relationship with the relative density. Since the soil parameters h and $\alpha$ representing yield function do not change much to the change of relative density and also closely related to failure criterion, they can be replaced by failure criterion ${\eta}_1$. We also observed that predicted values from the Lade's single hardening constitutive model were well consistent with the observed data.