• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.632-641
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• 2023

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1153-1164
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• 2024

In recent years, unmanned ground vehicles (UGVs) have been used to search for lost or stolen radioactive sources to avoid radiation exposure for operators. To achieve autonomous localization of radioactive sources, the UGVs must have the ability to automatically determine the next radiation measurement location instead of following a predefined path. Also, the radiation field of radioactive sources has to be reconstructed or inverted utilizing discrete measurements to obtain the radiation intensity distribution in the area of interest. In this study, we propose an effective source localization framework and method, in which UGVs are able to autonomously explore in the radiation area to determine the location of radioactive sources through an iterative process: path planning, radiation field reconstruction and estimation of source location. In the search process, the next radiation measurement point of the UGVs is fully predicted by the design path planning algorithm. After obtaining the measurement points and their radiation measurements, the radiation field of radioactive sources is reconstructed by the Gaussian process regression (GPR) model based on machine learning method. Based on the reconstructed radiation field, the locations of radioactive sources can be determined by the peak analysis method. The proposed method is verified through extensive simulation experiments, and the real source localization experiment on a Cs-137 point source shows that the proposed method can accurately locate the radioactive source with an error of approximately 0.30 m. The experimental results reveal the important practicality of our proposed method for source autonomous localization tasks.

• Smart Structures and Systems
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• v.33 no.3
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• pp.189-199
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• 2024

To properly extract the strain components under varying operational conditions is very important in bridge health monitoring. The abnormal sensor readings can be correctly identified and the expected operational performance of the bridge can be better understood if each strain components can be accurately quantified. In this study, strain components under varying load conditions, i.e., temperature variation and live-load variation are evaluated based on field strain measurements collected from a real concrete box-girder bridge. Temperature-induced strain is mainly regarded as the trend variation along with the ambient temperature, thus a smoothing technique based on the wavelet packet decomposition method is proposed to estimate the temperature-induced strain. However, how to effectively extract the vehicle-induced strain is always troublesome because conventional threshold setting-based methods cease to function: if the threshold is set too large, the minor response will be ignored, and if too small, noise will be introduced. Therefore, an autoencoder framework is proposed to evaluate the vehicle-induced strain. After the elimination of temperature and vehicle-induced strain, the left of which, defined as the model error, is used to assess the operational performance of the bridge. As empirical techniques fail to detect the degraded state of the structure, a clustering technique based on Gaussian Mixture Model is employed to identify the damage occurrence and the validity is verified in a simulation study.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.750-760
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• 2011

In this study, the reproducibility of the simulated current climate by using two regional climate models, such as Seoul National University Regional Climate Model (SNURCM) and Weather Resuearch and Forecasting (WRF), is evaluated in advance to produce the standard regional climate scenario of future climate. Within the evaluation framework of a COordinated Regional climate Downscaling EXperiment (CORDEX), 28-year-long (1978-2005) regional climate simulation was conducted by using the Hadley Centre Global Environmental Model (HadGEM2-AO) global simulation data of the National Institute of Meteorological Research (NIMR) as a lateral boundary forcing. The simulated annual surface temperatures were in good agreement with the observation; the spatial correlation coefficients between each model and observation were over 0.98. The cold bias, however, were shown over the northern boundary in the both simulated results. In evaluation of the simulated precipitation, the skill was reasonable and good. The spatial correlation coefficients for the precipitation over the land area were 0.85 and 0.79 in SNURCM and WRF, respectively. It is noted that two regional climate models (RCMs) have different characteristics for the distribution of precipitation over equatorial and midlatitude areas. SNURCM shows better distribution of the simulated precipitation associated with the East Asia summer monsoon in the mid-latitude areas, but WRF shows better in the equatorial areas in comparison to each other. The simulated precipitation is overestimated in summer season (JJA) rather than in spring season (MAM), whereas the spatial distribution of the precipitation in spring season corresponds to the observation better than in summer season. Also the RCMs were capable of reproducing the annual variability of the maximum amount and its timing in July, in which the skills over the inland area were in better agreement with the observation than over the maritime area. The simulated regional climates, however, have the limitation to represent the number of days for extremely hot temperature and heavy rainfall over South Korea.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.73-81
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• 2018

In this paper, we present a motion-driven rowing simulation framework that allows multiple players to row a boat together by their harmonized movements. In the actual rowing game, it is crucial for the players to synchronize their rowing with respect to time and pose so as to accelerate the boat. Inspired by this interesting feature, we measure the motion similarity among multiple players in real time while they are doing rowing motions and use it to control the velocity of the boat in a virtual environment. We also employ game components such as catching an item which can accelerate or decelerate the boat depending on its type for a moment once it has been obtained by synchronized catching behaviors of the players. By these components, the players can be encouraged to more actively participate in the training for a good teamwork to produce harmonized rowing movements Our methods for the motion recognition for rowing and item catch require the tracking data only for the head and the both hands and are fast enough to facilitate the real-time performance. In order to enhance immersiveness of the virtual environment, we project the rowing simulation result on a wide curved screen.

• Journal of Korean Society of Rural Planning
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• v.21 no.2
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• pp.33-49
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• 2015

The objective of this study was to predict land use change based on the land use change scenarios for the Hwangguji river watershed, South Korea. The land use change scenario was derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. The CLUE (conversion of land use and its effects) model was used to simulate the land use change. The CLUE is the modeling framework to simulate land use change considering empirically quantified relations between land use types and socioeconomic and biophysical driving factors through dynamical modeling. The Hwangguji river watershed, South Korea was selected as study area. Future land use changes in 2040, 2070, and 2100 were analyzed relative to baseline (2010) under the RCP4.5 and 8.5 scenarios. Binary logistic regressions were carried out to identify the relation between land uses and its driving factors. CN (Curve number) and impervious area based on the RCP4.5 and 8.5 scenarios were calculated and analyzed using the results of future land use changes. The land use change simulation of the RCP4.5 scenario resulted that the area of urban was forecast to increase by 12% and the area of forest was estimated to decrease by 16% between 2010 and 2100. The land use change simulation of the RCP8.5 scenario resulted that the area of urban was forecast to increase by 16% and the area of forest was estimated to decrease by 18% between 2010 and 2100. The values of Kappa and multiple resolution procedure were calculated as 0.61 and 74.03%. CN (III) and impervious area were increased by 0-1 and 0-8% from 2010 to 2100, respectively. The study findings may provide a useful tool for estimating the future land use change, which is an important factor for the future extreme flood.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.141-154
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• 2020

The accidents of toxic chemical spill into rivers are increasing in recent years due to expansion of heavy industries in Korea. In order to respond to the chemical spills, accident response systems have been established for both main rivers and tributary rivers. However, since these accident response system adopted the water quality models imported from the foreign countries, it is difficult to acquire the model parameters and to calibrate and validate the water quality models. Therefore, this study developed a depth-averaged two-dimensional river water quality model to analyze the behavior of hazardous chemicals in rivers and proposed an efficient simulation execution framework by identifying the significant reaction mechanisms considering the characteristics of the toxic chemicals. The depth-averaged two-dimensional river water quality model CTM-2D was upgraded by adding reaction terms representing mechanisms of the adsorption, desorption, and volatilization of toxic chemicals. In order to verify the model, the analytical solution was compared with the numerical solution, and results showed that the error was less than 0.1%. In addition, the model was applied to a virtual scenario which is a water pollution accident at the confluence of the Nakdong River - Kumho River, and model results showed that an efficient simulation could be carried out by activating only significant reactions which were assessed by the sensitivity analysis.

• Journal of Korean Society on Water Environment
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• v.31 no.2
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• pp.181-195
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• 2015

Algal blooms in lakes are one of major environmental issues in Korea. A three-dimensional, hydrodynamic and water quality model was developed and tested in Lake Euiam to assess the performance and limitations of numerical modeling with multiple algal groups using field data commonly collected for algal management. In this study, EFDC was adopted as the basic model framework. Simulated vertical profiles of water temperature, dissolved oxygen and nutrients monitored at five water quality monitoring stations from March to October 2013, which are closely related to algal dynamics simulation, showed good agreement with those of observed data. The overall spatio-temporal variations of three algal groups were reasonably simulated against the chlorophyll-a levels of those estimated from the limited monitoring data (chlorophyll-a level and cell numbers of algal species) with the RMSEs ranging from 2.6 to $17.5mg/m^3$. Also, note that $PO_4-P$ level in the water column was a key limiting factor controlling the growth of three algal groups during most of simulation period. However, the algal modeling results were not fully attainable to the levels of observation during short periods of time showing abrupt increase in algae throughout the lake. In particular, the green algae/cyanobacteria and diatom simulations were underestimated in late June to early July and early October, respectively. The results shows that better understanding of internal algal processes, neglected in most algal modeling studies, is necessary to predict the sudden algal blooms more accurately because the concentrations of external $PO_4-P$ and specific algal groups originated from the tributaries (mainly, dam water releases) during the periods were too low to fully capture the sharp rise of internal algal levels. In this respect, this study suggests that future modeling efforts should be focused on the quantification of internal cycling processes including vertical movement of algal species with respect to changes in environmental conditions to enhance the modeling performance on complex algal dynamics.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1187-1198
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• 2008

Many reservoirs in Korea and their downstream environments are under increased pressure for water utilization and ecosystem management from longer discharge of turbid flood runoff compared to a natural river system. Turbidity($C_T$) is an indirect measurement of water 'cloudiness' and has been widely used as an important indicator of water quality and environmental "health". However, $C_T$ modeling studies have been rare due to lack of experimental data that are necessary for model validation. The objective of this study is to validate a coupled three-dimensional(3D) hydrodynamic and particle dynamics model (ELCOM-CAEDYM) for the simulation of turbid density flows in stratified Daecheong Reservoir using extensive field data. Three different groups of suspended solids (SS) classified by the particle size were used as model state variables, and their site-specific SS-$C_T$ relationships were used for the conversion between field measurements ($C_T$) and state variables (SS). The simulation results were validated by comparing vertical profiles of temperature and turbidity measured at monitoring stations of Haenam(R3) and Dam(R4) in 2004. The model showed good performance in reproducing the reservoir thermal structure and propagation of stream density flow, and the magnitude and distribution of turbidity in the reservoir were consistent with the field data. The 3D model and turbidity modeling framework suggested in this study can be used as a supportive tool for the best management of turbidity flow in other reservoirs that have similar turbidity problems.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.216-227
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• 2004

A new cavitating model by using bubble size distribution based on bubbles-mass has been proposed. Both liquid and vapor phases are treated with Eulerian framework as a mixture containing minute cavitating bubbles. In addition vapor phase consists of various sizes of vapor bubbles, which are distributed to classes based on their mass. The bubble number-density for each class was solved by considering the change of the bubble-mass due to phase change as well as generation of new bubbles due to heterogeneous nucleation. In this method, the bubble-mass is treated as an independent variable, and the other dependent variables are solved in spatial coordinates and bubble-mass coordinate. Firstly, we employed this method to calculate bubble nucleation and growth in stationary super-heated liquid nitrogen, and bubble collapse in stationary sub-cooled one. In the case of bubble growth in super-heated liquid, bubble number-density of the smallest class based on its mass is increased due to the nucleation. These new bubbles grow with time, and the bubbles shift to larger class. Therefore void fraction of each class is increased due to the growth in the whole class. On the other hand, in the case of bubble collapse in sub-cooled liquid, the existing bubbles are contracted, and then they shift to smaller class. It finally becomes extinct at the smallest one. Secondly, the present method is applied to a cavitating flow around NACA00l5 foil. Liquid nitrogen and liquid oxygen are employed as working fluids. Cavitation number, $\sigma$, is fixed at 0.15, inlet velocities are changed at 5, 10, 20 and 50m/s. Inlet temperatures are 90K in case of liquid nitrogen, and 90K and 1l0K in case of liquid oxygen. 110K of oxygen is corresponding to the 90K of nitrogen because of the same relative temperature to the critical one, $T_{r}$=$T/T_c^{+}$. Cavitating flow around the NACA0015 foils was properly analyzed by using bubble size distribution. Finally, the method is applied to a cavitating flow in an inducer of the LE-7A hydrogen turbo-pump. This inducer has 3 spiral foils. However, for simplicity, 2D calculation was carried out in an unrolled channel at 0.9R cross-section. The channel moves against the fluid at a peripheral velocity corresponding to the inducer revolutions. Total inlet pressure, $Pt_{in}$, is set at l00KPa, because cavitation is not generated at a design point, $Pt_{in}$=260KPa. The bubbles occur upstream of the foils and collapse between them. Cavitating flow in the inducer was successfully predicted by using the bubble size distribution.