• Journal of the Korean Society of Radiology
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• v.7 no.2
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• pp.157-163
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• 2013

This study was to analyze quantitatively movement of planning target volume (PTV) and change of PTV volume through movement of diaphragm according to breathing phase. The purpose of present study was to investigate optimized respiration phase for radiation therapy of lung cancer. Simulated breathing training was performed in order to minimize systematic errors which is caused non-specific or irregular breathing. We performed 4-dimensional computed tomography (4DCTi) in accordance with each respiratory phase in the normalized respiratory gated radiation therapy procedures, then not only defined PTVi in 0 ~ 90%, 30 ~ 70% and 40 ~ 60% in the reconstructed 4DCTi images but analyzed quantitatively movement and changes of volume in PTVi. As a results, average respiratory cycle was $3.4{\pm}0.5$ seconds by simulated breathing training. R2-value which is expressed as concordance between clinically induced expected value and actual measured value, was almost 1. There was a statistically significant. And also movement of PTVi according to each respiration phase 0 ~ 90%, 30 ~ 70% and 40 ~ 60% were $13.4{\pm}6.4mm$, $6.1{\pm}2.9mm$ and $4.0{\pm}2.1mm$ respectively. Change of volume in PTVi of respiration phase 30 ~ 70% was decreased by $32.6{\pm}8.7%$ and 40 ~ 60% was decreased by $41.6{\pm}6.2%$. In conclusion, PTVi movement and volume change was reduced, when we apply a short breathing phase (40 ~ 60%: 30% duty cycle) range. Furthermore, PTVi margin considered respiration was not only within 4mm but able to get uniformity of dose.

• Restorative Dentistry and Endodontics
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• v.31 no.6
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• pp.477-484
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• 2006

The purposes of this study were to compare the apical terminus width of simulated curved root canal prepared with three NiTi file systems used by undergraduates for evaluation the effects of flute angle and pitch or radial land on reducing screw-in effect and to determine more safe NiTi file system for inexperienced operators. Fifty inexperienced undergraduate students prepared 150 simulated curved root canals in resin blocks with three NiTi file systems ; ProFile$^{(R)}$, Hero Shaper$^{(R)}$, K3$^{TM}$. The electric motor set at a speed of 300 rpm and torque of 30 in a 16 : 1 reduction handpiece was used. The simulated root canal was prepared to ISO #25 sizes with each file system. The scanned images of pre- and post-instrumented canal of resin block were superimposed. To evaluate the screw-in effect of three NiTi file systems, apical terminus width of root canal was measured from superimposed images and statistical analysis was performed. There were significant differences in three NiTi flle systems. ProFile$^{(R)}$ had significantly smaller width than Hero Shaper$^{(R)}$ and K3$^{TM}$"" (P < 0.05), but no significant difference was observed between K3$^{TM}$ and Hero Shaper$^{(R)}$. Under the condition of this study, active file system (Hero SHaper$^{(R)}$, K3$^{TM}$) with variable pitch and helical angle had more screw-in effect than passive file system (ProFile$^{(R)}$) with constant pitch and helical angle. It seems that the radial lands play more important role in reducing screw-in effect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5684-5691
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• 2011

The purpose of this study is to examine effects of constraint-induced movement therapy(CIMT) and/or cognitive-perceptual training(CPT) on the change of hand function in cerebrovascular accident(CVA) patients and to evaluate the change in the amount and quality of use of the affected upper extremity in performing daily living tasks. The subjects of study were 10 patients who had been under rehabilitation for more than three months after CVA onset. They were all determined as mild cognition impairment according to NCSE or MVPT test. For CIMT group, to restrict the movement of the unaffected hand the subjects had been worn modified resting arm-splint in daytime for 4 weeks. For CIMT+CPT group, the subjects were performed CPT with CIMT and control group had been under conventional occupational therapy for the same period. CIMT+CPT group showed significant improvement in simulated feeding, lifting large light objects, and lifting large heavy objects of Jebsen-Taylor Hand Function Test. CIMT group also showed significant improvement compared with control group. The mean changes of the amount of use(AOU) of the affected arm had a statistically significant difference among groups (p<.05). While CIMT+CPT group had the biggest change in the quality of movement(QOM) of upper extremity of the affected side, CTL group showed the smallest change. Both CIMT and CIMT+CPT groups had statistically significant difference in the change in the quality of movement in upper extremity of affected side with CTL group(p<.05), but there was not significant difference between CIMT group and CIMT+CPT group. CIMT performed to the patients of stroke, with mild impairment in cognitive perceptual abilities showed the improvement in hand movement and AOU and QOM of upper extremity in the affected side and the combination of CIMT with CPT showed synergic effects.

• Journal of Korean Society of Steel Construction
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• v.17 no.1 s.74
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• pp.1-11
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• 2005

A bi-level damage detection algorithm that utilizes the dynamic responses of the structure as input and neural network (NN) as pattern classifier is presented. Signal anomaly index (SAI) is proposed to express the amount of changes in the shape of frequency response functions (FRF) or strain frequency response function (SFRF). SAI is calculated using the acceleration and dynamic strain responses acquired from intact and damaged states of the structure. In a bi-level damage identification algorithm, the presence of damage is first identified from the magnitude of the SAI value, then the location of the damage is identified using the pattern recognition capability of NN. The proposed algorithm is applied to an experimental model bridge to demonstrate the feasibility of the algorithm. Numerically simulated signals are used for training the NN, and experimentally-acquired signals are used to test the NN. The results of this example application suggest that the SAI-based pattern recognition approach may be applied to the structural health monitoring system for a real bridge.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.97-107
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• 2011

For the purpose of enhancing usability of NWP (Numerical Weather Prediction), the quantitative precipitation prediction scheme was suggested. In this research, precipitation by leading time was predicted using 3-hour rainfall accumulation by meso-scale numerical weather model and AWS (Automatic Weather Station), precipitation water and relative humidity observed by atmospheric sounding station, probability of rainfall occurrence by leading time in June and July, 2001 and August, 2002. Considering the nonlinear process of ranfall producing mechanism, the ANN (Artificial Neural Network) that is useful in nonlinear fitting between rainfall and the other atmospheric variables. The feedforward multi-layer perceptron was used for neural network structure, and the nonlinear bipolaractivation function was used for neural network training for converting negative rainfall into no rain value. The ANN simulated rainfall was validated by leading time using Nash-Sutcliffe Coefficient of Efficiency (COE) and Coefficient of Correlation (CORR). As a result, the 3 hour rainfall accumulation basis shows that the COE of the areal mean of the Korean peninsula was improved from -0.04 to 0.31 for the 12 hr leading time, -0.04 to 0.38 for the 24 hr leading time, -0.03 to 0.33 for the 36 hr leading time, and -0.05 to 0.27 for the 48 hr leading time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.211-219
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• 2016

The current study was conducted to make pre-post comparisons of education done for 119 emergency medical technicians (EMT) on the patient assessment performance. The data are expected to offer applicable training methods and educational resources for emergency medical services. Twenty six EMT from four cities and provinces participated in the study, which was carried out from 14 to 17 December, 2015. The technicians performed a patient assessment and marked reports on simulated patients. In the course of the assessment, a pre-post evaluation of education was done using a checklist regarding the respective symptoms, such as headache, chest pain, and dyspnea. The median value (quartile value) was used as the descriptive analysis. While patient assessment scores marked 66 points (54.00-80.25) out of 100 (p<0.01) before education, there was a significant increase in the after-education scores, which reached 88.5 points (80.00-93.00). The patient assessment performances revealed a significant increase (p<.0.01) in 5 chest pain, 7 headache, and 9 dyspnea items after education. Similarly, there was an increase in wanting to meet the EMT again scale in regards to categories involved in developing positive relations with patients. Moreover, the adequacy in the patient condition reports all marked a significant increase (p<0.01) in assessment categories. The present study shows that education based on simulation practices are necessary for improvements in patient assessment performance of 119 EMT. Therefore, practical and systematic patient assessment educations may serve as a prerequisite. Further opportunities should be provided for the EMT consistently.

• Economic and Environmental Geology
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• v.53 no.3
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• pp.245-258
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• 2020

In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

• Journal of Biomedical Engineering Research
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• v.35 no.3
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• pp.50-54
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• 2014

It is being tried to control robot arm using brain signal in the field of brain-machine interface (BMI). This study is focused on applying guidance laws for efficient robot arm control using 3D coordinates obtained from Magnetoencephalography (MEG) signal which represents movement of upper limb. The 3D coordinates obtained from brain signal is inappropriate to be used directly because of the spatial difference between human upper limb and robot arm's end-effector. The spatial difference makes the robot arm to be controlled from a third-person point of view with assist of visual feedback. To resolve this inconvenience, guidance laws which are frequently used for tactical ballistic missile are applied. It could be applied for the users to control robot arm from a first-person point of view which is expected to be more comfortable. The algorithm which enables robot arm to trace MEG signal is provided in this study. The algorithm is simulated and applied to 6-DOF robot arm for verification. The result was satisfactory and demonstrated a possibility in decreasing the training period and increasing the rate of success for certain tasks such as gripping object.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.11-20
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• 2020

As the manufacturing environment becomes more complex, traditional simulation models alone are having a lot of difficulties in reflecting real-time manufacturing situations. Although the Digital Twin concept is actively discussed as an alternative to overcome theses issues, many studies are being carried out only in the product design phase. This research presents a Digital Twin-based manufacturing environment framework for applying the Digital Twin concept to the manufacturing process. Twin model that is operated in virtual space, physical system and databases describing the actual manufacturing environment, are proposed as detailed components that make up the framework. To check the applicability of proposed framework, a simple Digital Twin-based manufacturing system was simulated in a conveyor system using Arena software and Excel VBA. Experiment results have shown that the twin model is transmitted real time data from the physical system via DB and were operating in the same time unit. The Excel VBA fitted parameters defined by cycle time based on historical data that real-time and training data are being accumulated together. This study proposes operating method of digital twin model through the simple experiment examples. The results lead to the applicability of Digital twin model.

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.1-9
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• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.