The dose distributions of designed Ir-192 micro-source were investigated by dose computations which were accomplished by employing shape of encapsule material and thickness of the source for self-absorption. The computation dose derived from air-kerma rate (S$_{k}$ ) and dose rate constant (Λ) includes the anisotropy of dose distribution around the source. We got the dose rate constants in a water medium is 1.154 cGy h$^{-1}$ U$^{-1}$ . The size of the source was 0.5 mm in diameter and 3.5 mm in length and it was encapsuled in 1.1 mm$\Phi$${\times}$5.5 mm of stainless steel sealed with 0.3 mm of filter thickness. The tissue dose of reference point at 1.0 cm radial distance of the source axis was delivered 1.154 Uh$^{-1}$ (1.3167${\times}$10$^{-3}$ cGy/mCi-sec) from the S$_{k}$ 4.108U/mCi of Ir-192 source. The filtration effect contributed to air-kerma strength as exponential filtering effect of 86.2% in total attenuation, but self-absorption was 88.4% from radial dose distributions. In particular, the dose attenuations showed a rapid anisotropic distributions as 56% of reference dose along to $\pm$10 degrees from the tip of source axis and 50% for of that to source-cable direction. We persist in use the large diameter of applicator will avoid the dose anisotropy by the filtered attenuation effects along the axis of Ir-192 micro-source.
Kim, Dong-Seok;Kim, Seong-Hwan;Shim, Dong-Oh;Yoo, Hee-Jae
The Korean Journal of Nuclear Medicine Technology
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v.15
no.1
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pp.17-24
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2011
Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.
Kim, kwang-beak;Kang, hyo-joo;Kim, mi-jeong;Kim, gwang-ha
Proceedings of the Korea Contents Association Conference
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2009.05a
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pp.390-397
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2009
Endoscopic ultrasonography is a medical procedure in endoscopy combined with ultrasound to obtain images of the internal organs. It is useful to have a predictive pathological manifestation since a doctor can observe tumors under mucosa. However, it is often subjective to judge the degree of malignant degeneration of tumors. Thus, in this paper, we propose a feature analysis procedure to make the pathological manifestation more objective so as to improve the accuracy and recall of the diagnosis. In the process, we extract the ultrasound region from the image obtained by endoscopic ultrasonography. It is necessary to standardize the intensity of this region with the intensity of water region as a base since frequently found small intensity difference is only to be inefficient in the analysis. Then, we analyze the spot region with high echo and calcium deposited region by applying LVQ algorithm and bit plane partitioning procedure to tumor regions selected by medical expert. For detailed analysis, features such as intensity value, intensity information included within two random points chosen by medical expert in tumor region, and the slant of outline of tumor region in order to decide the degree of malignant degeneration. Such procedure is proven to be helpful for medical experts in tumor analysis.
The planetary exploration rover executes various missions after moving to the target point in an unknown environment in the shortest distance. Such missions include the researches for geological and climatic conditions as well as the existence of water or living creatures. If there is any obstacle on the way, it is detected by such sensors as ultrasonic sensor, infrared light sensor, stereo vision, and laser ranger finder. After the obtained data is transferred to the main controller of the rover, decisions can be made to either overcome or avoid the obstacle on the way based on the operating algorithm of the rover. All the planetary exploration rovers which have been developed until now receive the information of the height or width of the obstacle from such sensors before analyzing it in order to find out whether it is possible to overcome the obstacle or not. If it is decided to be better to overcome the obstacle in terms of the operating safety and the electric consumption of the rover, it is generally made to overcome it. Therefore, for the purpose of carrying out the planetary exploration task, it is necessary to design the proper suspension system of the rover which enables it to safely overcome any obstacle on the way on the surface in any unknown environment. This study focuses on the design of the new double 4-bar linkage type of suspension system applied to the Korea Aerospace Research Institute rover (a tentatively name) that is currently in the process of development by our institute in order to develop the planetary exploration rover which absolutely requires the capacity of overcoming any obstacle. Throughout this study, the negative moment which harms the capacity of the rover for overcoming an obstacle was induced through the dynamical modeling process for the rocker-bogie applied to the Mars exploration rover of the US and the improved version of rocker-bogie as well as the suggested double 4-bar linkage type of suspension system. Also, based on the height of the obstacle, a simulation was carried out for the negative moment of the suspension system before the excellence of the suspension system suggested through the comparison of responding characteristics was proved.
Kim, Junhwan;Lee, Chung Kuen;Kim, Hyunae;Lee, Byun Woo;Kim, Kwang Soo
Korean Journal of Agricultural and Forest Meteorology
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v.17
no.1
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pp.1-14
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2015
Climate change caused by elevated greenhouse gases would affect crop production through different pathways in agricultural ecosystems. Because an agricultural ecosystem has complex interactions between societal and economical environment as well as organisms, climate, and soil, adaptation measures in response to climate change on a specific sector could cause undesirable impacts on other sectors inadvertently. An integrated system, which links individual models for components of agricultural ecosystems, would allow to take into account complex interactions existing in a given agricultural ecosystem under climate change and to derive proper adaptation measures in order to improve crop productivity. Most of models for agricultural ecosystems have been used in a separate sector, e.g., prediction of water resources or crop growth. Few of those models have been desiged to be connected to other models as a module of an integrated system. Threfore, it would be crucial to redesign and to refine individual models that have been used for simulation of individual sectors. To improve models for each sector in terms of accuracy and algorithm, it would also be needed to obtain crop growth data through construction of super-sites and satellite sites for long-term monitoring of agricultural ecosystems. It would be advantageous to design a model in a sector from abstraction and inheritance of a simple model, which would facilitate development of modules compatible to the integrated prediction system. Because agricultural production is influenced by social and economical sectors considerably, construction of an integreated system that simulates agricultural production as well as economical activities including trade and demand is merited for prediction of crop production under climate change.
Monte Carlo N-Particle (MCNP) modeling algorithm based on the Monte Carlo method was used to perform the simulation of neutron logging in order to increase the reliability and utilization of neutron logs applied in geological and resource engineering fields. To perform the simulation using MCNP, we used a realistic three-dimensional configuration of neutron sonde and formation. Validation of the modeling was confirmed by comparing the calibration curves of sonde manufacture with those calculated by MCNP modeling. After the validation, lithology effects, pore fluid effects, borehole diameter change, casing effect, and effects of borehole water level were investigated through modeling experiments. Numerical tests indicate that changes in neutron count ratio according to the lithology were quantitatively understood. In case of a borehole with a diameter of 3 inches, ratio of counting rates was higher than expected to be interpreted as borehole fluid has small effects on neutron logging. Effect of casing was also small in general, particular when porosity increases. Since modeling results above the groundwater level showed a tendency opposite to those below the groundwater level, neutron logs can be used to detect groundwater level. The modeling results simulated in this study for various borehole environments are expected to be used for data processing and interpretation of neutron log.
Journal of the Korean Society of Fisheries and Ocean Technology
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v.36
no.1
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pp.54-59
/
2000
This paper presents a control system that uses a fuzzy algorithm in controlling the depth of a model midwater trawl net, and experimental results carried out in the circulating water channel by using a model trawl winch system.The fuzzy controller calculates the length of the warp to be changed, based on the depth error between the desired depth and actual depth of the model trawl net and the ratio of change in the depth error. The error and the error change are calculated every sampling time. Then the control input, i.e. desirable length of the warp, is determined by inference from the linguistic control rules which an experienced captain or navigator uses in controlling the depth of the trawl winch controller and the length of the warp is changed. Two kinds of fuzzy control rules were tested, one was obtained from the actual operations used by a skilled skipper or navigator, and the other was a modified from the former by considering the hydrodynamic characteristics of the model trawl system.Two kinds of fuzzy control were tested, one was obtained fro the actual operations used by a skilled skipper or navigator, and the other was a modified from the former by considering the hydrodynamic characteristics of the model trawl system.The results of these model experiments indicate that the proposed fuzzy controllers rapidly follow the desired depth without steady-state error although the desired depth was given in one step, and show robustness properties against changes in the parameters such as the change of the towing sped. Especially, a modified rule shows smaller depth fluctuations and faster setting times than those obtained by a field oriented rule.
Journal of Korean Tunnelling and Underground Space Association
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v.24
no.2
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pp.217-230
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2022
The adequate control of TBM face pressure is of vital importance to maintain face stability by preventing face collapse and surface settlement. An EPB shield TBM excavates the ground by applying face pressure with the excavated soil in the pressure chamber. One of the challenges during the EPB shield TBM operation is the control of face pressure due to difficulty in managing the excavated soil. In this study, the face pressure of an EPB shield TBM was predicted using the geological and operational data acquired from a domestic TBM tunnel site. Four machine learning algorithms: KNN (K-Nearest Neighbors), SVM (Support Vector Machine), RF (Random Forest), and XGB (eXtreme Gradient Boosting) were applied to predict the face pressure. The model comparison results showed that the RF model yielded the lowest RMSE (Root Mean Square Error) value of 7.35 kPa. Therefore, the RF model was selected as the optimal machine learning algorithm. In addition, the feature importance of the RF model was analyzed to evaluate appropriately the influence of each feature on the face pressure. The water pressure indicated the highest influence, and the importance of the geological conditions was higher in general than that of the operation features in the considered site.
Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.
Minsang Kim;Myung-Sook Park;Jae-Hyun Ahn;Gm-Sil Kang
Korean Journal of Remote Sensing
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v.39
no.6_2
/
pp.1541-1551
/
2023
Radiometric calibration is a fundamental step in ocean color remote sensing since the step to derive solar radiance spectrum in visible to near-infrared wavelengths from the sensor-observed electromagnetic signals. Generally, satellite sensor suffers from degradation over the mission period, which results in biases/uncertainties in radiometric calibration and the final ocean products such as water-leaving radiance, chlorophyll-a concentration, and colored dissolved organic matter. Therefore, the importance of radiometric calibration for the continuity of ocean color satellites has been emphasized internationally. This study introduces an approach to improve the radiometric calibration algorithm for the visible bands of the Geostationary Ocean Color Imager-II (GOCI-II) satellite with a focus on stability. Solar Diffuser (SD) measurements were employed as an on-orbit radiometric calibration reference, to obtain the continuous monitoring of absolute gain values. Time series analysis of GOCI-II absolute gains revealed seasonal variations depending on the azimuth angle, as well as long-term trends by possible sensor degradation effects. To resolve the complexities in gain variability, an azimuth angle correction model was developed to eliminate seasonal periodicity, and a sensor degradation correction model was applied to estimate nonlinear trends in the absolute gain parameters. The results demonstrate the effects of the azimuth angle correction and sensor degradation correction model on the spectrum of Top of Atmosphere (TOA) radiance, confirming the capability for improving the long-term stability of GOCI-II data.
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