Biao Zhang;Jinjia Cao;Shuang Lin;Xiaomeng Li;Yulong Zhang;Xiaochang Zheng;Wei Chen;Yingming Song
Nuclear Engineering and Technology
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v.56
no.1
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pp.160-166
/
2024
The inversion of radiation field distribution is of great significance in the decommissioning sites of nuclear facilities. However, the radiation fields often contain multiple mixtures of radionuclides, making the inversion extremely difficult and posing a huge challenge. Many radiation field reconstruction methods, such as Kriging algorithm and neural network, can not solve this problem perfectly. To address this issue, this paper proposes an optimized inverse distance weighted (IDW) interpolation algorithm for reconstructing the gamma radiation field. The algorithm corrects the difference between the experimental and simulated scenarios, and the data is preprocessed with normalization to improve accuracy. The experiment involves setting up gamma radiation fields of three Co-60 radioactive sources and verifying them by using the optimized IDW algorithm. The results show that the mean absolute percentage error (MAPE) of the reconstruction result obtained by using the optimized IDW algorithm is 16.0%, which is significantly better than the results obtained by using the Kriging method. Importantly, the optimized IDW algorithm is suitable for radiation scenarios with multiple radioactive sources, providing an effective method for obtaining radiation field distribution in nuclear facility decommissioning engineering.
In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R2) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.
Laura C. Zambrano-Jerez;Karen D. Diaz-Santamaria;Maria A. Rodriguez-Santos;Diego F. Alarcon-Ariza;Genny L. Melendez-Florez;Monica A. Ramirez-Blanco
Archives of Plastic Surgery
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v.50
no.6
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pp.627-634
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2023
In recent decades, a number of simulation models for microsurgical training have been published. The human placenta has received extensive validation in microneurosurgery and is a useful instrument to facilitate learning in microvascular repair techniques as an alternative to using live animals. This study uses a straightforward, step-by-step procedure for instructing the creation of simulators with dynamic flow to characterize the placental vascular tree and assess its relevance for plastic surgery departments. Measurements of the placental vasculature and morphological characterization of 18 placentas were made. After the model was used in a basic microsurgery training laboratory session, a survey was given to nine plastic surgery residents, two microsurgeons, and one hand surgeon. In all divisions, venous diameters were larger than arterial diameters, with minimum diameters of 0.8 and 0.6 mm, respectively. The majority of the participants considered that the model faithfully reproduces a real microsurgical scenario; the consistency of the vessels and their dissection are similar in in vivo tissue. Furthermore, all the participants considered that this model could improve their surgical technique and would propose it for microsurgical training. As some of the model's disadvantages, an abundantly thick adventitia, a thin tunica media, and higher adherence to the underlying tissue were identified. The color-perfused placenta is an excellent tool for microsurgical training in plastic surgery. It can faithfully reproduce a microsurgical scenario, offering an abundance of vasculature with varying sizes similar to tissue in vivo, enhancing technical proficiency, and lowering patient error.
Anemometer is a meteorological instrument that measures wind direction and wind speed in real time, and is mounted to the cranes that are used at ports, shipbuilding yards, off-shore structure, or construction sites that are influenced by wind, and it is used in conjunction with the safety system. Load cell-type anemometer measures the wind direction through the ratio of load between 4 positions by mounting the thin plate to 4 load cells, and measures wind velocity through the summation of loads. According to previous research, the load ratio between two adjacent windswept with respect to the wind direction has unstable value due to vortex around windswept. This causes the result that increases an error on the wind direction. In this study we compared and analyzed the difference between the load ratio with respect to three type windswept shapes in order to suggest the proper windswept shape to reduce this error. The computational fluid flow analysis is carried out with ANSYS CFX to analyze the load ratio between three windswept shapes. Wind direction was adopted as the design variable, and selected 9 wind direction conditions from $0^{\circ}{\sim}90^{\circ}$ with $11.25^{\circ}$ interval for computational fluid flow analysis.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.2
no.2
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pp.3-8
/
2009
The traction system has been mainly used for rehabilitation and correction of patients with spine or gait diseases in orthopedics or at home. Some problems could occur in human body when patients forced their training using the traction system. So it needs to measure a traction force and control the training time. However, most of products on market have no sensor measuring traction force. Thus we designed and made a sensor detecting traction force using strain gauge, amplifier for transition to output signal and experiment devices for performance test. We carried out experiment of a sensor detecting a traction force and measured electric responses of it with respect to traction loads. Maximum error was within about 1% for experiments in static condition and the average error was about 0.7% for experiments in dynamic condition. We concluded that it is possible to use the developed sensor for measurement of traction force since the maximum output variation of a sensor detecting a traction force was about 0.3% in $0^{\circ}C-60^{\circ}C$ temperature condition.
Kim Yong-Je;Cho Soo-Young;Yoon Yoon-Yeol;Lee Kil-Yong
Journal of Soil and Groundwater Environment
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v.11
no.5
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pp.59-66
/
2006
Optimal method of radon analysis in groundwater was studied using ultra low-level liquid scintillation counter (ULLLSC) which is well known as an analytical instrument for analyzing the alpha and beta radionuclides in environmental materials. Optimization of pulse shape analyzer (PSA) in operating the LSC was performed with $^{241}Am\;and\;^{90}Sr/^{90}Y$ as well as $^{226}Ra$ Also, the chemical quenching of scintillation generation and the color quenching of the generated photon to photomultiplier tubes (PMT) were determined their effects not only to decrease the analytical efficiency but also to change the optimal PSA level and background due to high ion contents of groundwaters. The optimal PSA level was shown in the range of 90 to 110 with less than 5% error. The effects of high ion contents in groundwater for the analytical efficiency show within 10% error from the different ion contents. The chloroform as a quenching agent was used to determine the analytical efficiency with the different amount, showing that the efficiency decreases 20% using the 2% of chloroform.
In this study, the effect of wavelength range and absorption cross-section used to retrieve nitrogen dioxide (NO2) vertical column density (VCD) from Pandora was analyzed using Differential Optical Absorption Spectroscopy (DOAS). During the GEMS Map of the Air Pollution (GMAP) 2020 campaign, data from direct sunlight observation with Pandora instrument in Seosan was used, and NO2 VCD was retrieved under four conditions. The average NO2 VCD under the four conditions ranged from 1.22×1016~1.38×1016 molec. cm-2, with a maximum difference of 0.16×1016 molec. cm-2 between each condition. The fitting error averaged 3.19~9.59%, showing an error within 10% in all cases, and the RMS was 5.11×10-3~7.16×10-3 molec. cm-2. The retrieved NO2 VCD using 4 conditions shows a slope in the range of 0.98 to 1.09 and correlation of 0.96 to 0.98 in comparison with Pandonia Global Network (PGN).
Land Surface Temperature (LST) is one of the useful parameters to diagnose the growth and development of crop and to detect crop stress. Unmanned Aerial Vehicle (UAV)-based LST (LSTUAV) can be estimated in the regional spatial scale due to miniaturization of thermal infrared camera and development of UAV. Given that meteorological variable, type of instrument, and surface condition can affect the LSTUAV, the evaluation for accuracy of LSTUAV is required. The purpose of this study is to evaluate the accuracy of LSTUAV using LST measured at ground (LSTGround) under various meteorological conditions and growth phases of garlic crop. To evaluate the accuracy of LSTUAV, Relative humidity (RH), absolute humidity (AH), gust, and vegetation index were considered. Root mean square error (RMSE) after minimizing the bias between LSTUAV and LSTGround was 2.565℃ under above 60% of RH, and it was higher than that of 1.82℃ under the below 60% of RH. Therefore, LSTUAV measurement should be conducted under the below 60% of RH. The error depending on the gust and surface conditions was not statistically significant (p-value < 0.05). LSTUAV had reliable accuracy under the wind speed conditions that allow flight and reflected the crop condition. These results help to comprehend the accuracy of LSTUAV and to utilize it in the agriculture field.
Aerosol Optical Properties (AOPs) are retrieved using the geostationary satellite instruments such as Geostationary Ocean Color Imager (GOCI), Meteorological Imager (MI), and Advanced Himawari Imager (AHI) through Yonsei AErosol Retrieval algorithm (YAER). In this study, the retrieved aerosol optical depths (AOD)s from each instrument were intercompared and validated with the ground-based sunphotometer AErosol Robotic NETwork (AERONET) data. As a result, the four AOD products derived from different instruments showed consistent results over land and ocean. However, AODs from MI and GOCI tend to be overestimated due to cloud contamination. According to the comparison results with AERONET, the percentage within expected errors (EE) are 36.3, 48.4, 56.6, and 68.2% for MI, GOCI, AHI-minimum reflectivity method (MRM), and AHI-estimated surface reflectance from shortwave Infrared (ESR) product, respectively. Since MI AOD is retrieved from a single visible channel, and adopts only one aerosol type by season, EE is relatively lower than other products. On the other hand, the AHI ESR is more accurate than the minimum reflectance method as used by GOCI, MI, and AHI MRM method in May and June when the vegetation is relatively abundant. These results are explained by the RMSE and the EE for each AERONET site. The ESR method result show to be better than the other satellite product in terms of EE for 15 out of 22 sites used for validation, and they are better than the other product for 13 sites in terms of RMSE. In addition, the error in observation time in each product is found by using characteristics of geostationary satellites. The absolute median biases at 00 to 06 Universal Time Coordinated (UTC) are 0.05, 0.09, 0.18, 0.18, 0.14, 0.09, and 0.10. The absolute median bias by observation time has appeared in MI and the only 00 UTC appeared in GOCI.
The Journal of Korean Society for Radiation Therapy
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v.23
no.1
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pp.31-39
/
2011
Purpose: Helical Tomotherapy allows only coplanar beam delivery because it does not allow couch rotation. We investigated a method to introduce non-coplanar beam by tilting a patient's head for Tomotherapy. The aim of this study was to compare intrafractional movement during Tomotherapy between coplanar and non-coplanar patient's setup. Materials and Methods: Helical Tomotherapy was used for treating eight patients with intracranial tumor. The subjects were divided into three groups: one group (coplanar) of 2 patients who lay on S-plate with supine position and wore thermoplastic mask for immobilizing the head, second group (non-coplanar) of 3 patients who lay on S-plate with supine position and whose head was tilted with Variable Axis Baseplate and wore thermoplastic mask, and third group (non-coplanar plus mouthpiece) of 3 patients whose head was tilted and wore a mouthpiece immobilization device and thermoplastic mask. The patients were treated with Tomotherapy after treatment planning with Tomotherapy Planning System. Megavoltage computed tomography (MVCT) was performed before and after treatment, and the intrafractional error was measured with lateral(X), longitudinal(Y), vertical(Z) direction movements and vector ($\sqrt{x^2+y^2+z^2}$) value for assessing overall movement. Results: Intrafractional error was compared among three groups by taking the error of MVCT taken after the treatment. As the correction values (X, Y, Z) between MVCT image taken after treatment and CT-simulation image are close to zero, the patient movement is small. When the mean values of movement of each direction for non-coplanar setup were compared with coplanar setup group, X-axis movement was decreased by 13%, but Y-axis and Z-axis movement were increased by 109% and 88%, respectively. Movements of Y-axis and Z-axis with non-coplanar setup were relatively greater than that of X-axis since a tilted head tended to slip down. The mean of X-axis movement of the group who used a mouthpiece was greater by 9.4% than the group who did not use, but the mean of Y-axis movement was lower by at least 64%, and the mean of Z-axis was lower by at least 67%, and the mean of Z-axis was lower by at least 67%, and the vector was lower by at least 59% with the use of a mouthpiece. Among these 8 patients, one patient whose tumor was located on left frontal lobe and left basal ganglia received reduced radiation dose of 38% in right eye, 23% in left eye, 30% in optic chiasm, 27% in brain stem, and 8% in normal brain with non-coplanar method. Conclusion: Tomotherapy only allows coplanar delivery of IMRT treatment. To complement this shortcoming, Tomotherapy can be used with non-coplanar method by artificially tilting the patient's head and using an oral immobilization instrument to minimize the movement of patient, when intracranial tumor locates near critical organs or has to be treated with high dose radiation.
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