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Kyungmo Sung,Seonghoon Jo,Jaewook Lee,Jeong Hoan Park,Young Hoon Park,Jeongjoo Moon,Sung June Kim,Joonsoo Jeong,Jonghwan Lee,Kyungsik Eom 대한의용생체공학회 2023 Biomedical Engineering Letters (BMEL) Vol.13 No.2
Heating nanoparticles with a magnetic field could facilitate selective remote control of neural activity in deep tissue. However,current magnetothermal stimulation approaches are limited to single-channel stimulation. Here, we investigated variousdesigns for multichannel magnetothermal stimulation based on an array of resonant coils that are driven by a single loop coil. Using a tuning capacitor that allows resonant coils to resonate at the operating frequency, each coil’s ON and OFF resonancecan be controlled, enabling us to select stimulation channels. We found that smaller inner diameters of resonant coils producemore localized magnetic fields while larger coils produce magnetic fields over a longer distance. The constructed multichannelresonant coil arrays can provide a high enough magnetic field intensity to raise the temperature of nanoparticles by 8 °Cwhen we apply 35.2 W into the loop coil that is spaced 1 mm from the target neurons. This multichannel stimulation usinga simple resonant circuit approach would be useful for clinical applications of magnetothermal neural stimulation.
Impact parameter prediction of a simulated metallic loose part using convolutional neural network
Moon, Seongin,Han, Seongjin,Kang, To,Han, Soonwoo,Kim, Kyungmo,Yu, Yongkyun,Eom, Joseph Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.4
The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.
문진석(Moon Jinseok),박경모(Park Kyungmo),최선미(Choi Sunmi) 한국한의학연구원 2007 한국한의학연구원논문집 Vol.13 No.2
General health exanimation comes into operation to focus on physical inspection for industrial workers and doesn't contain oriental health care. Thus we need information of health status and disease prevention. so develop a Questionnaire software for health examination in oriental medicine. Items of this software consists of personal information and symptoms to could check oneself, pulse and tongue diagnosis by oriental medical doctor. Symptoms are made up of syndrome differentiation about Qi and blood, Yin and Yang, body fluid, five Zang organs, Sasang Constitutional Medicine. And we reconstruct 116 items by whole body, chest and abdomen, urine and feces, head, limbs, waist and back, five sensory organs, objective signs. A subject enter symptoms and a oriental medical doctor input diagnosis of pulse and tongue, then this software return the result of health index and explanation for oriental health care. This software would be used as tool not only health examination but also clinical research
Sangjun Oh,Chulhee Lee,Heekyung Choi,Kyungmo Moon,Keeman Kim,Jiman Kim,Pyeong-Yeol Park IEEE 2008 IEEE transactions on applied superconductivity Vol.18 No.2
<P>We have developed a probe for the critical current measurements of low temperature superconducting strands at various field, temperature and strain. A 30 cm-long strand sample is soldered on a Walters spiral made of beryllium copper alloy and compressive or tensile axial strain can be applied up to 0.7%. Temperature control ability was tested using a MgB<SUB>2</SUB> wire up to 30 K. Three cernox sensors are attached on a spiral adjacent to the strand and the temperature of the spiral is controlled within plusmn50 mK of target temperature during the critical current measurement up to 80 A. Extensive critical current measurements have been carried out for an internal-tin processed Nb<SUB>3</SUB>Sn strand. It was found that the measured field, temperature and strain dependence of the critical current for the internal-tin Nb<SUB>3</SUB>Sn strand is in agreement with the recent scaling law based on strong coupling theory of superconductivity.</P>