• Progress in Superconductivity and Cryogenics
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• v.19 no.3
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• pp.1-7
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• 2017

It is required to reduce the cost of superconducting cable to realize a superconducting DC power network that covers a wide area in order to utilize renewable energy. In this paper a new concept of innovative cable is introduced that can enhance the current-carrying capacity even though the same superconducting tape is used. Such a cable can be realized by designing an optimal winding structure in such a way that the angle between the tape and magnetic field becomes small. This idea was confirmed by preliminary experiments for a single layer model cable made of Bi-2223 tapes and REBCO coated conductors. Experiments of three and four layer cables of practical sizes were also done and it was found that the current-carrying capacity increased as theoretically predicted. If the critical current properties of commercial superconducting tapes are further improved in a parallel magnetic field, the enhancement will become pronounced and this technology will surely contribute to realization of superconducting DC power network.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.59-61
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• 2010

본 논문은 U-City의 지하시설물 관리 등 원격 지중시설물 계측 및 지반조사정보의 원격계측 등 지중 토목계측 서비스를 위해서 필요한 지중무선통신기술에 대한 기술적 특성에 대해 서술하고, 지중무선통신기술 중 가장 효과적인 자기장통신기술(Magnetic Field Area Network, MFAN)에 대한 분석과 이를 이용한 지중계측 서비스모텔에 대해 연구한 결과를 정리하였다. 향후, 시설물 관리, 방재, 에너지의 효율적 분배, 공사현장의 안전관리 등 다양한 용도로 지중무선통신이 활용될 것으로 예상되며, 지중무선통신을 통해 수집되는 데이터는 GIS와 연계를 통해 효과적인 지중모니터링 시스템이 개발될 수 있을 것이다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1706-1711
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• 2016

Electromagnetic wave simulation was performed to predict characteristics of manufactured cutoff probe at low temperature magnetized plasma medium. Microwave cutoff probe is designed for research the properties of magnetized inductively coupled plasma. It was shown that the cutoff probe method can safely be used for weakly magnetized high density plasma sources. Cutoff probe system with two port network analyzer has been prepared and applied to measure electron density distributions in large area, 13.56MHz driven weakly magnetized inductively coupled plasma source. The results shown that, the plasma frequency confirmed cut-off characteristics in low temperature plasma. Especially, cut-off characteristics was found at upper hybrid resonance frequency in the environment of the magnetic field. In case of a induced weak magnetic field in inductively coupled plasma, plasma density estimated from the cutoff frequency in the same way at unmagnetized plasma due to nearly same plasma frequency and upper hybrid resonance frequency. The plasma density is increased and uniformity is improved by applying a induced weak magnetic field in inductively coupled plasma.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.11a
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• pp.14-14
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• 2009

High frequency electromagnetic(EM) waves are increasingly being applied in industries because of saturationat lower frequency bands as a result of huge demand. However, electromagneticinterference (EMI) has become a serious problem, and as a result, highfrequency EM absorbers are now being extensively studied. Also, recentdevelopments in absorber technology have focused on producing absorbers thatare thin, flexible, and strong. Hence, one-dimension ferrous nano-materials area potential research field, because of their interesting electronic andmagnetic properties. Commercially, EM wave absorbing products are made ofcomposites, which blend the insulating polymer with magnetic fillers. Inparticular, the shape of the magnetic fillers, such flaky, acicular, or fibrousmagnetic metal particles, rather than spherical, is essential for synthesizingthin and lightweight EM wave absorbers with higher permeability. High aspectratio materials exhibit a higher permeability value and therefore betterabsorption of the EM wave, because of electromagnetic anisotropy. Nanowires areusually fabricated by drawing, template synthesis, phase separation, selfassembly, and electrospinning with a thermal treatment and reduction process.Producing nanowires by the electrospinning method involves a conventionalsol-gel process that is simple, unique, and cost-effective. In thispresentation, Magnetic nanowire and dielectric materials coated magneticnanowire with a high aspect ratio were successfully synthesized by theelectrospinning process with heat treatment and reduction. In addition toestimating the EM wave absorption ability of the synthesized magnetic anddielectric materials coated magnetic nanowire with a network analyzer, weinvestigated the possibility of using these nanowires as high-frequency EM waveabsorbers. Furthermore, a wide variety of topics will be discussed such as thetransparent conducting nanowire and semiconducting nanowire/tube with theelectrospinning process.

• Journal of National Security and Military Science
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• s.7
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• pp.271-303
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• 2009

"Ubiquitous sensor network" definition is this-Someone attaches electro-magnetic tag everything which needs communication between man to man, man to material and material to material(Ubiquitous). By using attached every electro-magnetic tag, someone detects it's native information as well as environmental information such as temperature, humidity, pollution and infiltration information(Sensor). someone connects it realtime network and manage generated information(Network). 21st century's war is joint combined operation connecting with ground, sea and air smoothly in digitalized war field, and is systematic war provided realtime information from sensor to shooter. So, it needs dramatic development on watch reconnaissance, command and control, pinpoint strike etc. Ubiquitous computing and network technologies are essential in national defense to operate 21st century style war. It is possible to use many parts such as USN combined smart dust and sensor network to protect friend unit as well as to watch enemy's deep area by unmanned reconnaissance, wearable computer upgrading soldier's operational ability and combat power dramatically, RFID which can be used material management as well as on time support. Especially, unmanned watch system using USN is core part to transit network centric military service and to get national defense efficiency which overcome the dilemma of national defense person resource reducing, and upgrade guard quality level, and improve combat power by normalizing guardian's bio rhythm. According to the test result of sensor network unmanned watch system, it needs more effort and time to stabilize because of low USN technology maturity and using maturity. In the future, USN unmanned watch system project must be decided the application scope such as application area and starting point by evaluating technology maturity and using maturity. And when you decide application scope, you must consider not only short period goal as cost reduction, soldier decrease and guard power upgrade but also long period goal as advanced defense ability strength. You must build basic infra in advance such as light cable network, frequency allocation and power facility etc. First of all, it must get budget guarantee and driving force for USN unmanned watch system project related to defense policy. You must forwarded the USN project assuming posses of operation skill as procedure, system, standard, training in advance. Operational skill posses is come from step by step application strategy such as test phase, introduction phase, spread phase, stabilization phase and also repeated test application taking example project.

• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.298-304
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• 2011

We conducted magnetic survey using IBRV (Ice Breaker Research Vessel) ARAON of KORDI (Korea Ocean Research and Development Institute), ROV (Remotely Operated Vehicle) of Oceaneering Co. and three components vector magnetometer, at Apr., 2011 in the western slope of the caldera of TA25 seamount, the Lau Basin, the southwestern Pacific. The depth ranges of the survey area are from about 900 m to 1200 m, below sea level. For the deep sea magnetic survey, we made the nation's first small deep sea three components magnetometer of Korea. The magnetometer sensor and the data logger was attached with the upper part and lower part of ROV, respectively. ROV followed the planning tracks at 25 ~ 30 m above seafloor using the altimeter and USBL (Ultra Short Base Line) of ROV. The three components magnetometer measured the X (North), Y (East) and Z (Vertical) vector components of the magnetic field of the survey area. A motion sensor provided us the data of pitch, roll, yaw of ROV for the motion correction of the magnetic data. The data of the magnetometer sensor and the motion sensor were recorded on a notebook through the optical cable of ROV and the network of ARON. The precision positions of magnetic data were merged by the post-processing of USBL data of ROV. The obtained three components magnetic data are entirely utilized by finding possible hydrothermal vents of the survey area.

• Journal of Information Display
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• v.3 no.2
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• pp.26-30
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• 2002

Large area plasma source has been built for LCD etcher by an array of $2{\times}2$ ICP sources. Since only one RF power supply and one impedance matching network is used in this configuration, any difference in impedances of unit RF antennas causes unbalanced power delivery to the unit ICP. In order to solve this unavoidable unbalance, unit antenna is designed to have a movable tap, with which the inductance of each unit can be adjusted individually. The plasma density becomes symmetric and etch rate becomes more uniform with the impedance adjustment. The concept of adding axial time-varying magnetic field to the single ICP source is applied to the array ICP source, and is found to be effective in terms of etch rate and uniformity.

• Clinical and Experimental Pediatrics
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• v.63 no.3
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• pp.88-95
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• 2020

Accurate localization of the seizure onset zone is important for better seizure outcomes and preventing deficits following epilepsy surgery. Recent advances in neuroimaging techniques have increased our understanding of the underlying etiology and improved our ability to noninvasively identify the seizure onset zone. Using epilepsy-specific magnetic resonance imaging (MRI) protocols, structural MRI allows better detection of the seizure onset zone, particularly when it is interpreted by experienced neuroradiologists. Ultra-high-field imaging and postprocessing analysis with automated machine learning algorithms can detect subtle structural abnormalities in MRI-negative patients. Tractography derived from diffusion tensor imaging can delineate white matter connections associated with epilepsy or eloquent function, thus, preventing deficits after epilepsy surgery. Arterial spin-labeling perfusion MRI, simultaneous electroencephalography (EEG)-functional MRI (fMRI), and magnetoencephalography (MEG) are noinvasive imaging modalities that can be used to localize the epileptogenic foci and assist in planning epilepsy surgery with positron emission tomography, ictal single-photon emission computed tomography, and intracranial EEG monitoring. MEG and fMRI can localize and lateralize the area of the cortex that is essential for language, motor, and memory function and identify its relationship with planned surgical resection sites to reduce the risk of neurological impairments. These advanced structural and functional imaging modalities can be combined with postprocessing methods to better understand the epileptic network and obtain valuable clinical information for predicting long-term outcomes in pediatric epilepsy.

• Geophysics and Geophysical Exploration
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• v.8 no.3
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• pp.224-231
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• 2005

In geophysical field surveys, commercial equipments often fail to resolve the subsurface target or even sometimes fail to be applied because they do not fit to the various field situations or the physical properties of the medium or target. We developed a geophysical measurement system, which can be easily adapted for the various field situations and targets. The system based on PXI with A/D converter and some stand alone equipment such as Network Analyzer was applied to borehole radar survey, borehole sonic measurement and electromagnetic noise measurement. The system for borehole radar survey consists of PXI, Network Analyzer, dipole antennas, GPIB interface is used for PXI to control Network Analyzer. The system for borehole sonic measurement consists of PXI, 24 Bit A/D converter, high voltage pulse generator, transmitting and receiving piezoelectric sensors. The electromagnetic noise measurement system consists of PXI, 24 Bit A/D converter, 2 horizontal component electric field sensors and 2 horizontal and 1 vertical component magnetic filed sensors. The borehole radar system has been successfully applied to detect the width of the artificial tunnel through which the borehole pass and to image buried steel pipe, while the commercial borehole radar equipment failed. The borehole sonic system was tested to detect the width of artificial tunnel and showed a reasonable result. The characteristic of electromagnetic noise was grasped at an urban area with the data from the electromagnetic noise measurement system. The system is also applied to characterize the signal distortion by induction between the electric cables in resistivity survey. The system can be applied various geophysical problems with a simple modification of the system and sensors.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.