• Tribology and Lubricants
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• v.35 no.5
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• pp.317-322
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• 2019

In spite of progress in tribological research, machine component failure due to friction and wear has been reported frequently. This failure may lead to secondary damage that can cause huge expense for maintenance and repair. To prevent economic loss, it is important to detect and predict the initial failure point. In this sense, various researchers have been tried to develop Condition Monitoring (CM) method using Acoustic Emission (AE) generated while the materials undergo failure. In this study, effect of particles on friction and wear was investigated using the pin-on-plate friction test and AE signal was recorded with a band-width type AE sensor. The experiments were performed in dry and lubricant conditions using steel and glass as specimens. After the experiment, 3D laser microscope image was captured to evaluate the wear behavior quantitatively. The AE signal was analyzed in time-domain and frequency-domain. The amplitude was compared with the frictional results. The results of this study showed that particle generation accelerate wear, generate high magnitude AE signal and change the frequency characteristics of the signal. Also, lubricant condition test results showed low coefficient of friction, low wear rate, and low magnitude of AE signal compared to the dry condition. It is expected that the results of this study will aid in better assessment of wear in CM technology

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.363-370
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• 2022

Grasping a target object among clutter objects without collision requires machine intelligence. Machine intelligence includes environment recognition, target & obstacle recognition, collision-free path planning, and object grasping intelligence of robot hands. In this work, we implement such system in simulation and hardware to grasp a target object without collision. We use a RGB-D image sensor to recognize the environment and objects. Various path-finding algorithms been implemented and tested to find collision-free paths. Finally for an anthropomorphic robot hand, object grasping intelligence is learned through deep reinforcement learning. In our simulation environment, grasping a target out of five clutter objects, showed an average success rate of 78.8%and a collision rate of 34% without path planning. Whereas our system combined with path planning showed an average success rate of 94% and an average collision rate of 20%. In our hardware environment grasping a target out of three clutter objects showed an average success rate of 30% and a collision rate of 97% without path planning whereas our system combined with path planning showed an average success rate of 90% and an average collision rate of 23%. Our results show that grasping a target object in clutter is feasible with vision intelligence, path planning, and deep RL.

• Journal of Sensor Science and Technology
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• v.18 no.1
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• pp.77-85
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• 2009

We propose a new image pixel architecture which has OFD(Over Flow Device) node by improving conventional 3TR pixel structure. Newly designed pixel consists of photo diode which is verified with HSPICE simulation, PMOS reset transistor, several NMOS and several PMOS transistors. Photodiode signals from each PMOS and NMOS are detected by Reset PMOS. These output signals give enough chances to detect wide operation coverage because OFD node has overflow photocurrent. According to various light intensity, we analyzed characteristic of the output voltage with a SPICE tool. Proposed pixel output has specific value which can detect possible from $0.1{\mu}W/cm^2$ to $10W/cm^2$ light intensity. It has wide-dynamic range of 160 dB.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• 대한방사선치료학회:학술대회논문집
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• 2005.06a
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• pp.13-17
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• 2005

Introduction : For stereotactic radiosurgery (SRS) of a tumor in the region whose movement due to respiration is significant, like Lung lower lobe, the gated therapy, which delivers radiation dose to the selected respiratory phases when tumor motion is small, was peformed using the Respiratory gating system and its clinical effectiveness was evaluated. Methode and Materials : For two SRS patients with a tumor in Lung lower lobe, a marker block (infrared reflector) was attached on the abdomen. While patient' respiratory cycle was monitored with Real-time Position Management (RPM, Varian, USA), 4D CT was performed (10 phases per a cycle). Phases in which tumor motion did not change rapidly were decided as treatment phases. The treatment volume was contoured on the CT images for selected treatment phases using maximum intensity projection (MIP) method. In order to verify setup reproducibility and positional variation, 4D CT was repeated. Result : Gross tumor volume (GTV) showed maximum movement in superior-inferior direction. For patient $\#$1, motion of GTV was reduced to 2.6 mm in treatment phases ($30\%\~60\%$), while that was 9.4 mm in full phases ($0\%\~90\%$) and for patient $\#$2, it was reduced to 2.3 mm in treatment phases ($30\%\~70\%$), while it was 11.7 mm in full phases ($0\%\~90\%$). When comparing two sets of CT images, setup errors in all the directions were within 3 mm. Conclusion : Since tumor motion was reduced less than 5 mm, the Respiratory gating system for SRS of Lung lower lobe is useful.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.486-492
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• 2015

Radiation source imaging system is essential for protecting of radiation leakage accidents and minimizing damages from the radioactive materials, and is expected to play an important role in the nuclear plant decommissioning area. In this study, the stereoscopic camera principle was applied to develop a new radiation imaging device technology that can extract the radiation three-dimensional position information. This radiation three-dimensional imaging device (K3-RIS) was designed as a compact structure consisting of a radiation sensor, a CCD camera, and a pan-tilt only. It features the acquisition of stereoscopic radiation images by position change control, high-resolution detection by continuous scan mode control, and stereoscopic image signal processing. The performance analysis test of K3-RIS was conducted for a gamma-ray source(Cs-137) in radiation calibration facility. The test result showed that a performance error with less than 3% regardless of distances of the objects.

• Journal of Sensor Science and Technology
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• v.10 no.3
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• pp.196-206
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• 2001

Real temperature profiles of a planar chromel-alumel mutli-junction thermal converter(TC 1) were measured by thermal image. Temperature profiles as a function of input power of thermal converters(TC 1${\sim}$TC 6) were simulated by 3-dimensional ANSYS program based on finite element method. Temperature difference between the hot junction and the cold junction for TC 1 was smallest and largest for TC 6 and correspondingly, he voltage response for TC 1 and TC 6 showed the smallest value of 3.09 mV/mW and the largest value of 4.03 mV/mW, respectively.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.87-95
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• 2014

This paper describes a dual channel receiver design for CIS interfaces. Each channel includes CTLE(Continuous Time Linear Equalizer), sampler, deserializer and clocking circuit. The clocking circuit is composed of PLL, PI and CDR. Fast lock acquisition time, short latency and better jitter tolerance are achieved by adding OSPD(Over Sampling Phase Detector) and FSM(Finite State Machine) to PI-based CDR. The CTLE removes ISI caused by channel with -6 dB attenuation and the lock acquisition time of the CDR is below 1 baud period in frequency offset under 8000ppm. The voltage margin is 368 mV and the timing margin is 0.93 UI in eye diagram using 65 nm CMOS technology.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.29-39
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• 2015

This paper describes a design and implementation of fuzzy-based algorithm for hand-shake state detection and error compensation in the mobile optical image stabilization(OIS) motion detector. Since the gyro sensor output of the OIS motion detector includes inherent error signals, accurate error correction is required for prompt hand-shake error compensation and stable hand-shake state detection. In this research with a little computation overhead of fuzzy-based algorithm, the hand-shake error compensation could be improved by quickly reducing the angle and phase error for the hand-shake frequencies. Further, stability of the OIS system could be enhanced by the hand-shake states of {Halt, Little vibrate, Big vibrate, Pan/Tilt}, classified by subdividing the hand-shake angle. The performance and stability of the proposed algorithm in OIS motion detector is quantitatively and qualitatively evaluated with the emulated hand-shaking of ${\pm}0.5^{\circ}$, ${\pm}0.8^{\circ}$ vibration and 2~12Hz frequency. In experiments, the average error compensation gain of 3.71dB is achieved with respect to the conventional BACF/DCF algorithm; and the four hand-shake states are detected in a stable manner.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.4
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• pp.7-14
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• 2012

A image quality is limited by a sample-and-hold circuit of the X-ray CMOS image sensor even though simple mos switch or bootstrapped clock circuit are used to get high quality sampled signal. Because distortion of sampled signal is produced by the charge injection from sample-and-hold circuit even using bootstrapped. This paper presents the 3D micro-inductor design methode in the CMOS process. Using this methode, it is possible to increase the ENOB (effective number of bit) through the use of micro-inductor which is calculated and designed in standard CMOS process in this paper. The ENOB is improved 0.7 bit from 17.64 bit to 18.34 bit without any circuit just by optimized inductor value resulting in verified simulation result. Because of this feature, micro-inductor methode suggested in this paper is able to adapt a mamography that is needed high resolution so that it help to decrease patients dose amount.