• Analytical Science and Technology
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• v.34 no.2
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• pp.87-98
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• 2021

In this study, we developed the nanoparticle multi-generator by 3D printer fusion deposition modeling (FDM) method that can reliably generate and deliver nanoparticles at a constant concentration for inhalation risk assessment. A white ABS filament was used as the test material, and SMPS was used for concentration analysis such as particle size and particle distribution. In the case of particle size, the particle size was divided by 100 nm or less and 100 to 1,000 nm, and the number of particles concentration, mass concentration, median diameter of particles, geometric average particle diameter, etc were measured. The occurrence conditions were the extruder temperature, the extruding speed of the nozzle, and the air flow rate, and experiments were conducted according to the change of conditions including the manufacturer's standard conditions. In addition, the utility of inhalation risk assessment was reviewed through a stability maintenance experiment for 6 h. As a result of the experiment, the size of the nanoparticles increased as the discharger temperature increased, as the discharge speed of the nozzle increased, and as the air flow rate decreased. Also, a constant pattern was shown according to the conditions. Even when particles were generated for a long time (6 h), the concentration was kept constant without significant deviation. The distribution of the particles was approximately 80 % for particles of 60 nm to 260 nm, 1.7 % for 1 ㎛ or larger, 0.908 mg/㎥ for the mass concentration, 111 nm for MMAD and 2.10 for GSD. Most of the ABS particles were circular with a size of less than 10 nm, and these circular particles were aggregated to form a cluster of grape with a size of several tens to several hundred nm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1202-1208
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• 2020

In line with the current era of the 4th Industrial Revolution, it is necessary to prepare for the future by integrating AI elements in the ship sector. In addition, it is necessary to respond to this in the field of power management for the appearance of autonomous ships. In this study, we propose a battery-linked electric propulsion system (BLEPS) algorithm using machine learning's DNN. For the experiment, we learned the pattern of ship power consumption for each operation mode based on the ship data through LabView and derived the battery status through Python to check the flexibility of the generator and battery interlocking. As a result of the experiment, the low load operation of the generator was reduced through charging and discharging of the battery, and economic efficiency and reliability were confirmed by reducing the fuel consumption of 1% of LNG.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2237-2246
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• 2012

A bias circuit required for an oral sensor is manufactured inside the oral sensor chip to reduce its size and cost. The proposed DC-DC converter supplies the required reference and bias currents for their corresponding regulators by using IREF of the reference current generator. Their target voltages of the voltage regulators are regulated by the negative mechanism by generating their reference voltages required for their corresponding regulators. In addition, a constant current IB0/IB1 is supplied by being mirrored by a current mirror ratio and then VREF is generated. It is confirmed by measurements that the average volatge, ${\sigma}$, and $4{\sigma}$ of the designed DC-DC converter for intra oral sensors with a $0.18{\mu}m$ X-ray CMOS process are within their required ranges. And the line-pair pattern image shows a high-resolution characteristic without blurring. Also, a good oral image can be obtained.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.11-18
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• 2012

Deep packet inspection which perform pattern matching to search for malicious patterns in the packet is most computationally intensive task. Hardware-based pattern matching is required for real-time packet inspection in high-speed network. In this paper, we have designed and implemented network intrusion detection hardware as a Microblaze-based SoC using Virtex-6 FPGA, which capture the network input packet, perform hardware-based pattern matching for patterns in the Snort rule, and provide the matching result to the software. We verify the operation of the implemented system using traffic generator and real network traffic. The implemented hardware can be used in network intrusion detection system operated in wire-speed.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.5
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• pp.510-517
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• 2001

This paper describes an initial study for the application of eddy current pattern recognition approaches to more realistic flaw characterization in steam generator tubes. For this purpose, finite-element model-based theoretical eddy current testing (ECT) signals are simulated from 5 types of OD flaws with the variation in flaw size parameters and testing frequency. In addition, three kinds of software are developed for the convenience in the application of steps in pattern recognition approaches such as feature extraction feature selection and classification by probabilistic neural networks (PNNs). The cross point of the ECT signals simulated from flaws with non-symmetric cross-sections shows the deviation from the origin of the impedance plane. New features taking advantages of this phenomenon are added to complete the feature set with a total of 18 features. Then, classification with PNNs are performed based on this feature set. The PNN classifiers show high performance for the identification of symmetry in the cross-section of a flaw. However, they show very limited success in the interrogation of the sharpness of flaw tips.

• Wind and Structures
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• v.18 no.2
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• pp.195-213
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• 2014

Recently, the horizontal axis rotor performance optimizer (HARP_Opt) tool was developed in the National Renewable Energy Laboratory, USA. This innovative tool is becoming more popular in the wind turbine industry and in the field of academic research. HARP_Optwas developed on the basis of two fundamental modules, namely, WT_Perf, a performance evaluator computer code using the blade element momentum theory; and a genetic algorithm module, which is used as an optimizer. A pattern search algorithm was more recently incorporated to enhance the optimization capability, especially the calculation time and consistency of the solutions. The blade optimization is an aspect that is highly dependent on experience and requires significant consideration on rotor control strategies, wind data, and generator type. In this study, the effects of rotor control strategies including fixed speed and fixed pitch, variable speed and fixed pitch, fixed speed and variable pitch, and variable speed and variable pitch algorithms on optimal blade shapes and rotor performance are investigated using optimized blade designs. The effects of environmental wind data and the objective functions used for optimization are also quantitatively evaluated using the HARP_Opt tool. Performance indices such as annual energy production, thrust, torque, and roof-flap moment forces are compared.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.211-212
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• 2008

본 논문에서는 LCD 구동 모들 PCB의 기능 검사를 위한 자동 검사시스템인 EVT(Emulated Vision Tester)를 제안하고 구현하였다. 기존의 대표적인 자동검사 방법으로는 전기적 검사나 영상기반 검사방식이 있으나 전기적 검사만으로는 Timing이 주요한 변수가 되는 LED 장비에서는 검출할 수 없는 구동불량이 존재하며 영상기반 검사는 영상획득에 일관성이 결여되거나 Gray Scale의 구분이 불명확하며 검출결과의 재현성이 떨어진다. EVT 시스템은 Pattern Generator에서 인가된 입력 패턴 신호라 구동모듈을 통한 후 출력되는 디지털 신호를 직접 비교하여 패턴을 검사하고 아날로그 신호 (전압, 저항, 파형)의 이상 여부도 신속 정확하게 검사할 수 있는 H/W적인 방법이다. 높은 검출 신뢰도와 빠른 처리 속도 뿐만 아니라 간결한 시스템 구성으로 원가절감 실현 등 많은 장점을 가진다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2369-2377
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• 1998

Fault simulators are used to evaluate the quality of a test pattern generated. So far, most fault simulators did not handle bus conflicts properly. We analyzed . all possible bus conflicts when test patterns are applied to a circuit with bus structure and categorized bus conflicts into various types. Also. we proposed an efficient method to identify various types of bus conflicts. The fault simulator which employs the proposed method can evaluate the quality of test patterns generated and also can avoid destruction of bus drivers due to bus conflicts hy warning the use of test patterns which cause bus conflicts. The proposed method can also be incorperated into a test pattern generator so that it can generate conflict-free test patterns.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.228-238
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• 2017

The CALEB10 is a multi-legged biomimetic underwater robot. In the last research, we developed a swimming pattern named ESPG (Extended Swimming Pattern Generator) by observing diving beetle's swimming actions and experimented with a positive buoyancy state in which CALEB10 floats on the water. In this paper, however, we have experimented with CALEB10 in a neutral buoyancy state where it is completely immersed in water for pitch motion control experiment. And we found that CALEB10 was unstably swimming in the pitch direction in the neutral buoyancy state and analyzed that the reason was due to the weight proportion of the legs. In this paper, we propose a pitch motion control method to mimic the pitch motion of diving beetles and to solve the problem of CALEB10 unstably swimming in the pitch direction. To control the pitch motion, we use the method of controlling additional joints while swimming with the ESPG. The method of obtaining propulsive force by the motion of the leg has a problem of giving propulsive force in the reverse direction when swimming in the surge direction, but this new control method has an advantage that a propulsive moment generated by a swimming action only on a target pitch value. To demonstrate validity this new control method, we designed a dynamics-based simulator environment. And the control performance to the target pitch value was verified through simulation and underwater experiments.

• Smart Structures and Systems
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• v.8 no.1
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• pp.39-52
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• 2011

We are developing a biomimetic robot based on the Sea Lamprey. The robot consists of a cylindrical electronics bay propelled by an undulatory body axis. Shape memory alloy (SMA) actuators generate propagating flexion waves in five undulatory segments of a polyurethane strip. The behavior of the robot is controlled by an electronic nervous system (ENS) composed of networks of discrete-time map-based neurons and synapses that execute on a digital signal processing chip. Motor neuron action potentials gate power transistors that apply current to the SMA actuators. The ENS consists of a set of segmental central pattern generators (CPGs), modulated by layered command and coordinating neuron networks, that integrate input from exteroceptive sensors including a compass, accelerometers, inclinometers and a short baseline sonar array (SBA). The CPGs instantiate the 3-element hemi-segmental network model established from physiological studies. Anterior and posterior propagating pathways between CPGs mediate intersegmental coordination to generate flexion waves for forward and backward swimming. The command network mediates layered exteroceptive reflexes for homing, primary orientation, and impediment compensation. The SBA allows homing on a sonar beacon by indicating deviations in azimuth and inclination. Inclinometers actuate a bending segment between the hull and undulator to allow climb and dive. Accelerometers can distinguish collisions from impediment to allow compensatory reflexes. Modulatory commands mediate speed control and turning. A SBA communications interface is being developed to allow supervised reactive autonomy.