• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.195-195
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• 2000

TFT-LCD의 제조공정은 박막층의 식각 공정에 대해 기존의 습식 공정을 대치하는 건식식각이 선호되고 있다. 건식 식각 공정은 반도체 공저에 응용되면서 소자의 최소 선폰(CD)이 감소함에 따라 유도결합셩 프라즈마를 비롯한 고밀도 플라즈마 이용한 플라즈마 장비 사용이 증가하는 추세이다. 여기에 평판디스플레이의 공정을 위해서는 대면적과 사각형 기판에 대한 균일도를 보장할 수 있는 고밀도의 균일한 플라즈마 유지가 중요하다. 본 실험에서는 자장강화된 유도결합형 플라즈마의 플라즈마 밀도 및 균일도를 살펴보고 TFT-LCD에 gate 전극으로 사용되는 Al-Nd 박막의 식각을 통하여 식각균일도와 식각속도 및 식각 선택도 등의 건식 식각 특성을 보고자 한다. 영구자석 및 전자석의 설치는 사각형의 유도결합형 플라즈마는 소형 영구자석을 배열하여 부착하였으며, 외부에는 chamber와 같이 사각형태의 전자석을 500mm$\times$500mm의 크기를 갖는 z축 방향의 Helmholtz형으로 제작하였다. 더. 영구자석 배열에 대해서는 자석간의 거리와 세기 변화를 조합하여 magnetic cusping의 변화를 주었으며 전자석의 세기는 전류값을 기준으로 변화시켜 보았다. 실험을 통하여 플라즈마 균일도를 5% 이하로 개선하고 이러한 균일도를 유지하며 플라즈마 밀도를 높일 수 있는 조건을 찾을 수 있었다. 이러한 적합화된 조건에서 저장강화된 유도결합형 프라즈마를 Al-Nd 박막 식각에 응용한 결과, Al-Nd의 식각속도 및 식각 선택도는 유도결합형 프라즈마에 비해 크게 증가하였으며, 식각균일도가 개선되는 것을 관찰하였다. 또한 electrostatic probe(Hiden, Analytical)를 이용하여 Al-Nd 식각에 사용된 반응성 식각가스에 대한 저장강화된 유도결합형 플라즈마의 특성 분석을 수행하였다.c recoil detection, Rutherford backscattering spectroscopy, X-ray diffraction, secondary electron microscopy, atomic force microscoy, $\alpha$-step, Raman scattering spectroscopu, Fourier transform infrared spectroscopy 및 micro hardness tester를 이용하여 기판 bias 전압이 DLC 박막의 특성에 미치는 영향을 조사하였다. 분석결과 본 연구에서 제작된 DLC 박막은 탄소와 수소만으로 구성되어 있으며, 비정질 상태임을 알 수 있었다. 기판 bias 전압의 증가에 따라 박막의 두께가 감소됨을 알 수 있었고, -150V에서는 박막이 거의 만들어지지 않았으며, -200V에서는 기판 표면이 식각되었다. 이것은 기판 bias 전압과 ECR 플라즈마에 의한 이온충돌 효과 때문으로 판단되며, 150V 이하에서는 증착되는 양보다 re-sputtering 되는 양이 더 많을 것으로 생각된다. 기판 bias 전압을 증가시킬수록 플라즈마에 의한 이온충돌 현상이 두드러져 탄소와 결합하고 있던 수소원자들이 떨어져 나가는 탈수소화 (dehydrogenation) 현상을 확인할 수 있었으며, 이것은 C-H 결합에너지가 C-C 결합이나 C=C 결합보다 약하여 수소 원자가 비교적 해리가 잘되므로 이러한 현상이 일어난다고 판단된다. 결합이 끊어진 탄소 원자들은 다른 탄소원자들과 결합하여 3차원적 cross-link를 형성시켜 나가면서 내부 압축응력을 증가시키는 것으로 알려져 있으며, hardness 시험 결과로 이것을 확인할 수 있었다. 그리고 표면거칠기는 기판 bias 전압을 증가시킬수록 더 smooth 해짐을 확인하였다.인하였다.을 알 수 있

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.771-782
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• 2017

This paper describes the development of a wearable robot to assist ankle power for the elderly. Previously developed wearable robots have generally used motors and gears to assist muscle power during walking. However, the combination of motor and reduction gear is heavy and has limitations on the simultaneous control of stiffness and torque due to the friction of the gear reducer unlike human muscles. Therefore, in this study, Mckibben pneumatic muscle, which is lighter, safer, and more powerful than an electric motor with gear, was used to assist ankle joint. Antagonistic actuation using a pair of pneumatic muscles assisted the power of the soleus muscles and tibialis anterior muscles used for the pitching motion of the ankle joint, and the model parameters of the antagonistic actuator were experimentally derived using a muscle test platform. To recognize the wearer's walking intention, foot load and ankle torque were calculated by measuring the pressure and the center of pressure of the foot using force and linear displacement sensors, and the stiffness and the torque of the pneumatic muscle joint were then controlled by the calculated ankle torque and foot load. Finally, the performance of the developed ankle power assistive robot was experimentally verified by measuring EMG signals during walking experiments on a treadmill.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.10a
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• pp.351-356
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• 1996

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• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.806-818
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• 2009

Since the invention of the integrated circuit (IC) in 1950s, semiconductor technology has undergone dramatic development up to these days. A complete semiconductor is manufactured through a diversity of processes. For better semiconductor productivity, fault detection and classification (FDC) has been rigorously studied for finding faults even before the processes are completed. For FDC, various kinds of sensors are attached in many semiconductor manufacturing devices, and sensor values are collected in a periodic manner. The collection of sensor values consists of sequences of real numbers, and hence is regarded as a kind of time-series data. In this paper, we propose an algorithm for detecting and clustering faults in semiconductor processes. The proposed algorithm is a modification of the existing anomaly detection algorithm dealing with symbolically-represented time-series. The contributions of this paper are: (1) showing that a modification of the existing anomaly detection algorithm dealing with general time-series could be used for semiconductor process data and (2) presenting experimental results for improving correctness of fault detection and clustering. As a result of our experiment, the proposed algorithm caused neither false positive nor false negative.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.383-388
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• 2011

This paper presents to study the accuracy improvement of the laser navigation using FIS(fuzzy inference system) and the reliability. As wireless guidance system, the top-mounted laser with the laser navigation can rotate $360^{\circ}$ with phototransistor or other optical sensors that read the return signal from reflectors mounted at the perimeter of the workspace. The type of major existing guidance systems is a wire guidance system. Because they have high accuracy and fast response time, they are used to most industries. However, their installation cost is very expensive and maintenance is very difficult because their sensors are placed approximately 1 inch below the ground or embedded in the floor. To solve those problems, the laser navigation was developed as a wire guidance system. It does not need to reconstruct a floor or ground. And it can reduce costs of installation and maintenance because changing the layout is easy. However, it is difficult to apply to an industrial field because it is easily affected by disturbances which cause loss and damage of data, and has slow respond time. Therefore, we study the accuracy improvement of the laser navigation. The proposed method is a correction method using reliability of the laser navigation. here, reliability is calculated by FIS which is designed with the analyzed characteristics of the laser navigation. For performance comparison, we use original position data form the laser navigation and position data corrected by original reliability from the laser navigation. In experimental result, we verified that the performance of the proposed method compared the others is improved by about 50% or more.

• Journal of the Korean Society of Radiology
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• v.15 no.7
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• pp.943-948
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• 2021

The purpose of this study was to investigate changes in surface dose due to increased scattering of gamma rays from patients injected with ^99mTc and ¹⁸F, which are radioactive isotopes, in close contact with materials with high atomic number such as the walls of the stable room. Prepare ^99mTc and ¹⁸F by injecting 20 and 10 mCi respectively into the NEMA phantom, and then measuring the surface dose for 60 minutes by positioning the phantom at a height of 1 m above the surface, at a distance of 0, 5 and 10 cm from the wall, and at the same location as the phantom facing the wall. Each experiment was repeated five times for reproducibility of the experiment and one way analysis of variability (ANOVA) was performed for significance testing and Tukey was used as a post-test. The study found that surface doses of 220.268, 287.121, 243.957, and 226.272 mGy were measured at ^99mTc, respectively, in the case of empty space and in the case of 0, 5 and 10 cm, while those of ¹⁸F were measured at 637.111, 724.469, 657.107, and 640.365 mGy, respectively. In order to reduce changes in surface dose depending on the patient's location while waiting, it is necessary to keep the distance from the ground or the wall where the patient is closely adhered to, or install an air mattress, etc., to prevent the scattered lines as much as possible, considering the scattered lines due to the wall etc. in future setup of the patient waiting room and safety room, and in addition to the examination, the external skin width may be reduced.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.268-275
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• 2021

The three factors that determine the strength of concrete are the strength of cement paste, aggregate and ITZ(Interfacial Transition Zone) between aggregate and cement paste. Out of these, the strength of ITZ is the most vulnerable. ITZ is formed in 10~50㎛, the ratio of calcium hydroxide is high, and CSH appears low ratio. A high calcium hydroxide ratio causes a decrease in the bond strength of ITZ. ITZ is due to further weak area. The problem of ITZ appears as a more disadvantageous factor when it used lightweight aggregate. The previous study of ITZ properties have measured interfacial toughness, identified influencing factors ITZ, and it progressed SEM and XRD analysis on cement matrix without using coarse aggregates. also it was identified microstructure using EMPA-BSE equipment. However, in previous studies, it is difficult to understand the microstructure and mechanical properties. Therefore, in this study, a method of measuring electrical resistance using EIS(Electrochemical Impedance Spectroscopy) measuring equipment was adopted to identify the ITZ between natural aggregate and lightweight aggregate, and it was tested the change of ITZ by surface coating of lightweight aggregate with ground granulated blast furnace slag. As a result, the compressive strength of natural aggregate and lightweight aggregate appear high strength of natural aggregate with high density, surface coating lightweight aggregate appear strength higher than natural aggregate. The electrical resistivity of ITZ according to the aggregate appeared difference.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.242-250
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• 2019

In this paper, we propose a method to predict the failure of industrial robot using Seq2Seq (Sequence to Sequence) model, which is a model for transforming time series data among Artificial Neural Network models. The proposed method uses the data of the joint current and angular value, which can be measured by the robot itself, without additional sensor for fault diagnosis. After preprocessing the measured data for the model to learn, the Seq2Seq model was trained to convert the current to angle. Abnormal degree for fault diagnosis uses RMSE (Root Mean Squared Error) during unit time between predicted angle and actual angle. The performance evaluation of the proposed method was performed using the test data measured under different conditions of normal and defective condition of the robot. When the Abnormal degree exceed the threshold, it was classified as a fault, and the accuracy of the fault diagnosis was 96.67% from the experiment. The proposed method has the merit that it can perform fault prediction without additional sensor, and it has been confirmed from the experiment that high diagnostic performance and efficiency are available without requiring deep expert knowledge of the robot.

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.84-89
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• 2019

This is a pilot study of machine learning based structural health monitoring system using flight data of composite aircraft. In this study, the most suitable machine learning algorithm for structural health monitoring was selected and dimensionality reduction method for application on the actual flight data was conducted. For these tasks, impact test on the cantilever beam with added mass, which is the simulation of damage in the aircraft wing structure was conducted and classification model for damage states (damage location and level) was trained. Through vibration test of cantilever beam with fiber bragg grating (FBG) sensor, data of normal and 12 damaged states were acquired, and the most suitable algorithm was selected through comparison between algorithms like tree, discriminant, support vector machine (SVM), kNN, ensemble. Besides, through neighborhood component analysis (NCA) feature selection, dimensionality reduction which is necessary to deal with high dimensional flight data was conducted. As a result, quadratic SVMs performed best with 98.7% for without NCA and 95.9% for with NCA. It is also shown that the application of NCA improved prediction speed, training time, and model memory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.503-509
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• 2019

The demand for smaller, faster, and multi-functional mobile devices in increasing at a rapidly increasing rate. In response to these trends, Stacked Chip Scale Package (SCSP) is used widely in the assembly industry. A film type adhesive called die attach film (DAF) is used widely for bonding chips in SCSP. The DAF requires high flowability at high die attachment temperatures for bonding chips on organic substrates, where the DAF needs to feel the gap depth, or for bonding the same sized dies, where the DAF needs to penetrate bonding wires. In this study, the mixture design of experiment (DOE) was performed for three raw materials to obtain the optimized DAF recipe for low elastic modulus at high temperature. Three components are acrylic polymer (SG-P3) and two solid epoxy resins (YD011 and YDCN500-1P) with different softening points. According to the DOE results, the elastic modulus at high temperature was influenced greatly by SG-P3. The elastic modulus at $100^{\circ}C$ decreased from 1.0 MPa to 0.2 MPa as the amount of SG-P3 was decreased by 20%. In contrast, the elastic modulus at room temperature was dominated by YD011, an epoxy with a higher softening point. The optimized DAF recipe showed approximately 98.4% pickup performance when a UV dicing tape was used. A DAF crack that occurred in curing was effectively suppressed through optimization of the cure accelerator amount and two-step cure schedule. The imizadole type accelerator showed better performance than the amine type accelerator.