• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 추계학술대회 논문집
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• pp.189-192
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• 2001

Recently, STI process is getting attention as a necessary technology for making high density of semiconductor by devices isolation method. However, it does have various problems caused by CMP process, such as torn oxide defects, nitride residues on oxide, damages of si active region, contaminations due to post-CMP cleaning, difficulty of accurate end point detection in CMP process, etc. In this work, the various defects induced by CMP process was introduced and the above mentioned Problems of CMP process was examined in detail. Finally, the guideline of future CMP process was presented to reduce the effects of these defects.

• 로봇학회논문지
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• 제18권2호
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• pp.135-142
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• 2023

Light detection and ranging (LiDAR) sensors have been most widely used in terrestrial robotic applications because they can provide dense and precise measurements of the surrounding environments. However, the reliability of LiDAR measurements can considerably vary due to the different reflectivities of laser beams to the reflecting surface materials. This study presents a robust LiDAR-based mapping method for the varying laser reflectivities in indoor environments using the framework of simultaneous localization and mapping (SLAM). The proposed method can minimize the performance degradations in the SLAM accuracy by checking and discarding potentially unreliable LiDAR measurements in the SLAM front-end process. The gaps in point-cloud maps created by the proposed approach are filled by a Gaussian process regression method. Experimental results with a mobile robot platform in an indoor environment are presented to validate the effectiveness of the proposed methodology.

• 로봇학회논문지
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• 제19권2호
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• pp.176-187
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• 2024

Recently, automated solutions using collaborative robots have been emerging in various industries. Their primary functions include Pick & Place, Peg in the Hole, fastening and assembly, welding, and more, which are being utilized and researched in various fields. The application of these robots varies depending on the characteristics of the grippers attached to the end of the collaborative robots. To grasp a variety of objects, a gripper with a high degree of freedom is required. In this paper, we propose a service automation system using a multi-degree-of-freedom gripper, collaborative robots, and vision sensors. Assuming various products are placed at a checkout counter, we use three cameras to recognize the objects, estimate their pose, and create grasping points for grasping. The grasping points are grasped by the multi-degree-of-freedom gripper, and experiments are conducted to recognize barcodes, a key task in service automation. To recognize objects, we used a CNN (Convolutional Neural Network) based algorithm and point cloud to estimate the object's 6D pose. Using the recognized object's 6d pose information, we create grasping points for the multi-degree-of-freedom gripper and perform re-grasping in a direction that facilitates barcode scanning. The experiment was conducted with four selected objects, progressing through identification, 6D pose estimation, and grasping, recording the success and failure of barcode recognition to prove the effectiveness of the proposed system.

• 전자공학회논문지
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• 제54권5호
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• pp.42-47
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• 2017

본 논문에서는 디지털 영상의 배포에서, 위 변조에 사용되는 미디언 필터링 (Median Filtering : MF)을 분류하는 포렌식 검출 알고리즘을 제안한다. 이러한 문제를 해결하기 위한 특징벡터는 영상의 에지 검출량 정보 32, 64, 128에 대한 허프변환(Hough Transform)에 의하여, 각 허프라인 (Hough Line)의 양끝 좌표값과 Angle-Distance 좌표상의 허프픽크치 (Hough Peaks)를 조합하여 42-Dim.으로 구성하였다. 변조된 영상들 중에서 미디언 필터링을 분류하는 검출기는 SVM (Support Vector Machine)에서 특징벡터를 학습하여 구현되었다. 제안된 미디언 필터링 검출 알고리즘은 특징벡터의 길이가 10-Dim.의 MFR (Median Filtering Residual) 스킴 및 686-Dim.의 SPAM (Subtractive Pixel Adjacency Matrix) 스킴과 비교하여 원영상, 평균필터링 ($3{\times}3$), JPEG (QF=90, 70) 압축, 가우시안 필터링 ($3{\times}3$, $5{\times}5$) 영상 모두에서 미디언 필터링의 포렌식 분류율이 99% 이상의 성능을 확인하였다.

• 대한의용생체공학회:의공학회지
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• 제17권4호
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• pp.449-458
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• 1996

Most of the conventional electrocardiowaphs foil to detect signals other than P-QRS-T due to the limited SNR and bandwidth. High-resolution electrocardiography(HRECG) provides better SNR and wider bandwidth for the detection of micro-potentials with higher frequency components such as vontricular late potentials(LP). We have developed a HRECG using uncorrected XYZ lead for the detection of LPs. The overall gain of the amplifier is 4000 and the bandwidth is 0.5-300Hz without using 60Hz notch filter. Three 16-bit A/D converters sample X, Y, and Z signals simultaneously with a sampling frequency of 2000Hz. Sampled data are transmitted to a PC via a DMA-controlled, optically-coupled serial communication channel. In order to further reduce the noise, we implemented a signal averaging algorithm that averaged many instances of aligned beats. The beat alignment was carried out through the use of a template matching technique that finds a location maximizing cross-correlation with a given beat tem- plate. Beat alignment error was reduced to $\pm$0.25ms. FIR high-pass filter with cut-off frequency of 40Hz was applied to remove the low frequency components of the averaged X, Y, and Z signals. QRS onset and end point were determined from the vector magnitude of the sigrlaIL and some parameters needed to detect the existence of LP were estimated. The entire system was designed for the easy application of the future research topics including the optimal lead system, filter design, new parameter extraction, etc. In the developed HRECG, without signal averaging, the noise level was less than 5$\mu$V$_rms RTI$. With signal averaging of at least 100 beats, the noise level was reduced to 0.5$\mu$V$_rms RTI$, which is low enough to detect LPs. The developed HRECG will provide a new advanced functionality to interpretive ECG analyzers.

• 한국산학기술학회논문지
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• 제22권3호
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• pp.20-29
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• 2021

4차산업혁명 시대에는 대량의 데이터를 학습하여 예측과 분류의 정확성을 향상시킬 수 있는 인공지능의 활용이 핵심적이다. 그러나, 기존 이상탐지를 위한 방법은 제한된 데이터를 다루는 전통적인 통계 방법에 의존하고 있어, 정확한 이상탐지가 어렵다. 그러므로, 본 연구는 인공지능 기반 이상탐지 방법을 제시하여 예측 정확도를 높이고, 새로운 데이터 패턴을 정의하는 것을 목적으로 한다. 특히, 자동차의 경우 공회전 기간의 센서 데이터가 이상 탐지에 활용될 수 있다는 관점에서 데이터를 수집하고 분석하였다. 이를 위해, 예측 모델에 입력되는 데이터의 적정 시간 길이를 결정하고, 공회전 기간 데이터와 전체 운행 데이터의 분석 결과를 비교하며, 다양한 센서 데이터 조합에 의한 최적 예측 방법을 도출하였다. 또한, 인공지능 방법으로 선택된 CNN의 예측 정확성을 검증하기 위해 LSTM 결과와 비교하였다. 분석 결과, 공회전 데이터를 이용하고, 공회전 기간보다 1.5배 많은 기간의 데이터를 이용하며 LSTM보다는 CNN을 활용하는 것이 더 좋은 예측결과를 보였다.

• 한국방사선학회논문지
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• 제12권7호
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• pp.801-806
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• 2018

게르마늄 결정은 검출에 유용하지 않지만, 광자를 강하게 약화하기 때문에 효율성 저하를 일어키는 불감층을 가지고 있다. 따라서 제조업체가 제공하는 데이터를 검출기 시뮬레이션 모델에 사용하면 계산된 효율성과 측정된 효율성 사이에 약간의 큰 차이가 나타난다. 고순도 게르마늄(HPGe) 검출기의 모양과 치수는 CT 스캔을 통해 몬테카롤롤 시뮬레이션을 위해 형상을 정확하게 형상화하였다. 이 결과 불감층 두께 증가가 효율 감소과정에 미치는 영향을 연구하고자 한다. 불감층의 조정은 50 - 1500 keV의 에너지 범위에서 측정 효율과 시뮬레이션 효율 사이의 ${\pm}3%$의 상대편차와 함께 좋은 일치임을 확인하였다. 불감층 두께에 변화를 주어 시뮬레이션 데이터를 비교하였다. 몬테카롤로 시뮬레이션 결과를 실험 결과와 비교하여 새로운 불감층 두꼐를 얻었다. 1.4와 1.6 mm 두께의 End Cap 시뮬레이션 모델에서 1.5mm 두께의 End Cap시뮬레이션 모델에 대한 불감층 두꼐 결과의 차이는 End Cap 치수의 정확성으로 인한 체계적인 오류였다. 통계적 오류와 체계적 오류를 고려한 후, 검출기의 불감충 두께는 $1.02{\pm}0.14mm$로 도출되었다. 따라서 불감층 두께의 증가는 효율성 감소에 영향을 미치는 것을 확인하였다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.273-273
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• 2013

Recently, Point-of-care (POC) testing microdevices enable to do the patient monitoring, drug screening, pathogen detection in the outside of hospital. Immunochromatographic strip (ICS) is one of the diagnostic technologies which are widely applied to POC detection. Relatively low cost, simplicity to use, easy interpretations of the diagnostic results and high stability under any circumstances are representative advantages of POC diagnosis. It would provide colorimetric results more conveniently, if the genetic analysis microsystem incorporates the ICS as a detector part. In this work, we develop a reverse transcriptase-polymerase chain reaction (RT-PCR) microfluidic device integrated with a ROSGENE strip for colorimetric influenza H1N1 virus detection. The integrated RT-PCR- ROSGENE device is consist of four functional units which are a pneumatic micropump for sample loading, 2 ${\mu}L$ volume RT-PCR chamber for target gene amplification, a resistance temperature detector (RTD) electrode for temperature control, and a ROSGENE strip for target gene detection. The device was fabricated by combining four layers: First wafer is for RTD microfabrication, the second wafer is for PCR chamber at the bottom and micropump channel on the top, the third is the monolithic PDMS, and the fourth is the manifold for micropump operation. The RT-PCR was performed with subtype specific forward and reverse primers which were labeled with Texas-red, serving as a fluorescent hapten. A biotin-dUTP was used to insert biotin moieties in the PCR amplicons, during the RT-PCR. The RT-PCR amplicons were loaded in the sample application area, and they were conjugated with Au NP-labeled hapten-antibody. The test band embedded with streptavidins captures the biotin labeled amplicons and we can see violet colorimetric signals if the target gene was amplified with the control line. The off-chip RT-PCR amplicons of the influenza H1N1 virus were analyzed with a ROSGENE strip in comparison with an agarose gel electrophoresis. The intensities of test line was proportional to the template quantity and the detection sensitivity of the strip was better than that of the agarose gel. The test band of the ROSGENE strip could be observed with only 10 copies of a RNA template by the naked eyes. For the on-chip RT-PCR-ROSGENE experiments, a RT-PCR cocktail was injected into the chamber from the inlet reservoir to the waste outlet by the micro-pump actuation. After filling without bubbles inside the chamber, a RT-PCR thermal cycling was executed for 2 hours with all the microvalves closed to isolate the PCR chamber. After thermal cycling, the RT-PCR product was delivered to the attached ROSGENE strip through the outlet reservoir. After dropping 40 ${\mu}L$ of an eluant buffer at the end of the strip, the violet test line was detected as a H1N1 virus indicator, while the negative experiment only revealed a control line and while the positive experiment a control and a test line was appeared.

• 지능정보연구
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• 제29권4호
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• pp.15-30
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• 2023

최근 미디어 분야에도 인공지능(AI)을 적용한 다양한 서비스가 등장하고 있는 추세이다. 하지만 편집점을 찾아 영상을 이어 붙이는 영상 편집은, 대부분 수동적 방식으로 진행되어 시간과 인적 자원의 소요가 많이 발생하고 있다. 이에 본 연구에서는 Video Swin Transformer를 활용하여, 발화 여부에 따른 영상의 편집점을 탐지할 수 있는 방법론을 제안한다. 이를 위해, 제안 구조는 먼저 Face Alignment를 통해 얼굴 특징점을 검출한다. 이와 같은 과정을 통해 입력 영상 데이터로부터 발화 여부에 따른 얼굴의 시 공간적인 변화를 모델에 반영한다. 그리고, 본 연구에서 제안하는 Video Swin Transformer 기반 모델을 통해 영상 속 사람의 행동을 분류한다. 구체적으로 비디오 데이터로부터 Video Swin Transformer를 통해 생성되는 Feature Map과 Face Alignment를 통해 검출된 얼굴 특징점을 합친 후 Convolution을 거쳐 발화 여부를 탐지하게 된다. 실험 결과, 본 논문에서 제안한 얼굴 특징점을 활용한 영상 편집점 탐지 모델을 사용했을 경우 분류 성능을 89.17% 기록하여, 얼굴 특징점을 사용하지 않았을 때의 성능 87.46% 대비 성능을 향상시키는 것을 확인할 수 있었다.

• 한국기후변화학회지
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• 제6권2호
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• pp.61-72
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• 2015

In this study, we have investigated monthly changes in temperature extremes in South Korea for the past (1921~2010) and the future (2011~2100). We used seven stations' (Gangneung, Seoul, Incheon, Daegu, Jeonju, Busan, Mokpo) data from KMA (Korea Meteorological Administration) for the past. For the future we used the closest grid point values to observations from the RCP8.5 scenario of 1 km resolution. The Expert Team on Climate Change Detection and Indices (ETCCDI)'s climate extreme indices were employed to quantify the characteristics of temperature extremes change. Temperature extreme indices in summer have increased while those in winter have decreased in the past. The extreme indices are expected to change more rapidly in the future than in the past. The number of frost days (FD) is projected to decrease in the future, and the occurrence period will be shortened by two months at the end of the $21^{st}$ century (2071~2100) compared to the present (1981~2010). The number of hot days (HD) is projected to increase in the future, and the occurrence period is projected to lengthen by two months at the end of the $21^{st}$ century compared to the present. The annual highest temperature and its fluctuation is expected to increase. Accordingly, the heat damage is also expected to increase. The result of this study can be used as an information on damage prevention measures due to temperature extreme events.