• 제목/요약/키워드: Micro Feature

검색결과 186건 처리시간 0.03초

마이크로 플라즈마 전극가공을 위한 FIB 연구

  • 최헌종;강은구;이석우;홍원표
    • 한국반도체및디스플레이장비학회:학술대회논문집
    • /
    • 한국반도체및디스플레이장비학회 2004년도 춘계학술대회 발표 논문집
    • /
    • pp.229-233
    • /
    • 2004
  • The application of focused ion beam (FIB) technology in micro/nano machining has become increasingly popular. Its use in micro/nano machining has advantages over contemporary photolithography or other micro/nano machining technologies such as small feature resolution, the ability to process without masks and being accommodating for a variety of materials and geometries. This paper was carried out some experiments of the micro plasma electrode fabrications using FIB. The sputtering of FIB has one major problem that is redeposited by sputtered material including $Ga^+$ ion source. Therefore we have verified the effect of the reposition by EDX. And the optimal condition is suggested to machine the micro plasma electrode.

  • PDF

적층 공정에서의 상태 기반 모니터링 (Condition Monitoring in Multilayer Stacking Processes)

  • 민형철;이영곤;정해동;박승태;이승철
    • 한국소음진동공학회:학술대회논문집
    • /
    • 한국소음진동공학회 2014년도 추계학술대회 논문집
    • /
    • pp.739-742
    • /
    • 2014
  • In the process of MLCC manufacturing, MLCC stacking process is the key process of making high quality MLCC. Since MLCC is small components, the entire process of MLCC stacking process is minute and sensitive to micro errors. To prevent micro error, we suggest condition-based monitoring which quantifies error based on feature extraction and quantifying error method. As results, it has been shown that the suggested algorithm has effectiveness of condition based monitoring of MLCC stacker.

  • PDF

MicroRNA-Gene Association Prediction Method using Deep Learning Models

  • Seung-Won Yoon;In-Woo Hwang;Kyu-Chul Lee
    • Journal of information and communication convergence engineering
    • /
    • 제21권4호
    • /
    • pp.294-299
    • /
    • 2023
  • Micro ribonucleic acids (miRNAs) can regulate the protein expression levels of genes in the human body and have recently been reported to be closely related to the cause of disease. Determining the genes related to miRNAs will aid in understanding the mechanisms underlying complex miRNAs. However, the identification of miRNA-related genes through wet experiments (in vivo, traditional methods are time- and cost-consuming). To overcome these problems, recent studies have investigated the prediction of miRNA relevance using deep learning models. This study presents a method for predicting the relationships between miRNAs and genes. First, we reconstruct a negative dataset using the proposed method. We then extracted the feature using an autoencoder, after which the feature vector was concatenated with the original data. Thereafter, the concatenated data were used to train a long short-term memory model. Our model exhibited an area under the curve of 0.9609, outperforming previously reported models trained using the same dataset.

Design and estimation of a sensing attitude algorithm for AUV self-rescue system

  • Yang, Yi-Ting;Shen, Sheng-Chih
    • Ocean Systems Engineering
    • /
    • 제7권2호
    • /
    • pp.157-177
    • /
    • 2017
  • This research is based on the concept of safety airbag to design a self-rescue system for the autonomous underwater vehicle (AUV) using micro inertial sensing module. To reduce the possibility of losing the underwater vehicle and the difficulty of searching and rescuing, when the AUV self-rescue system (ASRS) detects that the AUV is crashing or encountering a serious collision, it can pump carbon dioxide into the airbag immediately to make the vehicle surface. ASRS consists of 10-DOF sensing module, sensing attitude algorithm and air-pumping mechanism. The attitude sensing modules are a nine-axis micro-inertial sensor and a barometer. The sensing attitude algorithm is designed to estimate failure attitude of AUV properly using sensor calibration and extended Kalman filter (SCEKF), feature extraction and backpropagation network (BPN) classify. SCEKF is proposed to be used subsequently to calibrate and fuse the data from the micro-inertial sensors. Feature extraction and BPN training algorithms for classification are used to determine the activity malfunction of AUV. When the accident of AUV occurred, the ASRS will immediately be initiated; the airbag is soon filled, and the AUV will surface due to the buoyancy. In the future, ASRS will be developed successfully to solve the problems such as the high losing rate and the high difficulty of the rescuing mission of AUV.

비행 단계별 특성벡터 융합을 통한 효과적인 탄두 식별방법 (Efficient Recognition Method for Ballistic Warheads by the Fusion of Feature Vectors Based on Flight Phase)

  • 최인오;김시호;정주호;김경태;박상홍
    • 한국전자파학회논문지
    • /
    • 제30권6호
    • /
    • pp.487-497
    • /
    • 2019
  • 탄도미사일은 작은 레이다 단면적 및 빠른 기동 특성으로 인하여 탐지가 매우 힘들며, 또한 탄도미사일의 각 비행단계에서 탄두와 유사한 운동 변수로 기동하는 연료탱크 및 기만체의 존재로 인하여 탄두의 식별 및 요격이 매우 어렵다. 따라서 비행 단계에 따라 표적의 기동 및 미세운동을 이용한 특성벡터가 필요하며, 또한 이를 적절히 융합하여 비행단계에 상관없이 식별하는 방법이 요구된다. 본 연구에서는 탄도미사일의 비행단계에 따른 유용한 특성벡터를 소개하고, 이를 특성벡터 및 구분기 레벨에서 융합하는 효과적인 기법을 제안한다. CAD 모델들을 사용하여 예측된 레이다 신호들로 시뮬레이션을 수행한 결과, 구분기 레벨 융합을 통하여 잡음환경 내에서 비행단계에 상관없이 종말 단계로 갈수록 보다 향상된 탄두 식별이 가능하였다.

Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

  • Yeom, Ha-Neul;Hwang, Myunggwon;Hwang, Mi-Nyeong;Jung, Hanmin
    • Journal of Information Science Theory and Practice
    • /
    • 제2권3호
    • /
    • pp.29-39
    • /
    • 2014
  • In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

채널 형상에 따른 마이크로 판형열교환기의 열적 특성 연구 (The Study on Thermal Characteristics in Micro Plated Heat Exchangers with Channel Shapes)

  • 김윤호;서장원;문정은;이규정
    • 대한기계학회:학술대회논문집
    • /
    • 대한기계학회 2007년도 춘계학술대회B
    • /
    • pp.1894-1899
    • /
    • 2007
  • This paper presents the thermal characteristics for micro heat exchanger with different micro-channel shapes. The shapes of micro-channel has been manufactured sheet metal by chemical etching for the I shape of straight channel and V and W shapes of chevron feature and fabricated micro plated heat exchangers using the vacuum brazing of bonding technology. The experimental study has been performed on heat transfer and pressure drop characteristics with various Reynolds number for water to water at the counter flows. The average heat transfer rate of V and W shapes has been showed about 1.5${\sim}$1.6 times large than those of I shape. For the comparison of Nusselt number, it is known that the convective heat transfer of V and W shapes represent more effect than I shape. The pressure drops of V and W shapes are about 1.2${\sim}$1.7 times lager than those of I shape.

  • PDF

Micro-Expression Recognition Base on Optical Flow Features and Improved MobileNetV2

  • Xu, Wei;Zheng, Hao;Yang, Zhongxue;Yang, Yingjie
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제15권6호
    • /
    • pp.1981-1995
    • /
    • 2021
  • When a person tries to conceal emotions, real emotions will manifest themselves in the form of micro-expressions. Research on facial micro-expression recognition is still extremely challenging in the field of pattern recognition. This is because it is difficult to implement the best feature extraction method to cope with micro-expressions with small changes and short duration. Most methods are based on hand-crafted features to extract subtle facial movements. In this study, we introduce a method that incorporates optical flow and deep learning. First, we take out the onset frame and the apex frame from each video sequence. Then, the motion features between these two frames are extracted using the optical flow method. Finally, the features are inputted into an improved MobileNetV2 model, where SVM is applied to classify expressions. In order to evaluate the effectiveness of the method, we conduct experiments on the public spontaneous micro-expression database CASME II. Under the condition of applying the leave-one-subject-out cross-validation method, the recognition accuracy rate reaches 53.01%, and the F-score reaches 0.5231. The results show that the proposed method can significantly improve the micro-expression recognition performance.

RFID Tag Protection using Face Feature

  • Park, Sung-Hyun;Rhee, Sang-Burm
    • 반도체디스플레이기술학회지
    • /
    • 제6권2호
    • /
    • pp.59-63
    • /
    • 2007
  • Radio Frequency Identification (RFID) is a common term for technologies using micro chips that are able to communicate over short-range radio and that can be used for identifying physical objects. RFID technology already has several application areas and more are being envisioned all the time. While it has the potential of becoming a really ubiquitous part of the information society over time, there are many security and privacy concerns related to RFID that need to be solved. This paper proposes a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. This method improved linear discriminant analysis has reduced the dimension of feature information which has large size of data. Therefore, face feature information can be stored in small memory field of RFID tag. The proposed algorithm in comparison with other previous methods shows better stability and elevated detection rate and also can be applied to the entrance control management system, digital identification card and others.

  • PDF

FIB를 이용한 나노가공공정 기술 개발 (Development of Nano Machining Technology using Focused ion Beam)

  • 최헌종;강은구;이석우;홍원표
    • 한국공작기계학회:학술대회논문집
    • /
    • 한국공작기계학회 2004년도 춘계학술대회 논문집
    • /
    • pp.482-486
    • /
    • 2004
  • The application of focused ion beam (FIB) technology in micro/nano machining has become increasingly popular. Its use in micro/nano machining has advantages over contemporary photolithography or other micro/nano machining technologies, such as small feature resolution, the ability to process without masks and being accommodating for a variety of materials and geometries. This paper presents that the recent development and our research goals in FIB nano machining technology are given. The emphasis will be on direct milling, or chemical vapor deposition techniques (CVD), and this can distinguish the FIB technology from the contemporary photolithography process and provide a vital alternative to it. After an introduction to the technology and its FIB principles, the recent developments in using milling or deposition techniques for making various high-quality devices and high-precision components at the micro/nano meter scale are examined and discussed. Finally, conclusions are presented to summarize the recent work and to suggest the areas for improving the FIB milling technology and for studying our future research.

  • PDF