• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2004.05a
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• pp.229-233
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• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.739-742
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• 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.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.294-299
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• 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.

• Ocean Systems Engineering
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• v.7 no.2
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• pp.157-177
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• 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.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.487-497
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• 2019

It is very difficult to detect ballistic missiles because of small cross-sections of the radar and the high maneuverability of the missiles. In addition, it is very difficult to recognize and intercept warheads because of the existence of debris and decoy with similar motion parameters in each flight phase. Therefore, feature vectors based on the maneuver, the micro-motion according to flight phase are needed, and the two types of features must be fused for the efficient recognition of ballistic warhead regardless of the flight phase. In this paper, we introduce feature vectors appropriate for each flight phase and an effective method to fuse them at the feature vector-level and classifier-level. According to the classification simulations using the radar signals predicted by the CAD models, the closer the warhead was to the final destination, the more improved was the classification performance. This was achieved by the classifier-level fusion, regardless of the flight phase in a noisy environment.

• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.29-39
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• 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.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.1894-1899
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• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.1981-1995
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• 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.

• Journal of the Semiconductor & Display Technology
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• v.6 no.2 s.19
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• pp.59-63
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• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.482-486
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• 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.