• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2010년도 하계학술대회 논문집
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• pp.120-120
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• 2010

To detect the PD events, we have studied a fusion sensor, the UHF sensor and the single-walled carbon nanotube(SWNT) gas sensor. We are accustomed to the UHF sensor which have employed to detect the partial discharges in apparatus GIS-like. But the SWNT gas sense is a newly way proposed to detect the partial discharges. In this study, we monitored not only the changes of the electrical conductance of the SWNT sensors in responding to the PD events but also the signal of the UHF sensor at the same time with IEC 60270 standard method for reference on the partial discharge events.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2010년도 하계학술대회 논문집
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• pp.173-173
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• 2010

We proposed viewing angle switchable liquid crystal display(LCD) associated with fringe-field switching (FFS) mode with high aperture ratio characteristic. In the device, single pixel is separated into two regions, named as main pixel for displaying images and sub pixel for viewing angle control. In sub pixel region, add the common electrode on the top substrate and the initial alignment of liquid crystal is Hybrid Alignment Nematic (HAN) state. In conclusion, we suggested that the device has high aperture ratio characteristic because the LC directors are rotated in which viewing angle control region are generated fringe electric field.

• 한국정밀공학회지
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• 제32권5호
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• pp.463-470
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• 2015

Solar cell is typical representative of renewable green energy. Silicon wafer contributes about 66 percent to its cost structure. In its manufacturing, micro-cracks are often occurred due to manufacturing process such as wire sawing, grinding and cleaning. Their detection and classification are important to process feedback information. In this paper, a classification method of micro-cracks is proposed, based on the fusion of principal component analysis(PCA) and neural network. The proposed method shows that it gives higher results than single application of two methods, in terms of shape and size classification of micro-cracks.

• Journal of Mechanical Science and Technology
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• 제15권1호
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• pp.26-34
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• 2001

Most research to date concerning the cryogenic toughness of austenitic stainless steels has concentrated on the base metal and weld metal in weldments. The most severe problem faced on the conventional austenitic stainless steel is the thermal aging degradation such as sensitization and carbide induced embrittlement. In this paper, we investigate the cryogenic toughness degradation which can be occurred for austenitic stainless in welding. The test materials are austenitic stainless JN1, JJ1 and JK2 steels, which are materials recently developed for use in nuclear fusion apparatus at cryogenic temperature. The small punch(SP) test was conducted to detect similar isothermally aging condition with material degradation occurred in service welding. The single-specimen unloading compliance method was used to determine toughness degradation caused by thermal aging for austenitic stainless steels. In addition, we have investigated size effect on fracture toughness by using 20% side-grooved 0.5TCT specimens.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.411-425
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• 2021

In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

• 로봇학회논문지
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• 제13권4호
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• pp.237-247
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• 2018

In this paper, we describe a sensor module that monitors fire environment by analyzing fire characteristics. We analyzed the smoke characteristics of indoor fire. Six different environments were defined according to the type of smoke and the flame, and the sensors available for each environment were combined. Based on this analysis, the sensors were selected from the perspective of firefighter. The sensor module consists of an RGB camera, an infrared camera and a radar. It is designed with minimum weight to fit on the robot. the enclosure of sensor is designed to protect against the radiant heat of the fire scene. We propose a single camera mode, thermal stereo mode, data fusion mode, and radar mode that can be used depending on the fire scene. Thermal stereo was effectively refined using an image segmentation algorithm, SLIC (Simple Linear Iterative Clustering). In order to reproduce the fire scene, three fire test environments were built and each sensor was verified.

• 한국멀티미디어학회논문지
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• 제25권6호
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• pp.819-832
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• 2022

Cross-domain recommender system transfers knowledge across different domains to improve the recommendation performance in a target domain that has a relatively sparse model. However, they suffer from the "negative transfer" in which transferred knowledge operates as noise. This paper proposes a novel Multiple Fusion-based Deep Cross-Domain Recommendation named MFDCR. We exploit Doc2Vec, one of the famous word embedding techniques, to fuse data user-wise and transfer knowledge across multi-domains. It alleviates the "negative transfer" problem. Additionally, we introduce a simple multi-layer perception to learn the user-item interactions and predict the possibility of preferring items by users. Extensive experiments with three domain datasets from one of the most famous services Amazon demonstrate that MFDCR outperforms recent single and cross-domain recommendation algorithms. Furthermore, experimental results show that MFDCR can address the problem of "negative transfer" and improve recommendation performance for multiple domains simultaneously. In addition, we show that our approach is efficient in extending toward more domains.

• 한국발생생물학회:학술대회논문집
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• 한국발생생물학회 2003년도 제3회 국제심포지움 및 학술대회
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• pp.133-133
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• 2003

Recently, sperm has been used as a vector to carry exogenous genes for the production of transgenic animals. However, the success in cattle is low, due to deficiencies in oocyte activation and sperm decondensation caused by high disulphide bond (S=S) content in mature sperm. This study was carried out to develop an effective method for producing transgenic animals with round spermatids (RS). Two methods of embryo production - electric fusion (EC) or intracyto-plasmic injection (IC) and three activation treatments were compared. RS were isolated from bull testes by Percoll density gradients (20, 35, 40, 45 and 90%). Fusion between ooplast and RS was performed with a single DC electric pulse (1.0 KV/cm, 45 sec) in 0.28 M mannitol solution supplemented with 100 M CaCl2 and 100 M MgCl$_2$. (중략)

• ETRI Journal
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• 제45권5호
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• pp.862-873
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• 2023

Determining whether an autonomous self-driving agent is in the middle of an intersection can be extremely difficult when relying on visual input taken from a single camera. In such a problem setting, a wider range of views is essential, which drives us to use three cameras positioned in the front, left, and right of an agent for better intersection recognition. However, collecting adequate training data with three cameras poses several practical difficulties; hence, we propose using data collected from one camera to train a three-camera model, which would enable us to more easily compile a variety of training data to endow our model with improved generalizability. In this work, we provide three separate fusion methods (feature, early, and late) of combining the information from three cameras. Extensive pedestrian-view intersection classification experiments show that our feature fusion model provides an area under the curve and F1-score of 82.00 and 46.48, respectively, which considerably outperforms contemporary three- and one-camera models.

• 한국안전학회지
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• 제25권6호
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• pp.14-21
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• 2010

A miniature single solder ball joint is designed to mimic the actual solder joints used in the micro-electric industries. Shear tests were conducted to evaluate the mechanical behavior of miniature single solder joints at intermediate strain rates from $0.019\;s^{-1}$ to $2.16\;s^{-1}$ at room temperature. The shear fracture strength of the present solder ball joints generally increased with increasing shear strain rate, ranging from 32 to 51MPa. This behavior is affected by the sensitivity of bulk solder strength to strain rate. Shear fracture mode changed from brittle to partial ductile (failure inside the bulk solder) with an increase of shear speed. The unloading shear fracture toughness is generally consistent with the measure of the amount of bulk solder on the fractured surface.