• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.25-31
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• 2022

By an aid of needle coating, we have fabricated a spherical microlens array using poly(methyl methacrylate) for potential applications in light extraction of organic light-emitting diodes. With an attempt to achieve high-density and high-aspect-ratio microlens arrays, we have investigated the coating behaviors by varying the material parameters such as the solute concentration and wettability of the poly(methyl methacrylate) solution and process parameters such as the dwell time of needle near the substrate, retract distance of needle from the substrate, and coating gap between the needle and substrate. Under the optimized coating conditions, it is demonstrated that high-aspect-ratio microlens arrays can be obtained using a coating solution with high solute concentration and a small amount of a hydrophobic solvent. It is found that the diameter and height of microlens array are decreased with increasing poly(methyl methacrylate) concentration, yet the overall aspect ratio is rather enhanced. By the addition of 5 wt% hexylamine in 35 wt% poly(methyl methacrylate) solution, we have achieved a spherical microlens with the height of 7.7 ㎛ and the width of 94.24 ㎛ (the aspect ratio of 0.082). To estimate the capability of light extraction by the microlens array, we have performed ray tracing simulations and demonstrated that the light extraction efficiency of organic light-emitting diode is expected to be enhanced up to 24%.

• KSBB Journal
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• v.25 no.5
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• pp.437-442
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• 2010

The objective of this study was to investigate the effect of ultrasound on the extraction of oil from canola seeds when supercritical carbon dioxide ($SCCO_2$) was used as an extraction solvent. The ultrasound-assisted $SCCO_2$ extraction were carried out while varying such operating parameters as particle size of crushed canola seed, flow rate of $SCCO_2$, aspect ratio of the extraction vessel, and ultrasound power. The extraction rate decreased with increasing particle size of samples, showing a maximun at a $CO_2$ flow rate of 6.2 L/min. Both the extraction rate and extraction yield increased with a decrease in the aspect ratio of the extraction vessel. For the ultrasoundassisted $SCCO_2$ extraction, the extraction yield was slightly increased when the $CO_2$ flow rate was below 6 mL/min with sample A and B.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.1-27
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• 2021

The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals' perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.2
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• pp.129-138
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• 2017

This paper has been shown for the extraction of Doppler signature from the radar signal for an air-breathing targets tracked in the ground radar. For the extractions, a Doppler resolution is confirmed from mathematical modeling of PT(pulse train) waveform. Doppler signatures of air-breathing target are varied to radar aspect angle of engine and are determined from physical parameter of jet engine. To confirm such Doppler signatures, the radar signal reflected from the air-breathing target is obtained by our radar signal storage. After this extraction, radar aspect angle of engine has estimated from tracking information. Relative differences of Doppler signatures to radar aspect angle of engine is verified from these results and Doppler profiles for radar target identification appliance are presented.

• Knowledge Management Research
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• v.21 no.4
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• pp.157-173
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• 2020

In accommodation sharing economy, customers take a risk of uncertainty about product quality, which is an important factor affecting users' satisfaction. This risk can be lowered by the information disclosed by the facility provider. Self-presentation of the hosts can make a positive effect on listing performance by eliminating psychological distance through emotional interaction with users. This paper analyzed the self-presentation text provided by Airbnb hosts and found key aspects in the text. In order to extract the aspects from the text, host descriptions were separated into sentences and applied the Attention-Based Aspect Extraction method, an unsupervised neural attention model. Then, we investigated the relationship between aspects in the host description and the listing performance via linear regression models. In order to compare their impact between the three facility types(Entire home/apt, Private rooms, and Shared rooms), the interaction effects between the facility types and the aspect summaries were included in the model. We found that specific aspects had positive effects on the performance for each facility type, and provided implication on the marketing strategy to maximize the performance of the shared economy.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1775-1781
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• 2016

Generally, in the underwater target recognition, feature vectors are extracted from the target signal utilizing spatial information according to target shape/material characteristics. In addition, various signal processing techniques have been studied to extract feature vectors which are less sensitive to the location of the receiver. In this paper, we synthesized active echo signals using 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to echo signals to extract signal features. For the performance verification, classification experiments were performed using backpropagation and probabilistic neural network classifiers based on single aspect and multi-aspect method. As a result, we obtained a better recognition result using proposed feature extraction and multi-aspect based method.

• The Korean Journal of Food And Nutrition
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• v.32 no.5
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• pp.504-510
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• 2019

The purpose of this study was to compare the effects of soaking and ultrasonic extraction by observing the change of contents with extraction time of physicochemical properties (solid content, colorness, caffeine, chlorogenic acid, total polyphenols, DPPH, and ABTS). As a result of the analysis, solid content increased with longer extraction time and the whiteness tended to decrease with longer extraction time. Conversely, the extraction of functional materials showed a tendency to increase as the extraction time increased. Caffeine reached the maximum value after two hours soaking, but showed the same result as one hour for sonication. Chlorogenic acid did not show difference from the content of coffee extracted for one hour soaking only by sonication extraction for 30 minutes. The total polyphenols eluted with approximately two hours of soaking even after 30 minutes of sonication. DPPH and ABTS were insignificant in their concentrations, but their antioxidative effect was more than two hours of soaking with only 30 minutes of sonication. Sonication has a short time extraction from a functional aspect (caffeine content, chlorogenic acid, polyphenol content, and antioxidant capacity) and this experiment can provide basic data for the development of innovative recipes.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1236-1239
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• 2002

When we see an object, we usually can say what it is easily even for the case where the object isn't shown in the frontal view. However, it is difficult to believe that all views of every object we have ever seen are fully memorized in our brain. Possibly, when an object is shown, we have some typical views of the object in our brain through our past experience and reconstruct the view to recognize what the presented object is. Non-negative Matrix Factorization (NMF) is one of the methods to extract the basis images from sample data set. The prominent feature of this method is that the reconstructed image is obtained by only additions of the basis images with suitable positive weights. So NMF can be seen more biologically plausible method than any other feature extraction methods such as Vector Quantization (VQ) and principal Component Analysis (PCA). In this paper, we adopt NMF to extract the aspect features from the set of images, which consists of various views of a given object. Some experiments are shown how much well NMF can extract the aspect features than any other methods such as VQ and PCA.

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.255-257
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• 1989

This paper proposes a method for extracting the imformation of aspect and modality from the predicative part which is consisted of main verbal and auxiiary verbals.Data which are expressed by the compound predicate with many consecutive verbals are collected and analyzed to thirty-six structual forms of the predicative part.Inthe final analysis, an extracting function of conceptual information is derived to find the connoted aspect and modality in each structure.The informations which are obtained by this function decrease the individual ambiguity of an auxiliary verbal and offer a detailed meaning inthe syntactic and semantic analysis of machine translation system or inference machine.

• Journal of the Korean Geographical Society
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• v.39 no.2
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• pp.283-296
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• 2004

More than 0.5 percent of land in Korea is used for cemetery and the rate is growing in spite of the increase in cremation these days. The systematic management of tombs may be possible through the ‘Feature Extraction’ method which is applied to the high-resolution satellite imagery. For this reason, this research focused on finding out the radiometric characteristics of tombs and the classification of them. An IKONOS image of northwest areas of Seoul with 8km x 10km dimension was analyzed. After sampling 24 tombs in the study area, the statistical radiometric characteristics of tombs are analyzed. And tombs were classified based on the criteria such as landscape, NDVI, and cluster analysis. In addition, it was investigated if the aspect or slope of the terrain influenced to the classification of tombs. As a result of this research, authors find that there is similarity between the classification tv NDVI and the classification through cluster analysis. And aspect or slope didn't have much influence on the classification of tombs.