• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2946-2952
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• 2014

Among the Example based Super Resolution(SR) techniques, Neighbor embedding(NE) has been inspired by manifold learning method, particularly locally linear embedding. However, the poor generalization of NE decreases the performance of such algorithm. The sizes of local training sets are always too small to improve the performance of NE. We propose the Learning Sparse-Neighbor Image Representation baesd on SVR having an excellent generalization ability to solve this problem. Given a low resolution image, we first use bicubic interpolation to synthesize its high resolution version. We extract the patches from this synthesized image and determine whether each patch corresponds to regions with high or low spatial frequencies. After the weight of each patch is obtained by our method, we used to learn separate SVR models. Finally, we update the pixel values using the previously learned SVRs. Through experimental results, we quantitatively and qualitatively confirm the improved results of the proposed algorithm when comparing with conventional interpolation methods and NE.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.23-32
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• 2024

NVS (Novel View Synthesis) is a field in computer vision that reconstructs new views of a scene from a set of input views. Real-time rendering and high performance are essential for NVS technology to be effectively utilized in various applications. Recently, 3D-GS (3D Gaussian Splatting) has gained popularity due to its faster training and inference times compared to those of NeRF (Neural Radiance Fields)-based methodologies. However, since 3D-GS reconstructs a 3D (Three-Dimensional) scene by splitting and cloning (Density Control) Gaussian points, the number of Gaussian points continuously increases, causing the model to become heavier as training progresses. To address this issue, we propose two methodologies: 1) Gaussian blending, an improved density control methodology that removes unnecessary Gaussian points, and 2) a performance enhancement methodology using a depth estimation model to minimize the loss in representation caused by the blending of Gaussian points. Experiments on the Tanks and Temples Dataset show that the proposed methodologies reduce the number of Gaussian points by up to 4% while maintaining performance.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.496-501
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• 2005

This paper presents experimental results of the frequency offset locking of He-Ne lasers and the stability analysis. The master laser is free running, and the slave laser is a single-mode operating laser. The frequency difference of two lasers is stabilized to 200 MHz which can be synchronized using PLL servo. The measured beat frequency between two lasers was 200.004 MHz ${\pm}$ 0.15 MHz. The square root of Allan variance as a measure of stability in time domain is also measured. The long-term stability of the beat was worse than sort-term stability. With a gate time $\tau=1000\;s$, the square root of Allan variance was about 1 GHz. The results of the square root of Allan variance of the stabilized beat signal was a gate time of $\tau=1000\;s$, the square root of Allan variance was about 1.5 kHz. The long-term stability was improved by more than several hundred times compared with that without the stabilization.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.119-122
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• 2007

Dual auxiliary pulses are adopted in an AC PDP with an auxiliary electrode. The secondary auxiliary pulse of dual auxiliary pulses efficiently utilizes priming particles and contributes to improved luminous efficacy. A shorter time interval between the two auxiliary pulses resulted in better efficacy. The maximum luminous efficacy was approximately 12 lm/W according to measurement of the discharge in a Ne+20%Xe gas-mixture and green cells.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2286-2309
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• 2016

Overlay networks have been widely deployed upon the Internet by Service Providers (SPs) to provide improved network services. However, the interaction between each overlay and traffic engineering (TE) as well as the interaction among co-existing overlays may occur. In this paper, we adopt both non-cooperative and cooperative game theory to analyze these interactions, which are collectively called hybrid interaction. Firstly, we model a situation of the hybrid interaction as an n+1-player non-cooperative game, in which overlays and TE are of equal status, and prove the existence of Nash equilibrium (NE) for this game. Secondly, we model another situation of the hybrid interaction as a 1-leader-n-follower Stackelberg-Nash game, in which TE is the leader and co-existing overlays are followers, and prove that the cost at Stackelberg-Nash equilibrium (SNE) is at least as good as that at NE for TE. Thirdly, we propose a cooperative coalition mechanism based on Shapley value to overcome the inherent inefficiency of NE and SNE, in which players can improve their performance and form stable coalitions. Finally, we apply distinct genetic algorithms (GA) to calculate the values for NE, SNE and the assigned cost for each player in each coalition, respectively. Analytical results are confirmed by the simulation on complex network topologies.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.57-67
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• 2022

The curing characteristics of naphthalene type epoxy resin systems according to the change of curing agent were investigated to develop a new next-generation EMC(Epoxy Molding Compound) with excellent warpage characteristics, low thermal expansion, and excellent fluidity for WLP(Wafer Level Package). As epoxy resins, DGEBA, which are representative bisphenol type epoxy resins, NE-16, which are the base resins of naphthalene type epoxy resins, and NET-OH, NET-MA, and NET-Epoxy resins newly synthesized based on NE-16 were used. As a curing agent, DDM (Diamino Diphenyl Methane) and CBN resin with naphthalene moiety were used. The curing reaction characteristics of these epoxy resin systems with curing agents were analyzed through thermal analysis experiments. In terms of curing reaction mechanism, DGEBA and NET-OH resin systems follow the nth curing reaction mechanism, and NE-16, NET-MA and NET-Epoxy resin systems follow the autocatalytic curing reaction mechanism in the case of epoxy resin systems using DDM as curing agent. On the other hand, it was found that all of them showed the nth curing reaction mechanism in the case of epoxy resin systems using CBN as the curing agent. Comparing the curing reaction rate, the epoxy resin systems using CBN as the curing agent showed a faster curing reaction rate than them with DDM as a hardener in the case of DGEBA and NET-OH epoxy resin systems following the same nth curing reaction mechanism, and the epoxy resin systems with a different curing mechanism using CBN as a curing agent showed a faster curing reaction rate than DDM hardener systems except for the NE-16 epoxy resin system. These reasons were comparatively explained using the reaction rate parameters obtained through thermal analysis experiments. Based on these results, low thermal expansion, warpage reduction, and curing reaction rate in the epoxy resin systems can be improved by using CBN curing agent with a naphthalene moiety.

• Proceedings of the KIEE Conference
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• 1997.07e
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• pp.1666-1668
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• 1997

This paper reports the optimal gas mixing ratio for color plasma display panel to improve luminous efficiency using gas dischage simulation which contains energy equation. We verified a simulation by measuring vacuum ultraviolet. The luminous efficiency has improved considerably(about 30%) by adding Ar (0.5%), compared with Ne-Xe(4%) mixing gas.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.459-472
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• 2011

The vast number of biomedical literature is an important source of biomedical interaction information discovery. However, it is complicated to obtain interaction information from them because most of them are not easily readable by machine. In this paper, we present a method for extracting biomedical interaction information assuming that the biomedical Named Entities (NEs) are already identified. The proposed method labels all possible pairs of given biomedical NEs as INTERACTION or NO-INTERACTION by using a Maximum Entropy (ME) classifier. The features used for the classifier are obtained by applying various NLP techniques such as POS tagging, base phrase recognition, parsing and predicate-argument recognition. Especially, specific verb predicates (activate, inhibit, diminish and etc.) and their biomedical NE arguments are very useful features for identifying interactive NE pairs. Based on this, we devised a twostep method: 1) an interaction verb extraction step to find biomedically salient verbs, and 2) an argument relation identification step to generate partial predicate-argument structures between extracted interaction verbs and their NE arguments. In the experiments, we analyzed how much each applied NLP technique improves the performance. The proposed method can be completely improved by more than 2% compared to the baseline method. The use of external contextual features, which are obtained from outside of NEs, is crucial for the performance improvement. We also compare the performance of the proposed method against the co-occurrence-based and the rule-based methods. The result demonstrates that the proposed method considerably improves the performance.

• ALGAE
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• v.34 no.2
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• pp.177-185
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• 2019

Ecklonia cava is popular in Korea as a marine functional materials. E. cava is generally collected and used on the coast of Jeju Island. However, the continuous use of collected natural E. cava may be limited because difficult to secure throughout the year and may be exposed to environmental pollution. Jeju magma seawater (MSW) was known to be significant advantages such as safety, cleanness, stability, and functional improvement. Attempts have been reported on application of MSW to the culturing of macro- and microalgae and showed improved results. Thus, the objective of the present study was to explore the anti-melanogenesis activity of brown seaweed E. cava (E. cava cultured with MSW [MSWE]) extract cultured in tanks with MSW of Jeju Island to evaluate the possibility of cosmeceutical industrial application. MSWE extract showed the higher polyphenolic and dieckol contents than natural E. cava (NE) extract. Anti-melanogenesis activity of MSWE extract and NE extract are tested and compared using tyrosinase and dihydroxyphenylalanine (DOPA) oxidation inhibition assay. MSWE extracts evidenced more effective tyrosinase and DOPA oxidation inhibition activity than that of the NE extracts and the commercial whitening agent, arbutin. MSWE extracts also markedly inhibited melanin synthesis and decreased the expression of melanogenesis-related protein in ${\alpha}$-melanocyte stimulating hormone-stimulated B16F10 melanoma cells without cytotoxicity. These results suggest that MSW cultivation process would be more effective in releasing bioactive compounds with whitening effect from seaweed such as E. cava at an industrial scale.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.