• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.247-253
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• 2023

As climate change problem has recently become serious, studies are being conducted to identify carbon dioxide (CO₂) emission dynamics based on satellite data to reduce emissions. It is also very important to analyze spatial patterns by estimating and mapping CO₂ emissions dynamic. Therefore, in this study, CO₂ emissions in the Korean Peninsula from 2013 to 2020 were estimated and mapped. To spatially estimate and map emissions, we use the enhanced vegetation index adjusted nighttime light index, an index that combines nighttime light (NTL) and vegetation index, to map both areas where NTL is observed and areas where NTL is not observed. In order to spatially estimate and map CO₂ emissions, the total annual emissions of the Korean Peninsula were calculated, resulting in an increase of 11% from 2013 to 2017 and a decrease of 13% from 2017 to 2020. As a result of the mapping, it was confirmed that the spatial pattern of CO₂ emissions in the Korean Peninsula were concentrated in urban areas. After being divided into 17 regions, which included the downtown area, the metropolitan area accounted for roughly 40% of CO₂ emissions in the Korean Peninsula. The region that exhibited the most significant change from 2013 to 2020 was Sejong City, showing a 96% increase.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.2
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• pp.87-94
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• 2023

Fresh bakery products are widely consumed worldwide and therefore particular requirements for their quality characteristics have been established. The shelf life of bakery products is mainly subjected to microbial spoilage and staling. This study investigated the optimum conditions of modified atmosphere packaging (MAP) application to extend the shelf life of the bakery products. The gas conditions of the headspace in 'Baumkuchen' cake were 0, 30, 70, and 100% CO₂ concentrations and stored at 30℃ for 5 days. The bakery samples were evaluated weight loss, hardness, color change, pH and total aerobic bacteria, yeast and molds count throughout the storage period. Values of the weight loss and hardness were increased over the storage period, meanwhile pH was significantly decreased. However, no significant color changes were observed during storage. It was also found no significant difference between the different gas treatments. Total aerobic bacteria count of the stored samples after day 5 was increased by 6.94 log CFU/g in the air filled package, compared to 6.20 log CFU/g in the 100% CO₂ filled package and 6.02 log CFU/g in the 70% CO₂ filled package. Yeast and molds count were 3.65 log CFU/g in air filled package, 2.66 log CFU/g in 100% CO₂ filled package, 2.64 log CFU/g in 70% CO₂ filled package, 2.86 log CFU/g in 30% CO₂ filled package and 3.31 log CFU/g in 100% N₂ filled package on day 2. In conclusion, it was shown that 70% and 100% CO₂ treatments in the package were effective to reduce microbial growth.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.645-651
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• 2007

In general, contours in digital vector maps, which represent terrain characteristics and shape, are created by 3D digitizing the same height points using aerial photographs on the analytical or digital plotters with stereoscopic viewing. Hence, it requires lots of task, and subjective decision and experience of the operators. DTMs are generated indirectly by using contours since the national digital maps do not include digital terrain model (DTM) data. In this study, model key points which depict the important information about terrain characteristics were extracted from the contours. Further, determination of the efficient and flexible grid sizes were proposed to generate optimal DTM in terms of both quantitative and qualitative aspects. For this purpose, a progressive sampling technique was implemented, i.e., the smaller grid sizes are assigned for the mountainous areas where have large relief while the larger grid sizes are assigned for the relatively flat areas. In consequence, DTMs with multi-grid for difference areas could be generated instead of DTMs with a fixed grid size. The multi-grid DTMs reduce computations for data processing and provide fast display.

• The Journal of the Acoustical Society of Korea
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• v.21 no.8
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• pp.708-718
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• 2002

In this paper, the problems in identifying the noise sources by using the sound intensity technique are dealt with for the general radiated near-field from vibro-acoustic sources. For this purpose, a three-dimensional model structure resembling the engine room of a car or heavy equipment is considered. Similar to the practical situations, the model contains many mutually coherent and incoherent noise sources distributed on the complicated surfaces. The sources are located on the narrow, connected, reflecting planes constructed with rigid boxes, of which a small clearance exists between the whole box structure and the reflecting bottom. The acoustic boundary element method is employed to calculate the acoustic intensity at the near-field surfaces and interior spaces. The effects of relative source phases, frequencies, and locations are investigated, from which the results are illustrated by the contour map, vector plot, and energy streamlines. It is clearly observed that the application of sound intensity technique to the reactive or reverberant field, e.g., scanning over the upper engine room as is usually practiced, can yield the detection of fake sources. For the precise result for such a field, the field reactivity should be checked a priori and the proper effort should be directed to reduce or improve the reactivity of sound field.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.111-122
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• 2015

This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.

• Korean Journal of Remote Sensing
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• v.32 no.3
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• pp.253-262
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• 2016

Here, we estimated daily Photosynthetically Available Radiation (PAR) from Geostationary Ocean Colour Imager (GOCI) and compared it with daily PAR derived from polar-orbiting MODIS images. GOCI-based PAR was also validated with in-situ measurements from ocean research station, Socheongcho. GOCI PAR showed similar patterns with in-situ measurements for both the clear-sky and cloudy day, whereas MODIS PAR showed irregular patterns at cloudy conditions in some areas where PAR could not be derived due to the clouds of sunglint. GOCI PAR had shown a constant difference with the in-situ measurements, which was corrected using the in-situ measurements obtained on the days of clear-sky conditions at Socheongcho station. After the corrections, GOCI PAR showed a good agreement excepting on the days with so thick cloud that the sensor was optically saturated. This study revealed that GOCI can estimate effectively the daily PAR with its advantages of acquiring data more frequently, eight times a day at an hourly interval in daytime, than other polar orbit ocean colour satellites, which can reduce the uncertainties induced by the existence and movement of the cloud and insufficient images to map the daily PAR at the seas around Korean peninsula.

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.25-32
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• 2017

This paper proposes a novel acceleration method for particle based large scale fluid simulation. Traditional particle-based fluid simulation has been implemented by interacting with physical quantities of neighbor particles through the Smoothed Particle Hydrodynamics(SPH) technique[1]. SPH method has the characteristic that there is no visible change compared to the computation amount in a part where the particle movement is small, such as a calm surface or inter-fluid. This becomes more prominent as the number of particles increases. Previous work has attempted to reduce the amount of spare computation by adaptively dividing each part of the fluid. In this paper, we propose a technique to calculate the motion of the entire particles by using the physical quantities of the near sampled particles by sampling the particles inside the fluid at regular intervals and using them as reference points of the fluid motion. We propose a technique to adaptively generate a triangle map based on the position of the sampled particles in order to efficiently search for nearby particles, and we have been able to interpolate the physical quantities of particles using the barycentric coordinate system. The proposed acceleration technique does not perform any additional correction for two classes of fluid particles. Our technique shows a large improvement in speed as the number of particles increases. The proposed technique also does not interfere with the fine movement of the fluid surface particles.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.745-756
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• 2009

An autonomous virtual character can conduct itself like a human after recognizing and interpreting the virtual environment. Artificial vision is mainly used in the recognition of the environment for a virtual character. The present artificial vision that has been developed takes all the information at once from everything that comes into view. However, this can reduce the efficiency and reality of the system by saving too much information at once, and it also causes problems because the speed slows down in the dynamic environment of the game. Therefore, to construct a vision system similar to that of humans, a visual observation system which saves only the required information is needed. For that reason, this research focuses on the descriptive artificial intelligence engine which detects the most important information visually recognized by the character in the virtual world and saves it into the memory by degrees. In addition, a visual system is constructed in accordance with an image transaction theory to make it sense and recognize human feelings. This system finds the attention area of moving objects quickly and effectively through the experiment of the virtual environment with three dynamic dimensions. Also the experiment enhanced processing speed more than 1.6 times.

• Nutrition Research and Practice
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• v.8 no.5
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• pp.501-508
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• 2014

BACKGROUND/OBJECTIVES: Rubus Coreanus Miquel (RCM), used as a traditional Korean medicine, reduces chronic inflammatory diseases such as cancer and rheumatoid arthritis. However, its mechanism has not been elucidated. In this study, we examine the anti-inflammatory effects of RCM and their possible mechanisms using RAW 264.7 cells. MATERIALS/METHODS: Unripe RCM ethanol extract (UE), unripe RCM water extract (UH), ripe RCM ethanol extract (RE), and ripe RCM water extract (RH) were prepared. Inflammatory response was induced with LPS treatment, and expression of pro-inflammatory mediators (iNOS, COX-2, TNF-${\alpha}$, IL-$1{\beta}$, and IL-6) and NO and $PGE_2$ productions were assessed. To determine the anti-inflammatory mechanism of RCM, we measured NF-${\kappa}B$ and MAPK activities. RESULTS: UE and UH treatment significantly reduced NF-${\kappa}B$ activation and JNK and p38 phosphorylation and reduced transcriptional activities decreased iNOS, COX-2, and pro-inflammatory cytokines expressions, and NO and $PGE_2$ productions. RE and RH treatments reduced IL-$1{\beta}$ and IL-6 expressions through suppressions of JNK and p38 phosphorylation. CONCLUSIONS: In this study, we showed that RCM had anti-inflammatory effects by suppression of pro-inflammatory mediator expressions. Especially, unripe RCM showed strong anti-inflammatory effects through suppression of NF-${\kappa}B$ and MAPK activation. These findings suggest that unripe RCM might be used as a potential functional material to reduce chronic inflammatory responses.

• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.