• Food Engineering Progress
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• v.13 no.3
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• pp.190-194
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• 2009

The aim of this study was to investigate the change of volatile aroma compounds in kimchi during fermentation, before and after drying process. Also, the encapsulation effect of cyclodextrin on volatiles during the drying process was examined. GC-MS was used for detection and identification of volatile compounds. During kimchi fermentation, in the early stage, dimethyl sulfide, carbon disulfide were detected as major compounds and after 7 days several sulfur compounds, dimethyl disulfide, methyl 2-propenyl disulfide, allyl methyl sulfide, and di-2-propenyl disulfide bacame the major volatiles. After vacuum-drying, the kimchi powder lost 11 compounds but still retained 13 volatiles of which major compounds were dimethyl sulfide, acetaldehyde and methanethiol. In order to keep volatiles in kimchi powder along with the drying process, 0.25-1.0% cyclodextrin was added in kimchi and dried-kimchi was prepared by using vacuum dryer. Cyclodextrin acted as an encapsulation agent for aroma compounds and it resulted in less loss of volatiles during drying process. Addition of cyclodextrin will permit industry-scale production of dried-kimchi powder with less loss of aroma compounds.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.543-551
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• 2006

Recently efforts to extract information about forests by using remote sensing techniques for efficient forest management have progressed actively. In terms of extraction of tree information using single remote sensing data, however, the accuracy of tree recognition and the quantity of extracted information is limited. The objective of this study is to carry out tree modeling in domestic environment applying the latest core technique for tree modeling using color aerial photographs and LiDAR data and to estimate the result of tree modeling. A small-scale coniferous forest was investigated in Daejeon. It was 0.77 that the $R^2$ of accuracy test of tree numbers that estimated with color aerial photography and LiDAR data. In terms of tree height, there was no difference between the estimated value and the field measurements in the case of the group accuracy test of the recently unchanged area. Moreover $R^2$ was 0.83 in the case of the individual accuracy test.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.871-884
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• 2021

The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that wasfinally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.26-49
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• 2018

The purpose of this study was to verify the reliability of the solar radiation model and discuss its applicability to the urban area of Seoul for summer heat stress mitigation. We extended the study area closer to the city scale and enhanced the spatial resolution sufficiently to determine pedestrian-level urban radiance. The domain was a $4km^2$ residential area with high-rise building sites. Radiance modelling (SOLWEIG) was performed with LiDAR (Light Detection and Ranging)-based detailed geomorphological land cover shape. The radiance model was evaluated using surface energy balance (SEB) observations. The model showed the highest accuracy on a clear day in summer. When the mean radiation temperature (MRT) was simulated, the highest value was for a low-rise building area and road surface with a low shadow effect. On the other hand, for high-rise buildings and vegetated areas, the effect of shadows was large and showed a relatively low value of mean radiation temperature. The method proposed in this study exhibits high reliability for the management of heat stress in urban areas at pedestrian height. It is applicable for many urban micro-climate management functions related to natural and artificial urban settings; for example, when a new urban infrastructure is planned.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.26-33
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• 2019

Recently, the rapid growth of the companion animal market has led to the development of animal disease diagnosis kits. Therefore, the utility of the introduction of biomarkers for the development of animal molecular diagnostics is being reevaluated. A good biomarker should be precise and reliable, distinguish between normal and diseased states, and differentiate between different diseases. Recently reported genetic markers, tumor markers (cell free DNA, circulating tumor cells, granzyme, and skin tumors), and others (brucellosis, programmed death recovery-1, symmetric dimethylarginine, periostin, and cysteinyl leukotrien) have been developed. The biomarkers are used for risk prediction or for the screening, diagnosis, and monitoring of disease progression. The most important criteria for related biomarkers are disease specificity. Many potential biomarkers have emerged from laboratory and test studies, but they have not been validated in independent or large-scale clinical studies. Candidate biomarkers evaluate disease associations, verify the effectiveness of biomarkers for early detection and disease progression, and incorporate them into humans and animals. In the future, it will be necessary to reevaluate the utility of well-structured biomarker-based research and study the development of kits that can be used in on-site tests in accordance with the trends introduced in the diagnosis of animal diseases.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1229-1238
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• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.52 no.5
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• pp.461-467
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• 2019

Several studies investigating the prevention and treatment of external parasites in farmed olive flounder Paralichthys olivaceus have found that the anticoccidial agent toltrazuril sulfone is an effective antiparasitic. Prior to undertaking a full-scale study, we developed analytical methods to detect the levels of toltrazuril and toltrazuril sulfone in farmed flounder samples using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-MS/MS). This analysis showed that LC-MS/MS changed the mobile phase and collision energy of toltrazuril and toltrazuril sulfone. This was validated using established conditions. Sample pre-treatment for this process involved extraction with dichloromethane and purification by liquid-liquid extraction in formic acid, acetonitrile, and h-hexane, followed by determination of all compounds by LC-MS/MS. Separation was achieved within 10 min by gradient elution using a Capcell Pak C18 ($3.0{\mu}m$, $100{\times}2.0mm$) analytical column (Shiseido UG 120V) with a mixture of 0.1% (v/v) formic acid and acetonitrile. Multiple reaction monitoring was used for selective detection of toltrazuril and toltrazuril sulfone. This method yields satisfactory results for linearity, precision, and limits of quantification. Therefore, the method established in our study will serve as a basis for further research on parasite control by toltrazuril and toltrazuril sulfone.

• Journal of the Korean Geotechnical Society
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• v.38 no.12
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• pp.19-28
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• 2022

Cavities behind concrete walls can adversely affect the stability of structures. Thus study aims to detect cavities behind concrete structures using a microphone in a laboratory model test. A small-scale concrete wall is constructed in a chamber, which is composed of a reinforced concrete plate and dry soil. A plastic bowl is then placed between the plate and soil to simulate a cavity behind the concrete structure. Leaky surface acoustic waves are generated by impacting the concrete plate using a hammer and are measured using a microphone. The measured signals are analyzed using natural frequencies, and cavity-free sections are evaluated. The test results show that the first natural frequency decreases at the cavity section due to the flexural vibration behavior of the plate. In addition, the amplitude corresponding to the first natural frequency decreases as the measurement location becomes farther from the cavity center and significantly decreases at the measurement locations near the rebars. This study demonstrates that a microphone may be useful to detect cavities behind concrete walls.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.2
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• pp.107-119
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• 2022

The frequent detection and occurrence of micropollutants (MPs) in aquatic ecosystems has raised public health concerns worldwide. In this study, the behavior of 50 MPs was investigated in three different domestic wastewater treatment plants (WWTPs). Furthermore, the Kruskal-Wallis test was used to assess the geographical and seasonal variation of MPs in the WWTPs. The results showed that the concentrations of 43 MPs ranged from less than 0.1 to 237.6 ㎍ L^-1, while other seven MPs including 17-ethynylestradiol, 17-estradiol, sulfathiazole, sulfamethazine, clofibric acid, simvastatin, and lovastatin were not detected in all WWTPs. Among the detected MPs, the pharmaceuticals such as metformin, acetaminophen, naproxen, and caffeine were prominent with maximum concentrations of 133.4, 237.6, 71.5, and 107.7 ㎍ L^-1, respectively. Most perfluorinated compounds and nitrosamines were found at trace levels of 1.2 to 55.3 ng L^-1, while the concentration of corrosion inhibitors, preservatives (parabens), and endocrine disruptors ranged from less than 0.1 to 4310.8 ng L^-1. Regardless of the type of biological treatment process such as MLE, A2O, and MBR, the majority of pharmaceuticals (except lincomycin, diclofenac, iopromide, and carbamazepine), parabens (except Methyl paraben), and endocrine disruptors were removed by more than 80%. However, the removal efficiencies of certain MPs such as atrazine, DEET, perfluorinated compounds (except PFHxA), nitrosamines, and corrosion inhibitors were relatively low or their concentration even increased after treatment. The results of statistical analysis reveal that there is no significant geographical difference in the removal efficacy of MPs, but there are temporal seasonal variations in all WWTPs.