• Journal of Life Science
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• v.33 no.11
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• pp.868-875
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• 2023

Kinesin-1 is a motor protein identified as the first member of the kinesin superfamily (KIF), which plays a role in intracellular cargo transport by acting as microtubule-dependent motor proteins within cells. Kinesin-1 consists of two heavy chains (KHCs, also known as KIF5s) and two light chains (KLCs). The 93 amino acids in the carboxyl (C)-terminal tail region of KIF5A are not homologous to the C-terminal tail region of KIF5B or the C-terminal tail region of KIF5C. In this study, we used a yeast two-hybrid screen to identify the binding proteins that interacted with the C-terminal region of KIF5A. We found an association between KIF5A and CUE domain containing 2 (CUEDC2), which is proposed to function as an adaptor protein involved in ubiquitination pathways and protein trafficking. CUEDC2 bound to the C-terminal region of KIF5A and did not interact with KIF5B (the motor of kinesin-1), KIF3A (the motor of kinesin-2), or kinesin light chain 1 (KLC1). KIF5A specifically bound to the C-terminal region of CUEDC2. Furthermore, KIF5A did not interact with another isoform: CUEDC1. In addition, glutathione S-transferase (GST) pull-downs showed that KIF5A directly bound GST-CUEDC2 but did not interact with GST-CUEDC1 and GST alone. When myc-KIF5A and EGFP-CUEDC2 were co-expressed in HEK-293T cells, CUEDC2 co-immunoprecipitated with kinesin-1, and myc-KIF5A and FLAG-CUEDC2 colocalized in the cells. These results suggest that in intracellular cargo transport by kinesin-1, CUEDC2 serves as an adaptor protein connecting kinesin-1 and cargo by binding to KIF5A.

• Journal of Marine Life Science
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• v.8 no.2
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• pp.136-149
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• 2023

Basic bioactivities (antioxidant, anti-inflammatory, antibacterial, anticancer, antiviral) were investigated from 370 strains of marine bacteria, fungi, and microalgae obtained from various marine environmental regions in Korea, and the activity results were obtained at the collection site, isolation source, and species level was compared. In the case of marine bacteria, strains belonging to the generally useful genera Streptomyces and Bacillus were observed to have particularly strong efficacy and useful resources were mainly isolated from marine sediments. In the case of marine fungi and microalgae, results showing strong species-specific activity were confirmed, and results showing efficacy-specific activity were also obtained. Based on these results, it is a research result that can facilitate priority access as a strategic material for industrial revitalization and the establishment of a strategy to secure resources based on usefulness when conducting research on chemicals that are selectively effective against specific diseases or when conducting resource-based research. In addition, we believe that by using these results as material for sale through the Marine BioBank (MBB), academia and industry can use them to help accelerate the revitalization of the marine bio industry.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.97-108
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• 2021

Labor contracts appear in form as an exchange relationship between labor products and wages, but since they transcend the level of simple barter, they can be economically identified as "trading" and can be identified as "rental." From a legal point of view, a legal device that legally supports and imposes binding force on commodity exchange relations is a contract. Such a labor contract led to a relationship in which wages were received and a certain amount of time was placed under the direction and supervision of the employer as a counter benefit to the receipt of wages. Since working hours are subordinate hours with one's labor under the disposition authority of the employer, long hours of work can be done for the health and safety of workers and furthermore, it can be an act that violates the value to enjoy as a human being. The reduction of working hours needs to be shortened in terms of productivity and enjoyment of workers' culture so that they can expand and reproduce, but users' corporate management labor and production activities should also be compatible compared to those pursued by capitalist countries. Working hours can be seen as individual time and time in society as a whole, and long hours of work at the individual level are reduced, which is undesirable at the individual level, but an increase in products due to an increase in production time at the social level can help social development. It is necessary to consider working hours in terms of finding the balance between these individual and social levels. If the regulation method of working hours was to regulate the total amount of working hours, flexibility and elasticity of working hours are a qualitative regulation method that allows companies to flexibly allocate and organize working hours within a certain range of up to 52 hours per week. Accordingly, it is necessary to shorten working hours, but expand and implement the flexible working hours system according to the situation of the company. To this end, it is necessary to flexibly operate the flexible working hours system, which is currently limited to six months, handle the selective working hours by agreement between employers and workers, and expand the target work of discretionary working hours according to the development of information and communication technology and new types based on the 4th industrial revolution.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.997-1008
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• 2023

Ship detection at sea can be performed in various ways. In particular, satellites can provide wide-area surveillance, and Synthetic Aperture Radar (SAR) imagery can be utilized day and night and in all weather conditions. To propose an efficient ship detection method from SAR images, this study aimed to apply the You Only Look Once Version 5 (YOLOv5) model to Sentinel-1 images and to analyze the difference between individual vs. integrated models and the accuracy characteristics by polarization. YOLOv5s, which has fewer and lighter parameters, and YOLOv5x, which has more parameters but higher accuracy, were used for the performance tests (1) by dividing each polarization into HH, HV, VH, and VV, and (2) by using images from all polarizations. All four experiments showed very similar and high accuracy of 0.977 ≤ AP@0.5 ≤ 0.998. This result suggests that the polarization integration model using lightweight YOLO models can be the most effective in terms of real-time system deployment. 19,582 images were used in this experiment. However, if other SAR images,such as Capella and ICEYE, are included in addition to Sentinel-1 images, a more flexible and accurate model for ship detection can be built.

• Clean Technology
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• v.29 no.4
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• pp.288-296
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• 2023

Coal is abundantly available compared to other energy sources and is used as a versatile energy resource worldwide. To address the environmental issues stemming from conventional coal utilization, efforts are underway to develop clean coal utilization technologies, with IGCC technology being a notable example. In IGCC plants, coal is subjected to a CMD process where both drying and pulverization are achieved by supplying hot air. However, if the temperature of the supplied hot air is excessively high, it can lead to devolatilization and spontaneous combustion, thereby compromising the stable operation of the CMD process. This study aimed to measure the devolatilization and spontaneous combustion temperatures of different types of bituminous coal, and to explore their correlations with the characteristics of the coals. Six coal types exhibited devolatilization between 350 and 400 ℃, while three coal types showed devolatilization at temperatures exceeding 400 ℃. Spontaneous combustion ℃curred in one coal type below 100 ℃, six coal types between 100 and 150 ℃, and two coal types above 150 ℃. The measured initiation temperatures were compared with the coal characteristics including the oxygen, moisture, Fe₂O₃, and CaO content, the H/C ratio, and the O/C ratio to establish correlations. Regression analysis was used to calculate the regression coefficients and determination coefficients for each ignition temperature. It was found that 52.44% of the FC/VM data significantly influenced the volatile matter ignition temperature, and 59.10% of the Fe₂O₃ data significantly affected the spontaneous combustionignition temperature.

• Korean Journal of Poultry Science
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• v.50 no.4
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• pp.303-310
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• 2023

The current study was conducted to compare the effect of crossbred on the body weight and laying performance of Korean native chicken from hatch to week 40. A total of 873 one-day-old chicks were divided into twelve crossbreds (i.e., CFCK, CFYC, CFYD, CKCF, CKYC, CKYD, YCYD, YCCF, YCCK, YDCF, YDCK, and YDYC) and commercial layer (Hy-Line Brown) were obtained as a counterpart in the study. All the birds are raised in battery cages (76 × 61 × 46 cm³) and then raised until 14 weeks and subsequently moved to layer battery cages (60 × 25 × 45 cm³) and raised until 16 weeks. The body weight and viability were measured biweekly from hatching to week 16. The week of 16, body weight range was about 1,010.24 to 1,411.77 g. The body weight of specific crossbreeds (i.e., CKCF, YCYD, and YDYC) was found to be comparable to that of Hy-Line Brown). The viability hatch to week 14 range was about 55 to 100% and however week 14 to 16 range was 80 to 100%. The crossbred (i.e., CKCF) recorded superior (P<0.05) viability throughout the whole experiment period, even compared with Hy-Line Brown (100% vs 96%). Our results are indicating that crossbreds Korean native chicken including CKCF, and YDYC has the potential to enhance key features of laying hens during the growing phase like optimal body weight and higher viability.