• Journal of the Korean earth science society
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• v.42 no.4
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• pp.445-458
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• 2021

Gravity Recovery and Climate Experiment (GRACE) gravimeter satellites observed the Earth gravity field with unprecedented accuracy since 2002. After the termination of GRACE mission, GRACE Follow-on (GFO) satellites successively observe global gravity field, but there is missing period between GRACE and GFO about one year. Many previous studies estimated terrestrial water storage (TWS) changes using hydrological models, vertical displacements from global navigation satellite system observations, altimetry, and satellite laser ranging for a continuity of GRACE and GFO data. Recently, in order to predict TWS changes, various machine learning methods are developed such as artificial neural network and multi-linear regression. Previous studies used hydrological and climate data simultaneously as input data of the learning process. Further, they excluded linear trends in input data and GRACE/GFO data because the trend components obtained from GRACE/GFO data were assumed to be the same for other periods. However, hydrological models include high uncertainties, and observational period of GRACE/GFO is not long enough to estimate reliable TWS trends. In this study, we used convolutional neural networks (CNN) method incorporating only climate data set (temperature, evaporation, and precipitation) to predict TWS variations in the missing period of GRACE/GFO. We also make CNN model learn the linear trend of GRACE/GFO data. In most river basins considered in this study, our CNN model successfully predicts seasonal and long-term variations of TWS change.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.927-938
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• 2021

A similar magnitude of non-gravitational perturbations are act on the formation flying low earth orbit satellites with a certain time difference. Using this temporal correlation, the non-gravity acceleration of the low earth orbiting satellites can be transferred for the othersatellites. There is a period in which the accelerometer data of one satellite is unavailable for GRACE and GRACE-FO satellites. In this case, the accelerometer data transplant method described above is officially used to recover the accelerometer data at the Jet Propulsion Laboratory (JPL). In this paper, we proposed a model for predicting accelerometer data of formation flying low earth orbit satellites using a neural network (NN) model to improve the estimation accuracy of the transplant method. Although the transplant method cannot reflect the satellite's position and space environmental factors, the NN model can use them as model inputs to increase the prediction accuracy. A prediction test of an accelerometer data using NN model was performed for one month, and the prediction accuracy was compared with the transplant method. The NN model outperformsthe transplant method with 55.0% and 40.1% error reduction in the along-track and radial directions, respectively.

• Fisheries and Aquatic Sciences
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• v.22 no.11
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• pp.25.1-25.9
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• 2019

Background: Due to the continuous demand for fish coupled with decline in capture fisheries, there is the need to increase aquaculture production to meet the demand. Aquaculture is faced with high cost of feeding since fish oil and fish meal are expensive. In view of this, there are calls to explore alternatives that are cheap and reliable. Objectives: This study on Oreochromis niloticus was conducted to evaluate the effects of replacing fish oil (FO) with palm oil (PO) at 0%, 25%, 50%, 75%, and 100% on muscle fatty acid and proximate composition as well as growthrelated enzyme activities and mRNA expression. Methods: Oreochromis niloticus were fed five experimental diets (33% crude protein and 10% crude lipid) for 8 weeks. Feed had variation in fish oil and palm oil contents. After the 8 weeks feeding trial, five fish were sampled from each tank (15 from each treatment) and euthanized using an excess dose of tricaine methane sulfonate (MS-222 at 200 mg/L). Fatty acid and enzyme activities were analyzed using standard protocols. Also, RT-qPCR was used to quantify the expression levels of selected growth-related genes. Results: Fish fed 25% PO recorded the least muscle protein content and was significantly lower than the group fed 100% PO. Paired box protein 7 (Pax-7) enzyme activity was significantly higher in the group fed 50% PO compared to the groups fed 25% PO and 100% PO, while caplain-3 (Capn-3) was significantly lower in the group fed 0% PO compared to all other groups. There was a significant difference among treatments with respect to mRNA expression of Pax-7 and Capn-3. Group fed 25% PO had significantly lower mRNA expression of Pax-7, while the group fed 75% PO recorded significantly higher mRNA expression of Capn-3 compared to groups fed 0% PO, 25% PO, and 100% PO. Pearson's correlation analysis revealed that Igf-I and Igf-II mRNA expression have significant correlation with n-3 polyunsaturated fatty acids content in muscle. Conclusion: The results suggest muscle protein content could be modified if FO is replaced with PO. Also, mRNA expression of Pax-7 and Capn-3 is affected by replacing FO with PO.