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2. Multimodal fusion for sea level anomaly forecasting

Author

Wang, Guosong, Wang, Xidong, Wu, Xinrong, Liu, Kexiu, Qi, Yiquan, Sun, Chunjian, and Fu, Hongli

Subjects
Physics - Atmospheric and Oceanic Physics, Physics - Data Analysis, Statistics and Probability
Abstract

The accumulated remote sensing data of altimeters and scatterometers have provided a new opportunity to forecast the ocean states and improve the knowledge in ocean/atmosphere exchanges. Few previous studies have focused on sea level anomaly (SLA) multi-step forecasting by multivariate deep learning for different modalities. For this paper, a novel multimodal fusion approach named MMFnet is used for SLA multi-step forecasting in South China Sea (SCS). First, a grid forecasting network is trained by an improved Convolutional Long Short-Term Memory (ConvLSTM) network on daily multiple remote sensing data from 1993 to 2016. Then, an in-situ forecasting network is trained by an improved LSTM network, which is decomposed by the ensemble empirical mode decomposition (EEMD-LSTM), on real-time, in-situ and remote sensing data. Finally, the two single-modal networks are fused by an ocean data assimilation scheme. During the test period from 2017 to 2019, the average RMSE of the MMFnet (single-modal ConvLSTM) is 4.03 cm (4.51 cm), the 15th-day anomaly correlation coefficient is 0.78 (0.67), the performance of MMFnet is much higher than those of current state-of-the-art dynamical (HYCOM) and statistical (ConvLSTM, Persistence and daily Climatology) forecasting systems. Sensitivity experiments analysis indicates that, the MMFnet, which added CCMP SCAT products and OISST for SLA forecasting, has improved the forecast range over a week and can effectively produce 15-day SLA forecasting with reasonable accuracies.In an extension of the validation over the North Pacific Ocean, MMFnet can calculate the forecasting results in a few minutes, and we find good agreement in amplitude and distribution of SLA variability between MMFnet and other classical operational model products.

Published
2020

11. Foliage colors improve relaxation and emotional status of university students from different countries

Author

Liu Kexiu, Mohamed Elsadek, Binyi Liu, and Eijiro Fujii

Subjects
Brain activity, Near-infrared spectroscopy, Landscape design, Color perception, Cultural difference, Emotional status, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

The therapeutic advantages of seeing plants have gained increasing consideration in stressful modern societies, however, evidence-based studies on how physiological and emotional states of individuals from different nationalities change when seeing different foliage colors are limited. The study was conducted to explore the physiological and psychological advantages of foliage colors as visual stimuli. The experiment included 40 men from two nations (age: 21.34 ± 3.50 years) and was carried out using five foliage colors including green, light green, green-yellow, green-red and green-white. Participants were exposed to each color for 2 min, when seeing the foliage colors, eye movements and oxy-Hb concentrations were continuously measured. Subjective evaluations of emotions were performed utilizing a semantic differential questionnaire. A significant decrease in oxy-Hb concentration in the frontal lobe was associated with the viewing of green and green-white plants by the Japanese participants and with viewing light green and green-yellow by the Egyptian participants. Participants spent higher fixation numbers and longer durations on these colors. The findings indicate that viewing of these plant colors was positively associated with physiological relaxation. Furthermore, these colors were associated with more positive feelings, such as calmness, comfort and naturalness. Therefore, the presence of these colors in spaces may have positive impacts on relaxation and emotional status.

Published
2021
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27. Foliage colors improve relaxation and emotional status of university students from different countries

Author

Eijiro Fujii, Binyi Liu, Mohamed Elsadek, and Liu Kexiu

Subjects
0301 basic medicine, Eye movement, Relaxation, Visual perception, genetic structures, Color vision, media_common.quotation_subject, Emotional status, Color perception, Developmental psychology, 03 medical and health sciences, 0302 clinical medicine, Near-infrared spectroscopy, lcsh:Social sciences (General), lcsh:Science (General), media_common, Landscape design, Multidisciplinary, Relaxation (psychology), Cultural difference, 030104 developmental biology, Feeling, Fixation (visual), lcsh:H1-99, Semantic differential, Psychology, Brain activity, 030217 neurology & neurosurgery, Research Article, lcsh:Q1-390
Abstract

The therapeutic advantages of seeing plants have gained increasing consideration in stressful modern societies, however, evidence-based studies on how physiological and emotional states of individuals from different nationalities change when seeing different foliage colors are limited. The study was conducted to explore the physiological and psychological advantages of foliage colors as visual stimuli. The experiment included 40 men from two nations (age: 21.34 ± 3.50 years) and was carried out using five foliage colors including green, light green, green-yellow, green-red and green-white. Participants were exposed to each color for 2 min, when seeing the foliage colors, eye movements and oxy-Hb concentrations were continuously measured. Subjective evaluations of emotions were performed utilizing a semantic differential questionnaire. A significant decrease in oxy-Hb concentration in the frontal lobe was associated with the viewing of green and green-white plants by the Japanese participants and with viewing light green and green-yellow by the Egyptian participants. Participants spent higher fixation numbers and longer durations on these colors. The findings indicate that viewing of these plant colors was positively associated with physiological relaxation. Furthermore, these colors were associated with more positive feelings, such as calmness, comfort and naturalness. Therefore, the presence of these colors in spaces may have positive impacts on relaxation and emotional status., Brain activity, near-infrared spectroscopy, landscape design, color perception, cultural difference, emotional status, eye movement, relaxation

Published
2021

30. Improving the performance of sea surface temperature predictions using a revised method.

Author

Liu, Jingjing, Yang, Jinkun, Liu, Kexiu, and Xu, Lingyu

Subjects
OCEAN temperature, SHORT-term memory, LONG-term memory, DEEP learning, FORECASTING
Abstract

Sea surface temperature (SST) prediction plays an important role in global and regional ocean-related research. With the rapid development of remote sensing technology, there are plenty of studies for SST prediction with deep learning to pursue better prediction performance and normalization was used for most studies. However, SST always fluctuates widely, so the denormalization scaled up the difference between normalized observed SSTs and normalized predicted SSTs (OnP-DIFF), and it results in a significant decline in the prediction performance. Therefore, a revision method used to revert the scale-up is proposed in this letter. This method uses cube B-spline interpolation to enhance OnP-DIFF, utilizes Long Short Term Memory network (LSTM) to train and predict OnP-DIFF and generate revision tensor (RT), and finally uses RT to revise denormalized predicted SSTs. To our knowledge, it is the first attempt to use the revision method to solve the problem of performance decline for SST prediction because of wide fluctuations of SST. The experiment results indicate that the proposed method can revert the performance back to and even better than the value before denormalization for deep learning models, significantly improving the prediction performance, and is reliable for SST prediction with high performance for a wide time range and large spatial scope. [ABSTRACT FROM AUTHOR]

Published
2022
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38. Numerical Simulation of the Influence of Mean Sea Level Rise on Typhoon Storm Surge in the East China Sea

Author

Gao, Zhigang, Han, Shuzong, Liu, Kexiu, Zhrng, Yunxia, and Yu, Huaming

Subjects
animal diseases, Sea level, Simulation
Abstract

In this paper, ECOMSED (Estuarine Coastal Ocean Model with sediment transport) model is employed to simulate storm surge process caused by typhoon passing across East China Sea in nearly years. Capability of ECOMSED to simulate storm surge is validated by comparing model result with observed data. Sensitivity experiments are designed to study the influence of sea level rise on typhoon storm surge. Numerical experiment shows that influence of mean sea level rise on typhoon storm surge is non-uniform spatially and changes as typhoon process differs. Maybe fixed boundary method would weaken the influence of mean sea level rise on storm surge, and free boundary method is suggested for the succeeding study. Published ECOMSED model

Published
2008

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