1,851 research outputs found
Partial-convolution-implemented generative adversarial network for global oceanic data assimilation
No full textThe oceanic data assimilation (DA) system has been developed to optimally combine numerical-model predictions with actual measurements from the ocean to create the best estimates of current ocean conditions and their uncertainties, improving our ability to forecast and understand the global climate variations. We developed DeepDA, a global oceanic DA system using deep learning, by integrating a partial convolutional neural network and a generative adversarial network. Partial convolution serves as an observation operator, mapping irregular observational data onto gridded fields, while generative adversarial network incorporates observational information from previous time frames. Our observing system simulation experiments, using simulated observations for the DA, revealed that DeepDA markedly reduces analysis error of the oceanic temperature, outperforming both background and observed values. DeepDA's real-case global temperature reanalysis spanning from 1981 to 2020 accurately reconstructs observed global climatological temperature fields, along with their seasonal cycles, major oceanic temperature variabilities and global warming trend. Developed solely with a long-term control simulation, DeepDA lowers technical hurdles in creating global ocean reanalysis datasets using multiple numerical models' physical constraints, thereby diminishing systematic uncertainties in estimating global oceanic states over decades with these models. Data assimilation (DA) techniques are commonly used to assess global Earth system variability but require considerable computational resources and struggle to handle sparse observational data. Ham and colleagues introduce a partial convolution and generative adversarial network-based global oceanic DA system and successfully reconstruct the observed global temperature in a real case study with smaller computational costs than traditional DA systems.N
A possible mechanism for El Niño-like warming in response to the future greenhouse warming
No full textUsing the climate change experiments generated for the Fourth Assessment of the Intergovernmental Panel on Climate Change, a possible mechanism for the El Nino-like warming in response to the greenhouse warming is suggested. From the coupled global climate model (CGCM) simulations with climate change scenario, it is found that the Bjerknes air-sea coupled process is a dominant contributor to the tropical Pacific response. However, it is revealed that most CGCMs commonly simulate the off-equatorial maximum of precipitation change. It is suggested here that the off-equatorial precipitation and the associated equatorial westerlies play a seeding role in triggering an El Nino-like warming response. Atmospheric GCM (AGCM) experiments show that even uniform sea-surface temperature (SST) warming leads to off-equatorial increase in precipitation which brings equatorial westerlies, implying that these non-uniform (off-equatorial) responses can play a seeding role for the El Nino-like warming pattern. Copyright (C) 2010 Royal Meteorological SocietyN
Incorrect computation of Madden-Julian oscillation prediction skill
No full textThe Madden-Julian oscillation (MJO) is a major tropical weather system and one of the largest sources of predictability for subseasonal-to-seasonal weather forecasts. Skillful prediction of the MJO has been a highly active area of research due to its large socio-economic impacts. Silini et al., herein S21, developed a machine learning model to predict the MJO, which they claimed to have an MJO prediction skill of 26-27 days over all seasons and 45 days for December-February (DJF) winter. If true, this would make the skill of their model competitive with that of the state-of-the-art dynamical MJO prediction systems at 20-35 days. However, here we show that the MJO prediction was calculated incorrectly in S21, which spuriously increased the performance of their model. Correctly computed skill of their model was substantially lower than that reported in S21; the skill for all seasons drops to 11-12 days and the skill for forecasts initialized during DJF drops to 15 days. Our findings clarify that the S21 machine learning model is not competitive with state-of-the-art numerical weather prediction models in predicting the MJO.Y
A Study on the User Empowerment and User Innovation in Game Industry: Focusing on Game Modification in Online and PC Game
No full textABFT: Anisotropic binary feature transform based on structure tensor space
No full textLocal feature matching is a fundamental step for many computer vision applications. Recently, binary feature transforms have been popularly proposed to improve the computational efficiency while preserving high matching performance. However, it is sensitive to noise and geometrical distortion such as affine transformation. In this paper, we propose ABFT framework, composed of a noise robust feature detection and affine invariant binary feature description based on a structure tensor space. Experimental results show that ABFT outperforms other state-of-the-art feature transforms in terms of the repeatability, recognition rate, and computational time. © 2013 IEEE
Symplectic Topology and Floer Homology: Volume 1, Symplectic Geometry and Pseudoholomorphic Curves
No full textPreface
Part I. Hamiltonian Dynamics and Symplectic Geometry:
1. Least action principle and the Hamiltonian mechanics
2. Symplectic manifolds and Hamilton's equation
3. Lagrangian submanifolds
4. Symplectic fibrations
5. Hofer's geometry of Ham(M, ω)
6. C0-Symplectic topology and Hamiltonian dynamics
Part II. Rudiments of Pseudoholomorphic Curves:
7. Geometric calculations
8. Local study of J-holomorphic curves
9. Gromov compactification and stable maps
10. Fredholm theory
11. Applications to symplectic topology
References
Index.Preface
Part I. Hamiltonian Dynamics and Symplectic Geometry:
1. Least action principle and the Hamiltonian mechanics
2. Symplectic manifolds and Hamilton's equation
3. Lagrangian submanifolds
4. Symplectic fibrations
5. Hofer's geometry of Ham(M, ω)
6. C0-Symplectic topology and Hamiltonian dynamics
Part II. Rudiments of Pseudoholomorphic Curves:
7. Geometric calculations
8. Local study of J-holomorphic curves
9. Gromov compactification and stable maps
10. Fredholm theory
11. Applications to symplectic topology
References
Index
Film Review: Yoo Hoo, Mrs. Goldberg
No full textThe author presents a review of the documentary Yoo Hoo, Mrs. Goldberg
SERUM ALPHA-1-ANTITRYPSIN IN PATIENTS WITH HEPATOCELLULAR-CARCINOMA
No full textTo evaluate the diagnostic value of alpha-1-antitrypsin (alpha-AT) as a tumor marker for hepatocellular carcinoma (HCC), we studied the serum levels of alpha-AT by rocket immunoelectrophoresis and alpha-fetoprotein (alpha-FP) by radioimmunoassay in 46 proven HCC patients, 43 cirrhosis patients and 200 healthy blood donors. The mean alpha-AT level of the 46 patients with HCC (4.8 +/- 2.7 mg/ml) was significantly higher than that of 200 healthy control subjects (1.7 +/- 0.7 mg/ml) (P < 0.0001). The sensitivity of alpha-AT in 24 patients with high level of alpha-FP (> 400 ng/ml) and 22 patients with low level of alpha-FP (< 400 ng/ml) were 96% and 64%, respectively. There was no substantial correlation between alpha-FP and alpha-AT in the two groups (alpha-FP > 400 ng/ml, alpha-FP < 400 ng/ml) (r = 0.078, 0.064). The sensitivity for HCC using alpha-FP level alone (> 400 ng/ml) was only 52%, and the sensitivity using alpha-AT level alone (> 3.2 mg/ml) was 76% of the 46 patients. Combining both tests, sensitivity was improved only to 80%
Acoustic Power Transfer Using Self-Focused Transducers for Miniaturized Implantable Neurostimulators
No full textAn emerging neurostimulation therapy utilizes electroceuticals to treat numerous neurological disorders. With the aim to discover novel clinical applications of neural stimulation, device miniaturization has been a key challenge for successful clinical translation of implantable stimulators. The battery size has been a limiting factor in further miniaturization, so wireless power transfer without the use of an implanted battery has gained interest. Among various power transfer techniques, acoustic power transfer (APT) provides substantial benefits for powering implantable devices due to its proven safety and efficiency for human body penetration. In this study, we proposed an APT-based neurostimulator with an integrated self-focused 3.6 MHz acoustic transducer and a receiver circuit composed of a power management module and pulse generator. The size of the entire device was 8 mm × 8 mm ×8.6 mm, which is small enough to be implanted with a small incision. A focused beam generated by an external transmitter was received by another focused beam from a receiver transducer, and this optimized pair of transducers with a receiver circuit generated 1.5 V, 1.3 ms pulse trains, which successfully transmitted stimulation pulses. We adopted a 1–3 composite with a piezolayer to implement a curved aperture, which enabled less-attenuated, focused, and matched beams for maximization of power transfer efficiency. We evaluated APT performance through rigorous bench-top and phantom tests and demonstrated the feasibility of stimulation through an in vivo experiment of sciatic nerve stimulation using a rat model.11Ysciescopu
Are there two types of La Nina?
No full textIn this study, the existence of two types of La Nina events is examined using observations and model output. We find that cold events in the central and eastern Pacific SST, are highly correlated unlike the corresponding warm events. When two types of La Nina are defined based on the same criteria for the types of warm events, the SST and precipitation patterns between the two types of La Nina are much less distinctive or less independent. In other words, there is a strong asymmetric character between warm and cold events. This asymmetric character is also examined in 20 climate models that participate in the CMIP3. Most climate models have difficulty in simulating independently the two types of El Nino and La Nina events; however, they simulate the two types of El Nino more independently than they simulate the two types of La Nina, supporting our observational arguments to some degree. Citation: Kug, J.-S., and Y.-G. Ham (2011), Are there two types of La Nina?, Geophys. Res. Lett., 38, L16704, doi: 10.1029/2011GL048237.11sciescopu
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