31,211 research outputs found
Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data
This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System(PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the IntegratedMultisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained
The quality of price formation at market openings and closings: evidence from the Nasdaq stock market
Central counterparties (CCPs) have increasingly become a cornerstone of financial markets infrastructure. We present a model where trades are time-critical, liquidity is limited and there is limited enforcement of trades. We show a CCP novating trades implements efficient trading behaviour. It is optimal for the CCP to face default losses to achieve the efficient level of trade. To cover these losses, the CCP optimally uses margin calls, and, as the default problem becomes more severe, also requires default funds and then imposes position limits
Deep Learning for Forecasting Stock Returns in the Cross-Section
Many studies have been undertaken by using machine learning techniques,
including neural networks, to predict stock returns. Recently, a method known
as deep learning, which achieves high performance mainly in image recognition
and speech recognition, has attracted attention in the machine learning field.
This paper implements deep learning to predict one-month-ahead stock returns in
the cross-section in the Japanese stock market and investigates the performance
of the method. Our results show that deep neural networks generally outperform
shallow neural networks, and the best networks also outperform representative
machine learning models. These results indicate that deep learning shows
promise as a skillful machine learning method to predict stock returns in the
cross-section.Comment: 12 pages, 2 figures, 8 tables, accepted at PAKDD 201
Digital image correlation (DIC) analysis of the 3 December 2013 Montescaglioso landslide (Basilicata, Southern Italy). Results from a multi-dataset investigation
Image correlation remote sensing monitoring techniques are becoming key tools for
providing effective qualitative and quantitative information suitable for natural hazard assessments,
specifically for landslide investigation and monitoring. In recent years, these techniques have
been successfully integrated and shown to be complementary and competitive with more standard
remote sensing techniques, such as satellite or terrestrial Synthetic Aperture Radar interferometry.
The objective of this article is to apply the proposed in-depth calibration and validation analysis,
referred to as the Digital Image Correlation technique, to measure landslide displacement.
The availability of a multi-dataset for the 3 December 2013 Montescaglioso landslide, characterized
by different types of imagery, such as LANDSAT 8 OLI (Operational Land Imager) and TIRS
(Thermal Infrared Sensor), high-resolution airborne optical orthophotos, Digital Terrain Models
and COSMO-SkyMed Synthetic Aperture Radar, allows for the retrieval of the actual landslide
displacement field at values ranging from a few meters (2â3 m in the north-eastern sector of the
landslide) to 20â21 m (local peaks on the central body of the landslide). Furthermore, comprehensive
sensitivity analyses and statistics-based processing approaches are used to identify the role of the
background noise that affects the whole dataset. This noise has a directly proportional relationship to
the different geometric and temporal resolutions of the processed imagery. Moreover, the accuracy
of the environmental-instrumental background noise evaluation allowed the actual displacement
measurements to be correctly calibrated and validated, thereby leading to a better definition of
the threshold values of the maximum Digital Image Correlation sub-pixel accuracy and reliability
(ranging from 1/10 to 8/10 pixel) for each processed dataset
Economic Integration in East Asia: Trends, Prospects, and a Possible Roadmap
This paper, which is a revised version of the ADB Working Paper on Regional Economic Integration No. 2, reviews trends in East Asian regionalism in the areas of trade and investment, money and finance, and infrastructure. It finds that trade and, to a lesser extent, financial integration is starting to increase in the region. It also finds that business cycles are starting to be more synchronized, enhancing the case for further monetary integration among these countries. The paper also outlines a roadmap for East Asian integration.
To be or not to Be? - First Evidence for Neutrinoless Double Beta Decay
Double beta decay is indispensable to solve the question of the neutrino mass
matrix together with oscillation experiments. Recent analysis of the most
sensitive experiment since nine years - the HEIDELBERG-MOSCOW experiment in
Gran-Sasso - yields a first indication for the neutrinoless decay mode. This
result is the first evidence for lepton number violation and proves the
neutrino to be a Majorana particle. We give the present status of the analysis
in this report. It excludes several of the neutrino mass scenarios allowed from
present neutrino oscillation experiments - only degenerate scenarios and those
with inverse mass hierarchy survive. This result allows neutrinos to still play
an important role as dark matter in the Universe. To improve the accuracy of
the present result, considerably enlarged experiments are required, such as
GENIUS. A GENIUS Test Facility has been funded and will come into operation by
early 2003.Comment: 16 pages, latex, 10 figures, Talk was presented at International
Conference "Neutrinos and Implications for Physics Beyond the Standard
Model", Oct. 11-13, 2002, Stony Brook, USA, Proc. (2003) ed. by R. Shrock,
also see Home Page of Heidelberg Non-Accelerator Particle Physics Group:
http://www.mpi-hd.mpg.de/non_acc
Economic Integration in East Asia: Trends, Prospects, and a Possible Roadmap
This paper reviews trends in East Asian regionalism in the areas of trade and investment, money and finance, and infrastructure. It presents various measures of trade and financial integration. An important finding of the paper is that increasing trade and financial integration in the region is now starting to lead to a synchronization of business cycles in a selected group of countries, further enhancing the case for monetary integration among these countries. The paper also outlines a roadmap for East Asian integration.ASEAN/East Asian economic cooperation and integration; business cycle synchronization; free trade agreements; policy coordination
The Effects of the Minimum Wage in the Private and Public Sectors in Brazil
The wage and employment effects of the minimum wage predicted by the standard neoclassical theory rely on a profit maximizing firm, not on a Government employer that can cover the higher wage bill by raising taxes, reducing expenditure, or simply printing money. If the public sector has an inelastic labour demand, the associated non-negative employment effect might offset some of the negative employment effect observed in the private sector and the overall employment effect might be less adverse. This is particularly so if the public sector is overpopulated by minimum wage workers, as in Brazil. There is very limited evidence on the minimum wage effects in developing countries, and none whatsoever on the minimum wage effects across the private and public sectors. This paper estimates the effects of the minimum wage on wages and employment in both the private and public sectors. The data used is an under-explored monthly Brazilian household survey from 1982 to 2000 at individual and regional levels. Robust results suggest that the minimum wage compresses the distribution of both sectors, but in line with a stronger effect in the private sector, more adverse employment effects in the long run are also observed in that sector. In the public sector, no evidence of adverse employment effects was uncovered.minimum wage; wage effect; employment effect; private sector; public sector; Brazil
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