A scheme for cancelling intercarrier interference using conjugate transmission in multicarrier communication systems

To mitigate intercarrier interference (ICI), a two-path algorithm is developed for multicarrier communication systems, including orthogonal frequency division multiplexing (OFDM) systems. The first path employs the regular OFDM algorithm. The second path uses the conjugate transmission of the first path. The combination of both paths forms a conjugate ICI cancellation scheme at the receiver. This conjugate cancellation (CC) scheme provides (1) a high signal to interference power ratio (SIR) in the presence of small frequency offsets (50 dB and 33 dB higher than that of the regular OFDM and linear self-cancellation algorithms [1], [2], respectively, at ΔfT = 0.1% of subcarrier frequency spacing); (2) better bit error rate (BER) performance in both additive white Gaussian noise (AWGN) and fading channels; (3) backward compatibility with the existing OFDM system; (4) no channel equalization is needed for reducing ICI, a simple low cost receiver without increasing system complexity. Although the two-path transmission reduces bandwidth efficiency, the disadvantage can be balanced by increasing signal alphabet sizes

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

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.

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

Remotely sensed dune celerity and sand flux measurements of the world's fastest barchans (Bodele, Chad)

Quantifying sand flux with field measurements is an expensive and time-consuming process. We here present an alternative approach using the COSI-Corr software package for Earth surface deformation detection. Using pairs of ASTER satellite images, we detected dune migration in the Bodélé depression of northern Chad over time intervals of one month to 6.5 years. The displacement map can be used to automatically distinguish dunes from interdunes, which is a crucial step towards calculating sand flux. We interpolated a surface between the interdune areas and subtracted it from a digital elevation model, thus obtaining dune heights and volumes. Multiplying height with celerity yields a pixel-by-pixel estimate of the sand flux. We applied this method to large diatomite dunes in the Bodélé, confirming that these are some of the world's fastest moving barchans. Plotting dune height against inverse celerity reveals sand flux at the dune crest of >200 m3/m/yr. Average dune sand flux values for the eastern and western Bodélé are 76 and 99 m3/m/yr, respectively. The contribution of the dunes to the total area-averaged sand flux is 24–29 m3/m/yr, which is ∼10% of the saltation flux determined by previously published field measurements

International Stock Return Comovements

We examine international stock return comovements using country-industry and country-style portfolios. We first establish that parsimonious risk-based factor models capture the covariance structure of the data better than the popular Heston-Rouwenhorst (1994) model. We then establish the following stylized facts regarding stock return comovements. First, we do not find evidence for an upward trend in return correlations, excpet for the European stock markets. Second, the increasing imporatnce of industry factors relative to country factors was a short-lived, temporary phenomenon. Third, we find no evidence for a trend in idiosyncratic risk in any of the countries we examine.

Application of chiral nuclear forces to light nuclei

In these proceedings, we discuss the current status of nuclear bound state predictions based on chiral nuclear interactions. Results of ordinary $s$- and $p$-shell nuclei and light hypernuclei are shown.Comment: 12 pages, 2 figures, corrected typos in Table 5, version as publishe

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 (2–3 m in the north-eastern sector of the landslide) to 20–21 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