Human Activity Recognition Using Deep Learning Networks with Enhanced Channel State Information

© 2018 IEEE. Channel State Information (CSI) is widely used for device free human activity recognition. Feature extraction remains as one of the most challenging tasks in a dynamic and complex environment. In this paper, we propose a human activity recognition scheme using Deep Learning Networks with enhanced Channel State information (DLN-eCSI). We develop a CSI feature enhancement scheme (CFES), including two modules of background reduction and correlation feature enhancement, for preprocessing the data input to the DLN. After cleaning and compressing the signals using CFES, we apply the recurrent neural networking (RNN) to automatically extract deeper features and then the softmax regression algorithm for activity classification. Extensive experiments are conducted to validate the effectiveness of the proposed scheme

Distributed transmit beamforming for UAV to base communications

© 2013 IEEE. Distributed transmit beamforming (DTB) is very efficient for extending the communication distance between a swarm of UAVs and the base, particularly when considering the constraints in weight and battery life for payloads on UAVs. In this paper, we review major function modules and potential solutions in realizing DTB in UAV systems, such as timing and carrier synchronization, phase drift tracking and compensation, and beamforming vector generation and updating. We then focus on beamforming vector generation and updating, and introduce a concatenated training scheme, together with a recursive channel estimation and updating algorithm. We also propose three approaches for tracking the variation of channels and updating the vectors. The effectiveness of these approaches is validated by simulation results

Synchronization of discrete-time complex networks with randomly occurring coupling and distributed time-varying delay

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Challenges for the recovery of the ozone layer

The recovery of stratospheric ozone from past depletion is underway owing to the 1987 Montreal Protocol and its subsequent amendments, which have been effective in phasing out the production and consumption of the major ozone-depleting substances (ODSs). However, there is uncertainty about the future rate of recovery. This uncertainty relates partly to unexpected emissions of controlled anthropogenic ODSs such as CCl₃F and slower-than-expected declines in atmospheric CCl₄. A further uncertainty surrounds emissions of uncontrolled short-lived anthropogenic ODSs (such as CH₂Cl₂ and CHCl₃), which observations show have been increasing in the atmosphere through 2017, as well as potential emission increases in natural ODSs (such as CH₃Cl and CH₃Br) induced by climate change, changes in atmospheric concentrations of greenhouse gases N₂O and CH₄, and stratospheric geoengineering. These challenges could delay the return of stratospheric ozone levels to historical values, (for example, the abundance in 1980), by up to decades, depending on the future evolution of the emissions and other influencing factors. To mitigate the threats to future ozone recovery, it is crucial to ensure that the Montreal Protocol and its amendments continue to be implemented effectively in order to have firm control on future levels of ODSs. This action needs to be supported by an expansion of the geographic coverage of atmospheric observations of ODSs, by enhancing the ability of source attribution modelling, and by improving understanding of the interactions between climate change and ozone recovery

Investigating eukaryotic elongation factor 2 kinase/eukaryotic translation elongation factor 2 pathway regulation and its role in protein synthesis impairment during disuse-induced skeletal muscle atrophy

The principal mechanism underlying the reduced rate of protein synthesis in atrophied skeletal muscle is largely unknown. Eukaryotic elongation factor 2 kinase (eEF2k) impairs the ability of eukaryotic translation elongation factor 2 (eEF2) to bind to the ribosome via T56 phosphorylation. Perturbations in the eEF2k/eEF2 pathway during various stages of disuse muscle atrophy have been investigated utilizing a rat hind limb suspension (HS) model. Two distinct components of eEF2k/eEF2 pathway misregulation were demonstrated, observing a significant (P 2+-dependent process with involvement of Cav1.1. The ratio of T56-phosphorylated/total eEF2 was robustly elevated after 3-day HS, which was completely reversed by 1,2-bis (2-aminophenoxy)ethane-N,N,N',N'-tetraacetic acid-acetoxymethyl ester (BAPTA-AM) and decreased by 1.7-fold (P < 0.05) by nifedipine. Transfection of C2C12 with cytomegalovirus promoter (pCMV)-eEF2k and administration with small molecules were used to modulate eEF2k and eEF2 activity. More importantly, pharmacologic enhancement of eEF2 phosphorylation induced phosphorylated ribosomal protein S6 kinase (T389) up-regulation and restoration of global protein synthesis in the HS rats. Taken together, the eEF2k/eEF2 pathway was up-regulated during disuse muscle atrophy involving calcium-dependent activation of eEF2k partly via Cav1.1. The study provides evidence, in vitro and in vivo, of the eEF2k/eEF2 pathway impact on ribosomal protein S6 kinase activity as well as protein expression of key atrophy biomarkers, muscle atrophy F-box/atrogin-1 and muscle RING finger-1

What determines the yen swap spread?

We investigate if Japanese yen denominated interest rate swap spreads price risks in addition to liquidity and default risk. These additional risks include: the time-varying correlation between interest rates of different types and maturities; business cycle risk; and market skewness risk. Our analysis, over a number of different maturities and sample periods, supports the existence of an additional risk premium. We also show that the time-varying correlation between short term market interest rates (e.g., TIBOR) and the longer term Government bond yield (e.g., Gensaki) is of particular importance. Japanese yen swap spreads are shown to contain both pro-cyclical and counter-cyclical elements of business cycle risk, positive risk premia for skewness risk and variable risk premia for correlation risk (between fixed and floating interest rates)

Operator theory and function theory in Drury-Arveson space and its quotients

The Drury-Arveson space $H^2_d$, also known as symmetric Fock space or the $d$-shift space, is a Hilbert function space that has a natural $d$-tuple of operators acting on it, which gives it the structure of a Hilbert module. This survey aims to introduce the Drury-Arveson space, to give a panoramic view of the main operator theoretic and function theoretic aspects of this space, and to describe the universal role that it plays in multivariable operator theory and in Pick interpolation theory.Comment: Final version (to appear in Handbook of Operator Theory); 42 page

Versatile method for template-free synthesis of single crystalline metal and metal alloy nanowires

© 2016 The Royal Society of Chemistry. Metal and metal alloy nanowires have applications ranging from spintronics to drug delivery, but high quality, high density single crystalline materials have been surprisingly difficult to fabricate. Here we report a versatile, template-free, self-assembly method for fabrication of single crystalline metal and metal alloy nanowires (Co, Ni, NiCo, CoFe, and NiFe) by reduction of metal nitride precursors formed in situ by reaction of metal salts with a nitrogen source. Thiol reduction of the metal nitrides to the metallic phase at 550-600 °C results in nanowire growth. In this process, sulfur acts as a uniaxial structure-directing agent, passivating the surface of the growing nanowires and preventing radial growth. The versatility of the method is demonstrated by achieving nanowire growth from gas-phase, solution-phase or a combination of gas- and solution-phase precursors. The fabrication method is suited to large-area CVD on a wide range of solid substrates