Domain Adaptive Neural Networks for Object Recognition

We propose a simple neural network model to deal with the domain adaptation problem in object recognition. Our model incorporates the Maximum Mean Discrepancy (MMD) measure as a regularization in the supervised learning to reduce the distribution mismatch between the source and target domains in the latent space. From experiments, we demonstrate that the MMD regularization is an effective tool to provide good domain adaptation models on both SURF features and raw image pixels of a particular image data set. We also show that our proposed model, preceded by the denoising auto-encoder pretraining, achieves better performance than recent benchmark models on the same data sets. This work represents the first study of MMD measure in the context of neural networks

Handwritten and Printed Text Separation in Real Document

The aim of the paper is to separate handwritten and printed text from a real document embedded with noise, graphics including annotations. Relying on run-length smoothing algorithm (RLSA), the extracted pseudo-lines and pseudo-words are used as basic blocks for classification. To handle this, a multi-class support vector machine (SVM) with Gaussian kernel performs a first labelling of each pseudo-word including the study of local neighbourhood. It then propagates the context between neighbours so that we can correct possible labelling errors. Considering running time complexity issue, we propose linear complexity methods where we use k-NN with constraint. When using a kd-tree, it is almost linearly proportional to the number of pseudo-words. The performance of our system is close to 90%, even when very small learning dataset where samples are basically composed of complex administrative documents.Comment: Machine Vision Applications (2013

Diffuse 0.5-1 keV X-Rays and Nuclear Gamma-Rays from Fast Particles in the Local Hot Bubble

We show that interactions of fast particles with the boundary shell of the local hot bubble could make an important contribution to the 0.5-1 keV diffuse X-ray background observed with ROSAT. The bulk of these nonthermal X-rays are due to line emission from fast O ions of energies around 1 MeV/nucleon. This is the typical energy per particle in the ejecta of the supernova which is thought to have energized the bubble. We find that there is sufficient total energy in the ejecta to produce X-rays of the required intensity, subject to the details of the evolution of the fast particle population since the supernova explosion (about 3 10$^5$ years ago based on the age of the Geminga pulsar). The unequivocal signature of lines from deexcitations in fast ions is their large width ($\delta E/E$~0.1 for O lines), which will clearly distinguishes them from X-ray lines produced in a hot plasma. If a small fraction of the total ejecta energy is converted into accelerated particle kinetic energy (>~30 MeV/nucleon), the gamma-ray line emission produced in the boundary shell of the local hot bubble could account for the recently reported COMPTEL observations of nuclear gamma-ray lines from a broad region towards the Galactic center.Comment: 13 pages, 4 figures, submitted to Ap

A non-dispersive Raman D-band activated by well-ordered interlayer interactions in rotationally stacked bi-layer Graphene

Raman measurements on monolayer graphene folded back upon itself as an ordered but skew-stacked bilayer (i.e. with interlayer rotation) presents new mechanism for Raman scattering in sp2 carbons that arises in systems that lack coherent AB interlayer stacking. Although the parent monolayer does not exhibit a D-band, the interior of the skewed bilayer produces a strong two-peak Raman feature near 1350 cm-1; one of these peaks is non-dispersive, unlike all previously observed D-band features in sp2 carbons. Within a double-resonant model of Raman scattering, these unusual features are consistent with a skewed bilayer coupling, wherein one layer imposes a weak but well-ordered perturbation on the other. The discrete Fourier structure of the rotated interlayer interaction potential explains the unusual non-dispersive peak near 1350 cm-1

eHealth interventions for people with chronic kidney disease

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows: This review aims to look at the benefits and harms of using eHealth interventions in the CKD population

Energy Efficient User Association and Power Allocation in Millimeter Wave Based Ultra Dense Networks with Energy Harvesting Base Stations

Millimeter wave (mmWave) communication technologies have recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave technology are expected to increase both energy efficiency and spectral efficiency. In this paper, user association and power allocation in mmWave based UDNs is considered with attention to load balance constraints, energy harvesting by base stations, user quality of service requirements, energy efficiency, and cross-tier interference limits. The joint user association and power optimization problem is modeled as a mixed-integer programming problem, which is then transformed into a convex optimization problem by relaxing the user association indicator and solved by Lagrangian dual decomposition. An iterative gradient user association and power allocation algorithm is proposed and shown to converge rapidly to an optimal point. The complexity of the proposed algorithm is analyzed and the effectiveness of the proposed scheme compared with existing methods is verified by simulations.Comment: to appear, IEEE Journal on Selected Areas in Communications, 201

Non-line-of-sight Node Localization based on Semi-Definite Programming in Wireless Sensor Networks

An unknown-position sensor can be localized if there are three or more anchors making time-of-arrival (TOA) measurements of a signal from it. However, the location errors can be very large due to the fact that some of the measurements are from non-line-of-sight (NLOS) paths. In this paper, we propose a semi-definite programming (SDP) based node localization algorithm in NLOS environment for ultra-wideband (UWB) wireless sensor networks. The positions of sensors can be estimated using the distance estimates from location-aware anchors as well as other sensors. However, in the absence of LOS paths, e.g., in indoor networks, the NLOS range estimates can be significantly biased. As a result, the NLOS error can remarkably decrease the location accuracy. And it is not easy to efficiently distinguish LOS from NLOS measurements. In this paper, an algorithm is proposed that achieves high location accuracy without the need of identifying NLOS and LOS measurement.Comment: submitted to IEEE ICC'1

The Atmospheric Monitoring Strategy for the Cherenkov Telescope Array

The Imaging Atmospheric Cherenkov Technique (IACT) is unusual in astronomy as the atmosphere actually forms an intrinsic part of the detector system, with telescopes indirectly detecting very high energy particles by the generation and transport of Cherenkov photons deep within the atmosphere. This means that accurate measurement, characterisation and monitoring of the atmosphere is at the very heart of successfully operating an IACT system. The Cherenkov Telescope Array (CTA) will be the next generation IACT observatory with an ambitious aim to improve the sensitivity of an order of magnitude over current facilities, along with corresponding improvements in angular and energy resolution and extended energy coverage, through an array of Large (23m), Medium (12m) and Small (4m) sized telescopes spread over an area of order ~km$^2$. Whole sky coverage will be achieved by operating at two sites: one in the northern hemisphere and one in the southern hemisphere. This proceedings will cover the characterisation of the candidate sites and the atmospheric calibration strategy. CTA will utilise a suite of instrumentation and analysis techniques for atmospheric modelling and monitoring regarding pointing forecasts, intelligent pointing selection for the observatory operations and for offline data correction.Comment: 6 pages. To appear in the proceedings of the Adapting to the Atmosphere conference 201

Surface compositional mapping by spectral ratioing of ERTS-1 MSS data in the Wind River Basin and Range, Wyoming

The author has identified the following significant results. ERTS data collected in August and October 1972 were processed on digital and special purpose analog recognition computers using ratio enhancement and pattern recognition. Ratios of band-averaged laboratory reflectances of some minerals and rock types known to be in the scene compared favorably with ratios derived from the data by ratio normalization procedures. A single ratio display and density slice of the visible channels of ERTS MSS data, Channel 5/Channel 4 (R5,4), separated the Triassic Chugwater formation (redbeds) from other formations present and may have enhanced iron oxide minerals present at the surface in abundance. Comparison of data sets collected over the same area at two different times of the year by digital processing indicated that spectral variation due to environmental factors was reduced by ratio processing