Person Re-Identification by Deep Joint Learning of Multi-Loss Classification

Existing person re-identification (re-id) methods rely mostly on either localised or global feature representation alone. This ignores their joint benefit and mutual complementary effects. In this work, we show the advantages of jointly learning local and global features in a Convolutional Neural Network (CNN) by aiming to discover correlated local and global features in different context. Specifically, we formulate a method for joint learning of local and global feature selection losses designed to optimise person re-id when using only generic matching metrics such as the L2 distance. We design a novel CNN architecture for Jointly Learning Multi-Loss (JLML) of local and global discriminative feature optimisation subject concurrently to the same re-id labelled information. Extensive comparative evaluations demonstrate the advantages of this new JLML model for person re-id over a wide range of state-of-the-art re-id methods on five benchmarks (VIPeR, GRID, CUHK01, CUHK03, Market-1501).Comment: Accepted by IJCAI 201

Nonlinear stabilization of tokamak microturbulence by fast ions

Nonlinear electromagnetic stabilization by suprathermal pressure gradients found in specific regimes is shown to be a key factor in reducing tokamak microturbulence, augmenting significantly the thermal pressure electromagnetic stabilization. Based on nonlinear gyrokinetic simulations investigating a set of ion heat transport experiments on the JET tokamak, described by Mantica et al. [Phys. Rev. Lett. 107 135004 (2011)], this result explains the experimentally observed ion heat flux and stiffness reduction. These findings are expected to improve the extrapolation of advanced tokamak scenarios to reactor relevant regimes.Comment: 5 pages, 5 figure

A comprehensive classification of galaxies in the SDSS: How to tell true from fake AGN?

We use the W_Ha versus [NII]/Ha (WHAN) diagram to provide a comprehensive emission-line classification of SDSS galaxies. This classification is able to cope with the large population of weak line galaxies that do not appear in traditional diagrams due to a lack of some of the diagnostic lines. A further advantage of the WHAN diagram is to allow the differentiation between two very distinct classes that overlap in the LINER region of traditional diagnostic diagrams. These are galaxies hosting a weakly active nucleus (wAGN) and "retired galaxies" (RGs), i.e. galaxies that have stopped forming stars and are ionized by their hot evolved low-mass stars. A useful criterion to distinguish true from fake AGN (i.e. the RGs) is the ratio (\xi) of the extinction-corrected L_Ha with respect to the Ha luminosity expected from photoionization by stellar populations older than 100 Myr. This ratio follows a markedly bimodal distribution, with a \xi >> 1 population composed by systems undergoing star-formation and/or nuclear activity, and a peak at \xi ~ 1 corresponding to the prediction of the RG model. We base our classification scheme on the equivalent width of Ha, an excellent observational proxy for \xi. Based on the bimodal distribution of W_Ha, we set the division between wAGN and RGs at W_Ha = 3 A. Five classes of galaxies are identified within the WHAN diagram: (a) Pure star forming galaxies: log [NII]/Ha 3 A. (b) Strong AGN (i.e., Seyferts): log [NII]/Ha > -0.4 and W_Ha > 6 A. (c) Weak AGN: log [NII]/Ha > -0.4 and W_Ha between 3 and 6 A. (d) RGs: W_Ha < 3 A. (e) Passive galaxies (actually, line-less galaxies): W_Ha and W_[NII] < 0.5 A. A comparative analysis of star formation histories and of other properties in these different classes of galaxies corroborates our proposed differentiation between RGs and weak AGN in the LINER-like family. (Abridged)Comment: Accepted for publication in MNRA

Outlier detection techniques for wireless sensor networks: A survey

In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree

Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems

Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER

The Purpose and Limits of Social Health Insurance

This contribution seeks to answer two related questions. First, what is the purpose of social health insurance? Or put in slightly different terms, what are the reasons for social (or public) health insurance to exist, even to dominate private health insurance in most developed countries? And second, what are the limits of social health insurance? Can one say that there is "too much" social health insurance in the following two senses: Should the balance be shifted towards the private alternative? And is the degree of coverage excessive?social health insurance, private health insurance, insurance coverage