Image tag completion by local learning

The problem of tag completion is to learn the missing tags of an image. In this paper, we propose to learn a tag scoring vector for each image by local linear learning. A local linear function is used in the neighborhood of each image to predict the tag scoring vectors of its neighboring images. We construct a unified objective function for the learning of both tag scoring vectors and local linear function parame- ters. In the objective, we impose the learned tag scoring vectors to be consistent with the known associations to the tags of each image, and also minimize the prediction error of each local linear function, while reducing the complexity of each local function. The objective function is optimized by an alternate optimization strategy and gradient descent methods in an iterative algorithm. We compare the proposed algorithm against different state-of-the-art tag completion methods, and the results show its advantages

Tunable near- to mid-infrared pump terahertz probe spectroscopy in reflection geometry

Strong-field mid-infrared pump--terahertz (THz) probe spectroscopy has been proven as a powerful tool for light control of different orders in strongly correlated materials. We report the construction of an ultrafast broadband infrared pump--THz probe system in reflection geometry. A two-output optical parametric amplifier is used for generating mid-infrared pulses with GaSe as the nonlinear crystal. The setup is capable of pumping bulk materials at wavelengths ranging from 1.2 $\mu$m to 15 $\mu$m and beyond, and detecting the subtle, transient photoinduced changes in the reflected electric field of the THz probe at different temperatures. As a demonstration, we present 15 $\mu$m pump--THz probe measurements of a bulk EuSbTe$_{3}$ single crystal. A $0.5\%$ transient change in the reflected THz electric field can be clearly resolved. The widely tuned pumping energy could be used in mode-selective excitation experiments and applied to many strongly correlated electron systems.Comment: 4 pages, 4 figure

Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems

Copyright © 2015 Sunjie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 11301118 and 61174136, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the Fundamental Research Funds for the Central Universities of China under Grant CUSF-DH-D-2013061, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Nitrogen Removal by HN-AD Bacteria Immobilized on Modified Absorbent Stone

How to simplify the nitrogen removal process, reduce the cost and improve the efficiency has become an urgent problem to be solved. In this research, the isolated HNAD (heterotrophic nitrification and aerobic denitrification) bacteria were used to remove the nitrogen in wastewater. Modified absorbent stone was used as high-efficiency and low-cost immobilized material. The modification effect was determined by the changes in mechanical strength, Zeta potential, pore structure, micrographs and biomass. The practicability of the modified carrier was further proved by experiments of environmental effect and reuse. The modified carrier had excellent performance. By comparing the degradation effects of immobilized microorganism and free microorganism, it was proved that the immobilized microorganisms have broad application prospects and strong adaptability to environmental factors. Under the optimum conditions (temperature of 30 oC, pH of 7, dissolved oxygen of 3.5 mg L–1), the removal efficiency of ammonia nitrogen reached 100 % in 40 hours, the removal efficiency of total nitrogen reached 60.11 % in 50 hours, and the removal rate of total nitrogen was 2.404 mg-NL–1 h–1 by immobilized microorganisms with the treatment of simulated nitrogen-containing wastewater. This research provides new material for the immobilization of HN-AD bacteria and a new way for nitrogen removal. This work is licensed under a Creative Commons Attribution 4.0 International License

Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS) receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS) path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Mobile Satellite (LMS) channel model [1]-[4], developed at the German Aerospace Center (DLR). The DLR LMS channel model is widely used for simulating the positioning accuracy of mobile satellite navigation receivers in urban outdoor scenarios. The main objective of this paper is to present a comprehensive analysis of some of the most promising techniques with the DLR LMS channel model in varying multipath scenarios. Four multipath mitigation techniques are chosen herein for performance comparison, namely, the narrow Early-Minus-Late (nEML), the High Resolution Correlator, the C/N0-based two stage delay tracking technique, and the Reduced Search Space Maximum Likelihood (RSSML) delay estimator. The first two techniques are the most popular and traditional ones used in nowadays GNSS receivers, whereas the later two techniques are comparatively new and are advanced techniques, recently proposed by the authors. In addition, the implementation of the RSSML is optimized here for a narrow-bandwidth receiver configuration in the sense that it now requires a significantly less number of correlators and memory than its original implementation. The simulation results show that the reduced-complexity RSSML achieves the best multipath mitigation performance in moderate-to-good carrier-to-noise density ratio with the DLR LMS channel model in varying multipath scenarios

Orientation and strain modulated electronic structures in puckered arsenene nanoribbons

Orthorhombic arsenene was recently predicted as an indirect bandgap semiconductor. Here, we demonstrate that nanostructuring arsenene into nanoribbons can successfully transform the bandgap to be direct. It is found that direct bandgaps hold for narrow armchair but wide zigzag nanoribbons, which is dominated by the competition between the in-plane and out-of-plane bondings. Moreover, straining the nanoribbons also induces a direct bandgap and simultaneously modulates effectively the transport property. The gap energy is largely enhanced by applying tensile strains to the armchair structures. In the zigzag ones, a tensile strain makes the effective mass of holes much higher while a compressive strain cause it much lower than that of electrons. Our results are crutial to understand and engineer the electronic properties of two dimensional materials beyond the planar ones like graphene