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Owing to the inherent sparse channel feature in multi-carrier modulation systems, compressed sensing (CS)-based techniques have been used for channel estimation with less pilot subcarriers for orthogonal frequency division multiplexing (OFDM) systems. Because of a sparse multipath channel’s characteristic of fractional delay, the channel measurement matrix that is generated by conventional time-domain sampling approaches cannot perfectly recover the channel impulse response (CIR), especially in the case of two adjacent paths that both have with non-negligible power. In this study, a fractional delay multipath channel model is used to simulate the wireless multipath channel. In addition, a time-domain oversampling based doubly reduced matching pursuit (DRMP) algorithm at the receiver is proposed to improve the estimation accuracy while reducing the computational complexity. Simulation results show that the proposed method can improve both the bit error rate (BER) performance and estimation time compared to conventional methods in an environment with fractional delay. [ABSTRACT FROM AUTHOR]

Measuring rail profile in the presence of multiple degrees of freedom vibration is a very challenging task. This paper presents a novel method based on the local affine invariant feature descriptor to calibrate distorted profiles, which are obtained by traditional rail measurement system. It has three major modules: local affine invariant (LAI) feature descriptor, affine transformation estimation and parameters refinement. LAI feature descriptor is based on the affine geometry invariant and generated by calculating the proportions of different areas. Using the proposed LAI descriptor, we implement a three-stage profile calibration including matching, estimation, and refinement based on grouping and fast iterative closest point (FICP) algorithm. The performance of proposed LAI descriptor and calibrating method is tested by performing extensive experiments. The experimental results show that our LAI descriptor is highly descriptive and robust with respect to varying resolution and noise, and the LAI descriptor based calibration is effective and repeatable. [ABSTRACT FROM AUTHOR]

• We propose a high-efficiency method based on edge feature to recover the absolute phase map. • An edge detection operator suitable for the wrapped phase map is explored. • An edge point correction method is proposed to remove invalid edge points. • A reverse fine correction method is presented to further optimize the fringe order. • The proposed method requires at least three fringe patterns to unfold the wrapped phase map without any auxiliary fringe patterns. Phase unwrapping (PU) technology is an important component of fringe projection profilometry (FPP). The key of PU is to obtain accurate fringe order. The existing PU methods are hard to make a tradeoff between efficiency and accuracy. To reduce the number of stripes, a phase unwrapping method based on edge feature (EFPU) is proposed. For this method, we make full use of the properties of wrapped phase map rather than auxiliary fringe patterns. We firstly analyze an edge detection operator suitable for wrapped phase map. Furthermore, in order to improve the stability of the proposed method, the edge correction method is proposed to correct edge point and the reverse correction method is presented to further optimize the fringe order. The experimental results show that the absolute phase map obtained by EFPU is similar to that of multi-wavelength phase-shifting (MWPS) method, but the number of fringe patterns is only one-third of MWPS. [ABSTRACT FROM AUTHOR]

Cigarette smoke and ozone (O 3) are two main pollutants in indoor environments and their mutual reaction can generate substantial detrimental substances having synergistic influences on the environment and human health. The aging process of cigarette smoke in the atmosphere is mainly gone through ozonolysis reaction attracting increasing attention in recent years. Herein, the ozonolysis reaction of cigarette smoke with indoor O 3 concentrations has been investigated in a Teflon chamber. The gas- and particle-phases of cigarette smoke are divided and their individual ozonolysis process can generate ultrafine particles (UFPs) with high number concentrations. The chemical compositions of the gas- and particle-phases of cigarette smoke as well as their nascent UFPs are measured and their differences during the ozonolysis have been clearly observed with vacuum ultraviolet (VUV) photoionization mass spectrometry. In particular, several representative key species of cigarette smoke, i.e. , the gas-phase furan and 2,5-dimethylfuran and the particle-phase nicotine, as well as their ozonolysis products are definitely identified and play an important role in the nucleation formation of UFPs. Their ozonolysis reaction mechanisms are also discussed. In addition, this work demonstrates that the ozonolysis of the particle-phase of cigarette smoke contributes more UFPs than that of the gas-phase. [Display omitted] • Ozonolysis reactions of cigarette smoke with indoor O 3 concentrations investigated. • Gas- and particle-phases of smoke generate ultrafine particles (UFPs) via ozonolysis. • Ozonolysis of particle-phase of smoke generates more UFPs than that of gas-phase. • Key species of smoke and their ozonolysis products are identified in mass spectra. [ABSTRACT FROM AUTHOR]

• A novel rail corrugation measurement system by using 2D laser displacement sensors is proposed. • The rail corrugation is effectively restored by the method of coarse-to-refine data splicing. • The sensor deviation and pitching vibration calibrating are achieved via a simple searching method. • Achieving accurate splicing via the MPGA-based refine splicing method. • The proposed measurement system owns high accuracy in measuring the waveband of rail corrugation varied from 10 mm to 1 m. Rail corrugation dynamic measurement techniques are essential to guide rail maintenance and ensuring the safety of railway transportation. However, the effective measuring wavebands covered by traditional techniques are limited. Hence, this paper constructs a novel measurement system by using 2D laser displacement sensors for accurate measuring rail corrugation (2D-RCM). At first, original discontinuous data of rail irregularities are sampled by 2D sensors, and then the accurate restoring of rail corrugation is completed by the coarse-to-refine data splicing method. Coarse splicing mainly extracts and calibrates the data of overlapping measurement area. The refine splicing is achieved by rigid transformation and multiple population genetic algorithm. The validity and repeatability of the 2D-RCM is tested by extensive experiments. The experimental results demonstrate that it owns high-precision on measuring the wavebands of corrugation varied from 10 mm to 1 m, and robust to deviations of 2D sensors and pitching vibrations of the 2D-RCM system. [ABSTRACT FROM AUTHOR]