A hierarchical RCNN for vehicle and vehicle license plate detection and recognition

Vehicle and vehicle license detection obtained incredible achievements during recent years that are also popularly used in real traffic scenarios, such as intelligent traffic monitoring systems, auto parking systems, and vehicle services. Computer vision attracted much attention in vehicle and vehicle license detection, benefit from image processing and machine learning technologies. However, the existing methods still have some issues with vehicle and vehicle license plate recognition, especially in a complex environment. In this paper, we propose a multivehicle detection and license plate recognition system based on a hierarchical region convolutional neural network (RCNN). Firstly, a higher level of RCNN is employed to extract vehicles from the original images or video frames. Secondly, the regions of the detected vehicles are input to a lower level (smaller) RCNN to detect the license plate. Thirdly, the detected license plate is split into single numbers. Finally, the individual numbers are recognized by an even smaller RCNN. The experiments on the real traffic database validated the proposed method. Compared with the commonly used all-in-one deep learning structure, the proposed hierarchical method deals with the license plate recognition task in multiple levels for sub-tasks, which enables the modification of network size and structure according to the complexity of sub-tasks. Therefore, the computation load is reduced

Evaluation of Climatic and Anthropogenic Impacts on Dust Erodibility: A Case Study in Xilingol Grassland, China

Aeolian dust is dependent on erosivity (i.e., wind speed) and erodibility (i.e., land surface conditions). The effect of erodibility on dust occurrence remains poorly understood. In this study, we proposed a composite erodibility index (dust occurrence ratio, DOR) and examined its interannual variation at a typical steppe site (Abaga-Qi) in Xilingol Grassland, China, during spring of 1974–2018. Variation in DOR is mainly responsible for dust occurrence (R2 = 0.80, p-value < 0.001). During 2001–2018, DOR values were notably higher than those during 1974–2000. There was also a general declining trend with fluctuations. This indicates that the land surface conditions became vulnerable to wind erosion but was gradually reversed with the implementation of projects to combat desertification in recent years. To understand the relative climatic and anthropogenic impacts on erodibility, multiple regression was conducted between DOR and influencing factors for the period of 2001–2018. Precipitation (spring, summer, and winter) and temperature (summer, autumn, and winter), together with livestock population (June) explained 82% of the variation in DOR. Sheep and goat population made the greatest contribution. Therefore, reducing the number of sheep and goat could be an effective measure to prevent dust occurrence in Xilingol Grassland

Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia

H8 filtering and control of 2-D systems

This thesis presents the research work on filtering and control for two-dimensional (2-D) discrete systems. We first establish several versions of 2-D Bounded Real Lemma in terms of solution of certain Riccati inequality or equation. Based on the derived Bounded Real Lemma, we consider the H8 filtering problem of 2-D discrete systems described by the Roesser model. 2-D .H8 filters of both an observer-based structure and a general state equation form are investigated. The solutions are obtained in terms of algebraic Riccati inequalities (ARIs) or linear matrix inequalities (LMIs).Doctor of Philosophy (EEE

Control performance comparison of PZT microactuator driven by voltage and current amplifiers in HDD dual-stage systems

In this paper, we investigate the effect of voltage and current amplifiers for PZT microactuators on the control performance of dual-stage servo systems in hard disk drives (HDDs), where the PZT microactuator is used as a secondary actuator and works together with the primary actuator of voice coil motor (VCM). First, the PZT microactuator's behavior in terms of motion linearization and frequency responses is experimentally studied and compared when it is driven by a conventional voltage amplifier and a charge or current amplifier. It is found that the PZT microactuator with current amplifier has less hysteresis than with voltage amplifier and its first resonance is relatively smaller. Inspired by this difference, the control performance of the dual-stage servo systems in track-seeking and track-following is then compared between the two driving methods for the PZT microactuator

Analysis of actuator in-phase property in terms of control performance and integrated plant/controller design using a novel model matching method

This paper is concerned with resonance in-phase property of a VCM (voice coil motor) plant system in the sense of control performance in HDDs (hard disk drives). Its relationships with the optimal performance level γopt, the stability margins and the disturbance rejection capability are revealed. It is found that the main resonance being in-phase is particularly beneficial to rejection of the narrow-band disturbances with frequencies near plant resonances. In order to meet the requirement on the inphase property, a partial model matching method is proposed. This model matching problem is solved by an H∞ method using an linear matrix inequality approach. The partial model matching method is then applied to the VCM plant system. We especially take into account the in-phase case for the purpose to improve the system ability to attenuate high frequency disturbance. For the new system designed using the proposed model matching method, a feedback controller and a group peak filter are designed to attenuate the disturbance near the plant resonances. The advantages of the in-phase resonances are illustrated, when compared with the original plant

Solutions for H-infinity filtering of two-dimensional systems

This paper deals with the H ∞ filtering problem for linear discrete-time two-dimensional (2-D) systems described by the Roesser model. It firstly establishes a version of the bounded real lemma to give a sufficient condition for quantification of the H ∞ noise attenuation for 2-D systems. Based on the bounded real lemma, the H ∞ filtering problem is investigated for filters of an observer-based structure or a general state equation form and the solutions are obtained in terms of Riccati inequalities or linear matrix inequalities. The design approach is illustrated by an example of a stationary field in image processing