Detecting incidental scene text is a challenging task because of multi-orientation, perspective distortion, and variation of text size, color and scale. Retrospective research has only focused on ...using rectangular bounding box or horizontal sliding window to localize text, which may result in redundant background noise, unnecessary overlap or even information loss. To address these issues, we propose a new Convolutional Neural Networks (CNNs) based method, named Deep Matching Prior Network (DMPNet), to detect text with tighter quadrangle. First, we use quadrilateral sliding windows in several specific intermediate convolutional layers to roughly recall the text with higher overlapping area and then a shared Monte-Carlo method is proposed for fast and accurate computing of the polygonal areas. After that, we designed a sequential protocol for relative regression which can exactly predict text with compact quadrangle. Moreover, a auxiliary smooth Ln loss is also proposed for further regressing the position of text, which has better overall performance than L2 loss and smooth L1 loss in terms of robustness and stability. The effectiveness of our approach is evaluated on a public word-level, multi-oriented scene text database, ICDAR 2015 Robust Reading Competition Challenge 4 "Incidental scene text localization". The performance of our method is evaluated by using F-measure and found to be 70.64%, outperforming the existing state-of-the-art method with F-measure 63.76%.
This paper reports an action research that aimed to examine how the author’s weekly use of reflection and questioning instructional methods affected learners’ learning in an online graduate class at ...a midwestern public university in the USA. The author employed the asynchronous online discussion on the discussion board in Blackboard for learners to complete course assignments. Specifically, the online instructional approach started with learners’ initial written reflection posts based on the assigned readings and personal experience, then followed by the instructor’s challenging questions based on the Socratic method and learners’ written responses to those questions. This method included discipline-specific questioning, creating a community where learners replied to the instructor’s and learners’ questions through modelling and facilitation, and promoting the instructor’s thinking-encouraging approach. The results of both quantitative and qualitative data indicated that the use of the reflection and questioning methods was effective in engaging and challenging online graduate learners. International implications across the discipline will result from the study.
This paper presents a novel convolutional neural network (CNN) -based method for high-accuracy real-time car license plate detection. Many contemporary methods for car license plate detection are ...reasonably effective under the specific conditions or strong assumptions only. However, they exhibit poor performance when the assessed car license plate images have a degree of rotation, as a result of manual capture by traffic police or deviation of the camera. Therefore, we propose the a CNN-based MD-YOLO framework for multi-directional car license plate detection. Using accurate rotation angle prediction and a fast intersection-over-union evaluation strategy, our proposed method can elegantly manage rotational problems in real-time scenarios. A series of experiments have been carried out to establish that the proposed method outperforms over other existing state-of-the-art methods in terms of better accuracy and lower computational cost.
With the development of deep learning, the use of convolutional neural networks (CNN) to improve the land cover classification accuracy of hyperspectral remote sensing images (HSRSI) has become a ...research hotspot. In HSRSI semantics segmentation, the traditional dataset partition method may cause information leakage, which poses challenges for a fair comparison between models. The performance of the model based on "convolutional-pooling-fully connected" structure is limited by small sample sizes and high dimensions of HSRSI. Moreover, most current studies did not involve how to choose the number of principal components with the application of the principal component analysis (PCA) to reduce dimensionality. To overcome the above challenges, firstly, the non-overlapping sliding window strategy combined with the judgment mechanism is introduced, used to split the hyperspectral dataset. Then, a PSE-UNet model for HSRSI semantic segmentation is designed by combining PCA, the attention mechanism, and UNet, and the factors affecting the performance of PSE-UNet are analyzed. Finally, the cumulative variance contribution rate (CVCR) is introduced as a dimensionality reduction metric of PCA to study the Hughes phenomenon. The experimental results with the Salinas dataset show that the PSE-UNet is superior to other semantic segmentation algorithms and the results can provide a reference for HSRSI semantic segmentation.
In this study, advanced hydrodynamic models are proposed to predict dynamic response of a floating offshore wind turbine (FOWT) in combined wave and current conditions and validated by laboratory and ...full-scale semi-submersible platforms. Firstly, hydrodynamic coefficient models are introduced to evaluate the added mass and drag coefficients in a wide range of Reynolds numbers. An advanced hydrodynamic model is then proposed to calculate the drag force of cylinder in combined wave and current conditions. The proposed model is validated by the water tank tests in the current-only, wave-only and current-wave conditions and is used to investigate the effect of current on the dynamic response of FOWT. Finally, the full-scale semi-submersible platform used in the Fukushima demonstration project is investigated. It is found that the predicted dynamic responses of platform by the proposed hydrodynamic models are improved by the directional spreading function of the sea wave spectrum and show favorable agreement with the field measurement.
The refractive index measurement of seawater has proven significance in oceanography, while an optical heterodyne interferometer is an important, highly accurate, tool used for seawater refractive ...index measurement. However, for practical seawater refractive index measurement, the refractive index of seawater needs to be monitored for long periods of time, and the influence of drift error on the measurement results for these cases cannot be ignored. This paper proposes a drift error compensation algorithm based on wavelet decomposition, which can adaptively separate the background from the signal, and then calculate the frequency difference to compensate for the drift error. It is suitable for unstable signals, especially signals with large differences between the beginning and the end, which is common in actual seawater refractive index monitoring. The authors identify that the primary cause of drift error is the frequency instability of the acousto-optic frequency shifter (AOFS), and the actual frequency difference was measured through experimentation. The frequency difference was around 0.1 Hz. Simulation experiments were designed to verify the effectiveness of the algorithm, and the standard deviation of the optical length of the results was on the scale of 10−8 m. Liquid refractive index measurement experiments were carried out in a laboratory, and the measurement error was reduced from 36.942% to 0.592% after algorithm processing. Field experiments were carried out regarding seawater refractive index monitoring, and the algorithm-processing results are able to match the motion of the target vehicle. The experimental data were processed with different algorithms, and, according to the comparison of the results, the proposed algorithm performs better than other existing drift error elimination algorithms.
This study investigates the sectional loads on an elastic semi-submersible platform for a 2 MW FOWT (floating offshore wind turbine) used in the Fukushima demonstration project. A water tank test is ...firstly carried out with an elastic model to study the dynamic responses and sectional loads of the platform in regular and irregular waves. Numerical simulations are then performed using multiple hydrodynamic bodies connected by elastic beams. The dynamic responses of the elastic model are compared to those of a rigid model to clarify the influence of the structural stiffness on the platform motion and mooring tension. The predicted sectional loads on the deck, brace and pontoon by the proposed nonlinear hydrodynamic models show good agreement with the experimental data obtained from the water tank test and a simplified formula is proposed to evaluate the distribution of the moments on the platform. Finally, the structural optimization of the elastic semi-submersible platform is conducted. The sectional moments and fatigue loadings on the pontoons are significantly reduced using the strut between the pontoons since the horizontal wave loads on the side column are dominant and the vertical wave loads acting on the platform are relatively small due to the deep draft.
A novel ameliorated phase generated carrier (PGC) demodulation algorithm based on arctangent function and differential-self-multiplying (DSM) is proposed in this paper. The harmonic distortion due to ...nonlinearity and the stability with light intensity disturbance (LID) are investigated both theoretically and experimentally. The nonlinearity of the PGC demodulation algorithm has been analyzed and an analytical expression of the total-harmonic-distortion (THD) has been derived. Experimental results have confirmed the low harmonic distortion of the ameliorated PGC algorithm as expected by the theoretical analysis. Compared with the traditional PGC-arctan and PGC-DCM algorithm, the ameliorated PGC algorithm has a much lower THD as well as a better signal-to-noise-and-distortion (SINAD). A THD of below 0.1% and a SINAD of 60 dB have been achieved with PGC modulation depth (C value) ranges from 1.5 to 3.5 rad. The stability performance with LID has also been studied. The ameliorated PGC algorithm has a much higher stability than the PGC-DCM algorithm. It can keep stable operations with LID depth as large as 26.5 dB and LID frequency as high as 1 kHz. The system employing the ameliorated PGC demodulation algorithm has a minimum detectable phase shift of 5 μrad/√Hz @ 1 kHz, a large dynamic range of 120 dB @ 100 Hz, and a high linearity of better than 99.99%.
ROOT MERISTEM GROWTH FACTOR (RGF) 1 is an important peptide hormone that regulates root growth. Upon binding to its receptor, RGFR1, RGF1 regulates the expression of two transcription factors, ...PLETHORA 1 and 2 (PLT1/2), to influence root meristem development. Here, we show that the ubiquitin-specific proteases UBP12 and UBP13 are positive regulators of root meristem development and that UBP13 interacts directly with RGF1 receptor (RGFR1) and its close homolog RGFR2. The ubp12,13 double-mutant root is completely insensitive to exogenous applied RGF1. Consistent with this result, RGF1-induced ubiquitination and turnover of RGFR1 protein were accelerated in ubp12,13-mutant plants but were delayed in transgenic plants overexpressing UBP13. Genetic analysis showed that PLT2 or RGFR1 overexpression partially rescued the short-root phenotype and the reduced cortical root meristem cell number in ubp12,13 plants. Together, our results demonstrate that UBP12/13 are regulators of the RGF1–RGFR1–PLT1/2 signaling pathway and that UBP12/13 can counteract RGF1-induced RGFR1 ubiquitination, stabilize RGFR1, and maintain root cell sensitivity to RGF1.
This perspective describes recent advances in the use of sulfur anions to promote molecular transformations under irradiation with visible light. The topics are classified by the following reaction ...modes performed by the key sulfur anions: (1) C–S coupling via electron donor–acceptor (EDA) interactions, (2) photoinduced molecular transformation via sulfur anion EDA catalysis, (3) sulfur anions as photoredox and hydrogen atom transfer (HAT) catalysts, and 4) dithiocarbamate and xanthate as nucleophilic catalysts for photoinduced radical cascade reactions.
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