集成视频监控的在线考试系统的设计与实现

在传统的开放式考试平台的基础上,利用Visual C 6.0开发了一个视频监控系统,从而保证考试的严肃性、公平性和公正性.     

Saliency model-based face segmentation and tracking in head-and-shoulder video sequences

In this paper, a novel face segmentation algorithm is proposed based on facial saliency map (FSM) for head-and-shoulder type video application. This method consists of three stages. The first stage is to generate the saliency map of input video image by our proposed facial attention model. In the second stage, a geometric model and an eye-map built from chrominance components are employed to localize the face region according to the saliency map. The third stage involves the adaptive boundary correction and the final face contour extraction. Based on the segmented result, an effective boundary saliency map (BSM) is then constructed, and applied for the tracking based segmentation of the successive frames. Experimental evaluation on test sequences shows that the proposed method is capable of segmenting the face area quite effectively.     

基于“三网融合”的可视化资源协同

网络的宽带化发展有效促进了可视化资源的使用,特别是"三网融合",推动了应用协作和资源共享的发展,在三网间共享资源,实现整个社会信息资源的重复利用和深度挖掘,必将给社会带来巨大的经济效益和社会效益.因此,探索在"三网"间进行可视化资源协同、信息共享是社会信息化发展的重要内容.     

UA(1) anomaly and $ \eta^{{\prime}}_{}$ -mass from an infrared singular quark-gluon vertex

The U _A(1) problem of QCD is inevitably tied to the infrared behaviour of quarks and gluons with its most visible effect being the -mass. A dimensional argument of Kogut and Susskind showed that the mixing of the pseudoscalar flavour-singlet mesons with gluons can provide a screening of the Goldstone pole in this channel if the full quark-quark interaction is strongly infrared singular as ∼ 1/k ⁴ . We investigate this idea using previously obtained results for the Landau gauge ghost and gluon propagator, together with recent determinations for the singular behaviour of the quark-gluon vertex. We find that, even with an infrared vanishing gluon propagator, the singular structure of the quark-gluon vertex for certain kinematics is apposite for yielding a non-zero screening mass.     

Scaling laws and higher-order effects in Coulomb excitation of neutron halo nuclei

Essential properties of halo nuclei can be described in terms of a few low-energy constants. For neutron halo nuclei, analytical results can be found for wave functions and electromagnetic transition matrix elements in simple but well-adapted models. These wave functions can be used to study nuclear reactions; an especially simple and instructive example is Coulomb excitation. A systematic expansion in terms of small parameters can be given. We present scaling laws for excitation amplitudes and cross-sections. The results can be used to analyze experiments like ¹¹Be Coulomb excitation. They also serve as benchmark tests for more involved reaction theories.     

Is the reliability of a visual analog scale higher than an ordinal scale? An experiment with the GRBAS scale for the perceptual evaluation of dysphonia

Perceptual evaluation of 14 pathological voices was performed by 29 listeners using the GRBAS scale. To evaluate scale effects on the judgments, 2 versions of the scale were presented: the original 4-point scale and a visual analog scale. Each listener used the same voice samples for both versions of the scale with an interval of 2 weeks. Agreement was found to be higher with the original 4-point scale than with the visual analog version for all scale items G, R, B, A and S. Although a visual analog scale seems to enable a finer judgment of voice quality, this study showed that, with increased freedom of judgment, the interrater agreement decreased considerably. Therefore, we recommend the use of the original 4-point version of the GRBAS scale.     

A simple visual method for DNA detection based on the formation of gold nanoparticles

A simple visual method for DNA detection during the formation of gold nanoparticles (AuNPs) was developed based on different electrostatic properties of single strand DNA (ssDNA) and double strand DNA (dsDNA). Since the ssDNA is easy to bind to AuNPs due to its exposed bases which could prevent salt-induced aggregation of AuNPs. The dsDNA always present negative charge because its negatively charged phosphate backbone is exposed. In this case, the dsDNA could disturb the adsorption between dsDNA and AuNPs and result in non-aggregation of AuNPs. After hybridization, chloroauric acid and ascorbic acid were added to the mixture solution, and the solution changed to red immediately and turned to purple in 10 min in the present of target DNA. TEM results confirmed that the change of color stemed from aggregation of AuNPs. In order to obtain accurate results by naked eye, the DNA detection assay should be conducted under pH 7.0.     

$${f(\mathcal R)}$$ quantum cosmology

We have quantized a flat cosmological model in the context of the metric models, using the causal Bohmian quantum theory. The equations are solved and then we have obtained how the quantum corrections influence the classical equations.     

Past is important: Improved image captioning by looking back in time

A major development in the area of image captioning consists of trying to incorporate visual attention in the design of language generative model. However, most previous studies only emphasize its role in enhancing visual composition at the current moment, while neglect its role in global sequence reasoning. This problem appears not only in captioning model, but also in reinforcement learning structure. To tackle this issue, we first propose a Visual Reserved model that enables previous visual context to be considered for the current sequence reasoning. Next, a Attentional-Fluctuation Supervised model is also proposed in reinforcement learning structure. Compared against the traditional strategies that only take non-differentiable Natural Language Processing (NLP) metrics as the incentive standard, the proposed model regards the fluctuation of previous attention matrix as an important indicator to judge the convergence of the captioning model. The proposed methods have been tested on MS-COCO captioning dataset and achieve competitive results evaluated by the evaluation server of MS COCO captioning challenge.     

WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.