No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

F-OFDM仿真系统设计与时频同步算法

针对新一代5G波形的F-OFDM技术开展了研究,通过把一个宽带分为若干个子带,对每个子带进行滤波处理以实现更好的通信效能。基于Simulink平台进行了F-OFDM仿真系统的搭建,重点对F-OFDM符号同步方法和频偏估计方法进行了研究与仿真分析。实验结果表明,基于Chu序列相比采用PN序列可以获得更好的同步效果,基于导频的Classen频偏估计算法相比基于CP的CFO估计算法和基于训练序列的Moose估计方法可以获得更好的频偏估计效果。     

儿童用品TBT通报数据可视化预警研究

探索采用数据可视化技术分析儿童用品TBT通报数据,以可视化图形图像呈现通报热点并揭示趋势信息,提出对策与建议,助力为儿童用品产业升级、TBT预警数据分析和信息传播工作提供新思路,提高中小企业的国外市场准入机会。     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

中国菊花主题花展及其对行业发展的作用

中国的菊花主题花展(菊花展览)是最重要的赏菊形式,对我国3种主要类型的菊花展览,即综合性菊花展览(中国菊花展览会、国际博览会菊花专项展和各级城市菊花展)、菊花专类园和菊花花田花海的发展现状进行了研究,并分析了菊花展览在促进菊花产业发展、弘扬菊花文化、服务生态文明及美丽乡村建设、加强菊花非物质文化遗产保护中的重要作用,为推动我国菊花展览水平的提高提供借鉴。     

Effects of apparent image velocity and complexity on the dynamic visual field using a high-speed train driving simulator

Train driving is a highly visual task. The visual capabilities of the train driver affects driving safety and driving performance. Understanding the effects of train speed and background image complexity on the visual behavior of the high-speed train driver is essential for optimizing performance and safety. This study investigated the role of the apparent image velocity and complexity on the dynamic visual field of drivers. Participants in a repeated-measures experiment drove a train at nine different speeds in a state-of-the-art high-speed train simulator. Eye movement analysis indicated that the effect of image velocity on the dynamic visual field of high-speed train driver was significant while image complexity had no effect on it. The fixation range was increasingly concentrated on the middle of the track as the speed increased, meanwhile there was a logarithmic decline in fixation range for areas surrounding the track. The extent of the visual search field decreased gradually, both vertically and horizontally, as the speed of train increased, and the rate of decrease was more rapid in the vertical direction. A model is proposed that predicts the extent of this tunnel vision phenomenon as a function of the train speed.Relevance to industryThis finding can be used as a basis for the design of high-speed railway system and as a foundation for improving the operational procedures of high-speed train driver for safety.     

Content of Vasoactive Amines in Sremski Kulen and Sremska Kobasica Traditional Dry Fermented Sausages From Vojvodina

The aim of this paper was to determine the content of vasoactive biogenic amines in Sremski kulen and Sremska kobasica and to estimate hygienic conditions and good manufacturing practice (GMP) according to proposed criteria. Formation of dansyl chloride derivatizated vasoactive amines were determined using HPLC–DAD. Tryptamine (47.6; 34.2 mg/kg), histamine (16.1; 6.42 mg/kg) and tyramine (95.1; 45.2 mg/kg) were detected in both investigated type of traditional dry fermented sausages while phenylethylamine was not detected. Total content of vasoactive amines did not exceed the sum (200 mg/kg) proposed as a possible indicator of hygienic conditions and GMP in sausage production.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

A primary study of the acoustics of Chinese traditional theatrical buildings

The traditional performing arts and theatrical buildings in China can be traced back to a long history and were well developed during Song and Yuan Dynasties, 11th-14th centuries. Pavilion stage, opened on three sides and thrusting into the audience area, was unique and the most popular form in the open-air theatres, the courtyard theatres, and the indoor theatres up to the present day. As the traditional Chinese opera is performed in an abstract way, no stage settings are required and used. Therefore, the pavilion stage including the flat or domed ceiling and the back wall is virtually functioned as a reflective shell, which increases the early reflections and also intensifies the sound in the audience area. Meanwhile, it provides sufficient self-support to the performers. Acoustical parameters including reverberation time RT, early decay time EDT, acoustic ratio C50, strength index (loudness) G, and stage support factor ST1 were measured and reported on several traditional theatrical buildings.