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Perceptual video quality assessment: a survey

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Science China(Information Sciences) 2024年第11期67卷 20-76页

作者： Xiongkuo MIN Huiyu DUAN Wei SUN Yucheng ZHU Guangtao ZHAI department of electronic {2. Shanghai Jiao Tong University

Perceptual video quality assessment plays a vital role in the field of video processing due to the existence of quality degradations introduced in various stages of video signal acquisition, compression,transmission and display. With the advancement of Internet communication and cloud service technology,video content and traffic are growing exponentially, which further emphasizes the requirement for accurate and rapid assessment of video quality. Therefore, numerous subjective and objective video quality assessment studies have been conducted over the past two decades for both generic videos and specific videos such as streaming, user-generated content, 3D, virtual and augmented reality, high dynamic range, high frame rate, audio-visual, etc. This survey provides an up-to-date and comprehensive review of these video quality assessment studies. Specifically, we first review the subjective video quality assessment methodologies and databases, which are necessary for validating the performance of video quality metrics. Second, the objective video quality assessment measures for general purposes are categorized and surveyed according to the methodologies utilized in the quality measures. Third, we overview the objective video quality assessment measures for specific applications and emerging topics. Finally, the performance of the state-of-the-art video quality assessment measures is compared and analyzed. This survey provides a systematic overview of both classical works and recent progress in the realm of video quality assessment, which can help other researchers quickly access the field and conduct relevant research.

关键词： video quality assessment human visual system subjective quality assessment objective quality assessment survey

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Next generation multiple access for IMT towards 2.30 and beyond

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Science China(Information Sciences) 2024年第6期67卷 448-450页

作者： Zhiguo DING Robert SCHOBER Pingzhi FAN H.Vincent POOR department of Computer and Information engineering Khalifa University department of Electrical and electronic {2. University of Manchester Institute for Digital Communications Friedrich Alexander-University Erlangen-Nurnberg (FAU) CSNMT International Cooperation Research Center (MoST) Southwest Jiaotong University department of Electrical and Computer engineering Princeton University

Multiple access techniques are fundamental to the design of wireless communication systems,since many crucial components of such systems depend on the choice of the multiple access technique[1].For example,the use of ...

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.E.Al-Atroush A.E.Aboelela Ezz El-Din Hemdan Civil and Environmental engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia department of Structural engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and Materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and engineering department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2.2.,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

Low-temperature chemistry in plasma-driven ammonia oxidative pyrolysis

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Green Energy & Environment 2024年第9期9卷 1477-1488页

作者： Mingming Zhang Qi Chen Guangzhao Zhou Jintao Sun He Lin School of Mechanical Electronic and Control Engineering Beijing Jiaotong University School of Mechanical engineering Shanghai Jiao Tong University

Ammonia is gaining increasing attention as a green alternative fuel for achieving large-scale carbon emission reduction. Despite its potential technical prospects, the harsh ignition conditions and slow flame propagation speed of ammonia pose significant challenges to its application in engines. Non-equilibrium plasma has been identified as a promising method, but current research on plasma-enhanced ammonia combustion is limited and primarily focuses on ignition characteristics revealed by kinetic models. In this study, low-temperature and low-pressure chemistry in plasma-assisted ammonia oxidative pyrolysis is investigated by integrated studies of steady-state GC measurements and mathematical simulation. The detailed kinetic mechanism of NH3decomposition in plasma-driven Ar/NH3and Ar/NH3/O2.ixtures has been developed. The numerical model has good agreements with the experimental measurements in NH3/O2.onsumption and N2.H2.eneration, which demonstrates the rationality of modelling. Based on the modelling results, species density profiles, path flux and sensitivity analysis for the key plasmaproduced species such as NH2. NH, H2. OH, H, O, O（1D）, O2.a1△g）, O2.b1∑g+）, Ar*, H-, Ar+, NH3+, O2.in the discharge and afterglow are analyzed in detail to illustrate the effectiveness of the active species on NH3excitation and decomposition at low temperature and relatively higher E/N values. The results revealed that NH2. NH, H as well as H2.re primarily generated through the electron collision reactions e + NH3→ e + NH2. H, e + NH3→ e + NH + H2.nd the excited-argon collision reaction Ar*+ NH3+ H → Ar + NH2. 2., which will then react with highly reactive oxidative species such as O2., O*, O, OH, and O2.o produce stable products of NOx and H2.. NH3→ NH is found a specific pathway for NH3consumption with plasma assistance, which further highlights the enhanced kinetic effects.

关键词： Non-equilibrium plasma Ammonia fuel Oxidative pyrolysis Pathway flux analysis Sensitivity analysis

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More Than Lightening:A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 622-637页

作者： Han Xu Jiayi Ma Yixuan Yuan Hao Zhang Xin Tian Xiaojie Guo the electronic Information School Wuhan UniversityWuhan 430072China IEEE the department of electronic {2. Chinese University of Hong KongHong Kong 999077China the College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Low-light images suffer from low quality due to poor lighting conditions,noise pollution,and improper settings of *** enhance low-light images,most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is *** contrast,a self-supervised method breaks free from the reliance on normal-light data,resulting in more convenience and better *** self-supervised methods primarily focus on illumination adjustment and design pixel-based adjustment methods,resulting in remnants of other degradations,uneven brightness and *** response,this paper proposes a self-supervised enhancement method,termed as *** can handle multiple degradations including illumination attenuation,noise pollution,and color shift,all in a self-supervised *** attenuation is estimated based on physical principles and local neighborhood *** removal and correction of noise and color shift removal are solely realized with noisy images and images with color ***,the comprehensive and fully self-supervised approach can achieve better adaptability and *** is applicable to various low light conditions,and can reproduce the original color of scenes in natural *** experiments conducted on four public datasets demonstrate the superiority of SLIE to thirteen state-of-the-art *** code is available at https://***/hanna-xu/SLIE.

关键词： Color correction low-light image enhancement self-supervised learning.

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Robot-Oriented 6G Satellite-UAV Networks: Requirements, Paradigm Shifts, and Case Studies

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China Communications 2024年第2期21卷 74-84页

作者： Peng Wei Wei Feng Yunfei Chen Ning Ge Wei Xiang department of electronic {2. Tsinghua UniversityBeijing 100084China department of engineering University of DurhamDH13LEDurhamUK School of Computing Engineering and Mathematical SciencesLa Trobe UniversityMelbourneVIC 3086Australia

Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links,via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener’s Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage,enabling new orchestration between network serving and positive mobility control of robots. Moreover,the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing(MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.

关键词： closed-loop communication mobility control satellite-UAV network structured resource allocation

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Integrated optical frequency transfer and optical physical layer key distribution with enhanced link reciprocity detection

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Science China(Information Sciences) 2024年第7期67卷 335-336页

作者： Kunfeng XIE Liang HU Jianping CHEN Guiling WU State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic EngineeringShanghai Jiao Tong University

Optical fiber transmission has been widely used in communications and metrology, wherein optical frequency transfer (OFT) and optical physical layer secure key distribution (OKD) have become research hotspots [1, 2.. Moreover,OFT can perform a comparison between state-of-the-art optical atomic clocks and implement coherent optical phase transfer over long distances to support geodesy [1, 3].

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A Temporal Convolutional Network Based Hybrid Model for Short-term Electricity Price Forecasting

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 1119-1130页

作者： Haoran Zhang Weihao Hu Di Cao Qi Huang Zhe Chen Frede Blaabjerg School of Mechanical and Electrical engineering University of Electronic Science and Technology of ChinaChengduChina department of Energy Technology Aalborg UniversityAalborgDenmark IEEE

Electricity prices have complex features,such as high frequency,multiple seasonality,and *** factors will make the prediction of electricity prices ***,accurate electricity price prediction is important for energy producers and consumers to develop bidding *** improve the accuracy of prediction by using each algorithms’advantages,this paper proposes a hybrid model that uses the Empirical Mode Decomposition(EMD),Autoregressive Integrated Moving Average(ARIMA),and Temporal Convolutional Network(TCN).EMD is used to decompose the electricity prices into low and high frequency *** frequency components are forecasted by the ARIMA model and the high frequency series are predicted by the TCN *** results using the realistic electricity price data from Pennsylvania-New Jersey-Maryland(PJM)electricity markets show that the proposed method has a higher prediction accuracy than other single methods and hybrid methods.

关键词： Autoregressive integrated moving average model electricity price forecasting empirical mode decomposition temporal convolutional network

Development of Multi-Agent-Based Indoor 3D Reconstruction

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Computers, Materials and Continua 2024年第1期81卷 161-181页

作者： Cheng H.C. Hong F.Z. Hussain B. Wang Y. Yue C.P. Optical Wireless Lab Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Large-scale indoor 3D reconstruction with multiple robots faces challenges in core enabling technologies. This work contributes to a framework addressing localization, coordination, and vision processing for multi-agent reconstruction. A system architecture fusing visible light positioning, multi-agent path finding via reinforcement learning, and 360° camera techniques for 3D reconstruction is proposed. Our visible light positioning algorithm leverages existing lighting for centimeter-level localization without additional infrastructure. Meanwhile, a decentralized reinforcement learning approach is developed to solve the multi-agent path finding problem, with communications among agents optimized. Our 3D reconstruction pipeline utilizes equirectangular projection from 360° cameras to facilitate depth-independent reconstruction from posed monocular images using neural networks. Experimental validation demonstrates centimeter-level indoor navigation and 3D scene reconstruction capabilities of our framework. The challenges and limitations stemming from the above enabling technologies are discussed at the end of each corresponding section. In summary, this research advances fundamental techniques for multi-robot indoor 3D modeling, contributing to automated, data-driven applications through coordinated robot navigation, perception, and modeling. © 2.2. The Authors. Published by Tech Science Press.

关键词： 3D reconstruction multi-agent path finding Multi-agent system multi-robot human collaboration reinforcement learning visible light communication visible light positioning