Ramsey interferometry through coherent X2Σg+−A2Πu−B2Σu+X^2\Sigma_g^+ - A^2\Pi_u - B^2\Sigma_u^+ coupling and population transfer in N2+^+_2 air laser

The laser-like coherent emission at 391nm from N$_2$ gas irradiated by strong 800nm pump laser and weak 400nm seed laser is theoretically investigated. Recent experimental observations are well simulated, including temporal profile, optical gain and periodic modulation of the 391nm signal from N$_2^+$. Our calculation sheds light on the long standing controversy on whether population inversion is indispensable for the optical gain. We demonstrate the Ramsey interference fringes of the emission intensity at 391nm formed by additionally injecting another 800nm pump or 400nm seed, which are well explained by the coherent modulation of transition dipole moment and population between the $A^2\Pi_u(\nu=2)$-$X^2\Sigma_g^+$ states as well as the $B^2\Sigma_u^+ (\nu=0)$-$X^2\Sigma_g^+$ states. This study provides versatile possibilities for the coherent control of $\text{N}_2^+$ air laser.Comment: 5 pages, 5 figure

Predicting the quality of images compressed after distortion in two steps

In a typical communication pipeline, images undergo a series of processing steps that can cause visual distortion before being viewed. Given a high-quality reference image, a reference image quality assessment (IQA) algorithms can be applied after compression or transmission. However, the assumption of a high quality reference image is often not fulfilled in practice, contributing to less accurate quality predictions. Towards ameliorating this problem, we have devised a novel two-step image quality prediction approach that combines no-reference with reference quality measurements. Applying a first stage of no-reference IQA to determine the possibly degraded quality of the source image yields information that can be used to quality-modulate the reference prediction to improve its accuracy. We devise a simple and efficient weighted product of reference and no-reference stages that produces more reliable objective prediction scores. We also constructed a new dedicated database that is specialized for the design and testing of 'two-step' IQA models. Using this new resource, we show that two-step approaches yield outstanding performance when applied to compressed images whose original, pre-compression quality covers a wide range of realistic distortion types and severities. The two-step concept is versatile as it can use any desired reference and no-reference components. [...]Electrical and Computer Engineerin

Perceptual quality assessment of user-generated-content images and videos

Because of the increasing ease of image and video capture, many millions of consumers create and upload large volumes of User-Generated-Content (UGC) images and videos to social and streaming media sites over the Internet. UGC images and videos are commonly captured by naive users having limited skills and imperfect techniques, and tend to be afflicted by mixtures of highly diverse in-capture distortions. They are then often uploaded for sharing onto cloud servers, where they are further compressed for storage and transmission. My Ph.D. research first tackles the highly practical problem of predicting the quality of compressed images and videos with only (possibly severely) distorted UGC references. To address this problem, we develop a novel two-step image quality prediction concept called 2stepQA, and a novel Video Quality Assessment (VQA) framework called 1stepVQA. We construct a new, first-of-a-kind dedicated image quality database specialized for the design and testing of two-step IQA models, and a new dedicated video database, which was created by applying a realistic VMAF-Guided perceptual rate distortion optimization (RDO) criterion to create realistically compressed versions of UGC source videos, which typically have pre-existing distortions. Furthermore, we also study the automatic quality prediction of a particular UGC category, UGC gaming videos. To do this, we create a novel UGC gaming video resource, called the LIVE-YouTube Gaming video quality (LIVE-YT-Gaming) database, comprised of 600 real UGC gaming videos. We create a new VQA model specifically designed to succeed on UGC gaming videos, called the Gaming Video Quality Predictor (GAME-VQP). GAME-VQP successfully predicts the unique statistical characteristics of gaming videos by drawing upon features designed under modified natural scene statistics models, combined with gaming specific features learned by a Convolution Neural Network. We study the performance of 2stepQA, 1stepVQA, and GAME-VQP on the three new video (image) databases, respectively, and find that they all outperform other mainstream VQA models.Electrical and Computer Engineerin

RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content

Blind or no-reference video quality assessment of user-generated content (UGC) has become a trending, challenging, heretofore unsolved problem. Accurate and efficient video quality predictors suitable for this content are thus in great demand to achieve more intelligent analysis and processing of UGC videos. Previous studies have shown that natural scene statistics and deep learning features are both sufficient to capture spatial distortions, which contribute to a significant aspect of UGC video quality issues. However, these models are either incapable or inefficient for predicting the quality of complex and diverse UGC videos in practical applications. Here we introduce an effective and efficient video quality model for UGC content, which we dub the Rapid and Accurate Video Quality Evaluator (RAPIQUE), which we show performs comparably to state-of-the-art (SOTA) models but with orders-of-magnitude faster runtime. RAPIQUE combines and leverages the advantages of both quality-aware scene statistics features and semantics-aware deep convolutional features, allowing us to design the first general and efficient spatial and temporal (space-time) bandpass statistics model for video quality modeling. Our experimental results on recent large-scale UGC video quality databases show that RAPIQUE delivers top performances on all the datasets at a considerably lower computational expense. We hope this work promotes and inspires further efforts towards practical modeling of video quality problems for potential real-time and low-latency applications. To promote public usage, an implementation of RAPIQUE has been made freely available online: \url{https://github.com/vztu/RAPIQUE}.Comment: IEEE Open Journal of Signal Processing 202

Six-Degree-of-Freedom Posture Measurement Technologies Using Position Sensitive Detectors (PSDs): State of the Art

Six degree-of-freedom (6-DOF) posture measurement is an important academic research topic which has been broadly applied in many fields. As a high-speed photoelectronic sensor with ultra-high resolution and precision, position sensitive detector (PSD) has shown to be one of the most competitive candidates in 6-DOF measurement. This review presents the research progress of PSD-based 6-DOF posture measurement systems in the field of large-scale equipment assembly, ultra-precision manufacturing and other emerging areas. A total of six methods for implementing 6-DOF measurement are summarized and their advantages and limitations are discussed. Meanwhile, the paper illustrates challenges, potential solutions and future development trends

A method for Absolute Protein Expression Quantity Measurement Employing Insulator RiboJ

Measuring the absolute protein expression quantity for a specific promoter is necessary in the fields of both molecular biology and synthetic biology. The strength of a promoter is traditionally characterized by measuring the fluorescent intensity of the fluorescent protein downstream of the promoter. Until now, measurement of the absolute protein expression quantity for a promoter, however, has been unsuccessful in synthetic biology. The fact that the protein coding sequence influences the expression level for different proteins, and the inconvenience of measuring the absolute protein expression level, present a challenge to absolute quantitative measurement. Here, we introduce a new method that combines the insulator RiboJ with the standard fluorescence curve in order to measure the absolute protein expression quantity quickly; this method has been validated by modeling verification. Using this method, we successfully measured nine constitutive promoters in the Anderson promoter family. Our method provides data with higher accuracy for pathway design and is a straightforward way to standardize the strength of different promoters. Keywords: RiboJ, Promoter measurement, Synthetic biolog