Quality Classified Image Analysis with Application to Face Detection and Recognition

Motion blur, out of focus, insufficient spatial resolution, lossy compression and many other factors can all cause an image to have poor quality. However, image quality is a largely ignored issue in traditional pattern recognition literature. In this paper, we use face detection and recognition as case studies to show that image quality is an essential factor which will affect the performances of traditional algorithms. We demonstrated that it is not the image quality itself that is the most important, but rather the quality of the images in the training set should have similar quality as those in the testing set. To handle real-world application scenarios where images with different kinds and severities of degradation can be presented to the system, we have developed a quality classified image analysis framework to deal with images of mixed qualities adaptively. We use deep neural networks first to classify images based on their quality classes and then design a separate face detector and recognizer for images in each quality class. We will present experimental results to show that our quality classified framework can accurately classify images based on the type and severity of image degradations and can significantly boost the performances of state-of-the-art face detector and recognizer in dealing with image datasets containing mixed quality images.Comment: 6 page

Finite element modeling and active vibration control of high-speed spinning flexible beam

Finite element modeling and active vibration control of a high-speed spinning flexible coupled electromechanical beam is investigated using a first-order approximation coupling (FOAC) model. Due to centrifugal forces caused by eccentricity in a spinning flexible beam, there exists coupling between axial and transverse vibration modes. The partial differential equations of motion of the beam governing this coupling are derived using Hamilton’s principle based on an FOAC model, and a finite element method for discretization is given. It is observed that the zero-order approximate coupling (ZOAC) model is valid for dynamic description of the flexible beam spinning at low speeds, but no longer valid at high speeds. However, the validity of FOAC model is confirmed at different speeds. Piezoelectric elements for active vibration control of the spinning flexible beam are analyzed and a velocity feedback controller is proposed. Simulation results demonstrate good performance of the proposed velocity feedback controller

A Conditional Variational Framework for Dialog Generation

Deep latent variable models have been shown to facilitate the response generation for open-domain dialog systems. However, these latent variables are highly randomized, leading to uncontrollable generated responses. In this paper, we propose a framework allowing conditional response generation based on specific attributes. These attributes can be either manually assigned or automatically detected. Moreover, the dialog states for both speakers are modeled separately in order to reflect personal features. We validate this framework on two different scenarios, where the attribute refers to genericness and sentiment states respectively. The experiment result testified the potential of our model, where meaningful responses can be generated in accordance with the specified attributes.Comment: Accepted by ACL201

A measurement and modelling study of hair partition of neutral, cationic and anionic chemicals

Various neutral, cationic and anionic chemicals contained in hair care products can be absorbed into hair fiber to modulate physicochemical properties such as color, strength, style and volume. For environmental safety, there is also an interest in understanding hair absorption to wide chemical pollutants. There have been very limited studies on the absorption properties of chemicals into hair. Here, an experimental and modelling study has been carried out for the hair-water partition of a range of neutral, cationic and anionic chemicals at different pH. The data showed that hair-water partition not only depends on the hydrophobicity of the chemical but also the pH. The partition of cationic chemicals to hair increased with pH and this is due to their electrostatic interaction with hair increased from repulsion to attraction. For anionic chemicals, their hair-water partition coefficients decreased with increasing pH due to their electrostatic interaction with hair decreased from attraction to repulsion. Increase in pH didn’t change the partition of neutral chemicals significantly. Based on the new physicochemical insight of the pH effect on hair-water partition, a new QSPR model has been proposed, taking into account of both the hydrophobic interaction and electrostatic interaction of chemical with hair fiber

Modeling simulation and parameters optimization for hydraulic impactor

The paper analyzes the working principle of hydraulic impactor, describes the return and stroke order of action and establishes the nonlinear mathematical model describing its dynamic characteristic. The simulation model of hydraulic impactor is established based on AMESim. The structural features of trial machine is used to constrain variables, the piston speed is assigned as the optimizing objective, and the NLPSL algorithm is used to optimize the parameters of system model of hydraulic impactor, after which the system performance is obviously improved

Single-Cell RNA Sequencing of hESC-Derived 3D Retinal Organoids Reveals Novel Genes Regulating RPC Commitment in Early Human Retinogenesis.

The development of the mammalian retina is a complicated process involving the generation of distinct types of neurons from retinal progenitor cells (RPCs) in a spatiotemporal-specific manner. The progression of RPCs during retinogenesis includes RPC proliferation, cell-fate commitment, and specific neuronal differentiation. In this study, by performing single-cell RNA sequencing of cells isolated from human embryonic stem cell (hESC)-derived 3D retinal organoids, we successfully deconstructed the temporal progression of RPCs during early human retinogenesis. We identified two distinctive subtypes of RPCs with unique molecular profiles, namely multipotent RPCs and neurogenic RPCs. We found that genes related to the Notch and Wnt signaling pathways, as well as chromatin remodeling, were dynamically regulated during RPC commitment. Interestingly, our analysis identified that CCND1, a G1-phase cell-cycle regulator, was coexpressed with ASCL1 in a cell-cycle-independent manner. Temporally controlled overexpression of CCND1 in retinal organoids demonstrated a role for CCND1 in promoting early retinal neurogenesis. Together, our results revealed critical pathways and novel genes in early retinogenesis of humans

Solvatochromic Parameters of the Binary Mixtures of Imidazolium Chloride Ionic Liquid Plus Molecular Solvent

Imidazolium-based chloride ionic liquids (ILs) have exhibited remarkable performance in several important applications such as biomass dissolution and extraction, but their large viscosity is a non-negligible problem. Adding molecular co-solvents into chloride ILs is effective in reducing viscosity; nevertheless, understanding of the accompanied change of thermodynamic polarity is quite few. Therefore, in this work we reported three Kamlet-Taft solvatochromic parameters, including dipolarity/polarizability π*), hydrogen-bond acidity (α) and hydrogen-bond basicity (β), for the binary mixtures of several imidazolium-based chloride ILs plus either dipolar protic solvents (water and methanol) or dipolar aprotic solvents (dimethyl sulfoxide, N,N-dimethylformamide and acetonitrile). The results demonstrated that those parameters could be altered by the structure of IL and type of co-solvent owing to the solute-solvent and solvent-solvent interactions. The structure of alkyl chain of cation had considerable impact on the π* variation of IL aqueous solution against IL concentration but hardly affected other mixtures. Moreover, remarkable preferential solvation of probes was observed for β and α in the mixtures of IL and dipolar aprotic co-solvents, whereas the hydrogen-bond interactions between IL and dipolar protic co-solvent enabled the preferential solvation to be alleviated and resulted in more linear variation of β and α against the molar fraction of IL. The results not only contribute to a better understanding of the effect of co-solvent on imidazolium-based chloride ILs, but also are instructive for improving the thermodynamic performance of IL-based applications via providing IL+co-solvent mixtures with desirable physicochemical properties