Objective and subjective assessment of perceptual factors in HDR content processing

The development of the display and camera technology makes high dynamic range (HDR) image become more and more popular. High dynamic range image give us pleasant image which has more details that makes high dynamic range image has good quality. This paper shows us the some important techniques in HDR images. And it also presents the work the author did. The paper is formed of three parts. The first part is an introduction of HDR image. From this part we can know why HDR image has good quality

DEM Study of Wet Cohesive Particles in the Presence of Liquid Bridges in a Gas Fluidized Bed

A modified discrete element method (DEM) was constructed by compositing an additional liquid-bridge module into the traditional soft-sphere interaction model. Simulations of particles with and without liquid bridges are conducted in a bubbling fluidized bed. The geometry of the simulated bed is the same as the one in Müller’s experiment (Müller et al., 2008). A comparison between the dry and the wet particular systems is carried out on the bubble behavior, the bed fluctuation, and the mixing process. The bubble in the dry system possesses a regular round shape and falling of scattered particles exists while the bubble boundary of the wet particles becomes rough with branches of agglomerates stretching into it. The mixing of the dry system is quicker than that of the wet system. Several interparticle liquid contents are applied in this work to find their influence on the kinetic characteristic of the wet particle flow. With an increase of liquid content, the mixing process costs more time to be completed. Symmetrical profiles of the velocity and granular temperature are found for two low liquid contents (0.001% and 0.01%), while it is antisymmetrical for the highest liquid content (0.1%)

Origin-Destination Travel Time Oracle for Map-based Services

Given an origin (O), a destination (D), and a departure time (T), an Origin-Destination (OD) travel time oracle~(ODT-Oracle) returns an estimate of the time it takes to travel from O to D when departing at T. ODT-Oracles serve important purposes in map-based services. To enable the construction of such oracles, we provide a travel-time estimation (TTE) solution that leverages historical trajectories to estimate time-varying travel times for OD pairs. The problem is complicated by the fact that multiple historical trajectories with different travel times may connect an OD pair, while trajectories may vary from one another. To solve the problem, it is crucial to remove outlier trajectories when doing travel time estimation for future queries. We propose a novel, two-stage framework called Diffusion-based Origin-destination Travel Time Estimation (DOT), that solves the problem. First, DOT employs a conditioned Pixelated Trajectories (PiT) denoiser that enables building a diffusion-based PiT inference process by learning correlations between OD pairs and historical trajectories. Specifically, given an OD pair and a departure time, we aim to infer a PiT. Next, DOT encompasses a Masked Vision Transformer~(MViT) that effectively and efficiently estimates a travel time based on the inferred PiT. We report on extensive experiments on two real-world datasets that offer evidence that DOT is capable of outperforming baseline methods in terms of accuracy, scalability, and explainability.Comment: 15 pages, 12 figures, accepted by SIGMOD International Conference on Management of Data 202

Processing outcomes of the AFM probe-based machining approach with different feed directions

We present experimental and theoretical results to describe and explain processing outcomes when producing nanochannels that are a few times wider than the atomic force microscope (AFM) probe using an AFM. This is achieved when AFM tip-based machining is performed with reciprocating motion of the tip of the AFM probe. In this case, different feed directions with respect to the orientation of the AFM probe can be used. The machining outputs of interest are the chip formation process, obtained machined quality, and variation in the achieved channel depth. A three-sided pyramidal diamond probe was used under load-controlled conditions. Three feed directions were first investigated in detail. The direction parallel to and towards the probe cantilever, which is defined as “edge forward”, was then chosen for further investigation because it resulted in the best chip formation, machining quality, and material removal efficiency. To accurately reveal the machining mechanisms, several feed directions with different included angles for the pure edge-forward direction were investigated. Upon analysis of the chips and the machined nanochannels, it was found that processing with included angles in the range 0–30° led to high-quality channels and high material-removal efficiency. In this case, the cutting angles, such as the rake angle, clearance angle, and shear angle, have an important influence on the obtained results. In addition, a machining model was developed to explain the observed machined depth variation when scratching in different feed directions

The effect of ions doping on the rheological properties of ferrite ferrofluids

A series of ferrite nanoparticles were synthesized via ion doping and then were coated by surfactant and dispersed in perfluorinated polyether oil (PFPE-oil), and the various ferrite ferrofluids were obtained. The scanning electron microscope was used to characterize the morphology of particles and the dispersed state of ferrofluid, energy-dispersive spectroscopy was used to study the chemical composition of particles, fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis were used to study the coated effect of PFPE-acids on particles, vibrating sample magnetometer was used to research the magnetization curves of ferrite particles, and the rheological property of the ferrite ferrofluids was studied by a rheometer. The results show that Zn2+, Mn2+/Zn2+, and Dy3+ ions were doped in the ferrite nanoparticles with a size less than 50 nm. The four kinds of ferrite nanoparticles have the characteristics of super-paramagnetic materials, and the M-T curves decrease with increasing temperature, while their decline rates are notably different. The ferrite particles are coated with PFPE acids chemically, and the ferrofluids have well dispersion stability. The rheological properties of the ferrite ferrofluids change with the variation of ion doping, magnetic field strength, temperature, etc. The magnetism and viscosity of ferrite ferrofluids are regularly affected by ion doping, and the results will have a great significance on basic research and related applications