MobileDiffusion: Subsecond Text-to-Image Generation on Mobile Devices

The deployment of large-scale text-to-image diffusion models on mobile devices is impeded by their substantial model size and slow inference speed. In this paper, we propose \textbf{MobileDiffusion}, a highly efficient text-to-image diffusion model obtained through extensive optimizations in both architecture and sampling techniques. We conduct a comprehensive examination of model architecture design to reduce redundancy, enhance computational efficiency, and minimize model's parameter count, while preserving image generation quality. Additionally, we employ distillation and diffusion-GAN finetuning techniques on MobileDiffusion to achieve 8-step and 1-step inference respectively. Empirical studies, conducted both quantitatively and qualitatively, demonstrate the effectiveness of our proposed techniques. MobileDiffusion achieves a remarkable \textbf{sub-second} inference speed for generating a $512\times512$ image on mobile devices, establishing a new state of the art

UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs

Text-to-image diffusion models have demonstrated remarkable capabilities in transforming textual prompts into coherent images, yet the computational cost of their inference remains a persistent challenge. To address this issue, we present UFOGen, a novel generative model designed for ultra-fast, one-step text-to-image synthesis. In contrast to conventional approaches that focus on improving samplers or employing distillation techniques for diffusion models, UFOGen adopts a hybrid methodology, integrating diffusion models with a GAN objective. Leveraging a newly introduced diffusion-GAN objective and initialization with pre-trained diffusion models, UFOGen excels in efficiently generating high-quality images conditioned on textual descriptions in a single step. Beyond traditional text-to-image generation, UFOGen showcases versatility in applications. Notably, UFOGen stands among the pioneering models enabling one-step text-to-image generation and diverse downstream tasks, presenting a significant advancement in the landscape of efficient generative models

Applying the Cox Model to Study Online Gambling Behavior

Although a key objective of Internet gambling service providers is player retention, there is a concomitant need to reduce the social costs of gambling. Our study shows how habit and prospect theories help build an integrative framework for decision support in regulated Internet gambling environments. To illustrate the practical implication of this framework, we applied the Cox model with time-dependent covariates on real gambling data collected from 4,222 users of a gambling website. The results help establish the positive association of key indicators such as the prior outcomes on the activity lifespan of an Internet gambler and the moderating effect of gambling frequency on the positive association between prior outcomes and gambling lifespan. This research is expected to contribute to the literatures on IT adoption and diffusion in general, and IT-based addictive behavior in particular

Characterization of CoTiO3 Nanocrystallites Prepared by Homogeneous Precipitation Method

Nanocrystalline cobalt titanate (CoTiO3) has been synthesized from a well-mixed precursor. The precursor was prepared by a homogeneous precipitation method, in which urea was used as the precipitator. The as-synthesized sample is a mixture of CoTiO3 and rutile nanocrystallites with mean sizes of around 50 nm. It strongly absorbs visible light in the wavelength range of 500-690 nm besides ultraviolet light (wavelength < 370 nm). We found the synthetic CoTiO3 is a semiconducting material with a direct band gap of 2.53 eV. The green CoTiO3 has two absorbance peaks at the wavelengths of 537 and 606 nm, which correspond to the photon energies of 2.31 and 2.05 eV, respectively. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3195

Chrome-free Samarium-based Protective Coatings for Magnesium Alloys

AbstractThe microstructure of chrome-free samarium-based conversion coating on magnesium alloy was investigated and the corrosion resistance was evaluated as well. The micro-morphology, transverse section, crystal structure and composition of the coating were observed by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS) and X- ray photoelectron spectroscopy (XPS), respectively. The corrosion resistance was evaluated by potentiodynamic polarization curve and electrochemical impedance spectroscopy (EIS). The results reveal that the morphology of samarium conversion coating is of crack-mud structure. Tiny cracks distribute in the compact coating deposited by samarium oxides. XRD, EDS and XPS results characterize that the coating is made of amorphous and trivalent-samarium oxides. The potentiodynamic polarization curve, EIS and OCP indicate that the samarium conversion coating can improve the corrosion resistance of magnesium alloys