Mutual information maximizing GAN inversion for real face with identity preservation

Recent generative adversarial networks (GANs) have yielded remarkable performance in face image synthesis. GAN inversion embeds an image into the latent space of a pretrained generator, enabling it to be used for real face manipulation. However, current inversion approaches for real faces suffer the dilemma of initialization collapse and identity loss. In this paper, we propose a hierarchical GAN inversion for real faces with identity preservation based on mutual information maximization. We first use a facial domain guaranteed initialization to avoid the initialization collapse. Furthermore, we prove that maximizing the mutual information between inverted faces and their identities is equivalent to minimizing the distance between identity features from inverted and original faces. Optimization for real face inversion with identity preservation is implemented on this mutual information-maximizing constraint. Extensive experimental results show that our approach outperforms state-of-the-art solutions for inverting and editing real faces, particularly in terms of face identity preservation.     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

A Pattern Recognition Method of Personalized Adaptive Learning in Online Education

Mobile Networks and Applications - In order to effectively identify the pattern of personalized adaptive learning in online education and improve the recommendation satisfaction of personalized...     

Priority-MECE: A Mobile Edge Cloud Ecosystem Based on Priority Tasks Offloading

Mobile Networks and Applications - With the rapid development of Internet of things, the traditional city model is no longer applicable. Therefore, the emerging concept of smart city meets the...     

Rip currents near coastal structures in Lake Michigan: Characterization and assessment for warnings

Rip currents near coastal structures commonly occur in Lake Michigan in the Great Lakes region of the United States. Lack of timely warning due to undocumented characteristics of rip currents and no assessment tool can contribute to tragic drownings incidents. In this paper, we characterized rip current occurrences near breakwater structures and developed an assessment tool for providing timely rip current warnings to beachgoers at the study site, City of Port Washington, WI. Characteristics of rip currents near the structure were observed from field measurements or visual images. Deflection rip currents had speeds of ～ 0.2 m/s and lasted for several hours. The rip current occurrences were associated with environmental proxies. It was found that rip currents can occur even when the water appears calm near the structure. A Structure Rip Checklist and Assessment Matrix (SRiCAM) with a four-tiered risk was developed and validated using observations. Furthermore, the SRiCAM was integrated into cyberinfrastructure with a data contingency plan to provide real-time warnings to the public. The applicability of the SRiCAM to other locations across Lake Michigan was further tested and results are promising. Overall, the SRiCAM has the potential to be widely extended to foster recreational water safety and resilience to rip current hazards in the Great Lakes.     

Formation of Sn filled CNTs nanocomposite: Study of their magnetic,dielectric properties and enhanced microwave absorption performance at gigahertz frequencies

The Simplistic formation, advantageous configuration, non-colossal magnetoresistance and broadband absorption are important parameters for microwave absorbent materials. In this study, a core-shell nanocomposite comprising of Sn-filled carbon nanotubes (Sn/CNTs) was prepared by arc discharge method. The microstructure, morphology and surface composition of Sn/CNTs-based core-shell nanocomposites were characterized in detail. Sn/CNTs nanocomposite showed a magnetic signal due to the broken bonds and defects at interfaces in Sn/CNTs. The weak ferromagnetism was found to be helpful in improving magnetic permeability in the Sn/CNTs which confirms its role as a magnetic loss material under incident electromagnetic wave. Sn-filled CNTs revealed an appropriate value of dielectric constant, which plays an important role in impedance matching upon incident electromagnetic wave. The composite of Sn-CNTs and paraffin with a 50 wt % loading showed the lowest reflection loss (RL) of ?43.87 dB at 10 GHz, with a wide effective absorption band (RL ≤ ?10 dB) of 3 GHz in thickness of 2.3 mm. This enhanced performance is attributed to the combined effect of the conduction loss in one-dimensional core-shell architecture, the interfacial loss Sn-CNT interface, the magnetic loss due to defects-induced ferromagnetism in Sn shell, and in the carbon-containing atomic layers of CNTs.     

Mg gas infiltration for the fabrication of MgB2 pellets using nanosized and microsized B powders

MgB₂ superconductor pellets were synthesized through Mg gas infiltration method using nanosized- and microsized B powders. There was a marked difference in the superconducting properties of the two samples, particularly in the pinning force and dominant pinning mechanism. The microstructures of the samples were observed using HR-TEM and STEM-HAADF, and the results showed that the primary reason for the difference in the superconducting properties is the distribution of the nanosized second-phase particle MgO. Additionally, a feasible reaction model for the Mg gas infiltration method was established. Compared to the Mg liquid infiltration method, the gas infiltration showed better penetrability ability with a small amount of residual Mg. This study presents a novel synthesis process to fabricate an MgB₂ pellet with superior density and superconducting properties. This method can be used in multiple applications such as superconducting bearings, compact superconductor magnets, and magnetic shielding.     

Software Optimization in Ultrasound Imaging Technique Using Improved Deep Belief Learning Network on the Internet of Medical Things Platform

Wireless Personal Communications - The Internet of Medical Things (IoMT) is the array of medical instruments and related technologies that link Information Technology (IT) systems in...     

Live video streaming service with pay-as-you-use model on Ethereum Blockchain and InterPlanetary file system

Wireless Networks - In centralized video streaming platforms, the platform owner, rather than the content producer, controls most of the content uploaded on the centralized video...