Plasma-induced unconventional shock waves on oil surfaces

Electric corona discharge in a multi-phase system results in complex electro-hydrodynamic phenomena. We observed unconventional shock wave propagation on an oil thin film sprayed over a polymer-coated conductor. A hair-thin single shock wave arose when the high voltage bias of an overhung steel needle was abruptly removed. However, such solitary waves possess neither interference nor reflection properties commonly known for ordinary waves, and also differ from the solitons in a canal or an optical fiber. We also observed time-retarded movement for dispersed oil droplets at various distances from the epicenter which have no physical contact, as if a wave propagating on a continuous medium. Such a causality phenomenon for noncontact droplets to move resembling wave propagation could not be possibly described by the conventional surface wave equation. Our systematic studies reveal a mechanism involving oil surface charges driven by reminiscent electric fields in the air when the needle bias is suddenly removed

Towards a deep-learning-based framework of sentinel-2 imagery for automated active fire detection

This paper proposes an automated active fire detection framework using Sentinel-2 imagery. The framework is made up of three basic parts including data collection and preprocessing, deep-learning-based active fire detection, and final product generation modules. The active fire detection module is developed on a specifically designed dual-domain channel-position attention (DCPA)+HRNetV2 model and a dataset with semi-manually annotated active fire samples is constructed over wildfires that commenced on the east coast of Australia and the west coast of the United States in 2019-2020 for the training process. This dataset can be used as a benchmark for other deep-learning-based algorithms to improve active fire detection accuracy. The performance of active fire detection is evaluated regarding the detection accuracy of deep-learning-based models and the processing efficiency of the whole framework. Results indicate that the DCPA and HRNetV2 combination surpasses DeepLabV3 and HRNetV2 models for active fire detection. In addition, the automated framework can deliver active fire detection results of Sentinel-2 inputs with coverage of about 12,000 km(2) (including data download) in less than 6 min, where average intersections over union (IoUs) of 70.4% and 71.9% were achieved in tests over Australia and the United States, respectively. Concepts in this framework can be further applied to other remote sensing sensors with data acquisitions in SWIR-NIR-Red ranges and can serve as a powerful tool to deal with large volumes of high-resolution data used in future fire monitoring systems and as a cost-efficient resource in support of governments and fire service agencies that need timely, optimized firefighting plans

C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference

Recently, private inference (PI) has addressed the rising concern over data and model privacy in machine learning inference as a service. However, existing PI frameworks suffer from high computational and communication costs due to the expensive multi-party computation (MPC) protocols. Existing literature has developed lighter MPC protocols to yield more efficient PI schemes. We, in contrast, propose to lighten them by introducing an empirically-defined privacy evaluation. To that end, we reformulate the threat model of PI and use inference data privacy attacks (IDPAs) to evaluate data privacy. We then present an enhanced IDPA, named distillation-based inverse-network attack (DINA), for improved privacy evaluation. Finally, we leverage the findings from DINA and propose C2PI, a two-party PI framework presenting an efficient partitioning of the neural network model and requiring only the initial few layers to be performed with MPC protocols. Based on our experimental evaluations, relaxing the formal data privacy guarantees C2PI can speed up existing PI frameworks, including Delphi [1] and Cheetah [2], up to 2.89x and 3.88x under LAN and WAN settings, respectively, and save up to 2.75x communication costs

High‐Performance Pseudocubic Thermoelectric Materials from Non‐cubic Chalcopyrite Compounds

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107585/1/adma201400058-sup-0001-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/107585/2/adma201400058.pd

Plasma-induced unconventional shock waves on oil surfaces

Electric corona discharge in a multi-phase system results in complex electro-hydrodynamic phenomena. We observed unconventional shock wave propagation on an oil thin film sprayed over a polymer-coated conductor. A hair-thin single shock wave arose when the high voltage bias of an overhung steel needle was abruptly removed. However, such solitary waves possess neither interference nor reflection properties commonly known for ordinary waves, and also differ from the solitons in a canal or an optical fiber. We also observed time-retarded movement for dispersed oil droplets at various distances from the epicenter which have no physical contact, as if a wave propagating on a continuous medium. Such a causality phenomenon for noncontact droplets to move resembling wave propagation could not be possibly described by the conventional surface wave equation. Our systematic studies reveal a mechanism involving oil surface charges driven by reminiscent electric fields in the air when the needle bias is suddenly removed

High frequency CMOS amplifier with improved linearity

In this paper, a novel amplifier linearisation technique based on the negative impedance compensation is presented. As demonstrated by using Volterra model, the proposed technique is suitable for linearising amplifiers with low open-loop gain, which is appropriate for RF/microwave applications. A single-chip CMOS amplifier has been designed using the proposed method, and the simulation results show that high gain accuracy (improved by 38%) and high linearity (IMD3 improved by 14 dB, OIP3 improved by 11 dB and adjacent channel power ratio (ACPR) improved by 44% for CDMA signal) can be achieved

Entropy as a Gene‐Like Performance Indicator Promoting Thermoelectric Materials

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138909/1/adma201702712.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138909/2/adma201702712-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138909/3/adma201702712_am.pd