We present an experimental demonstration of a thermoelectric sensor coupled with nanoantenna as alternative option for detecting infrared energy. Two design (single element and array) variations based on Yagi-Uda technology one separate nano-thermoelectric junction array were fabricated tested. The nanoantennas tuned to operate respond at center wavelength 1550 nm (193.5 THz) optical C-band win...

A pattern-reconfigurable Yagi–Uda antenna based on liquid metal is presented. The consists of a balun-fed active dipole and pair stretchable passive parasitic dipoles, which are implemented by eutectic gallium-indium (EGaIn) alloy embedded in microfluidic channels. dipoles driven at each end two low-cost, three-dimensional printed media rods. Afterward, spinning the rods different angles leads ...

Recent studies have shown that pseudo labels can contribute to unsupervised domain adaptation (UDA) for speaker verification. Inspired by the self-training strategies use an existing classifier label unlabeled data retraining, we propose a cluster-guided UDA framework target clustering and combines labeled source pseudo-labeled train embedding network. To improve cluster quality, network dedica...

Memory built-in self-test (BIST) is a widely used technique to allow the and self-checking of embedded memories on chips after fabrication process. It can be by implementing standard testing algorithm available in EDA tool library or user-defined (UDA). This paper presents development software that automatically generates description file UDA deployed for memory BIST circuit implementation usin...

Collection of real world annotations for training semantic segmentation models is an expensive process. Unsupervised domain adaptation (UDA) tries to solve this problem by studying how more accessible data such as synthetic can be used train and adapt images without requiring their annotations. Recent UDA methods applies self-learning on pixel-wise classification loss using a student teacher ne...

We develop an algorithm for adapting a semantic segmentation model that is trained using labeled source domain to generalize well in unlabeled target domain. A similar problem has been studied extensively the unsupervised adaptation (UDA) literature, but existing UDA algorithms require access both data and training agnostic model. Relaxing this constraint enables user adapt pretrained models do...

MHC class I proteins mediate a variety of functions in antiviral defense. In humans and mice, three MHC class I loci each contribute one or two alleles and each can present a wide variety of peptide Ags. In contrast, many lower vertebrates appear to use a single MHC class I locus. Previously we showed that a single locus was predominantly expressed in the mallard duck (Anas platyrhynchos) and t...

We propose a hypothesis disparity regularized mutual information maximization (HDMI) approach to tackle unsupervised transfer---as an effort towards unifying transfer learning (HTL) and domain adaptation (UDA)---where the knowledge from source is transferred solely through hypotheses adapted target in manner. In contrast prevalent HTL UDA approaches that typically use single hypothesis, HDMI em...

Contrastive learning is a promising approach to unsupervised learning, as it inherits the advantages of well-studied deep models without dedicated and complex model design. In this paper, based on bidirectional encoder representations from transformers (BERT) long-short term memory (LSTM) neural networks, we propose self-supervised contrastive (SCL) well few-shot (FCL) with data augmentation (U...