6,651 research outputs found
Large-Scale Highly Aligned Nanowire Printing
Nanowires (NWs) are 1D confined nanostructures; this geometry gives them unique properties that have been exploited in fabrication of high-density and high-tech electronic devices. Current method to produce NWs cannot fabricate large-scale-aligned NW arrays with precise control of length, orientation, location, and number of NWs individually; these inabilities hinder application of NWs in practical electronics. This paper describes e-nanowire printing, a method to print highly aligned NWs on a large scale, and then reviews recent progress in various electronic applications with highly aligned NWs. Finally, future research is suggested to advance nanoelectronics.1110Ysciescopu
RFID Information Value Chain and ETRI RFID Ecosystem: Value-added Environment Linking Physical and Virtual Worlds
Design and Analysis of LoS MIMO Systems with Uniform Circular Arrays
We consider the design of a uniform circular array (UCA) based multiple-input
multiple-output (MIMO) system over line-of-sight (LoS) environments in which
array misalignment exists. In particular, optimal antenna placement in UCAs and
transceiver architectures to achieve the maximum channel capacity without the
knowledge of misalignment components are presented. To this end, we first
derive a generic channel model of UCA-based LoS MIMO systems in which three
misalignment factors including relative array rotation, tilting and
center-shift are reflected concurrently. By factorizing the channel matrix into
the singular value decomposition (SVD) form, we demonstrate that the singular
values of UCA-based LoS MIMO systems are \textit{independent} of tilting and
center-shift. Rather, they can be expressed as a function of the \textit{radii
product-to-distance ratio} (RPDR) and the angle of relative array rotation.
Numerical analyses of singular values show that the RPDR is a key design
parameter of UCA systems. Based on this result, we propose an optimal design
method for UCA systems which performs a one-dimensional search of RPDR to
maximize channel capacity. It is observed that the channel matrix of the
optimally designed UCA system is close to an orthogonal matrix; this fact
allows channel capacity to be achieved by a simple zero-forcing (ZF) receiver.
Additionally, we propose a low-complexity precoding scheme for UCA systems in
which the optimal design criteria cannot be fulfilled because of limits on
array size. The simulation results demonstrate the validity of the proposed
design method and transceiver architectures.Comment: 13 pages, 10 figures, This work has been submitted to the IEEE for
possible publication. Copyright may be transferred without notice, after
which this version may no longer be accessibl
Continuous Facial Motion Deblurring
We introduce a novel framework for continuous facial motion deblurring that
restores the continuous sharp moment latent in a single motion-blurred face
image via a moment control factor. Although a motion-blurred image is the
accumulated signal of continuous sharp moments during the exposure time, most
existing single image deblurring approaches aim to restore a fixed number of
frames using multiple networks and training stages. To address this problem, we
propose a continuous facial motion deblurring network based on GAN (CFMD-GAN),
which is a novel framework for restoring the continuous moment latent in a
single motion-blurred face image with a single network and a single training
stage. To stabilize the network training, we train the generator to restore
continuous moments in the order determined by our facial motion-based
reordering process (FMR) utilizing domain-specific knowledge of the face.
Moreover, we propose an auxiliary regressor that helps our generator produce
more accurate images by estimating continuous sharp moments. Furthermore, we
introduce a control-adaptive (ContAda) block that performs spatially deformable
convolution and channel-wise attention as a function of the control factor.
Extensive experiments on the 300VW datasets demonstrate that the proposed
framework generates a various number of continuous output frames by varying the
moment control factor. Compared with the recent single-to-single image
deblurring networks trained with the same 300VW training set, the proposed
method show the superior performance in restoring the central sharp frame in
terms of perceptual metrics, including LPIPS, FID and Arcface identity
distance. The proposed method outperforms the existing single-to-video
deblurring method for both qualitative and quantitative comparisons
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