84 research outputs found
Reliable diameter control of carbon nanotube nanowires using withdrawal velocity
Carbon nanotube (CNT) nanobundles are widely used in nanoscale imaging, fabrication, and electrochemical and biological sensing. The diameter of CNT nanobundles should be controlled precisely, because it is an important factor in determining electrode performance. Here, we fabricated CNT nanobundles on tungsten tips using dielectrophoresis (DEP) force and controlled their diameters by varying the withdrawal velocity of the tungsten tips. Withdrawal velocity pulling away from the liquid-air interface could be an important, reliable parameter to control the diameter of CNT nanobundles. The withdrawal velocity was controlled automatically and precisely with a one-dimensional motorized stage. The effect of the withdrawal velocity on the diameter of CNT nanobundles was analyzed theoretically and compared with the experimental results. Based on the attachment efficiency, the withdrawal velocity is inversely proportional to the diameter of the CNT nanobundles; this has been demonstrated experimentally. Control of the withdrawal velocity will play an important role in fabricating CNT nanobundles using DEP phenomena.110Ysciescopu
Enabling Hard Constraints in Differentiable Neural Network and Accelerator Co-Exploration
Co-exploration of an optimal neural architecture and its hardware accelerator
is an approach of rising interest which addresses the computational cost
problem, especially in low-profile systems. The large co-exploration space is
often handled by adopting the idea of differentiable neural architecture
search. However, despite the superior search efficiency of the differentiable
co-exploration, it faces a critical challenge of not being able to
systematically satisfy hard constraints such as frame rate. To handle the hard
constraint problem of differentiable co-exploration, we propose HDX, which
searches for hard-constrained solutions without compromising the global design
objectives. By manipulating the gradients in the interest of the given hard
constraint, high-quality solutions satisfying the constraint can be obtained.Comment: publisehd at DAC'2
Multi-modal imaging using a cascaded microscope design
We present a new Multimodal Fiber Array Snapshot Technique (M-FAST), based on
an array of 96 compact cameras placed behind a primary objective lens and a
fiber bundle array. which is capable of large-area, high-resolution,
multi-channel video acquisition. The proposed design provides two key
improvements to prior cascaded imaging system approaches: a novel optical
arrangement that accommodates the use of planar camera arrays, and the new
ability to acquire multi-modal image data acquisition. M-FAST is a multi-modal,
scalable imaging system that can acquire snapshot dual-channel fluorescence
images as well as d phase contrast measurements over a large 8x10mm^2 FOV at
2.2um full-pitch resolution
An Autonomous Human Following Caddie Robot with High-Level Driving Functions
Nowadays, mobile robot platforms are utilized in various fields not only for transportation but also for other diverse services such as industrial, medical and, sports, etc. Mobile robots are also an emerging application as sports field robots, where they can help serve players or even play the games. In this paper, a novel caddie robot which can autonomously follow the golfer as well as provide useful information such as golf course navigation system and weather updates, is introduced. The locomotion of the caddie robot is designed with two modes: autonomous human following mode and manual driving mode. The transition between each mode can be achieved manually or by an algorithm based on the velocity, heading angle, and inclination of the ground surface. Moreover, the transition to manual mode is activated after a caddie robot has recognized the human intention input by hand. In addition, the advanced control algorithm along with a trajectory generator for the caddie robot are developed taking into consideration the locomotion modes. Experimental results show that the proposed strategies to drive various operating modes are efficient and the robot is verified to be utilized in the golf course. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.1
One-directional flow of ionic solutions along fine electrodes under an alternating current electric field
Electric fields are widely used for controlling liquids in various research fields. To control a liquid, an alternating current (AC) electric field can offer unique advantages over a direct current (DC) electric field, such as fast and programmable flows and reduced side effects, namely the generation of gas bubbles. Here, we demonstrate one-directional flow along carbon nanotube nanowires under an AC electric field, with no additional equipment or frequency matching. This phenomenon has the following characteristics: First, the flow rates of the transported liquid were changed by altering the frequency showing Gaussian behaviour. Second, a particular frequency generated maximum liquid flow. Third, flow rates with an AC electric field (approximately nanolitre per minute) were much faster than those of a DC electric field (approximately picolitre per minute). Fourth, the flow rates could be controlled by changing the applied voltage, frequency, ion concentration of the solution and offset voltage. Our finding of microfluidic control using an AC electric field could provide a new method for controlling liquids in various research fields
Transient motion classification through turbid volumes via parallelized single-photon detection and deep contrastive embedding
Fast noninvasive probing of spatially varying decorrelating events, such as
cerebral blood flow beneath the human skull, is an essential task in various
scientific and clinical settings. One of the primary optical techniques used is
diffuse correlation spectroscopy (DCS), whose classical implementation uses a
single or few single-photon detectors, resulting in poor spatial localization
accuracy and relatively low temporal resolution. Here, we propose a technique
termed Classifying Rapid decorrelation Events via Parallelized single photon
dEtection (CREPE)}, a new form of DCS that can probe and classify different
decorrelating movements hidden underneath turbid volume with high sensitivity
using parallelized speckle detection from a pixel SPAD array. We
evaluate our setup by classifying different spatiotemporal-decorrelating
patterns hidden beneath a 5mm tissue-like phantom made with rapidly
decorrelating dynamic scattering media. Twelve multi-mode fibers are used to
collect scattered light from different positions on the surface of the tissue
phantom. To validate our setup, we generate perturbed decorrelation patterns by
both a digital micromirror device (DMD) modulated at multi-kilo-hertz rates, as
well as a vessel phantom containing flowing fluid. Along with a deep
contrastive learning algorithm that outperforms classic unsupervised learning
methods, we demonstrate our approach can accurately detect and classify
different transient decorrelation events (happening in 0.1-0.4s) underneath
turbid scattering media, without any data labeling. This has the potential to
be applied to noninvasively monitor deep tissue motion patterns, for example
identifying normal or abnormal cerebral blood flow events, at multi-Hertz rates
within a compact and static detection probe.Comment: Journal submissio
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