1,516 research outputs found
Improving the Expressiveness of Deep Learning Frameworks with Recursion
Recursive neural networks have widely been used by researchers to handle
applications with recursively or hierarchically structured data. However,
embedded control flow deep learning frameworks such as TensorFlow, Theano,
Caffe2, and MXNet fail to efficiently represent and execute such neural
networks, due to lack of support for recursion. In this paper, we add recursion
to the programming model of existing frameworks by complementing their design
with recursive execution of dataflow graphs as well as additional APIs for
recursive definitions. Unlike iterative implementations, which can only
understand the topological index of each node in recursive data structures, our
recursive implementation is able to exploit the recursive relationships between
nodes for efficient execution based on parallel computation. We present an
implementation on TensorFlow and evaluation results with various recursive
neural network models, showing that our recursive implementation not only
conveys the recursive nature of recursive neural networks better than other
implementations, but also uses given resources more effectively to reduce
training and inference time.Comment: Appeared in EuroSys 2018. 13 pages, 11 figure
Frequency limits of sequential readout for sensing AC magnetic fields using nitrogen-vacancy centers in diamond
The nitrogen-vacancy (NV) centers in diamond have ability to sense
alternating-current (AC) magnetic fields with high spatial resolution. However,
the frequency range of AC sensing protocols based on dynamical decoupling (DD)
sequences has not been thoroughly explored experimentally. In this work, we
aimed to determine the sensitivity of ac magnetic field as a function of
frequency using sequential readout method. The upper limit at high frequency is
clearly determined by Rabi frequency, in line with the expected effect of
finite DD-pulse width. In contrast, the lower frequency limit is primarily
governed by the duration of optical repolarization rather than the decoherence
time (T) of NV spins. This becomes particularly crucial when the repetition
(dwell) time of the sequential readout is fixed to maintain the acquisition
bandwidth. The equation we provide successfully describes the tendency in the
frequency dependence. In addition, at the near-optimal frequency of 1 MHz, we
reached a maximum sensitivity of 229 pT/ by employing the
XY4-(4) DD sequence.Comment: 7 pages, 5 figure
Quantum diamond microscopy with sub-ms temporal resolution
Quantum diamond magnetometers using lock-in detection have successfully
detected weak bio-magnetic fields from neurons, a live mammalian muscle, and a
live mouse heart. This opens up the possibility of quantum diamond
magnetometers visualizing microscopic distributions of the bio-magnetic fields.
Here, we demonstrate a lock-in-based wide-field quantum diamond microscopy,
achieving a mean volume-normalized per pixel sensitivity of 43.9
. We obtain the sensitivity by
implementing a double resonance with hyperfine driving and magnetic field
alignment along the orientation of the diamond. Additionally, we have
demonstrated that sub-ms temporal resolution ( 0.4 ms) can be achieved at
a micrometer scale with tens of nanotesla per-pixel sensitivity using quantum
diamond microscopy. This lock-in-based diamond quantum microscopy could be a
step forward in mapping functional activity in neuronal networks in micrometer
spatial resolution
Incidental thyroid lesions detected by FDG-PET/CT: prevalence and risk of thyroid cancer
<p>Abstract</p> <p>Background</p> <p>Incidentally found thyroid lesions are frequently detected in patients undergoing FDG-PET/CT. The aim of this study was to investigate the prevalence of incidentally found thyroid lesions in patients undergoing FDG-PET/CT and determine the risk for thyroid cancer.</p> <p>Methods</p> <p>FDG-PET/CT was performed on 3,379 patients for evaluation of suspected or known cancer or cancer screening without any history of thyroid cancer between November 2003 and December 2005. Medical records related to the FDG-PET/CT findings including maximum SUV(SUV<sub>max</sub>) and pattern of FDG uptake, US findings, FNA, histopathology received by operation were reviewed retrospectively.</p> <p>Results</p> <p>Two hundred eighty five patients (8.4%) were identified to have FDG uptake on FDG-PET/CT. 99 patients with focal or diffuse FDG uptake underwent further evaluation. The cancer risk of incidentally found thyroid lesions on FDG-PET/CT was 23.2% (22/99) and the cancer risks associated with focal and diffuse FDG uptake were 30.9% and 6.4%. There was a significant difference in the SUV<sub>max </sub>between the benign and malignant nodules (3.35 ± 1.69 vs. 6.64 ± 4.12; P < 0.001). There was a significant correlation between the SUV<sub>max </sub>and the size of the cancer.</p> <p>Conclusion</p> <p>The results of this study suggest that incidentally found thyroid lesions by FDG-PET/CT, especially a focal FDG uptake and a high SUV, have a high risk of thyroid malignancy. Further diagnostic work-up is needed in these cases.</p
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