873 research outputs found
Feature Representation Analysis of Deep Convolutional Neural Network using Two-stage Feature Transfer -An Application for Diffuse Lung Disease Classification-
Transfer learning is a machine learning technique designed to improve
generalization performance by using pre-trained parameters obtained from other
learning tasks. For image recognition tasks, many previous studies have
reported that, when transfer learning is applied to deep neural networks,
performance improves, despite having limited training data. This paper proposes
a two-stage feature transfer learning method focusing on the recognition of
textural medical images. During the proposed method, a model is successively
trained with massive amounts of natural images, some textural images, and the
target images. We applied this method to the classification task of textural
X-ray computed tomography images of diffuse lung diseases. In our experiment,
the two-stage feature transfer achieves the best performance compared to a
from-scratch learning and a conventional single-stage feature transfer. We also
investigated the robustness of the target dataset, based on size. Two-stage
feature transfer shows better robustness than the other two learning methods.
Moreover, we analyzed the feature representations obtained from DLDs imagery
inputs for each feature transfer models using a visualization method. We showed
that the two-stage feature transfer obtains both edge and textural features of
DLDs, which does not occur in conventional single-stage feature transfer
models.Comment: Preprint of the journal article to be published in IPSJ TOM-51.
Notice for the use of this material The copyright of this material is
retained by the Information Processing Society of Japan (IPSJ). This material
is published on this web site with the agreement of the author (s) and the
IPS
Note on massless bosonic states in two-dimensional field theories
In a wide class of invariant two-dimensional
super-renormalizable field theories, the parity-odd part of the two-point
function of global currents is completely determined by a fermion one-loop
diagram. For any non-trivial fermion content, the two-point function possesses
a massless pole which corresponds to massless bosonic physical states. As an
application, we show that two-dimensional supersymmetric
gauge theory without a superpotential possesses symmetry
and contains one massless bosonic state per fixed spatial momentum. The
supersymmetric pure Yang-Mills theory possesses
symmetry, and there exist at least three massless
bosonic states.Comment: 17pages, 4 figures, uses PTPTeX.cls and feynMF, added an appendi
Axial symmetry at high temperature in 2-flavor lattice QCD
We investigate the axial symmetry breaking above the critical
temperature in two-flavor lattice QCD. The ensembles are generated with
dynamical M\"obius domain-wall or reweighted overlap fermions. The
susceptibility is extracted from the low-modes spectrum of the overlap Dirac
eigenvalues. We show the quark mass and temperature dependences of
susceptibility. Our results at imply that the
symmetry is restored in the chiral limit. Its coincidence with vanishing
topological susceptibility is observed.Comment: 8 pages, 4 figures, Proceedings of the 35th International Symposium
on Lattice Field Theory, June 18-24, 2017, Granada, Spai
Axial U(1) symmetry and Dirac spectra in high-temperature phase of lattice QCD
The axial symmetry in the high-temperature phase is investigated with
lattice QCD simulations. The gauge ensembles are generated with
M\"obius domain-wall fermions, and the overlap/domain-wall reweighting is
applied. We find that the susceptibility evaluated from the spectrum
of overlap-Dirac eigenvalues is strongly suppressed in the chiral limit. We
also study its volume dependence.Comment: 7 pages, 2 figures, talk presented at the 36th International
Symposium on Lattice Field Theory (Lattice 2018), 22-28 July, 2018, Michigan,
US
Delay of Onset of Symptoms of Japanese Cedar Pollinosis by Treatment with a Leukotriene Receptor Antagonist
ABSTRACTBackgroundLeukotriene receptor antagonists (LTRAs) are effective for prophylactic treatment of pollinosis based on studies showing that administration of LTRAs prior to or at the start of the pollen season reduces symptoms and QOL disturbance at the peak of pollen dispersal. Two goals of prophylactic treatment of pollinosis are use of fewer types of drugs and delay of onset of symptoms and impairement of QOL. Therefore, this study was performed to determine if pranlukast, a LTRA, met these goals in treatment of pollinosis.MethodsPranlukast or placebo was administered to patients who visited our hospital immediately before the start of Japanese cedar pollen dispersal. The study was performed for 4 weeks as a double blind randomized trial. Subsequently, all patients were given pranlukast for a further 4 weeks from the peak until the end of pollen dispersal. The incidence of symptoms and use of concomitant drugs were investigated from daily nasal allergy records kept by patients. QOL was evaluated using the JRQLQ questionnaire.ResultsIn the double blind period of the study, the percentage of patients who used concomitant drugs for nasal symptoms was significantly lower in the pranlukast group compared to the placebo group. Development of nasal symptoms (sneezing, runny nose and nasal congestion) and disturbance of daily activities were significantly delayed in the pranlukast group. No serious adverse reactions occurred in the pranlukast group and no patient withdrew from treatment with pranlukast.ConclusionsPranlukast is effective for prophylactic treatment of pollinosis
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