8,194 research outputs found
DeepVar: An End-to-End Deep Learning Approach for Genomic Variant Recognition in Biomedical Literature
We consider the problem of Named Entity Recognition (NER) on biomedical
scientific literature, and more specifically the genomic variants recognition
in this work. Significant success has been achieved for NER on canonical tasks
in recent years where large data sets are generally available. However, it
remains a challenging problem on many domain-specific areas, especially the
domains where only small gold annotations can be obtained. In addition, genomic
variant entities exhibit diverse linguistic heterogeneity, differing much from
those that have been characterized in existing canonical NER tasks. The
state-of-the-art machine learning approaches in such tasks heavily rely on
arduous feature engineering to characterize those unique patterns. In this
work, we present the first successful end-to-end deep learning approach to
bridge the gap between generic NER algorithms and low-resource applications
through genomic variants recognition. Our proposed model can result in
promising performance without any hand-crafted features or post-processing
rules. Our extensive experiments and results may shed light on other similar
low-resource NER applications.Comment: accepted by AAAI 202
Mobility enhancement and highly efficient gating of monolayer MoS2 transistors with Polymer Electrolyte
We report electrical characterization of monolayer molybdenum disulfide
(MoS2) devices using a thin layer of polymer electrolyte consisting of
poly(ethylene oxide) (PEO) and lithium perchlorate (LiClO4) as both a
contact-barrier reducer and channel mobility booster. We find that bare MoS2
devices (without polymer electrolyte) fabricated on Si/SiO2 have low channel
mobility and large contact resistance, both of which severely limit the
field-effect mobility of the devices. A thin layer of PEO/ LiClO4 deposited on
top of the devices not only substantially reduces the contact resistance but
also boost the channel mobility, leading up to three-orders-of-magnitude
enhancement of the field-effect mobility of the device. When the polymer
electrolyte is used as a gate medium, the MoS2 field-effect transistors exhibit
excellent device characteristics such as a near ideal subthreshold swing and an
on/off ratio of 106 as a result of the strong gate-channel coupling.Comment: 17 pages, 4 figures, accepted by J. Phys.
From SMOTE to Mixup for Deep Imbalanced Classification
Given imbalanced data, it is hard to train a good classifier using deep
learning because of the poor generalization of minority classes. Traditionally,
the well-known synthetic minority oversampling technique (SMOTE) for data
augmentation, a data mining approach for imbalanced learning, has been used to
improve this generalization. However, it is unclear whether SMOTE also benefits
deep learning. In this work, we study why the original SMOTE is insufficient
for deep learning, and enhance SMOTE using soft labels. Connecting the
resulting soft SMOTE with Mixup, a modern data augmentation technique, leads to
a unified framework that puts traditional and modern data augmentation
techniques under the same umbrella. A careful study within this framework shows
that Mixup improves generalization by implicitly achieving uneven margins
between majority and minority classes. We then propose a novel margin-aware
Mixup technique that more explicitly achieves uneven margins. Extensive
experimental results demonstrate that our proposed technique yields
state-of-the-art performance on deep imbalanced classification while achieving
superior performance on extremely imbalanced data. The code is open-sourced in
our developed package https://github.com/ntucllab/imbalanced-DL to foster
future research in this direction.Comment: 25 pages, 3 figures. The paper is accepted by TAAI 202
Willingness to Continue with Software Projects: Effects of Feedback Direction and Optimism under High and Low Accountability Conditions
The willingness of managers to continue with software projects can be both beneficial and troubling. Management optimism can help bring promising projects to fruition, but can also cause valuable resources to be expended on faltering projects. This study examines three factors that can affect the willingness of managers to continue with software projects: feedback direction, feedback optimism, and accountability. Feedback direction is the objective information reflecting project prospects. Feedback optimism is the subjective mode with which the objective information has been framed. Accountability is the extent to which the manager feels responsible for project outcomes. Results of a study that manipulated these three factors showed that the effects of feedback direction and feedback optimism on willingness to continue with software projects were additive (either factor alone affected willingness to continue with software projects) when accountability was high but were interactive (both factors jointly affected willingness to continue with software projects) when accountability was low. These findings have useful implications for practice and further research
Non-zero Integral Spin of Acoustic Vortices and Spin-orbit Interaction in Longitudinal Acoustics
Spin and orbital angular momenta (AM) are of fundamental interest in wave
physics. Acoustic wave, as a typical longitudinal wave, has been well studied
in terms of orbital AM, but still considered unable to carry non-zero integral
spin AM or spin-orbital interaction in homogeneous media due to its spin-0
nature. Here we give the first self-consistent analytical calculations of spin,
orbital and total AM of guided vortices under different boundary conditions,
revealing that vortex field can carry non-zero integral spin AM. We also
introduce for acoustic waves the canonical-Minkowski and kinetic-Abraham AM,
which has aroused long-lasting debate in optics, and prove that only the former
is conserved with the corresponding symmetries. Furthermore, we present the
theoretical and experimental observation of the spin-orbit interaction of
vortices in longitudinal acoustics, which is thought beyond attainable in
longitudinal waves in the absence of spin degree of freedom. Our work provides
a solid platform for future studies of the spin and orbital AM of guided
acoustic waves and may open up a new dimension for acoustic vortex-based
applications such as underwater communications and object manipulations
Containment Control of Multi-Agent Systems with Dynamic Leaders Based on a -Type Approach
This paper studies the containment control problem of multi-agent systems
with multiple dynamic leaders in both the discrete-time domain and the
continuous-time domain. The leaders' motions are described by -order
polynomial trajectories. This setting makes practical sense because given some
critical points, the leaders' trajectories are usually planned by the
polynomial interpolations. In order to drive all followers into the convex hull
spanned by the leaders, a -type ( and are short for {\it
Proportion} and {\it Integration}, respectively; implies that the
algorithm includes high-order integral terms) containment algorithm is
proposed. It is theoretically proved that the -type containment algorithm
is able to solve the containment problem of multi-agent systems where the
followers are described by any order integral dynamics. Compared with the
previous results on the multi-agent systems with dynamic leaders, the
distinguished features of this paper are that: (1) the containment problem is
studied not only in the continuous-time domain but also in the discrete-time
domain while most existing results only work in the continuous-time domain; (2)
to deal with the leaders with the -order polynomial trajectories,
existing results require the follower's dynamics to be -order integral while
the followers considered in this paper can be described by any-order integral;
and (3) the "sign" function is not employed in the proposed algorithm, which
avoids the chattering phenomenon. Furthermore, in order to illustrate the
practical value of the proposed approach, an application, the containment
control of multiple mobile robots is studied. Finally, two simulation examples
are given to demonstrate the effectiveness of the proposed algorithm
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