8,194 research outputs found

    DeepVar: An End-to-End Deep Learning Approach for Genomic Variant Recognition in Biomedical Literature

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    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

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    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

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    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

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    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

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    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 PInPI^n-Type Approach

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    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 (n−1)(n-1)-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 PInPI^n-type (PP and II are short for {\it Proportion} and {\it Integration}, respectively; InI^n implies that the algorithm includes high-order integral terms) containment algorithm is proposed. It is theoretically proved that the PInPI^n-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 (n−1)(n-1)-order polynomial trajectories, existing results require the follower's dynamics to be nn-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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