A Generalized Recurrent Neural Architecture for Text Classification with Multi-Task Learning

Multi-task learning leverages potential correlations among related tasks to extract common features and yield performance gains. However, most previous works only consider simple or weak interactions, thereby failing to model complex correlations among three or more tasks. In this paper, we propose a multi-task learning architecture with four types of recurrent neural layers to fuse information across multiple related tasks. The architecture is structurally flexible and considers various interactions among tasks, which can be regarded as a generalized case of many previous works. Extensive experiments on five benchmark datasets for text classification show that our model can significantly improve performances of related tasks with additional information from others

On the Existence of Solutions for Impulsive Duffing Dynamic Equations on Time Scales with Dirichlet Boundary Conditions

By using critical point theory, some new sufficient conditions for the existence of solutions of impulsive Duffing dynamic equations on time scales with Dirichlet boundary conditions are obtained. Some examples are also given to illustrate our results

Existence of periodic solutions for a periodic mutualism model on time scales

AbstractBy using Mawhin's continuation theorem of coincidence degree theory, sufficient criteria are obtained for the existence of periodic solutions of the mutualism model{xΔ(t)=r1(t)[K1(t)+α1(t)exp{y(t−τ2(t,y(t)))}1+exp{y(t−τ2(t,y(t)))}−exp{x(t−σ1(t,x(t)))}],yΔ(t)=r2(t)[K2(t)+α2(t)exp{x(t−τ1(t,x(t)))}1+exp{x(t−τ1(t,x(t)))}−exp{y(t−σ2(t,y(t)))}], where ri,Ki,αi∈C(T,R+), αi>Ki, i=1,2, τi,σi∈C(T×R,T+), i=1,2, ri, Ki, αi, τi, σi (i=1,2) are functions of period ω>0

Extremal Solutions of Periodic Boundary Value Problems for First-Order Impulsive Integrodifferential Equations of Mixed-Type on Time Scales

We consider the existence of minimal and maximal solutions of periodic boundary value problems for first-order impulsive integrodifferential equations of mixed-type on time scales by establishing a comparison result and using the monotone iterative technique

Characteristics of traditional Chinese medicine users and prescription analysis for pediatric atopic dermatitis

Abstract Background: Traditional Chinese medicine is commonly used to treat children with atopic dermatitis. This research study reviewed patients with atopic dermatitis, recorded in Taiwan’s National Health Insurance Research Database, to investigate the characteristics and prescriptions of traditional Chinese medicine (TCM) so as to propose the use of TCM for a broader societal application. Objective: The aim of this study is to determine the application mode of TCM in children with atopic dermatitis, specifically the combination of Chinese herbal medicines (CHMs) used. Methods: The database reported atopic dermatitis-diagnosed children aged 5 to 12. TCM users documented data relate to age, diagnostic code, residence area and the use of corticosteroids. An analysis of the medications used for atopic dermatitis was achieved through a review of examining the association of various factors. Results: A total of 13,646 children with atopic dermatitis, and treated using TCM, were sampled from different area of Taiwan. The use of TCM is associated with use by women (male: OR 0.83), adolescence (OR: 10.0, 95% CI: 8.88-11.15) and allergic rhinitis (OR: 2.44; 95 % CI: 2.10-2.85). Fewer TCM users than non-users receive corticosteroid therapy (35.8% of all users receive TCM). Still, the percentage of TCM users who use long-lastingcorticosteroid therapy is greater than TCM non-users (10.6% of TCM users and 2.0% of TCM non-users). In total, 36,398 CHM prescriptions were used by 93.7% of Chinese medicine users. There was a total of 5.62 types CHM types used. Relationships between the Chinese herbal medicine forms network, where Xiao fengsan is the primary treatment for atopic dermatitis. Conclusions: The article describes features of children with atopic dermatitis who are treated with Chinese medicine. Xiao fengsan is the most common CHM used to treat atopic dermatitis in children. Further research on the safety and efficiency of this treatment is still required. [Ethiop. J. Health Dev. 2020; 34(4):253-261] Key words: Traditional Chinese medicine, atopic dermatitis, paediatrics, Chinese herbal medicin

Semantic Interleaving Global Channel Attention for Multilabel Remote Sensing Image Classification

Multi-Label Remote Sensing Image Classification (MLRSIC) has received increasing research interest. Taking the cooccurrence relationship of multiple labels as additional information helps to improve the performance of this task. Current methods focus on using it to constrain the final feature output of a Convolutional Neural Network (CNN). On the one hand, these methods do not make full use of label correlation to form feature representation. On the other hand, they increase the label noise sensitivity of the system, resulting in poor robustness. In this paper, a novel method called Semantic Interleaving Global Channel Attention (SIGNA) is proposed for MLRSIC. First, the label co-occurrence graph is obtained according to the statistical information of the data set. The label co-occurrence graph is used as the input of the Graph Neural Network (GNN) to generate optimal feature representations. Then, the semantic features and visual features are interleaved, to guide the feature expression of the image from the original feature space to the semantic feature space with embedded label relations. SIGNA triggers global attention of feature maps channels in a new semantic feature space to extract more important visual features. Multihead SIGNA based feature adaptive weighting networks are proposed to act on any layer of CNN in a plug-and-play manner. For remote sensing images, better classification performance can be achieved by inserting CNN into the shallow layer. We conduct extensive experimental comparisons on three data sets: UCM data set, AID data set, and DFC15 data set. Experimental results demonstrate that the proposed SIGNA achieves superior classification performance compared to state-of-the-art (SOTA) methods. It is worth mentioning that the codes of this paper will be open to the community for reproducibility research. Our codes are available at https://github.com/kyle-one/SIGNA.Comment: 14 pages, 13 figure

Receding Horizon Trajectory Optimization with Terminal Impact Specifications

The trajectory optimization problem subject to terminal impact time and angle specifications can be reformulated as a nonlinear programming problem using the Gauss pseudospectral method. The cost function of the trajectory optimization problem is modified to reduce the terminal control energy. A receding horizon optimization strategy is implemented to reject the errors caused by the motion of a surface target. Several simulations were performed to validate the proposed method via the C programming language. The simulation results demonstrate the effectiveness of the proposed algorithm and that the real-time requirement can be easily achieved if the C programming language is used to realize it