Learning to Sample: an Active Learning Framework

Meta-learning algorithms for active learning are emerging as a promising paradigm for learning the ``best'' active learning strategy. However, current learning-based active learning approaches still require sufficient training data so as to generalize meta-learning models for active learning. This is contrary to the nature of active learning which typically starts with a small number of labeled samples. The unavailability of large amounts of labeled samples for training meta-learning models would inevitably lead to poor performance (e.g., instabilities and overfitting). In our paper, we tackle these issues by proposing a novel learning-based active learning framework, called Learning To Sample (LTS). This framework has two key components: a sampling model and a boosting model, which can mutually learn from each other in iterations to improve the performance of each other. Within this framework, the sampling model incorporates uncertainty sampling and diversity sampling into a unified process for optimization, enabling us to actively select the most representative and informative samples based on an optimized integration of uncertainty and diversity. To evaluate the effectiveness of the LTS framework, we have conducted extensive experiments on three different classification tasks: image classification, salary level prediction, and entity resolution. The experimental results show that our LTS framework significantly outperforms all the baselines when the label budget is limited, especially for datasets with highly imbalanced classes. In addition to this, our LTS framework can effectively tackle the cold start problem occurring in many existing active learning approaches.Comment: Accepted by ICDM'1

Role of GABAAR in the Transition From Acute to Chronic Pain and the Analgesic Effect of Electroacupuncture on Hyperalgesic Priming Model Rats

Chronic pain is a costly health problem that impairs health-related quality of life when not effectively treated. Regulating the transition from acute to chronic pain is a new therapeutic strategy for chronic pain that presents a major clinical challenge. The underlying mechanisms of pain transition are not entirely understood, and strategies for preventing this transition are lacking. Here, a hyperalgesic priming model was used to study the potential mechanism by which γ-aminobutyric acid receptor type A (GABAAR) in the dorsal root ganglion (DRG) contributes to pain transition. Furthermore, electroacupuncture (EA), a modern method of acupuncture, was administered to regulate pain transition, and the mechanism underlying EA's regulatory effect was investigated. Hyperalgesic priming was induced by intraplanar injection of carrageenan (Car)/prostaglandin E2 (PGE2). The decrease in mechanical withdrawal threshold (MWT) induced by PGE2 returned to baseline 4 h after injection in NS + PGE2 group, and still persisted 24 h after injection in Car + PGE2 group. Lower expression of GABAAR in the lumbar DRG was observed in the model rats. Furthermore, activating or blocking GABAAR could reversed the long-lasting hyperalgesia induced by Car/PGE2 injection or produced a persistent hyperalgesia. In addition, GABAAR may be involved in Protein Kinase C epsilon (PKCε) activation in the DRG, a mark molecular of pain transition. EA considerably increased the mechanical pain thresholds of hyperalgesic priming model mammals in both the acute and chronic phases. Furthermore, EA upregulated the expression of GABAAR and inhibited the activation of PKCε in the DRG. In addition, peripheral administration of picrotoxin blocked the analgesic effect of EA on the model rats and abolished the regulatory effect of EA on PKCε activation. These findings suggested that GABAAR plays a key role in both the transition from acute to chronic pain and the analgesic effect of EA on hyperalgesic priming

Carboxylated Carbon Nanotube/Polyimide Films with Low Thermal Expansion Coefficient and Excellent Mechanical Properties

Polyimide (PI) films with excellent heat resistance and outstanding mechanical properties have been widely researched in microelectronics and aerospace fields. However, most PI films can only be used under ordinary conditions due to their instability of dimension. The fabrication of multifunctional PI films for harsh conditions is still a challenge. Herein, flexible, low coefficient of thermal expansion (CTE) and improved mechanical properties films modified by carboxylated carbon nanotube (C-CNT) were fabricated. Acid treatment was adapted to adjust the surface characteristics by using a mixture of concentrated H2SO4/HNO3 solution to introduce carboxyl groups on the surface and improve the interfacial performance between the CNT and matrix. Moreover, different C-CNT concentrations of 0, 1, 3, 5, 7, and 9 wt.% were synthesized to use for the PI film fabrication. The results demonstrated that the 9 wt.% and 5 wt.% C-CNT/PI films possessed the lowest CTE value and the highest mechanical properties. In addition, the thermal stability of the C-CNT/PI films was improved, making them promising applications in precise and harsh environments

Study of Compaction Properties and Permeability Prediction of Multilayered Quadriaxial Non-Crimp Fabric in Liquid Composite Molding Process

A systematic experimental study was performed to detect the compaction and permeability properties of multilayered biaxial and quadriaxial preforms under vacuum pressure. Compression response on ply level showed that the degree of nesting between quadriaxial NCF was more pronounced and the nesting deformation mechanism was affected by the interaction with stitch yarns. Owing to the meso-channels in the fibrous structure and the nesting between layers, the in-plane permeability of quadriaxial NCF did not follow an inverse proportion relationship with the fiber volume fraction. To predict the in-plane permeability of multilayered quadriaxial NCFs, unit cell models at a high level of geometrical details were built, including local variations in yarn cross-sections and the nesting deformation between layers. Numerical methods were implemented, and the prediction results were in very good agreement with the experimental data. Besides, the major contributing parameters to the enhancement of the in-plane permeabilities were identified by investigating the correlation between permeability and structural parameters of quadriaxial NCF. The modeling methodology and the principles established can be applied to the design of the quadriaxial NCF fabrics, where the permeability enhancement was evidenced

Detecting the Trajectory of Moving Object for Single-Pixel Imaging System

In order to get the trajectory of moving object using single-pixel imaging system, an algorithm is proposed. The same pseudorandom masks are employed to illuminate the different time scene. A time weighted sum of the background correction signals is employed to get the trajectory information using compressed sensing (CS) method. In ideal situation, we can obtain other parameters (e.g., speed, orientation) besides the trajectory. However, the reflective intensity of the object can be change due to the reflective angle change caused by the motion in some situations. This will mislead for achieving the speed, orientation parameters. In order to eliminate this effect, a division method is utilized. At last, the computer simulation results prove the effect validity of the proposed algorithm

Detecting the Trajectory of Moving Object for Single-Pixel Imaging System

In order to get the trajectory of moving object using single-pixel imaging system, an algorithm is proposed. The same pseudorandom masks are employed to illuminate the different time scene. A time weighted sum of the background correction signals is employed to get the trajectory information using compressed sensing (CS) method. In ideal situation, we can obtain other parameters (e.g., speed, orientation) besides the trajectory. However, the reflective intensity of the object can be change due to the reflective angle change caused by the motion in some situations. This will mislead for achieving the speed, orientation parameters. In order to eliminate this effect, a division method is utilized. At last, the computer simulation results prove the effect validity of the proposed algorithm

High-Performance Polyimide Filaments and Composites Improved by O2 Plasma Treatment

Interface issues urgently need to be addressed in high-performance fiber reinforced composites. In this study, different periods of O2 plasma treatment are proposed to modify twist-free polyimide (PI) filaments to improve hydrophilicity and mechanical and interfacial properties. Feeding O2 produces chemically active particles to modify the filament surface via chemical reactions and physical etching. According to the X-ray photoelectron spectroscopy (XPS) results, the PI filaments exhibit an 87.16% increase in O/C atomic ratio and a 135.71% increase in the C–O functional group after 180 s O2 plasma treatment. The atomic force microscope (AFM) results show that the root mean square roughness (Rq) of the treated PI filaments increases by 105.34%, from 38.41 to 78.87 nm. Owing to the increased surface oxygenic functional groups and roughness after O2 plasma treatment, the contact angle between treated PI filaments and water reduces drastically from the pristine state of 105.08° to 56.15°. The O2 plasma treated PI filaments also demonstrate better mechanical properties than the pristine PI filaments. Moreover, after O2 plasma treatment, the adhesion between PI filaments and poly(amic acid) (PAA) is enhanced, and the tensile strength of the polyimide/poly(amic acid) (PI/PAA) self-reinforced composites increases from 136 to 234 MPa, even causing the failure mode of the composite changes from adhesive failure to partly cohesive failure