Targeted Influence with Community and Gender-Aware Seeding

When spreading information over social networks, seeding algorithms selecting users to start the dissemination play a crucial role. The majority of existing seeding algorithms focus solely on maximizing the total number of reached nodes, overlooking the issue of group fairness, in particular, gender imbalance. To tackle the challenge of...

A 2m-Range 711uW Body Channel Communication Transceiver Featuring Dynamically-Sampling Bias-Free Interface Front End

Body Channel Communication (BCC) offers a low-loss signal transmission medium for ultra-low-power wearable devices on human body [1]. However, the effective communication range on human body is limited to less than 1m in the state-of-the-art BCC transceivers [2], where the signal loss at the interface of body surface and BCC receiver remains to...

Critical proof load for proof load testing of concrete bridges based on scripted FEM analysis

As the bridge stock in The Netherlands and Europe is ageing, various methods to analyse the capacity of existing bridges are being studied. Proof load testing is one of the method to test the capacity of bridges by applying loads on the existing concrete bridges with small spans. Because of the fact that neither the actual traffic load nor the...

LearningQ: A Large-scale Dataset for Educational Question Generation

We present LearningQ, a challenging educational question generation dataset containing over 230K document-question pairs. It includes 7K instructor-designed questions assessing knowledge concepts being taught and 223K learner-generated questions seeking in-depth understanding of the taught concepts. We show that, compared to existing datasets...

Interfacial Failure Characterization of Electronic Packaging Component Using a Multiscale Modelling Approach

Interfacial properties of Cu/SiO₂ in semiconductor devices has been a challenging study for many years because of its difficulties in experimentally quantifying the critical strength of interface. In this paper, a multi-scale modeling approach is built to characterize the interfacial properties between Cu and SiO₂. The...

MRLR: Multi-level representation learning for personalized ranking in recommendation

Representation learning (RL) has recently proven to be effective in capturing local item relationships by modeling item co-occurrence in individual user's interaction record. However, the value of RL for recommendation has not reached the full potential due to two major drawbacks: 1) recommendation is modeled as a rating prediction problem...