Ping Wang

Understanding bilingual education: an overview of key notions in the literature and the implications for Chinese university EFL education

2016 · Cambridge Journal of Education

This article starts with a review of definitions of bilingualism. It then discusses the definition of bilingual education with its focus on the analysis of bilingual competence. It is subsequently suggested that a theoretical hard …

Understanding Human-Chosen PINs

2017

Personal Identification Numbers (PINs) are ubiquitously used in embedded computing systems where user input interfaces are constrained. Yet, little attention has been paid to this important kind of authentication credentials, especially for 6-digit PINs which …

Multitarget tracking in sensor networks via efficient information-theoretic sensor selection

2017 · International Journal of Advanced Robotic Systems

In networks composed of moving robots or static sensing nodes, multitarget tracking is critical and fundamental for high-level applications, such as scene analysis or event detection. However, tracking multiple targets in the sensor network is …

Institutional Barriers and World Income Disparities

2018

Why have the income disparities between fast-growing economies and development laggards widened over the past five decades? How important is the role played by institutional barriers with relation to technology adoption? 

Floating-Point Multiplication Timing Attack on Deep Neural Network

2019

Deep neural network (DNN) is being adopted in many security-critical and privacy-sensitive smart Internet of Things areas, such as smart city, smart home and intelligent transportation. Therefore, the data privacy of these DNN systems is …

Toward an Automated Auction Framework for Wireless Federated Learning Services Market

2020 · IEEE Transactions on Mobile Computing

In traditional machine learning, the central server first collects the data owners' private data together and then trains the model. However, people's concerns about data privacy protection are dramatically increasing. The emerging paradigm of federated …

Construction of typhoon disaster knowledge graph based on graph database Neo4j

2020

The typhoon knowledge graph can correlate various kinds of information in the typhoon data, conduct overall and related analysis, and finally provide effective assistance for typhoon prevention and post-disaster protection. The data of typhoon landing …

Few-shot Image Classification with Multi-Facet Prototypes

2021 · Open Access at Essex (University of Essex)

The aim of few-shot learning (FSL) is to learn how to recognize image categories from a small number of training examples. A central challenge is that the available training examples are normally insufficient to determine …

Fast-Convergent Federated Learning With Adaptive Weighting

2021 · IEEE Transactions on Cognitive Communications and Networking

Federated learning (FL) enables resource-constrained edge nodes to collaboratively learn a global model under the orchestration of a central server while keeping privacy-sensitive data locally. The non-independent-and-identically-distributed (non-IID) data samples across participating nodes slow model …

Attention-based aspect reasoning for knowledge base question answering on clinical notes

2022

Question Answering (QA) in clinical notes has gained a lot of attention in the past few years. Existing machine reading comprehension approaches in clinical domain can only handle questions about a single block of clinical …

A Pruning Regularization Stochastic Configuration Network Algorithm Based on Node Contribution and Its Application in Soft Sensor Development

2022 · 2022 34th Chinese Control and Decision Conference (CCDC)

Stochastic configuration network (SCN) has emerged as an efficient nonlinear regression modeling method. However, the traditional SCN has to set the model training stop criterion (e.g. the maximal hidden layer node number, or the expected …

Straggler-resilient Federated Learning: Tackling Computation Heterogeneity with Layer-wise Partial Model Training in Mobile Edge Network

2023 · arXiv (Cornell University)

Federated Learning (FL) enables many resource-limited devices to train a model collaboratively without data sharing. However, many existing works focus on model-homogeneous FL, where the global and local models are the same size, ignoring the …

Predictions of Aeroengines’ Infrared Radiation Characteristics Based on HKELM Optimized by the Improved Dung Beetle Optimizer

2024 · Sensors

To solve the problems of high computational cost and the long time required by the simulation and calculation of aeroengines' exhaust systems, a method of predicting the characteristics of infrared radiation based on the hybrid …

Natural Language Querying on Domain-Specific NoSQL Database with Large Language Models

2024

Efficiently and accurately retrieving specific information from healthcare datasets, such as the Vaccine Adverse Event Reporting System (VAERS)1, presents significant challenges. A promising solution to this problem is the Text-to-ESQ approach, which is akin to …

To Learn Better Character Embeddings in Generative Models for Password Attack

2025

Variational Autoencoder (VAE) has been used as password generative model for trawling attack in multiple works. Its sample distribution can be easily changed by controling the mean and variance of the prior distribution, which makes …

Adaptive Password Guessing Framework Using Various Datasets

2025

Password guessing attack is a significant threat to account security. Understanding this attack is crucial for identifying the vulnerabilities of current password systems and for developing more effective methods to protect user accounts. Adaptive password …

K-BERT: Enabling Language Representation with Knowledge Graph

2020 · Proceedings of the AAAI Conference on Artificial Intelligence

Pre-trained language representation models, such as BERT, capture a general language representation from large-scale corpora, but lack domain-specific knowledge. When reading a domain text, experts make inferences with relevant knowledge. For machines to achieve this …