A Self-Bias-Flip with Charge Recycle Interface Circuit with No External Energy Reservoir for Piezoelectric Energy Harvesting Array

This article presents a piezoelectric energy harvesting (PEH) interface circuit using a new self-bias-flip with the charge recycle (SBFR) technique without employing any additional energy reservoir. Traditional designs, including synchronous-switch harvesting on inductor (SSHI), synchronous-switch harvesting on capacitor (SSHC), synchronous...

A Self Bias-flip Piezoelectric Energy Harvester Array without External Energy Reservoirs achieving 488% Improvement with 4-Ratio Switched-PEH DC-DC Converter

With the advent of the lnternet-of-Things (1oT) era, sensor nodes are required in almost all fields to achieve a better interaction between humans and the environment. Piezoelectric energy harvester (PEH), which exhibits an equivalent electrical model of an AC current source /P in parallel with the inherent capacitor CP, is a promising...

Multiple Strategies Differential Privacy on Sparse Tensor Factorization for Network Traffic Analysis in 5G

Due to high capacity and fast transmission speed, 5G plays a key role in modern electronic infrastructure. Meanwhile, sparse tensor factorization (STF) is a useful tool for dimension reduction to analyze high-order, high-dimension, and sparse tensor (HOHDST) data, which is transmitted on 5G Internet-of-things (IoT). Hence, HOHDST data relies...

New innovations in pavement materials and engineering: A review on pavement engineering research 2021

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges. In the past 10 years, the pavement infrastructure strongly supports the rapid development of the global social economy. New theories, new methods, new technologies and new materials related to pavement engineering are emerging....

SlimML: Removing Non- critical Input Data in Large-scale Iterative Machine Learning

The core of many large-scale machine learning (ML) applications, such as neural networks (NN), support vector machine (SVM), and convolutional neural network (CNN), is the training algorithm that iteratively updates model parameters by processing massive datasets. From a plethora of studies aiming at accelerating ML, being data...