HAS-RL: A Hierarchical Approximate Scheme Optimized With Reinforcement Learning for NoC-Based NN Accelerators

Network-on-Chip (NoC) is a scalable on-chip communication architecture for the NN accelerator, but with the increase in the number of nodes, the communication delay becomes higher. Applications such as machine learning have a certain resilience to noisy/erroneous transmitted data. Therefore, approximate communication becomes a promising solution...

In Situ XPS Analysis of Tribo-chemical Behavior in Titanium Alloy Exposed to Fretting Wear Under the Vacuum Environments

A systematic experimental investigation concerning the fretting-induced tribo-chemical state and its effect on the fretting wear behavior of titanium alloys under the vacuum atmospheres (4 × 10^–3 Pa and 4 × 10^–1 Pa) in different fretting regimes is reported. An in situ XPS analysis tester was developed to capture the...

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...

Sensing and Machine Learning for Automotive Perception: A Review

Automotive perception involves understanding the external driving environment and the internal state of the vehicle cabin and occupants using sensor data. It is critical to achieving high levels of safety and autonomy in driving. This article provides an overview of different sensor modalities, such as cameras, radars, and light detection and...

Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework

Accurate recognition of driver behaviours is the basis for a reliable driver assistance system. This paper proposes a novel fusion framework for driver behaviour recognition that utilises the traffic scene and driver gaze information. The proposed framework is based on the graph neural network (GNN) and contains three modules, namely, the...

Morphodynamic changes in the Yangtze Estuary under the impact of the Three Gorges Dam, estuarine engineering interventions and climate-induced sea level rise

The estuarine turbidity maximum (ETM) in the Yangtze Estuary Delta (YED) is muddy by definition and lacks bottom undulations. However, since 2013, a remarkable change has occurred in the YED. Recent images detected by a multibeam echosounder system, SeaBat 7125, for the first time have confirmed widespread regions of subaqueous dunes in the...

Random forest incorporating ab-initio calculations for corrosion rate prediction with small sample Al alloys data

Corrosion jeopardizes the materials longevity and engineering safety, hence the corrosion rate needs to be forecasted so as to better guide materials selection. Although field exposure experiments are dependable, the prohibitive cost and their time-consuming nature make it difficult to obtain large dataset for machine learning. Here, we...

Application of YOLOv4 Algorithm for Foreign Object Detection on a Belt Conveyor in a Low-Illumination Environment

The most common failures of belt conveyors are runout, coal piles and longitudinal tears. The detection methods for longitudinal tearing are currently not particularly effective. A key study area for minimizing longitudinal belt tears with the advancement of machine learning is how to use machine vision technology to detect foreign items on...

Sample Regenerating Particle Filter Combined With Unequal Weight Ensemble Kalman Filter for Nonlinear Systems

We present an approach which combines the sample regenerating particle filter (SRGPF) and unequal weight ensemble Kalman filter (UwEnKF) to obtain a more accurate forecast for nonlinear dynamic systems. Ensemble Kalman filter assumes that the model errors and observation errors are Gaussian distributed. Particle filter has demonstrated its...

Practical Threshold Multi-Factor Authentication

Multi-factor authentication (MFA) has been widely used to safeguard high-value assets. Unlike single-factor authentication (e.g., password-only login), t-factor authentication (tFA) requires a user always to carry and present t specified factors so as to strengthen the security of login. Nevertheless, this may restrict user experience in...

Towards understanding and prediction of atmospheric corrosion of an Fe/Cu corrosion sensor via machine learning

The atmospheric corrosion of carbon steel was monitored by a Fe/Cu type galvanic corrosion sensor for 34 days. Using a random forest (RF)-based machine learning approach, the impacts of relative humidity, temperature and rainfall were identified to be higher than those of airborne particles, sulfur dioxide, nitrogen dioxide, carbon monoxide...

Revealing the Impact of Space-Charge Layers on the Li-Ion Transport in All-Solid-State Batteries

The influence of space-charge layers on the ionic charge transport over cathode-solid electrolyte interfaces in all-solid-state batteries remains unclear because of the difficulty to unravel it from other contributions to the ion transport over the interfaces. Here, we reveal the effect of the space-charge layers by systematically tuning the...

Research on Bearing Fault Diagnosis Method Based on Filter Features of MOMLMEDA and LSTM

As the supporting unit of rotating machinery, bearing can ensure efficient operation of the equipment. Therefore, it is very important to monitor the status of bearings accurately. A bearing fault diagnosis mothed based on Multipoint Optimal Minimum Local Mean Entropy Deconvolution Adjusted (MOMLMEDA) and Long Short-Term Memory (LSTM) is...

Research of planetary gear fault diagnosis based on permutation entropy of CEEMDAN and ANFIS

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete...

Planetary gear fault diagnosis via feature image extraction based on multi central frequencies and vibration signal frequency spectrum

Poor working environment leads to frequent failures of planetary gear trains. However, complex structure and variable transmission make the vibration signal strongly non-linear and non-stationary, which brings big problems to fault diagnosis. A method of planetary gear fault diagnosis via feature image extraction based on multi central...

Current and future trends in topology optimization for additive manufacturing

Manufacturing-oriented topology optimization has been extensively studied the past two decades, in particular for the conventional manufacturing methods, for example, machining and injection molding or casting. Both design and manufacturing engineers have benefited from these efforts because of the close-to-optimal and friendly-to-manufacture...