Wanli Yu
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View article: Design of Escalator Fault Prediction and Intelligent Maintenance System Based on Machine Learning
Design of Escalator Fault Prediction and Intelligent Maintenance System Based on Machine Learning Open
As urban transit systems become increasingly dependent on vertical transportation infrastructure, ensuring the reliability and safety of escalators is critical for operational efficiency and public safety. Traditional escalator maintenance…
View article: Task-Specific Energy Profiling for Microcontroller Selection in Energy-Autonomous Wireless Sensor Nodes
Task-Specific Energy Profiling for Microcontroller Selection in Energy-Autonomous Wireless Sensor Nodes Open
View article: Recursive regulator: a deep-learning and real-time model adaptation strategy for nonlinear systems
Recursive regulator: a deep-learning and real-time model adaptation strategy for nonlinear systems Open
Adaptive modeling is imperative for analyzing nonlinear systems deployed in natural dynamic environments. It facilitates filtering, prediction, and automatic control of the target object in real time to respond to unpredictable and non-rep…
View article: Procedural Content Generation via Generative Artificial Intelligence
Procedural Content Generation via Generative Artificial Intelligence Open
The attempt to utilize machine learning in PCG has been made in the past. In this survey paper, we investigate how generative artificial intelligence (AI), which saw a significant increase in interest in the mid-2010s, is being used for PC…
View article: Language guided 3D object detection in point clouds for MEP scenes
Language guided 3D object detection in point clouds for MEP scenes Open
In recent years, contrastive language‐image pre‐training (CLIP) has gained popularity for processing 2D data. However, the application of cross‐modal transferable learning to 3D data remains a relatively unexplored area. In addition, high‐…
View article: A Width Multi-Scale Adversarial Domain Adaptation Residual Network with AConvolutional Block Attention Module
A Width Multi-Scale Adversarial Domain Adaptation Residual Network with AConvolutional Block Attention Module Open
Although the fault diagnosis methods based on deep learning have attracted widespread attention in the academic field in recent years, such methods still face many challenges, including complex and variable working conditions, insufficient…
View article: CNN Sensor Analytics With Hybrid-Float6 Quantization on Low-Power Embedded FPGAs
CNN Sensor Analytics With Hybrid-Float6 Quantization on Low-Power Embedded FPGAs Open
The use of artificial intelligence (AI) in sensor analytics is entering a new era based on the use of ubiquitous embedded connected devices. This transformation requires the adoption of design techniques that reconcile accurate results wit…
View article: A wavelet packet transform-based deep feature transfer learning method for bearing fault diagnosis under different working conditions
A wavelet packet transform-based deep feature transfer learning method for bearing fault diagnosis under different working conditions Open
View article: Hybrid Genetic Algorithm and Simulated Annealing for Task Allocation with Data Security
Hybrid Genetic Algorithm and Simulated Annealing for Task Allocation with Data Security Open
View article: A Wavelet Packet Transform Based Deep Feature Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions
A Wavelet Packet Transform Based Deep Feature Transfer Learning Method for Bearing Fault Diagnosis Under Different Working Conditions Open
View article: A Joint Optimization Framework of the Embedding Model and Classifier for Meta-Learning
A Joint Optimization Framework of the Embedding Model and Classifier for Meta-Learning Open
The aim of meta-learning is to train the machine to learn quickly and accurately. Improving the performance of the meta-learning model is important in solving the problem of small samples and in achieving general artificial intelligence. A…
View article: Efficient Attention Mechanism for Dynamic Convolution in Lightweight Neural Network
Efficient Attention Mechanism for Dynamic Convolution in Lightweight Neural Network Open
Light-weight convolutional neural networks (CNNs) suffer limited feature representation capabilities due to low computational budgets, resulting in degradation in performance. To make CNNs more efficient, dynamic neural networks (DyNet) ha…
View article: A New Transferable Fault Diagnosis Approach of Rotating Machinery Based on Deep Autoencoder and Dominant Features Selection under Different Operating Conditions
A New Transferable Fault Diagnosis Approach of Rotating Machinery Based on Deep Autoencoder and Dominant Features Selection under Different Operating Conditions Open
In the actual industrial scenarios, most existing fault diagnosis approaches are faced with two challenges, insufficient labeled training data and distribution divergences between training and testing datasets. For the above issues, a new …
View article: Combination of Task Allocation and Approximate Computing for Fog-Architecture-Based IoT
Combination of Task Allocation and Approximate Computing for Fog-Architecture-Based IoT Open
Achieving energy efficiency is always a primary concern for fog-architecture-based Internet of Things (IoT) applications. As the IoT devices are typically of small sizes and powered by battery energy, it is essential to address the energy …
View article: SATA: An Intelligent Security Aware Task Allocation for Multihop Wireless Networks
SATA: An Intelligent Security Aware Task Allocation for Multihop Wireless Networks Open
Multihop wireless networks, which consist of sets of battery powered wireless nodes, have been widely spreading in numerous IoT applications. As the nodes typically have limited resources, many energy aware task allocation schemes are cond…
View article: Attention-Based Convolutional LSTM for Describing Video
Attention-Based Convolutional LSTM for Describing Video Open
Video description technique has been widely used in the computer community for many applications. The typical approaches are mainly based on the encode-decode framework: the fixed-length video representation vectors are extracted by the en…
View article: Energy aware task allocation algorithms for wireless sensor networks
Energy aware task allocation algorithms for wireless sensor networks Open
Complex wireless sensor network (WSN) applications, such as those in Internet of things or in-network processing, are pushing the requirements of energy efficiency and long-term operation of the network drastically. Energy aware task alloc…