Adaptive Positional Encoding with Regularization for Robust Edge Computing Applications
The paper addresses communication bottlenecks in Federated Learning and introduces Selective Compression via Adaptive Lightweight Protocol.
Addressing Data Security in IoT: Minimum Sample Size and Denoising Diffusion Models for Improved Malware Detection
This paper investigates on how to define the miimum sample siz and improving the data agumentation for Traffic Images.
The intrinsic convenience of federated learning in malware IoT detection
This paper investigates on on how to implement a federated malware recognition system.
Automating Heterogeneous Internet of Things Device Networks from Multiple Brokers with Multiple Data Models
This paper discusses the automatic harvesting of news from new devices to integrate into existing IoT systems.
Taming Bandwidth Bottlenecks in Federated Learning via ECN-based Gradient Compression
The paper addresses communication bottlenecks in Federated Learning and introduces Selective Compression via Adaptive Lightweight Protocol.
Load Profile Generation for Robust Optimization: A Stochastic Approach Based on Conditional Probability Approximation
This paper investigates on how to generate load profile with stochastic approach.
A Convolutional Neural Network to Locate Unbalance in Turbomachinery Supported by AMBs
This paper studies the fault recognitions in an ABMs system.
A Convolutional Neural Network for Electrical Fault Recognition in Active Magnetic Bearing Systems
This paper presents a case study on the application of Convolutional Neural Networks (CNNs) for the recognition of electrical faults in Active Magnetic Bearing systems.