Search Results for author:
Found 9 papers, 4 papers with code
Disentangling Imperfect: A Wavelet-Infused Multilevel Heterogeneous Network for Human Activity Recognition in Flawed Wearable Sensor Data
To address these challenges, we propose a multilevel heterogeneous neural network, called MHNN, for sensor data analysis.
High-order Spatial Interactions Enhanced Lightweight Model for Optical Remote Sensing Image-based Small Ship Detection
Accurate and reliable optical remote sensing image-based small-ship detection is crucial for maritime surveillance systems, but existing methods often struggle with balancing detection performance and computational complexity.
A Review of Federated Learning in Energy Systems
Then, we conducted a comprehensive review of FL applications in the energy domain (refer to the smart grid in this paper).
Smart Meter Data Anomaly Detection using Variational Recurrent Autoencoders with Attention
This paper proposes an unsupervised anomaly detection method based on a Variational Recurrent Autoencoder with attention mechanism.
SEGSys: A mapping system for segmentation analysis in energy
This paper showcases the system on the segmentation analysis using an electricity consumption data set and validates the effectiveness of the system.
Databases
$E^3$: Visual Exploration of Spatiotemporal Energy Demand
Understanding demand-side energy behaviour is critical for making efficiency responses for energy demand management.
Human-Computer Interaction Computers and Society
Regression-based Online Anomaly Detection for Smart Grid Data
With the widely used smart meters in the energy sector, anomaly detection becomes a crucial mean to study the unusual consumption behaviors of customers, and to discover unexpected events of using energy promptly.
Databases
Two-level Data Staging ETL for Transaction Data
The proposed method detects the changes of the data from transactional processing systems, identifies the corresponding operation codes for the changes, and uses two staging databases to facilitate the data processing in an ETL process.
Databases
Optimizing ETL Dataflow Using Shared Caching and Parallelization Methods
In order to minimize the time and the resources required by ETL dataflows, this paper presents a framework to optimize dataflows using shared cache and parallelization techniques.
Databases
