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Found 7 papers, 0 papers with code
Effectiveness and predictability of in-network storage cache for scientific workflows
We also build a machine learning model to study the predictability of the cache behavior.
Feature Engineering and Classification Models for Partial Discharge in Power Transformers
These features represent the entire signal and not just a single phase, so the feature set has a fixed size and is easily comprehensible.
Extract Dynamic Information To Improve Time Series Modeling: a Case Study with Scientific Workflow
In this work, we describe a number of techniques to extract dynamic information about the current state of a large scientific workflow, which could be generalized to other types of applications.
Access Trends of In-network Cache for Scientific Data
Our study shows that this distributed storage cache is able to reduce the network traffic volume by a factor of 2. 35 during a part of the study period.
Improving Botnet Detection with Recurrent Neural Network and Transfer Learning
Botnet detection is a critical step in stopping the spread of botnets and preventing malicious activities.
Botnet Detection Using Recurrent Variational Autoencoder
Botnets are increasingly used by malicious actors, creating increasing threat to a large number of internet users.
An Ensemble Approach toward Automated Variable Selection for Network Anomaly Detection
While variable selection is essential to optimize the learning complexity by prioritizing features, automating the selection process is preferred since it requires laborious efforts with intensive analysis otherwise.
