Aptiv and Vecna Robotics announced a strategic collaboration to co-develop next-generation Autonomous Mobile Robot (AMR) solutions designed to deliver cost-efficient automation. This partnership ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

5.1 RQ1: How does our proposed anomaly detection model perform compared to the baselines? 5.2 RQ2: How much does the sequential and temporal information within log sequences affect anomaly detection?

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

Unusual status codes, Spikes in error rates, Error categorization related to databases. The Flask app exposes a /predict endpoint, which accepts log data and returns ...

Abstract: Anomaly detection refers to the task of estimating and finding patterns which do not comply with the general behavior of data. Moreover, a range of assumptions are made so as to ...

This is the initial docs-only release of the Compliance & Anomaly Detection – Big-4 Audit & Consulting Firm (Azure + Databricks) project.

Abstract: Anomaly detection is becoming a powerful and necessary component as wireless networks gain popularity. In this paper, we evaluate the efficacy of PCA based anomaly detection for wireless ...