Artificial Intelligence

This dataset includes generated demand series, forecasts, forecast errors, and simulation results for the manuscript "Assessing the Effect of One-Step and Multi-Step Forecasting on Bullwhip Effect and Supply Chain Performance." Autoregressive demand series were generated using varying parameters, specifically based on an AR(1) demand process. Additionally, the M5 series, derived from Walmart, one of the world’s largest retailers, captures actual sales data from Walmart stores across the United States and is included as real-world data.

Brushless DC (BLDC) motors depend on accurate rotor position detection via Hall sensors for optimal performance. Faults, such as sensor displacement, can disrupt commutation and lead to efficiency losses. This study utilizes deep learning to detect Hall sensor faults, focusing on a meticulously prepared dataset designed for this purpose. The dataset study consists of phase current measurements under various Hall sensor displacement conditions, categorized as No Delay, 0.0001 Delay, 0.005 Delay, and 0.01 Delay.

The Universal Networking Language (UNL) UDE Dictionary for French Cooking is a pioneering framework aimed at facilitating seamless communication and knowledge sharing across diverse languages and cultures, with a special focus on the rich culinary traditions of France. This dictionary provides a comprehensive and structured representation of essential culinary terms, ingredients, cooking techniques, and descriptors in French, paired with their corresponding UNL equivalents. Each entry includes a UNL term, a definition and examples.

The dataset provides a collection of image-based classification and regression problems for artificial intelligence, under extreme visual attention constraints. Spatial shapes with simple geometries and called geometrons are embedded in an intense visual texture stream, with the aim of investigating the limits of artificial visual attention to capture known or unknown, but ghost or buried shapes.