hypedarhypedar
feedtrendsdiscovershowcasearchive
login
login
login
FeedTrendsDiscoverShowcaseArchiveDashboard
Submit Showcase

Trending now

Security + Agents + Infrastructure60Security + Vulnerability35Code Generation + Agents + Inference31
View all trends →

hypedar

AI trend radar for developers. Catch emerging papers, repos, and discussions before the hype peaks.

AboutGitHubDiscord

By the makers of hypedar

Codepawl

Open-source tools for developers.

Explore our tools →
AboutPrivacyTermsX

© 2026 Codepawl

Built by Codepawl·© 2026

About·Terms·Privacy·Security

GitHub·Discord·X

feedtrendsdiscovershowcasearchive
← feed
arXiv2h ago
4.6

Toward Reducing Unproductive Container Moves: Predicting Service Requirements and Dwell Times

Elena Villalobos (Tecnol\'ogico de Monterrey, Mexico City, Mexico), Adolfo De Un\'anue T. (Tecnol\'ogico de Monterrey, Mexico City, Mexico), Fernanda Sobrino (Tecnol\'ogico de Monterrey, Mexico City, Mexico), David Ak\'e (Tecnol\'ogico de Monterrey, Mexico City, Mexico), Stephany Cisneros (Tecnol\'ogico de Monterrey, Mexico City, Mexico), Jorge Lecona (Container Terminal Operations, Veracruz, Mexico), Alejandra Matadamaz (Container Terminal Operations, Veracruz, Mexico)

View original ↗

Analysis

Viral velocity
low
Implementation gapYES
Novelty6/10
Categorypaper
Topics
logisticsoptimizationml

Opportunity Brief

Build a reusable ML pipeline for terminal and logistics scheduling. This empowers supply chain developers to reduce dwell times through predictive modeling without custom building from scratch.

Suggested repo: PortFlow

"Cut terminal congestion with predictive container scheduling."

Estimated effort: 50h