Fr. 123.00

Industrial Engineering and Operations Management - 10th North American Conference - Computer Science Tracks, IEOM-CS 2025, Orlando, USA, June 17-19, 2025, Proceedings

English · Paperback / Softback

Will be released 13.08.2025

Description

Read more

This book constitutes the refereed conference proceedings of the 10th North American Conference - Computer Science Tracks, IEOM-CS 2025, held in Orlando, USA during June 17 19, 2025.
The 22 full papers included in this book were carefully reviewed and selected from 121 submissions. They are categorized into the following topical sections:

  1. Artificial Intelligence
  2. Autonomous Systems
  3. Data Analysis
  4. Decision Systems
  5. Learning Management Systems
  6. Machine Learning
  7. Security Systems

List of contents

Artificial Intelligence
AI-Based Solutions for Optimizing Lane Change Safety in Connected Automated Vehicles.- 
AI-Driven Platform Architecture for Business Plan Formulation in Indigenous Communities: A Gender-Focused Case Study in Colombia.-
Automated Detection of Pulmonary Thromboembolism in Computed Tomography Pulmonary Angiography Images Using Convolutional Neural Networks: A Literature Review.- 
Development of Agentic Workflows with LangGraph for Software Development Life Cycle Automation.- 
Last-Mile Delivery in High-Density Emerging Economy Cities Using Crowd-Generated Data and Artificial Intelligence.- 
Systematic Review of AI and Non-AI Approaches for Personalized Learning Paths.- 
 
Autonomous Systems
Smart Detection and Measurement: The Real-AODM System.- 
Tracking the Unseen: Autonomous Multi-Object Motion Analysis in Complex Environments.- 
 
Data Analysis
BayesIntuit: A Neural Framework for Intuition-Based Reasoning.- 
Dynamic Simulation Tool for the Analysis of the Effects of Man-Machine Ratio on the Productivity of Test Manufacturing of a Semiconductor Company.- 
 
Decision Systems
An Analysis of Water Supply System Losses: A Case Study of Santa Catarina State, Brazil.- 
Comparison on the use of Hybrid and Plugin Hybrid Electric Buses for Sustainable Urban Transportation Split Use Case.- 
Consumption and Runtime Automatic Software Performance Optimization on Android Smartphones.- 
RECO: An AI-Powered Chatbot System for Optimizing Reverse Agri-Food Logistics and Fighting Food Insecurity in Colombia.- 
Revamping Agile Logistics for Emergency Management.- 
Spiral Design and Simulation-Driven Deployment of a Drive-Through COVID-19 Testing and Housing Check-In System at a Large Public University.- 
 
Learning Management Systems
Enhancing STEM Education with AI: Fostering Soft Skills and Inclusion.- 
 
Machine Learning
Bridging the Black Box: Data Mining Enhanced Machine Learning Interpretability for Exoplanet Discovery.- 
Cost Optimization in Mold-Making: A Conceptual Industry 4.0 Framework.- 
Enhancing Multi-Echelon Home Improvement Supply Chain Responsiveness Through Machine Learning-Enabled Inventory Segmentation and Positioning.- 
Ensemble Machine Learning for Healthcare Data: A Comparative Analysis of Chronic Kidney Disease and Cardiovascular Risk Prediction with NHANES Data.- 
 
Security Systems
Preliminary Modeling of Cyber Attackers in Microgrids: An Agent-Based and System Dynamics Approach Enhanced with Statecharts.

Summary

This book constitutes the refereed conference proceedings of the 10th North American Conference - Computer Science Tracks, IEOM-CS 2025, held in Orlando, USA during June 17–19, 2025.
The 22 full papers included in this book were carefully reviewed and selected from 121 submissions. They are categorized into the following topical sections:

  1. Artificial Intelligence
  2. Autonomous Systems
  3. Data Analysis
  4. Decision Systems
  5. Learning Management Systems
  6. Machine Learning
  7. Security Systems

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.