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Supplier selection strategies evaluation: a multi-agent based simulation

Published in: International Journal of Economics and Business Research

Jun 01, 2025

Belkacem Athamena Zina Houhamdi Mohamed Raid Athamena Ghaleb Elrefae Kholoud Al Qeisi

Local food systems have gained prominence in response to increasing consumer demand for locally produced food, driven by heightened interest in diet, food quality, sourcing, production methods, and food safety. These systems support the economic sustainability of small and medium-sized farms and promote consumer awareness through enhanced transparency and direct farmer-customer relationships. However, the effectiveness of these systems depends on robust and efficient supply chain operations, wh...


Article

Hierarchical Multiparty Digital Signature for Distributed Systems: Application in Intelligent Vehicle Surveillance

Published in: Journal of Cybersecurity and Privacy

May 21, 2025

The rapid expansion of distributed systems such as the Internet of Things (IoT) has increased the need for robust authentication and data integrity mechanisms to ensure public security in dynamic environments. This article presents a hierarchical multiparty digital signature (HMPS) technique designed to address the unique challenges of resource-constrained and decentralized systems. By integrating a modified ElGamal-based individual signature with linear encryption and hierarchical aggregation,...


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Supervised methods of machine learning for email classification: a literature survey

Published in: Systems Science & Control Engineering

May 15, 2025

Muath AlShaikh Yasser Alrajeh Sultan Alamri Suhib Melhem Ahmed Abu-Khadrah

In today’s digital landscape, email is acknowledged as a critical conduit for global data exchanges. With a surge in data volume, malefactors exploit user identities, leading to data misuse. Cybercriminals employ electronic transgressions such as phishing and spam to orchestrate security infractions. Machine learning counters these breaches using myriad techniques, demonstrating significant efficiency in identifying phishing emails. We can divide machine learning into two types: supervised and ...

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