Disasters are unforeseen occurrences requiring extensive transport deployment to support and relieve victims. Sometimes, this transportation is not feasible directly from some supply points to some destination points. Due to this tragedy, it is unclear precisely what is available at supply...

By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering change (EC) process. Here, failing to adhere to planned...

Maintenance strategies are vital for industrial and manufacturing systems. This study considers a proactive maintenance strategy and emphasizes using analytics and data science. We propose an Explainable Artificial Intelligence (XAI) methodology for predictive maintenance. The proposed method...

Software-defined Networking (SDN) offers flexibility and programmability, making it a desirable option for modern network architecture. SDN provides numerous benefits to network administrators due to its centralized control architecture. This allows network administrators to manage and configure...

Visually impaired individuals encounter numerous impediments when traveling, such as navigating unfamiliar routes, accessing information, and transportation, which can limit their mobility and restrict their access to opportunities. However, assistive technologies and infrastructure solutions...

The real-world production inventory systems involve uncertainties surrounding demand, production, defectiveness, and costs, which pose significant challenges. Various methodologies, including interval, fuzzy, stochastic, and fuzzy-stochastic approaches, have been developed to address these...

Wireless sensor networks (WSNs) are widely utilized in various applications due to their compact size, cost-effectiveness, and ease of deployment. Nonetheless, one of the biggest problems in WSNs is getting a reasonable estimate of the average location error of a node at the setup in the least...

The present study aims to explain and predict the monetary amount awarded by courts as compensation for harm suffered. A set of machine-learning algorithms was applied to a sample of decisions handed down by the Polish common courts. The methodology involved two steps: identification of words...

Production systems influence cost performance and carbon emissions. Environmental concerns compel companies to optimize energy efficiency in their production processes. This study explores the dilemma associated with fixed-time and fixed-lot systems during random disruptions and how these...

Researchers have been working on developing new effective, reliable, and environmentally friendly crop recommendation systems. This study introduces a thorough framework for predicting crop recommendations by combining sophisticated machine learning (ML) classifiers with a multi-class...