Decision-making in supply chains is challenged by high complexity, a combination of
continuous and discrete processes, integrated and interdependent operations, dynamics …

The impact of the Internet of Things (IoT) on the advancement of the healthcare industry is
immense. The ushering of the Medicine 4.0 has resulted in an increased effort to develop …

Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …

Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …

Abstract Machine learning (ML) technology is a powerful tool in food science and
engineering offering numerous advantages, from recognizing patterns and predicting …

Large amounts of patient vital/physiological signs data are usually acquired in hospitals
manually via centralized smart devices. The vital signs data are occasionally stored in …

This paper aims to evaluate the degree of affinity that Nordic companies' reports published
under the Global Reporting Initiatives (GRI) framework have. Several natural language …

Introduction: recent initiatives in healthcare reform have pushed for a better understanding of
data complexity and revolution. Given the global prevalence of Non-Communicable …

Purpose In today's fast developing era, the volume of data is increasing day by day. The
traditional methods are lagging for efficiently managing the huge amount of data. The …

In deep learning, artificial intelligence does influence numerous sides of smart cities. Deep
learning is an auspicious approach for extracting the exact information from raw sensor data …