Finding low-cost and insightful methods to reinforce the diagnosis of Parkinson's disease is a major challenge today, and using dynamic handwritten data may be one of the solutions. Artificial intelligence and machine learning methods can be used to create predictive models for disease...

Increased environmental awareness has inspired the industrial community to develop sustainable business models (SBMs). Accordingly, SBM has become a trendy topic in the research community. This review analyses SBM to understand its significance, emerging trends, opportunities, challenges, and...

Data Envelopment Analysis (DEA), Multi-criteria Decision Analysis (MCDA), and Cluster Analysis (CA) are techniques widely used to help decision-makers determine the solution to problems with multiple and often conflicting criteria. This study presents a comprehensive review of the literature on...

There is a localization wave in the semiconductor industry for pushing wafer foundries to transfer their production capacity to where chip designers are located. The main reasons for the localization of semiconductor supply chains include the US-China trade war, geopolitics, COVID-19, the...

This study presents the design and development of a Remora Optimization -Tilt Integral-Derivative-Filter (RO-TIDF) controller to infuse ideal insulin doses to manage Blood Glucose (BG) levels in Type-I Diabetes Mellitus (TIDM) patients with Artificial Pancreas (AP). In this control technique,...

Artificial intelligence (AI) systems can assist in analyzing medical images and aiding in the early detection of diseases. AI can also ensure the quality of services by avoiding misdiagnosis caused by human errors. This study proposes a deep neural network (DNN) model with fine-tuned training...

A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...

The blood supply chain (BSC) is a complex system with optimization challenges, whose activities impact carbon emissions and the environment, especially with regard to the disposal of expired blood bag waste. This study proposes a new mixed-integer linear programming (MILP) model that considers...

The outbreak of COVID-19 has caused an unprecedented increase in the usage of e-Learning platforms. The closure of educational institutions globally has significantly impacted the traditional education system. Without physical interaction, engaging students in an e-Learning environment has...

Over the last decade, there has been a considerable increase in the popularity of online education. As a result, the online learning or e-learning industry has flourished, providing benefits to students, learners, educators, and education experts. Despite the advantages of e-learning, it also...