Journal of Computer Science Research

Abstract:

Reducing neonatal mortality is a critical global health objective, especially in resource-constrained developing countries. This study employs machine learning (ML) techniques to predict fetal health status based on cardiotocography (CTG) examination findings, utilizing a dataset from the Kaggle repository due to the limited comprehensive healthcare data available in developing nations. Features such as baseline fetal... More

Abstract:

Homogeneous binary function products are often encountered in the sub-universes modeled by databases, from genealogical trees to sports, from education to healthcare, etc. Their properties must be discovered and enforced by the software applications managing such data to guarantee plausibility. The (Elementary) Mathematical Data Model provides 17 dyadic-type homogeneous binary function product constraint types. MatBase, an... More

Abstract:

In this work, Digital Twins based on Neural Networks for the steady state production of styrene were generated. Thus, both the Aspen Technology AI Model Builder (alternative 1) and a homemade MS Excel VBA code connected to Aspen HYSYS and Aspen Plus (alternative 2) were used with this same aim. The raw data used for generating... More

Abstract:

Big data has had significant impacts on our lives, economies, academia and industries over the past decade. The current questions are: What is the future of big data? What era do we live in? This article addresses these questions by looking at meta as an operation and argues that we are living in the era of big intelligence... More