Academic Articles & Research Papers

Editorial: Modern machine learning approaches for quantitative inference of gene regulation from genomic and epigenomic features

Improving Intrusion Detection Model Prediction by Threshold Adaptation

Network traffic exhibits a high level of variability over short periods of time. This variability impacts negatively on the accuracy of anomaly-based network intrusion detection systems (IDS) that are built using predictive models in a batc...

An assessment of subject-comprehension and subject-command attained through digital learning platforms

Abstract A synthesized investigation, employing graphical and analytical approach, has been conducted to examine inadequacy of electronic education and limitations posed by transformative mode of learning from students’ perspective. Moreove...

An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch

Static Transfer Switch (STS) is required for high-speed transfer of essential load to the alternate power source when the main source fails due to power disturbance (PD). A fast and accurate PD detection method is required to ensure trans...

Integrating BIM, Machine Learning, and PMBOK for Green Project Management in Saudi Arabia: A Framework for Energy Efficiency and Environmental Impact Reduction

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...

Machine Learning: A Bayesian and Optimization Perspective

This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabil...

Applied Machine Learning

A review of machine learning in obesity

Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine lea...

Machine learning for alloys

A First Course in Machine Learning

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations ...

Machine Learning Research

Machine Learning Research (MLR) is a scholarly open access, peer-reviewed, and fully refereed journal. This journal provides a unified forum for researchers and scientists to share the latest research and developments in all areas of machin...

Machine Learning for Evolution Strategies

Machine Learning and the Future of Cardiovascular Care

The role of physicians has always been to synthesize the data available to them to identify diagnostic patterns that guide treatment and follow response. Today, increasingly sophisticated machine learning algorithms may grow to support clin...

Machine Learning Approaches for Clinical Psychology and Psychiatry

Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide...

Machine Learning Methods for Histopathological Image Analysis

Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have so...

Machine Learning in Compiler Optimization

In the last decade, machine-learning-based compilation has moved from an obscure research niche to a mainstream activity. In this paper, we describe the relationship between machine learning and compiler optimization and introduce the main ...

Machine Learning

Introduction to machine learning: k-nearest neighbors

Machine learning techniques have been widely used in many scientific fields, but its use in medical literature is limited partly because of technical difficulties. k-nearest neighbors (kNN) is a simple method of machine learning. The articl...

Machine learning techniques

Correction: The BCPM method: decoding breast cancer with machine learning