Academic Articles & Research Papers

Machine learning and soil sciences: a review aided by machine learning tools

Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...

Prediction of overall survival in acute myeloid leukemia using supervised machine learning.

Predicting Stock Price Movements with Combined Deep Learning Models and Two-Tier Metaheuristic Optimization Algorithm

Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...

Data-driven performance prediction of polymer solar cells using multi-layer perceptron with Bayesian hyperparameter tuning

Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...

COVID-19 Outbreak Prediction with Machine Learning

Abstract Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simpl...

Decoding the genetic complexity in a pediatric case of B-ALL through long-read genomic sequencing and RNA sequencing.

A cascaded classification approach using transfer learning and feature engineering for improved breast cancer classification

The primary objective of this study is to design a cascaded classification framework that integrates deep-learning representations with handcrafted and clinical features to enhance the reliability and accuracy of breast cancer detection in ...

Performance Analysis and Optimization of Terahertz Metamaterial Absorbers Using Machine Learning-Based Inverse Modeling

We present a tunable broadband terahertz (THz) metamaterial absorber with a structurally simple, single-layered vanadium dioxide (VO2) elliptical ring resonator. This design achieves a wide, near-perfect absorption band (3.5–5 THz) w...

Key factors and serial mediation analysis of anxiety and depression among university students: a cross-sectional study

BackgroundAnxiety and depressive symptoms are prevalent among university students; however, their risk factors are unlikely to operate in isolation. Instead, they may be organized in a multilevel structure that progressively approaches emot...

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...

Student Modeling and Machine Learning

After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge neces...

Machine Learning in Healthcare Communication

Machine learning (ML) is a study of computer algorithms for automation through experience. ML is a subset of artificial intelligence (AI) that develops computer systems, which are able to perform tasks generally having need of human intelli...

eD octor: machine learning and the future of medicine

Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often ...

MARKETING ACTIVITIES OF IT COMPANIES: INFORMATION AND ORGANISATIONAL CAPABILITIES FOR DIGITAL PRODUCT DEVELOPMENT

The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysi...

Statistical Characteristics of Nighttime Medium‐Scale Traveling Ionospheric Disturbances From 10‐Years of Airglow Observation by the Machine Learning Method

Abstract For the first time, we used the machine learning method to analyze the statistical occurrence and propagation characteristics of nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) from October 2011 to December 2021 ...

Real time identification of phishing attacks through machine learning enhanced browser extensions

Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...

Application of Machine Learning in Microbiology

Microorganisms are ubiquitous and closely related to people's daily lives. Since they were first discovered in the 19th century, researchers have shown great interest in microorganisms. People studied microorganisms through cultivation, but...

Machine Learning: ECML 2001

Editorial for the Special Issue “Machine Learning in Computer Vision and Image Sensing: Theory and Applications”

Machine learning (ML) models have experienced remarkable growth in their application for multimodal data analysis over the past decade [...]...