Academic Articles & Research Papers

Evaluation of 3D Vulnerable Objects’ Detection Using a Multi-Sensors System for Autonomous Vehicles

One of the primary tasks undertaken by autonomous vehicles (AVs) is object detection, which comes ahead of object tracking, trajectory estimation, and collision avoidance. Vulnerable road objects (e.g., pedestrians, cyclists, etc.) pose a g...

Research on Prediction of Movable Fluid Percentage in Unconventional Reservoir Based on Deep Learning

In order to improve the measurement speed and prediction accuracy of unconventional reservoir parameters, the deep neural network (DNN) is used to predict movable fluid percentage of unconventional reservoirs. The Adam optimizer is used in ...

UAV-Embedded Sensors and Deep Learning for Pathology Identification in Building Façades: A Review

The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...

Digital Twins in Solar Farms: An Approach through Time Series and Deep Learning

The generation of electricity through renewable energy sources increases every day, with solar energy being one of the fastest-growing. The emergence of information technologies such as Digital Twins (DT) in the field of the Internet of Thi...

Introducing Deep Learning Self-Adaptive Misuse Network Intrusion Detection Systems

The intrusion detection systems (IDSs) are essential elements when it comes to the protection of an ICT infrastructure. A misuse IDS is a stable method that can achieve high attack detection rates (ADR) while keeping false alarm rates under...

Data Mining and Machine Learning

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...

Machine Learning in Nutrition Research

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and ...

Foundations of Machine Learning

This chapter focuses on providing a complete grasp of the foundations of machine learning (ML). Machine learning is a rapidly evolving domain with wide-ranging applications, from natural language processing to autonomous vehicles. This chap...

Fairness in Machine Learning: A Survey

When Machine Learning technologies are used in contexts that affect citizens, companies as well as researchers need to be confident that there will not be any unexpected social implications, such as bias towards gender, ethnicity, and/or pe...

A Machine Learning-Oriented Survey on Tiny Machine Learning

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...

An explainable machine learning framework for cross-dataset chronic kidney disease risk prediction using hybrid data balancing.

An adaptive energy management and control framework for long-endurance UAV missions in dynamic environments: A reproducible simulation study.

Development of a SCGP-CGAN framework for bidirectional H&E–Masson’s Trichrome Virtual Staining.

Availability-Aware Multitask Learning for Robust Clinical Prediction from Incomplete Electronic Health Records

This study presents NORIA, an availability-aware multitask learning framework for clinical prediction from incomplete electronic health records (EHRs). We analyzed a public dataset of 77,724 patients and 107 numerical features. To prevent t...

Towards Neural‐Network‐Based Optical Temperature Sensing of Semiconductor Membrane External Cavity Laser

Abstract A machine‐learning (ML) non‐contact method to determine the temperature of a laser gain medium via its laser emission with a trained few‐layer neural‐network (NN) model is presented. The training of the feed‐forward NN enables the ...

Integrative multiomics analysis of platelet-related genes unveils molecular subtypes and prognostic signatures in acute myeloid leukemia

Abstract Acute myeloid leukemia (AML) remains challenging due to molecular heterogeneity and limited prognostic models integrating tumor microenvironment dynamics. While thrombocytopenia correlates with poor outcomes, the roles of platelet-...

Context-Aware LLM-Guided Neighbourhood Search for Simulation-Based Production Scheduling

The paper presents a novel large language model-based neighbourhood search method for production scheduling using discrete-event simulation (DES) as the modelling and evaluation engine. The combination of large language models (LLMs) and DE...

Cyclic multiplex fluorescent immunohistochemistry and machine learning reveal distinct states of astrocytes and microglia in normal aging and Alzheimer’s disease

Abstract Background Astrocytes and microglia react to Aβ plaques, neurofibrillary tangles, and neurodegeneration in the Alzheimer’s disease (AD) brain. Single-nuclei and single-cell RNA-seq have revealed multiple states or subpopulations of...

Upper Limb Movement Prediction Based on Segmented sEMG Signals

Motion intent recognition research is one of the key challenges in achieving human-robot collaboration in rehabilitation robots. In the traditional method, intention recognition is performed based on the complete sEMG, however, due to the m...

A novel framework for spatio-temporal prediction of environmental data using deep learning

Abstract As the role played by statistical and computational sciences in climate and environmental modelling and prediction becomes more important, Machine Learning researchers are becoming more aware of the relevance of their work to help ...