Academic Articles & Research Papers

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...

Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and th...

Machine learning insight in quality control and maintenance management of drilling mud pumps

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

In vivo prediction of carcass and meat quality in lambs using multi-site bioelectrical impedance combined with body morphometrics.

Using fuzzy and machine learning iterative optimized models to generate the flood susceptibility maps: case study of Prahova River basin, Romania

AbstractIn this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating D...

A synergistic enhancement of the Ivy algorithm for GAN-based imbalanced classification

Abstract The Ivy Algorithm (IVYA), a swarm intelligence algorithm inspired by plant growth, presents a novel framework for optimization. To unlock its full potential in complex, high-dimensional problems, it is crucial to address the fundam...

Machine Learning in Orthopedics: A Literature Review

In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic probl...

A review of the application of machine learning in water quality evaluation

With the rapid increase in the volume of data on the aquatic environment, machine learning has become an important tool for data analysis, classification, and prediction. Unlike traditional models used in water-related research, data-driven...

Specimen quality shapes the actionable genomic landscape in comprehensive cancer genomic profiling.

Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better unde...

Precision water quality indices forecasting through an optimized hybrid SMW-LSSVM-R model enhanced by SATLDE and uncertainty analysis

Precise forecasting of water quality indices (WQI) is essential for safeguarding ecosystems, human health, and sustainable water resource management. This study presents an innovative approach for evaluating river Water Quality Indices usin...

Burnout Risk Profiles in Psychology Students: An Exploratory Study with Machine Learning

University students are at increased risk of developing burnout and psychological distress from high academic workloads and performance expectations. The purpose of this study is to analyze the relationship between psychological and lifesty...

Generative-Adversarial-Network-Based Image Reconstruction for the Capacitively Coupled Electrical Impedance Tomography of Stroke

This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

BackgroundSentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its...

A Sensor-to-API Data Infrastructure for Building Digital Twins: Harmonizing Multi-Rate IoT Energy and Indoor Data Streams for Proactive Analytics

Digital twins are increasingly used in smart buildings to monitor energy use. This requires reliable sensor data, geospatial information, and semantically rich 3D building geometry. However, building sensor data often has inconsistent sampl...

A Survey on Distributed Machine Learning

The demand for artificial intelligence has grown significantly over the past decade, and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, to increase the qual...

Automated speech-fluency explanations for schizophrenia diagnosis

Abstract Schizophrenia is a chronic and severe mental disorder that still relies on time-intensive, clinician-administered assessments. Although several automated approaches have been proposed to support diagnosis, these systems often lack ...

The challenge of studying perovskite solar cells’ stability with machine learning

Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technolog...

Machine Learning in Agriculture: A Review

Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...

Harnessing genetic variation for grain quality from diverse wheat landraces.