Academic Articles & Research Papers

Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data

Abstract Background Coronavirus disease 2019 (COVID-19) is a novel infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite the paucity of evidence, various complementary, alternative and integr...

Target reindexing and residual reconstruction enable reliable retrieval augmented few shot recognition

Abstract Retrieval-augmented few-shot recognition supplements sparsely annotated target classes with external visual samples, but open retrieval results may exhibit unstable quality, semantic mismatch, and cross-domain feature shifts. Direc...

Neural transfer learning for natural language processing

The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...

Enhancing adult lifelong learning through data fusion algorithms and quality assurance

Abstract This study presents a Data Fusion + Random Forest (RF) framework to predict adult learners’ educational outcomes, such as dropout risk and course completion. Adult lifelong learning is crucial for personal and professional growth, ...

THE NORTHERN LABOR MARKET IN A RESOURCE-BASED REGIONAL ECONOMY: THE CASE OF THE KHANTY-MANSIYSK AUTONOMOUS OKRUG—YUGRA

This study examines the labor market of the Khanty-Mansi Autonomous Okrug–Yugra. The relevance of the research stems from the region’s strong dependence on natural resource reserves and production volumes, driven by the dominance of the min...

Valorisation of agri-food by-products into bioactive compounds: Green extraction, microbial biotransformation and circular biorefinery strategies

Agri-food processing generates large volumes of by-products that remain insufficiently exploited despite their content of phenolic compounds, peptides, polysaccharides, carotenoids, dietary fibres and other functional constituents. These si...

Deep learning for natural language processing: advantages and challenges

Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...

Natural Language Processing in Radiology: A Systematic Review

Radiological reporting has generated large quantities of digital content within the electronic health record, which is potentially a valuable source of information for improving clinical care and supporting research. Although radiology repo...

Natural Language Processing for Requirements Engineering

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...

Natural language processing with Python

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'...

Mobile learning for less-commonly taught languages: design and application

The increasing development of emerging technologies contributes to ubiquitous and personalized language learning. Hence this study reported a project of designing and applying mobile learning for a less-commonly taught language, Fijian lang...

Artificial Intelligence in Routine IVF Practice

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

Computer vision methods and algorithms for automatic detection and classification of objects in decision support systems in agriculture

The paper examines aspects of developing and formalizing the task of applying computer vision methods and algorithms using OpenCV (implemented in Python version 3.13 notation) for automatic detection and classification of objects in decisio...

Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery

Mechanical site preparation by mounding is often used by the forest industry to provide optimal growth conditions for tree seedlings. Prior to planting, an essential step consists in estimating the number of mounds at each planting block, w...

Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour

Melanoma is the skin cancer caused by the ultraviolet radiation from the Sun and has only 15-20% of survival rate. Late diagnosis of melanoma leads to the severe malignancy of disease, and metastasis expands to the other body organs i.e. li...

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

Kernel Methods in Computer Vision

Over the last years, kernel methods have established themselves as powerful tools for computer vision researchers as well as for practitioners. In this tutorial, we give an introduction to kernel methods in computer vision from a geometric ...

Repurposing a commercial artificial intelligence vision platform for automated surgical instrument identification: a proof-of-concept study

Abstract Background Retained surgical items are classified as never events but continue to occur, and the count meant to prevent them is often recorded as correct even when an item is retained. Computer vision could provide an independent c...

An integrated CT/MRI diagnostic system for pancreatic cystic lesions that supports pathological classification and risk stratification.