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This study aims to identify the best predictive model for analysing online product reviews (OPRs) in the electronics industry, with a secondary focus on leveraging unstructured customer feedback to support product improv...

Extensive research has demonstrated that music enhances cognitive functions, such as learning, reasoning, and memory. This study investigated the influence of music on short- and long-term memory while learning through t...

Background For those with hearing loss, sign language (SL) is an essential communication tool. The most common and basic type of SL is American SL (ASL). ASL plays a vital role in various communicative contexts, includin...

Marketplace platforms have become a central component of digital commerce, particularly in Southeast Asia where Shopee has emerged as one of the dominant e-commerce ecosystems. The increasing number of sellers on the pla...

Traditional measures for assessing the performance of classification models for binary outcomes are the ROC curve and the area under the ROC curve (AUC). Reclassification tables (Cook, 2008), net reclassification improv...

Abstract Synchronous reluctance motors (SynRMs) are increasingly critical in industrial and traction applications due to their high efficiency, magnet-free construction, and thermal robustness. However, fault diagnosis f...

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, which seriously affects children’s normal life. Screening potential autistic children before professional diagnose is helpful to early detection and earl...

Imbalanced data is an important issues and challenges faced in data classification. This will lead to poor performance of binary classifiers, this is due to bias in classification in favour of the majority class and lack...

Attacks on network components and devices pose a significant threat to service continuity, necessitating robust detection mechanisms. This paper presents a Distributed Denial of Service (DDoS) attack detection framework ...

The P300 component of event-related potentials (ERPs) is widely used in the implementation of brain computer interfaces (BCI). In this context, one of the main issues to solve is the binary classification problem that en...

Falls among older adults pose a major healthcare and social burden, making early identification of high-risk individuals essential for prevention. This study presents a portable, non-invasive AI-based wearable system tha...

The rapid expansion of digital communication has made social media an integral part of daily life, yet it has simultaneously amplified the reach of harmful behaviors. Early detection of cyberbullying is recognized as a c...

Class imbalance remains a critical challenge in medical data classification, particularly in diabetes prediction, as it significantly degrades minority-class sensitivity. This study proposes an Adaptive Feature-Aware Hyb...

Global food security relies heavily on rice production, which is continuously threatened by crop diseases. Although deep learning (DL) models have demonstrated strong diagnostic performance, their high computational and ...

Credit scoring has become an important issue because competition among financial institutions is intense and even a small improvement in predictive accuracy can result in significant savings. Financial...

Abstract Background This study aims to explore spatial heterogeneity within tumors, establish and validate an interpretable machine learning model combining habitat radiomics and deep learning, and investigate its predic...

The classification of edible versus poisonous mushrooms presents a critical challenge in the domains of applied biology and public health, particularly due to the serious implications of misidentification. This research ...

O presente trabalho tem como objetivo analisar o potencial de imagens SAR polarimétricas do sensor TerraSAR-X, no modo StripMap, para mapear o uso e cobertura da terra na região sudoeste da Amazônia brasileira. No pro...

The swift expansion of the digital gaming sector, especially online games like Free Fire, has produced extensive user feedback via platforms like the Google Play Store. This research utilizes the K-Nearest Neighbor (KNN)...

Abstract We developed and evaluated a deep learning system integrating segmentation and classification for automated detection of Weiss rings on fundus photographs (FPs). A U-Net segmenter and two EfficientNet-B0 classif...

Abstract Building energy consumption is dominated by lighting and heating, ventilation, and air conditioning (HVAC) systems, whose operation is often inefficient due to inadequate control strategies and unreliable occupa...

Information campaigns increasingly use LLMs to generate persuasive competing narratives around federal research agency press releases. Prior work largely centers on post hoc assessment, emphasizing detectability, charact...

In this paper, we present the Sperm Motility Tracker v2.0 that integrates a clustering module to the typical CASA sperm motility analysis adapted to semen from different species. The novelty of the new software is the in...