Academic Articles & Research Papers

Machine learning in pain research

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

Benchmarking Supervised Classifiers for Concurrent Multidomain Dropout-Intention Attributions in Higher Education: Evidence from a Colombian Public University

Student retention analytics often treats withdrawal as a single outcome, although students may attribute dropout intention to personal, socioeconomic, and academic pressures simultaneously. We benchmarked nine supervised classifiers for ide...

Investment portfolio optimization with supervised learning and attention mechanism

Portfolio optimization is a process that involves distribution of capital with the purpose of maximizing returns and at the same time minimizing risks. The current paper discusses the use of Transformer networks in supervised learning for p...

Application of MRI-Based Radiomics in Preoperative Prediction of NF2 Alteration in Intracranial Meningiomas

PurposeThis study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma.MethodsThis retrospective study included 105 patients with meningiomas, incl...

A novel machine learning-based model for predicting the transition fatigue lifetime in piston aluminum alloys

The estimation of transition fatigue lifetimes for piston aluminum alloys was carried out using unsupervised machine learning (ML) with the K-means algorithm. For this purpose, an experimental dataset representing standard ISO specimens wit...

An ensemble approach for imbalanced multiclass malware classification using 1D-CNN

Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...

TRIST: TREE RECOGNITION INTELLIGENT SYSTEM

Plant recognition represents a challenging computer vision problem due to the great variations of shape and texture among plant organs, within the same species. This paper proposes a light-weight, but reasonably deep Convolutional Neural Ne...

AN IMPROVED GRU BASED ON RECURRENT ATTENTION UNIT AND SELF- ATTENTION TECHNIQUE FOR TEXT SENTIMENT ANALYSIS

In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...

Feature-driven static analysis for learning-based android malware detection: A review

The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...

A Novel End-to-End Corporate Credit Rating Model Based on Self-Attention Mechanism

In traditional financial analysis discriminant analyses with statistic methods are considered as primary and widely applied corporate credit rating bases in which human impact plays an essential role. Machine learning approaches enormously ...

Machine Learning Model Coupled with Graphical User Interface for Predicting Mechanical Properties of Flax Fiber

Machine learning model coupled with graphical user interface was developed to predict mechanical properties of flax fiber. The experiment was conducted using test setup which applies constant rate of loading (CRL). Flax fiber was tested und...

Online exam cheating detection and blockchain trusted deposit based on YOLOv12

Abstract In recent years, online examinations have been widely adopted because of their flexibility, but the covert and diverse nature of cheating behaviour poses a serious challenge to the fairness and integrity of examinations. Existing a...

Lightweight Ensemble Learning based on Post-Hoc Probability Fusion with Its Application to Lung CT Image Classification.

Vestibular-Visual Reweighting in Persistent Postural-Perceptual Dizziness: A Multilevel Resting-State fMRI Study

Persistent postural-perceptual dizziness (PPPD) is a disabling functional vestibular disorder characterized by chronic dizziness and visually and motion-induced unsteadiness that markedly impairs daily activities, yet it lacks objective neu...

A multi-organization epigenetic age prediction based on a channel attention perceptron networks

DNA methylation indicates the individual’s aging, so-called Epigenetic clocks, which will improve the research and diagnosis of aging diseases by investigating the correlation between methylation loci and human aging. Although this discover...

Associations of pre-pregnancy weight, gestational weight gain, and postpartum weight retention with metabolic health: Findings from the MISC cohort study.

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Abstract Background Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HR...

Optimizing Energy Consumption of Edge-Cloud Environments: A comparative Study Between PPO and PSO

Abstract As the usage of the edge-cloud continuum increases, Kubernetes presents itself as a solution that allows easy control and deployment of applications in these highly-distributed and heterogeneous environments. In this context, Artif...