Academic Articles & Research Papers

Resource allocation under uncertainty and equity constraints in Parkinson's disease care: An econometrically grounded machine learning framework.

Whole-genome sequencing-driven source tracing of foodborne diseases: from cgMLST/SNP typing toward an integrated framework of pan-genomics and machine learning.

Optimization Method for Classifier Output Repeatability Based on Siamese Networks

In industrial surface Quality Control (QC) scenarios, deep classification neural networks are widely used to classify product images for qualified judgment or quality grading. However, surface QC equipment equipped with deep classification ...

Modular multi-fidelity simulation framework for advanced sail-driven spacecraft control and dynamics in perturbation-rich regimes

This work presents a high-fidelity Software-in-the-Loop (SIL) simulation framework for the development and validation of control strategies for sail-driven spacecraft operating in Low Earth Orbit (LEO). The framework integrates NVIDIA Omniv...

A SAM2 and VLM-Based Automatic Radiological Reporting System for Pneumothorax Detection

Background/Objectives: Pneumothorax, caused by air accumulation in the pleural space, can lead to lung collapse and, if diagnosis is delayed, respiratory or cardiovascular deterioration. Most deep-learning studies on pneumothorax address cl...

Identification and structural analysis of the interactional effect of the change drivers on the field of education

Due to its wide range and importance, the education system has very important and complex elements that if we neglect to monitor their future variations, it can lead to undeniable and profound damages to the results that are expected to be ...

Large-scale screening of high-entropy materials for superionic solid electrolytes

Abstract Solid electrolytes have emerged as a promising alternative to conventional liquid electrolytes that have posed safety concerns. However, the relatively low ionic conductivity of solid electrolytes is one of the challenges for their...

Optimal pre-train/fine-tune strategies for accurate material property predictions

Abstract A pathway to overcome limited data availability in materials science is to use the framework of transfer learning, where a pre-trained (PT) machine learning model (on a larger dataset) can be fine-tuned (FT) on a target (smaller) d...

Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods

Globally, cervical cancer remains as the foremost prevailing cancer in females. Hence, it is necessary to distinguish the importance of risk factors of cervical cancer to classify potential patients. The present work proposes a cervical can...

LncRNA-Top: Controlled deep learning approaches for lncRNA gene regulatory relationship annotations across different platforms

Summary: By soaking microRNAs (miRNAs), long non-coding RNAs (lncRNAs) have the potential to regulate gene expression. Few methods have been created based on this mechanism to anticipate the lncRNA-gene relationship prediction. Hence, we pr...

Hybrid heterogeneous ensemble learning framework for flood susceptibility mapping in Balochistan, Pakistan

Study region: The National Highways 85 and 50, key routes of the China–Pakistan Economic Corridor (CPEC) in Balochistan, Pakistan. Study focus: Flooding is a natural disaster that is becoming increasingly frequent and severe. The National H...

Automated wound care by employing a reliable U-Net architecture combined with ResNet feature encoders for monitoring chronic wounds

Quality of life is greatly affected by chronic wounds. It requires more intensive care than acute wounds. Schedule follow-up appointments with their doctor to track healing. Good wound treatment promotes healing and fewer problems. Wound ca...

Automatic Detection of Abnormal EEG Signals Using WaveNet and LSTM

Neurological disorders have an extreme impact on global health, affecting an estimated one billion individuals worldwide. According to the World Health Organization (WHO), these neurological disorders contribute to approximately six million...

Model Optimasi SVM Dengan PSO-GA dan SMOTE Dalam Menangani High Dimensional dan Imbalance Data Banjir

Banjir merupakan salah satu bencana alam yang sering terjadi di Indonesia, termasuk di Kota Samarinda dengan 18-33 titik desa terdampak dari tahun 2018-2021. Penggunaan machine learning dalam mengklasifikasi bencana banjir sangat penting un...

A database of experimentally measured lithium solid electrolyte conductivities evaluated with machine learning

Abstract The application of machine learning models to predict material properties is determined by the availability of high-quality data. We present an expert-curated dataset of lithium ion conductors and associated lithium ion conductivit...

A deep learning recognition model for landslide terrain based on multi-source data fusion

The traditional high-level remote landslide recognition efficiency which relies on the artificial discrimination of geological experts is low. In this paper, an automatic landslide terrain recognition model based on deep learning is develop...

Non-Motorized License Plate Recognition and Localization Method Based on Semantic Alignment and Hierarchical Optimization

Holding non-motorized vehicles accountable for legal violations effectively enhances urban traffic safety. Non-motorized vehicle license plates are characterized by small size, dense distribution, and ease of being obscured, which leads to ...

THE PROPERNESS OF ADOBE FLASH BASIS INTERACTIVE MEDIA FOR RESPIRATORY SYSTEM LEARNING MATERIAL

This study aimed to determine the feasibility of adobe flash-based interactive media on the material of respiratory system. This research was a descriptive qualitative. The data were validated by using questionnaire. The validation was done...

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathol...

Temperature- and vacancy-concentration-dependence of heat transport in Li3ClO from multi-method numerical simulations

Abstract Despite governing heat management in any realistic device, the microscopic mechanisms of heat transport in all-solid-state electrolytes are poorly known: existing calculations, all based on simplistic semi-empirical models, are unr...