Academic Articles & Research Papers

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

Machine learning in materials science

Abstract Traditional methods of discovering new materials, such as the empirical trial and error method and the density functional theory (DFT)‐based method, are unable to keep pace with the development of materials science today due to the...

On-board Clutch Slippage Detection and Diagnosis in Heavy Duty Machine

In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machine in combination with feature extraction and classification...

Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted ...

Machine learning-based diagnostic prediction of minimal change disease: model development study

Abstract Minimal change disease (MCD) is a common cause of nephrotic syndrome. Due to its rapid progression, early detection is essential; however, definitive diagnosis requires invasive kidney biopsy. This study aims to develop non-invasiv...

Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges

Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. ...

A Novel Approach for Multichannel Epileptic Seizure Classification Based on Internet of Things Framework Using Critical Spectral Verge Feature Derived from Flower Pollination Algorithm

A novel approach for multichannel epilepsy seizure classification which will help to automatically locate seizure activity present in the focal brain region was proposed. This paper suggested an Internet of Things (IoT) framework based on a...

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need ...

Pandemic preparedness: Potential of routine general practice data for infectious disease early signal detection.

PANDA pediatric arousal neural detection architecture.

Tackling visual impairment: emerging avenues in ophthalmology

Visual impairment, stemming from genetic, degenerative, and traumatic causes, affects millions globally. Recent advancements in ophthalmology present novel strategies for managing and potentially reversing these conditions. Here, we explore...

MONITORING SYSTEM FOR CRITICAL INFRASTRUCTURE OBJECTS BASED ON DIGITAL TWINS

Critical infrastructures are fundamental to the seamless operation of modern societies, encompassing sectors such as energy, healthcare, transportation, and communications. Ensuring their reliability, performance, continuous operation, safe...

A Proposed Arabic Handwritten Text Normalization Method

Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, t...

Single lead electrocardiographic detection of left ventricular systolic dysfunction in pediatric and congenital heart disease.

Spatiotemporal deep learning for early detection of isolated REM sleep behavior disorder and Parkinson's disease using functional MRI data.

CeCILE - An Artificial Intelligence Based Cell-Detection for the Evaluation of Radiation Effects in Eucaryotic Cells

The fundamental basis in the development of novel radiotherapy methods is in-vitro cellular studies. To assess different endpoints of cellular reactions to irradiation like proliferation, cell cycle arrest, and cell death, several assays ar...

Advances in ligand-targeted nanodelivery systems for leukemia therapy: from single- to dual-ligand strategies

Abstract Background Leukemia is a highly heterogeneous and aggressive hematological malignancy. Current therapeutic approaches (e.g. chemotherapy, radiotherapy, small-molecule targeted therapies, and hematopoietic stem cell transplantation,...

Research on Oil and Gas Pipeline Leakage Detection Based on MSCNN-Transformer

The leakage detection of oil and gas is very important for the safe operation of pipelines. The existing working condition recognition methods have limitations in processing and capturing complex multi-category leakage signal characteristic...

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...

A hybrid transformer–neuromorphic framework for robust pest detection in agriculture

Abstract Detecting pests in agricultural fields remains one of the challenging tasks due to the small size of the objects and occlusion effects. In this paper, Trans-Neu-Pest, a hybrid framework, has been proposed by integrating the Swin Tr...