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Unmanned Aerial Vehicle-Based Structural Health Monitoring and Computer Vision-Aided Procedure for Seismic Safety Measures of Linear Infrastructures

Luna Ngeljaratan, Elif Ecem Bas, Mohamed A. Moustafa • Sensors (2024)

Computer vision in the structural health monitoring (SHM) field has become popular, especially for processing unmanned aerial vehicle (UAV) data, but still has limitations both in experimental testing and in practical applications. Prior wo...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24051450

An Implementation of an optimized dual-axis solar tracking algorithm for concentrating solar power plants deployment

Eric Tutu Tchao, Simon Atuah Asakipaam, Yesuenyeagbe Atsu Kwabla Fiagbe, Bright Yeboah-Akowuah et al. • Scientific African (2022)

A recent assessment of a pilot concentrating solar power plant in Ghana noticed the failure of the tracking system to accurately align the multifaceted heliostats toward the sun and focus the sunbeams onto the target. A further review of so...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.sciaf.2022.e01228

Assessment of the possibility of machine learning for electronic equipment quality prediction

Anna S. Kolosova, Anna S. Kameneva, Georgii G. Chukov, Alexander Y. Nikiforov • Безопасность информационных технологий (2023)

The major algorithms and methods of machine learning are considered. A possibility of machine learning and neural network using for electronic equipment quality prediction is assessed. The paper provides examples of the successful applicati...

DOAJ Open Access (DOAJ) DOI: 10.26583/bit.2023.1.09

Tamarind health assessment dataset: Images of shelled, unshelled, and mixed tamarind podsMendeley Data

Amol Bhosle, Deepali Godse, Sandip Thite, Kailas Patil et al. • Data in Brief (2025)

This data paper provides image dataset that includes 8432 high-quality images of Tamarindus indica [1] (tamarind), categorized into six types: Shelled Healthy Single, Shelled Healthy Multiple, Unshelled Healthy Single, Unshelled Healthy Mul...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111917

Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring

Billie F. Spencer, Vedhus Hoskere, Yasutaka Narazaki • Engineering (2019)

Computer vision techniques, in conjunction with acquisition through remote cameras and unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure condition assessment. The ultimate goal of such a system i...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eng.2018.11.030

Integrating Computer Vision: Advancements in Fire and Smoke Detection Using CNNs

Sanaz Janibeigi, Mahdi Bahaghighat, Zahra Yaghoubi, Nastooh Taheri Javan • CLEI Electronic Journal (2026)

Conventional fire detection systems, which depend on smoke and fire sensors, frequently have problems with calibration, susceptibility to environmental changes, and the requirement for ongoing maintenance. These flaws can result in unfavora...

DOAJ Open Access (DOAJ) DOI: 10.19153/cleiej.29.2.5

Artificial Intelligence in Healthcare: Advancing Innovation and Ethics to Foster Well-Being

Bayram B., Leventi N., Vodenicharova A., Lamprianidou A. et al. • Acta Medica Bulgarica (2026)

Artificial intelligence (AI) is reshaping healthcare by enhancing diagnostic precision, treatment personalization, and overall patient care. By leveraging technologies such as machine learning, deep learning, natural language processing, an...

DOAJ Open Access (DOAJ) DOI: 10.2478/amb-2026-0050

From Data to Decisions: AI in Varicose Veins—Predicting, Diagnosing, and Guiding Effective Management

Lakshmi Sree Pugalenthi, Chris Garapati, Srivarshini Maddukuri, Fnu Kanwal et al. • Journal of Vascular Diseases (2025)

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency a...

DOAJ Open Access (DOAJ) DOI: 10.3390/jvd4020019

HawkEye: AI-Driven Software for Objective Analysis and Characterization of Nodular Cast Iron Microstructures

Javier Nieves, Antonio Serena-Barriuso, Guillermo Elejoste-Rementeria • Applied Sciences (2025)

Metallographic evaluation of nodular cast iron is crucial for quality control in the foundry industry. Traditionally, this process relies on experts who visually interpret microscopic images. This study introduces HawkEye, a comprehensive s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15136991

Algoritms for determining the attitude position of an unmanned aerial vehicle relative to the landing platform by using computer vision

T. Yu. Gainutdinova, S. V. Novikova, V. G. Gainutdinov, M. V. Trusfus et al. • Вестник Самарского университета: Аэрокосмическая техника, технологии и машиностроение (2023)

Algorithms for determining the attitude position of an aircraft or helicopter-type unmanned aerial vehicle relative to the landing platform with special optical marks are considered. An assessment is made of the possibility of calculating t...

DOAJ Open Access (DOAJ) DOI: 10.18287/2541-7533-2023-22-4-37-51

Non-Destructive Monitoring of External Quality of Date Palm Fruit (<i>Phoenix dactylifera</i> L.) During Frozen Storage Using Digital Camera and Flatbed Scanner

Younes Noutfia, Ewa Ropelewska, Zbigniew Jóźwiak, Krzysztof Rutkowski • Sensors (2024)

The emergence of new technologies focusing on “computer vision” has contributed significantly to the assessment of fruit quality. In this study, an innovative approach based on image analysis was used to assess the external quality of fresh...

DOAJ Open Access (DOAJ) DOI: 10.3390/s24237560

Addressing practical challenge of using autopilot drone for asphalt surface monitoring: Road detection, segmentation, and following

Hormazd Ranjbar, Perry Forsythe, Alireza Ahmadian Fard Fini, Mojtaba Maghrebi et al. • Results in Engineering (2023)

According to the recent world bank report, around 80% of a life-cycle cost of a road is devoted to maintenance which includes monitoring and repair processes. To more effectively keep road serviceability, knowing the current status of road ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rineng.2023.101130

Evaluation of Indoor Thermal Environments Using a Novel Predicted Mean Vote Model Based on Artificial Neural Networks

Xiaosai Duan, Suihuai Yu, Jianjie Chu, Dengkai Chen et al. • Buildings (2022)

The assessment of indoor thermal environments is crucial to achieving thermal comfort and energy efficiency. However, the inaccurate evaluation and strong nonlinear variations of thermal comfort parameters limit engineering designs. Therefo...

DOAJ Open Access (DOAJ) DOI: 10.3390/buildings12111880

Surrogate Modeling of the Electric Field in the End-Winding Region of Pumped-Storage Generator Stators Based on Deep Neural Networks

Chunxu Qin, Yiran Ma, Huijuan Liang, Zhifan Wang et al. • Modelling (2026)

The end-winding insulation structure of stator windings in pumped-storage generator units is complex, with pronounced electric field concentration under out-of-phase conditions, making them critical concerns in insulation design and conditi...

DOAJ Open Access (DOAJ) DOI: 10.3390/modelling7050190

Predicting air quality index using artificial neural network: a case study of the Coimbatore region

P. Jagadesh, J. Harshini, D. Arul, Solomon Oyebisi et al. • Discover Civil Engineering (2026)

Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44290-026-00423-z