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Automation of Structural Health Monitoring for Civil Infrastructures Using AI and ML

This review explores the critical role of image-processing technologies in structural health monitoring (SHM) for civil infrastructures. It highlights the integration of artificial intelligence (AI) and machine learning (ML) to enhance SHM automation and accuracy. Various imaging modalities, including drones, thermography, LiDAR, and satellite imagery, are discussed for damage detection, crack identification, and deformation monitoring.

23 Apr 2024

Carrot Quality Assessment Using Hyperspectral Imaging and Multivariate Analysis

Through hyperspectral imaging (HSI) and multivariate analysis, researchers accurately predicted pH and carotenoid content in carrots, crucial for nutritional assessment. Models utilizing partial least squares regression (PLSR) and least squares support vector machine (LS-SVM) showed LS-SVM's superiority in pH prediction and carotenoid content, offering a promising approach for internal quality evaluation in carrots.

22 Apr 2024

Automated Detection of Epiretinal Membranes in OCT Scans

Researchers developed a deep neural network (DNN) ensemble to automatically detect and classify epiretinal membranes (ERMs) in optical coherence tomography (OCT) scans of the macula. Leveraging over 11,000 images, the ensemble achieved high accuracy, particularly in identifying small ERMs, aided by techniques like mixup for data augmentation and t-stochastic neighborhood embeddings (t-SNE) for dimensional reduction.

20 Apr 2024

Machine Learning Analysis of Urban Residential Water Consumption in Developing Countries

Researchers employed machine learning techniques to analyze residential water consumption patterns in Adama City, Ethiopia, highlighting factors influencing water usage. Findings emphasized low per capita usage rates and the need for infrastructure improvements. ML models identified key determinants and suggested targeted interventions for promoting water conservation and sustainability.

16 Apr 2024

Integrated Machine Learning for Enhancing Footing Stability Prediction in Shallow Foundations

Researchers introduced two novel predictive models employing metaheuristic algorithms, Backtracking Search Algorithm (BSA) and Equilibrium Optimizer (EO), combined with artificial neural networks (ANNs) to assess the bearing capacity of footings on two-layered soil masses. Both BSA-ANN and EO-ANN models demonstrated improved prediction accuracy over conventional ANN models, with EO exhibiting superior performance.

16 Apr 2024

Dynamic Bayesian Network Structure Learning with Improved Bacterial Foraging Optimization Algorithm

Researchers introduced an Improved Bacterial Foraging Optimization Algorithm (IBFO-A) to enhance Dynamic Bayesian Network (DBN) structure learning, addressing issues of search space complexity and reduced accuracy. The proposed IBFO-D method combined dynamic K2 scoring, V-structure orientation, and elimination-dispersal strategies, showcasing improved efficiency, accuracy, and stability in engineering applications.

16 Apr 2024

Emergency Communication with UAVs: ISATR Algorithm Optimization

Researchers propose the ISATR algorithm to optimize trajectory planning and resource allocation for UAV-assisted emergency communication. By employing cellular automata for user trajectory prediction and iterative scheduling, the algorithm effectively enhances communication quality in disaster scenarios like earthquakes.

15 Apr 2024

Remote Homologous Protein Detection Using Protein Language Model Search

Researchers introduced Protein Language Model Search (PLMSearch), a method designed to improve sensitivity and accuracy in detecting remote homologous proteins. Leveraging deep representations from a pre-trained protein language model, PLMSearch effectively identifies evolutionary relationships solely based on sequence information.

12 Apr 2024

Using AI and Satellite Imagery to Predict Citizen Deprivation Perception

Researchers leverage AI and earth observation techniques to predict citizen perceptions of deprivation in Nairobi's slums. Combining satellite imagery and citizen science, their methodology accurately forecasts deprivation, offering policymakers invaluable insights for targeted interventions aligned with Sustainable Development Goal 11, potentially benefiting millions worldwide.

10 Apr 2024

Innovative Modeling and Navigation for Deformable-Wheeled Robots

Researchers introduce a groundbreaking parameterized water-bomb wheel modeling method and multi-link supporting structure, enhancing precision and reducing workload in rescue robotics. Their approach integrates IMU-fused odometry and parametric kinematic solutions, achieving high-precision navigation with minimal error rates, validated in both simulation and real environments.

9 Apr 2024

Optimizing Thermoelectric Properties with Bayesian Optimization

This study harnesses Bayesian optimization (BO) to enhance the thermoelectric properties of multicomponent III–V materials. Through iterative cycles of thin-film deposition, property measurements, and BO recommendations, the research achieves notable improvements in thermoelectric performance, underscoring the effectiveness of machine learning-driven optimization.

9 Apr 2024

Enhanced Vision SLAM for Wheeled Robots

Researchers unveil IMS-VSLAM, an advanced algorithm blending visual and inertial sensors to bolster wheeled robot navigation in low-texture environments. With superior accuracy and real-time performance, it marks a significant leap in robotic autonomy and efficiency.

7 Apr 2024

Innovative YOLO Algorithm Boosts PCB Defect Detection

Researchers from China introduce CDI-YOLO, an algorithm marrying coordination attention with YOLOv7-tiny for swift and precise PCB defect detection. With superior accuracy and a balance between parameters and speed, it promises efficient quality control in electronics and beyond.

7 Apr 2024

Random Forest Models to Enhance Real Estate Tax Compliance

Researchers detail advancements in using Random Forest (RF) models to pinpoint tax risks within real estate, providing insights into discrepancies between declared values and model judgments. By meticulously selecting indicators and leveraging historical data, the RF model emerges as a robust tool for tax risk identification, offering decision support for tax authorities and promoting improved compliance levels within the real estate industry.

4 Apr 2024

Digital Twins in Industry: Theory, Technology, and Challenges

This study provides an in-depth exploration of the advancements, challenges, and future prospects of digital twins in various industrial applications. It covers the theoretical frameworks, technological implementations, and practical considerations essential for understanding and leveraging digital twins effectively across different sectors.

3 Apr 2024

Enhanced Land Cover Classification in Remote Sensing

Chinese researchers introduce a groundbreaking deep inverse convolutional neural network approach tailored for land cover remote sensing images. This novel method effectively addresses data imbalance, significantly improving classification accuracy and precision, with potential applications in urban planning, agriculture, and environmental monitoring.

2 Apr 2024

Smart Libraries: IoT and SDN Revolution

Researchers introduced a cost-effective IoT-based architecture using SDN for smart libraries, enhancing efficiency and reducing operational costs significantly. By integrating RFID and SDN technologies, the system automated processes, improved accuracy, and showcased scalability for modernizing library operations.

1 Apr 2024

Deep Learning for Real-time Safety Helmet Detection

Researchers in a Scientific Reports paper propose BiFEL-YOLOv5s, an advanced deep learning model, for real-time safety helmet detection in construction settings. By integrating innovative techniques like BiFPN, Focal-EIoU Loss, and Soft-NMS, the model achieves superior accuracy and recall rates while maintaining detection speed, offering a robust solution for safety monitoring in complex work environments.

1 Apr 2024

Brewing Innovation: Machine Learning Enhances Beer Flavor

This study delves into the utilization of machine learning techniques to predict and enhance the flavor of beer, based on its intricate chemical properties, aiming to tailor brews to consumer preferences. By integrating vast datasets encompassing chemical properties, sensory attributes, and consumer feedback, researchers developed accurate predictive models, offering promising avenues for personalized beer variants and enhanced consumer satisfaction.

1 Apr 2024

Hybrid Detection Algorithms Enhance 5G Healthcare Latency

This study introduces innovative hybrid detection algorithms aimed at reducing latency in 5G/B5G communication for smart healthcare in rural regions. By combining QR decomposition with advanced detection techniques, such as QRM-MLD-MMSE and QRM-MLD-ZF, the study achieves significant improvements in latency, throughput, and bit error rate (BER) performance, demonstrating the feasibility of enhancing smart healthcare connectivity in underserved areas

1 Apr 2024