Clinical diagnosis of conjunctival microcirculation in hypertensive patients using shadowless imaging optical technology based on artificial intelligence by SONG Tianli, LI Haixia, LIU Li’an

Get full text

Using Convolutional Neural Networks for Segmentation of Multiple Sclerosis Lesions in 3D Magnetic Resonance Imaging by Abdulsattar Abdullah Hamad, Mustafa Musa Jaber, Mohammed Altaf Ahmed, Ghaida Muttashar Abdulsahib, Osamah Ibrahim Khalaf, Zelalem Meraf

Get full text

South-Oriented PV Trackers: A Solution for Tree Plantations? by Jean-Baptiste Pasquier, Jules Chéron, Farida Amichi

“…We propose innovative tracking algorithms to mitigate shading effects during different seasons, preserving both electrical output and agricultural productivity. …”
Get full text

Two-Dimensional Numerical Method for Predicting the Resistance of Ships in Pack Ice: Development and Validation by Yan Huang, Ce Sun, Jianqiao Sun

“…This study lays a solid foundation for future research on autonomous ship navigation in pack ice.…”
Get full text

Fault Diagnosis of Wind Turbine Gearbox Based on Mel Spectrogram and Improved ResNeXt50 Model by Xiaojuan Zhang, Feixiang Jia, Yayu Chen

“…Through comparison with classical algorithms, we demonstrated that the research method proposed in this study exhibits better diagnostic capability in classifying wind turbine gearbox sound signals.…”
Get full text

An Autonomous Vehicle Behavior Decision Method Based on Deep Reinforcement Learning with Hybrid State Space and Driving Risk by Xu Wang, Bo Qian, Junchao Zhuo, Weiqun Liu

“…Finally, the effectiveness of the proposed method is proved by training verification in different simulation scenarios, and the results show that the proposed method can enable autonomous vehicles to make safe and efficient behavior decisions in complex driving environments. Compared with advanced algorithms, the method proposed in this paper improves the driving distance of autonomous vehicle by 3.3%, the safety by 2.1%, and the calculation time by 43% in the experiment.…”
Get full text

Advanced Ai Tools for Predicting Mechanical Properties of Self-Compacting Concrete by AGRAWAL Achal, CHANDAK Narayan

Get full text

Load Probability Density Forecasting Under FDI Attacks Based on Double-Layer LSTM Quantile Regression by Pei Zhao, Jie Zhang, Guang Ling

“…The final results show that the proposed model has a 1.13 and 0.26 reduction in MAPE and MSE compared to the original LSTM. According to our research, the suggested model can successfully describe future power systems full of possible risks and uncertainties with great accuracy.…”
Get full text

TSCAPE: time series clustering with curve analysis and projection on an Euclidean space by Jeremy Renaud, Raphaël Couturier, Christophe Guyeux, Benoit Courjal

“…The methodology exhibits significant potential for diverse applications, accommodating varied data types and irregular time series shapes. The research compares multiple variants and proposes metrics to assess their effectiveness on two open-access datasets. …”
Get full text

Can Ai Revolutionize Qspr Models for the Chemical Mixtures Hazards? by Guillaume Fayet, Nour Helou, Patricia Rotureau

“…To this end, applications of different machine learning methods were tested to evidence the advantages and limits of these Advanced AI algorithms compared to the more classical MLR approach when developing models for the flammability of liquid mixtures.…”
Get full text

Diabetes diagnosis using a hybrid CNN LSTM MLP ensemble by Yanmin Fan

“…To diagnose sickness, the MLP model serves as a meta-learner to combine and convert the data from the two feature extraction algorithms into the target variable. According to the implementation results, the suggested approach outperformed the compared approaches in terms of average accuracy and precision, achieving 98.28% and 0.99%, respectively, indicating a very great capacity to identify diabetes.…”
Get full text

6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
Get full text

Dataset creation of thermal images of pomegranate for internal defect detectionMendeley Data by Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole

“…Datasets are crucial in various fields, especially in the context of machine learning, data science and research. Datasets are used to train machine learning models. …”
Get full text

Filtering Techniques To Reduce Speckle Noise And Image Quality Enhancement Methods On Porous Silicon Images Layers by Tifouti Issam, Rahmouni Salah, Meriane Brahim

“…Furthermore, the description of these techniques facilitates the operations of evaluations and research with a more specific scope. This study initially covers the definition and modeling of speckle noise. …”
Get full text

Enhanced AODV routing analysis for mobile Ad Hoc networks by Arvind Kumar, Adesh Kumar, Anurag Vijay Agrawal

“…Conventional routing algorithms such as ad-hoc on-demand distance vector (AODV) frequently struggle with hardware inefficiencies and increase overhead in large-scale networks. …”
Get full text

Developing Computer Vision Models for Classifying Grain Shapes of Crushed Stone by Alexey N. Beskopylny, Evgenii M. Shcherban’, Sergey A. Stel’makh, Alexandr A. Shilov, Irina Razveeva, Diana Elshaeva, Andrei Chernil’nik, Gleb Onore

“…The utilization of modern technologies enables us to enhance building processes to a new quality level, decreasing the construction pace without precision losses compared to traditional methods. This research introduces a novel method for characterizing crushed stone grain morphology using the application of specially designed three-dimensional computer vision neural networks to point data clouds. …”
Get full text

Optimization Design of Space Camera Enclosure Based on Bionics by Hongyu Li, Fu Li, Zhihua Zhao, Janfeng Yang, Juan Lv

“…This offers a novel approach for research in this field.…”
Get full text

Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

Get full text

A Review of Abnormal Crowd Behavior Recognition Technology Based on Computer Vision by Rongyong Zhao, Feng Hua, Bingyu Wei, Cuiling Li, Yulong Ma, Eric S. W. Wong, Fengnian Liu

“…Secondly, typical abnormal behavior datasets at home and abroad are sorted out, and the characteristics of these datasets are compared in detail from multiple perspectives such as scale, characteristics, and uses, and the performance indicators of different algorithms on the datasets are compared and analyzed. …”
Get full text

A novel machine learning models for meteorological drought forecasting in the semi-arid climate  region by Chaitanya Baliram Pande, Dinesh Kumar Vishwakarma, Aman Srivastava, Kanak N. Moharir, Fahad Alshehri, Norashidah Md Din, Lariyah Mohd Sidek, Bojan Đurin, Abebe Debele Tolche

“…Given the limited studies on ensemble and Machine Learning (ML) models for drought forecasting, this research compares five ML models [Robust Linear Regression, Bagged Trees, Boosted Trees, Support Vector Machine (SVM), and Matern Gaussian Process Regression (GPR)] to determine superior accuracy in the regional context. …”
Get full text