HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…However, both conventional field monitoring and machine learning algorithms remain challenged in achieving rapid and accurate detection. …”
Get full text

Artificial intelligence‐enabled innovations in cochlear implant technology: Advancing auditory prosthetics for hearing restoration by Guodao Zhang, Rui Chen, Hamzeh Ghorbani, Wanqing Li, Arsen Minasyan, Yideng Huang, Sen Lin, Minmin Shao

“…The review emphasizes how advanced AI algorithms and data‐driven approaches enhance CI adaptability and functionality, enabling personalized rehabilitation strategies and improving speech enhancement. …”
Get full text

Evaluation of machine learning techniques for real-time prediction of implanted lower limb mechanics by Chase Maag, Clare K. Fitzpatrick, Paul J. Rullkoetter

“…Several predictive algorithms were explored, including linear regression (LRM), multilayer perceptron (MLP), bi-directional long short-term memory (biLSTM), convolutional neural network (CNN), and transformer-based approaches. …”
Get full text

Demonstration of 4 <inline-formula> <tex-math notation="LaTeX">$\times$</tex-math></inline-formula> 128-Gb/s DFT-S OFDM Signal Transmission over 320-km SMF With IM/DD by Yuanquan Wang, Jianjun Yu, Nan Chi

“…Meanwhile, a combination of advanced digital signal processing (DSP) algorithms, such as pre-equalization, nonlinearity equalization (NE), and decision-directed least mean square (DDLMS), are utilized to mitigate the system distortions and improve system performance. …”
Get full text

Integrating dimension reduction and out-of-sample extension in automated classification of ex vivo human patellar cartilage on phase contrast X-ray computed tomography. by Mahesh B Nagarajan, Paola Coan, Markus B Huber, Paul C Diemoz, Axel Wismüller

“…However, the large size of feature sets extracted in such studies motivates an investigation into algorithmic feature reduction for computing efficient feature representations without compromising their discriminatory power. …”
Get full text

Event recognition technology and short-term rockburst early warning model based on microseismic monitoring and ensemble learning by Zibin Li, Dengpan Qiao, Tianyu Yang, Jun Wang, Hao Chen

“…The rockburst early warning model V-soft achieves peak accuracy and F1 scores of 0.9394 and 0.9173, respectively, demonstrating performance improvements of 6.59–15.68% in accuracy and 14.11–27.21% in F1 score compared to conventional machine learning algorithms and ensemble classifiers. …”
Get full text

Advancements in Retinal Tissue-Mimicking Optical Coherence Tomography Phantoms: Materials, Properties, and Applications by Mukhit Kulmaganbetov

“…Optical coherence tomography (OCT) phantoms are essential tools for calibrating imaging systems, validating diagnostic algorithms, and bridging technological advancements with clinical applications. …”
Get full text

Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

“…The investigation utilized a range of machine learning algorithms, such as random forest, support vector machine (SVM), XGBoost, CatBoost, and LightGBM, to develop models. …”
Get full text

Comprehensive flexible framework for using multi-machine learning methods to optimal dynamic transient stability prediction by considering prediction accuracy and time by Ali Abdalredha, Alireza Sobbouhi, Abolfazl Vahedi

“…This paper presents a flexible framework for using the desired number of ML algorithms and combines the results of them to extract the final optimal transient stability perdition (TSP). …”
Get full text

STRATEGIC MANAGEMENT OF THE ECONOMIC SUSTAINABILITY OF A COMPANY IN THE PARADIGM OF FUZZY LOGIC by Yu. A. Malyukov, A. O. Nedosekin, Z. I. Abdoulaeva

“…It is necessary to develop optimal algorithms for managing economic systems under adverse effects (AE) of a natural, technological, or military nature. …”
Get full text

Predicting fertilizer treating of maize using digital image processing and deep learning approaches by Eshete Derb Emiru, Kassie Bishaw

“…A Convolutional Neural Network (CNN) with VGG16 and VGG19 architectures, along with a SoftMax classifier, was employed to analyze and classify the images into eight distinct categories based on their characteristics. …”
Get full text

Countermeasuring Anti-Ship Missiles for Surface Naval Platforms: A Machine Learning Approach With Explainable Artificial Intelligence by Murat Ertop, Ali Oter, Ali Kara

“…Chaffs and flares can be launched from naval platforms as soft-kill countermeasures to address such threats within the context of conflict. …”
Get full text

Sentiment analysis of pilgrims using CNN-LSTM deep learning approach by Aisha Alasmari, Norah Farooqi, Youseef Alotaibi

“…The generated feature maps are passed to the SoftMax layer to classify final outputs. The proposed model is applied to a real case study of issues related to pre-prepared food at Hajj 1442. …”
Get full text

Jet substructure probe on scalar leptoquark models via top polarization by Anupam Ghosh, Partha Konar, Tousik Samui, Ritesh K. Singh

“…To enhance the efficacy of the analysis, we employ jet substructure techniques like Soft Drop, N-subjettiness, and our custom b-tagging method, along with other event variables. …”
Get full text

Intelligent Recognition and Automated Production of Chili Peppers: A Review Addressing Varietal Diversity and Technological Requirements by Sheng Tai, Zhong Tang, Bin Li, Shiguo Wang, Xiaohu Guo

“…., robotic systems incorporating diverse end-effectors like soft grippers or cutting mechanisms and motion planning algorithms such as RRT) as well as seed cleaning/separation techniques and simulations (e.g., CFD and DEM) for equipment optimization. …”
Get full text

Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification by Brindha Subburaj, Rohan M, Samhruth Ananthanarayanan, Daehan Won

“…Most computerized methods involve some form of Deep Learning algorithms and models to automate the detection process. …”
Get full text

Blind Remote Sensing Image Deblurring Based on Local Maximum High-Frequency Coefficient Prior and Graph Regularization by Zhidan Cai, Ming Fang, Zhe Li, Jinyi Ming, Huimin Wang

“…In satellite remote sensing imaging, factors such as optical axis shift, image plane jitter, movement of the target object, and Earth&#x0027;s rotation can induce image blur. …”
Get full text

The Gut Microbiota and Colorectal Cancer: Understanding the Link and Exploring Therapeutic Interventions by Imen Zalila-Kolsi, Dhoha Dhieb, Hussam A. Osman, Hadjer Mekideche

“…The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. …”
Get full text

A Novel Logarithmic Approach to General Relativistic Hydrodynamics in Dynamical Spacetimes by Mario Imbrogno, Rita Megale, Luca Del Zanna, Sergio Servidio

“…This method employs a “3 + 1” decomposition of spacetime, complemented by the “1 + log” slicing condition and Gamma-driver shift conditions, which have been shown to improve numerical stability in spacetime evolution. …”
Get full text

Designing a sustainable and resilient agri-food closed-loop supply chain network for porcine products by Álvaro Ronaldo Elizalde Camacho, Fatemeh Gholian-Jouybari, Behzad Mosallanezhad, Neale R. Smith, Mostafa Hajiaghaei-Keshteli

“…In 86 % of numerical tests, the H_KASA outperforms other proposed algorithms in terms of objective function value. Sensitivity analysis reveals that production capacity and customer demand have a significant impact on supply chain costs, leading to a shift of over 20 % when either parameter increases by 50 %. …”
Get full text