Recurrent neural networks for aerodynamic parameter estimation with Lyapunov stability analysis by Sara Mohan George, S. S. Selvi, J. R. Raol

“…The RNN-Gradient shows a 20% performance improvement over RNN-WB. Satisfactory simulation results from both algorithms provide a promising foundation for their potential applications to real flight test data.…”
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Approaches for Localizing the Origin of PVCs in the Outflow Tract: Future Perspectives and Challenges by Baiping Sui, Yingjie Ji, Ying Wang, Ling Gao, Minghao Li

“…To decrease human error and achieve more efficient PVC localization, algorithmic analysis and anatomical modeling with computer-based methods have emerged as promising new approaches. …”
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Emerging and Pioneering AI Technologies in Aesthetic Dermatology: Sketching a Path Toward Personalized, Predictive, and Proactive Care by Diala Haykal

“…Perspectives: Looking forward, the development of diverse, inclusive datasets and transparent, patient-centered AI models will be essential to ensure that AI’s benefits reach all patients equitably and safely. …”
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Beyond purchase patterns: harnessing predictive analytics to anticipate unarticulated consumer needs by Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Mansour

“…The results underscore the importance of integrating human-centered design with algorithmic precision to translate predictive insights into actionable business value.…”
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Water Quality Monitoring: A Water Quality Dataset from an On-Site Study in Macao by Jiawei Gao, Bochao Chen, Su-Kit Tang

“…Among these models, Random Forest exhibited the best overall performance, achieving an accuracy of 98.10% and an F1 score of 98.99%. …”
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Filtering Techniques To Reduce Speckle Noise And Image Quality Enhancement Methods On Porous Silicon Images Layers by Tifouti Issam, Rahmouni Salah, Meriane Brahim

“…In the case of digital images, noise can produce difficulties in the diagnosis of images details, such as edges and limits, should be preserved. Most algorithms can reduce or remove speckle noise, but they do not consider the conservation of these details. …”
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Lentil plant disease and quality assessment: A detailed dataset of high-resolution images for deep learning researchMendeley Data by Eram Mahamud, Md Assaduzzaman, Shayla Sharmin

“…The dataset aims to support the development of machine-learning models for precise disease detection and quality assessment in lentil cultivation. …”
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Dynamic Dwell Time Adjustment in Wire Arc-Directed Energy Deposition: A Thermal Feedback Control Approach by Md Munim Rayhan, Abderrachid Hamrani, Fuad Hasan, Tyler Dolmetsch, Arvind Agarwal, Dwayne McDaniel

“…Future work should focus on integrating multi-axis thermal sensors, extending the framework to multi-material deposition scenarios and implementing machine learning algorithms for predictive thermal modeling.…”
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Artificial Intelligence-based Rice Variety Classification: A State-of-the-art Review and Future Directions by Md. Masudul Islam, Galib Muhammad Shahriar Himel, Md. Golam Moazzam, Mohammad Shorif Uddin

“…The study examines key steps in the automation process, including image acquisition, pre-processing, feature extraction, and classification algorithms, with particular emphasis on machine learning and deep learning methods such as Convolutional Neural Networks (CNNs), which have demonstrated exceptional performance in recent research. …”
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Mammography reporting dataset with BI-RADS system for natural language processing applications: Addressing public data gaps in SpanishZENODO by José Luis Vázquez Noguera, Alejandro Torres-Hurtado, Helena Gómez-Adorno, Julio César Mello-Román, Enrique Javier Fleitas-Alvarez, Federico Fernando Espinola Schulze, Miguel Garcia-Torres, Carlos Domingo Méndez Gaona, Pedro Esteban Gardel Sotomayor, Silvia Vázquez Noguera, Norma Elizabeth Zaracho Amarilla, Oxades Wilfrido Gamarra Esquivel

“…It provides real-world data for developing and testing NLP algorithms and machine learning models, specifically for automating BI-RADS classification and analyzing mammography reports.…”
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One-Class Anomaly Detection for Industrial Applications: A Comparative Survey and Experimental Study by Davide Paolini, Pierpaolo Dini, Ettore Soldaini, Sergio Saponara

“…The article concludes with a discussion of additional strategies to enhance the runtime analysis of these algorithms, offering insights into potential future applications and improvement directions.…”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…This paper explores the application of Deep Reinforcement Learning (DRL) to optimize adaptive observation strategies for multi-AUV systems in complex marine environments. Traditional algorithms struggle with the strong coupling between environmental information and observation modeling, making it challenging to derive optimal strategies. …”
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Strategies and Challenges for Unmanned Aerial Vehicle-Based Continuous Inspection and Predictive Maintenance of Solar Modules by Ghulam E. Mustafa Abro, Amjad Ali, Sufyan Ali Memon, Tayab Din Memon, Faheem Khan

“…The choice to prioritize thermal and visual imaging above mathematical modeling or optimization algorithms arises from the necessity of delivering practical, scalable inspection solutions that can be readily implemented in the field. …”
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A Hybrid Automata-Driven Machine Learning Framework for Real-Time Energy Optimization in Smart Buildings by Rikame Rajashri, Ranjan Mritunjay Kr., Jadhav Monali, Wankhede Shrushti, Bankar Sakshi, Bachhav Pranjal

“…These inputs train the predictive models like Random Forest, XGBoost, LightGBM, and Neural Networks to predict energy requirements. …”
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Machine Learning-Based Detection of Archeological Sites Using Satellite and Meteorological Data: A Case Study of Funnel Beaker Culture Tombs in Poland by Krystian Kozioł, Natalia Borowiec, Urszula Marmol, Mateusz Rzeszutek, Celso Augusto Guimarães Santos, Jerzy Czerniec

“…The machine learning models, including logistic regression and decision tree-based algorithms, demonstrated strong potential for predicting site visibility. …”
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Applications of molecular dynamics in nanomaterial design and characterization - A review by Md. Aminul Islam, S M Maksudur Rahman, Juhi Jannat Mim, Safiullah Khan, Fardin Khan, Md. Ahadul Islam Patwary, Nayem Hossain

“…Recent advances, such as improved multiscale modeling and computational algorithms and real-time simulations, shed light onto MD processes of revolutionizing nanotechnology. …”
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer by Lu Cao, Ruimin He, Ao Zhang, Lingmei Li, Wenfeng Cao, Ning Liu, Peisen Zhang

“…Finally, patient-level artificial intelligence models were developed by integrating deep learning -generated pathology features with several machine learning algorithms. …”
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Challenges of manufacturing for energy efficiency: towards a systematic approach through applications of machine learning by Elaheh Gholamzadeh Nabati, Maria Teresa Alvela Nieto, Dennis Bode, Thimo Florian Schindler, André Decker, Klaus-Dieter Thoben

“…Essential applications and technical challenges for data mapping, integrating, modelling, implementing, and deploying machine learning algorithms in manufacturing processes for increasing energy efficiency are presented. …”
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On the issue of analysis of legal documents on information security of automated systems of internal affairs bodies of the Russian Federation to assess the level of their security by E. A. Rogozin, I. G. Drovnikova, A. O. Yefimov, V. R. Romanova

“…An analysis of international, Russian, as well as departmental legal documents on information security of the ATS of the Russian Federation showed that the documents on the protection of information of the ATS of the Russian Federation, as well as the methodology for quantifying the level of security of these systems, have been developed insufficiently, in particular, they are absent a system of indicators, as well as mathematical models and algorithms for assessing the level of security of the ATS of the Russian Federation, which requires significant improvement of these documents.…”
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Blind Recognition of Convolutional Codes Based on the ConvLSTM Temporal Feature Network by Lu Xu, Yixin Ma, Rui Shi, Juanjuan Li, Yijia Zhang

“…Our method effectively distinguishes diverse coding features, surpassing existing models and establishing a new benchmark for channel-coding recognition.…”
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