Novel Computer Software for Interpolation and Approximation of Ravine and Stiff Digital Dependencies Using Root-Polynomoal and Root-Fractional-Rational Functions by Igor Melnyk, Mykhailo Skrypka, Alina Pochynok, Olga Demyanchenko

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Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review by Masoud Tafavvoghi, Lars Ailo Bongo, Nikita Shvetsov, Lill-Tove Rasmussen Busund, Kajsa Møllersen

“…In this scoping review, we identified the publicly available datasets of breast H&E-stained whole-slide images (WSIs) that can be used to develop deep learning algorithms. We systematically searched 9 scientific literature databases and 9 research data repositories and found 17 publicly available datasets containing 10 385 H&E WSIs of breast cancer. …”
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Enhancing blockchain transaction classification with ensemble learning approaches by Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Rourab Paul, Ajit Kumar Nayak, Subrata Chowdhury, Ramya Govindaraj, J Shreyas

“…Various ML classification algorithms are applied to the selected features from two ensemble feature selection algorithms as the base learners to make initial predictions. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Abstract This research proposes a novel framework for enhancing heart disease prediction using a hybrid approach that integrates classical and quantum-inspired machine learning techniques. …”
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Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…Sentiment-based movie recommendation system research employs techniques such as natural language processing and hybrid models with the goal of increasing user satisfaction. …”
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Drone-based fault recognition in power systems: a systematic review of intelligent methods by Carlos A. F. Persiani, Felipe M. Sallazar, Roberto S. Inoue, Valdir Grassi, Marco H. Terra, Mário Oleskovicz

“…The identification of literature gaps and future research directions reveals the path for further exploration, including the need for more robust algorithms to improve fault detection accuracy, techniques to mitigate the impact of blurred images, methods for detecting multiple faults simultaneously, advancements in real-time processing, increased automation for field deployment, and the development of more comprehensive and diverse datasets.…”
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A systematic review of machine learning and deep learning approaches in plant species detection by Deepti Barhate, Sunil Pathak, Bhupesh Kumar Singh, Amit Jain, Ashutosh Kumar Dubey

“…In this article, we presented a systematic review of effective machine learning methods and image processing and deep learning algorithms for plant species recognition that have been used by researchers. …”
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Systematic review on effective positive coping-based interventions in teachers by Eduardo-Andrés Torres-Santos, José Albeiro Tamara-Uribe, Marcela Flórez Romero, Gabriela Sequeda, Diego Rivera-Porras

“…A search strategy was created with algorithms and DECS and MESH terms, combining logical operators and symbols. …”
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Prospects for Legal Regulation of Quantum Communication by A. Minbaleev, S. Zenin, K. Evsikov

“…The analysis showed that a significant number of states and interstate associations are conducting research in this area, relying only on investment growth. …”
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Solar FaultNet: Advanced Fault Detection and Classification in Solar PV Systems Using SwinProba‐GeNet and BaBa Optimizer Models by Praveen Kumar Balachandran, Muhammad Ammirrul Atiqi Mohd Zainuri, Faisal Alsaif

“…However, most of the existing research studies related to fault detection methods have suffered from low accuracy, higher error rates, and time‐consuming processes when dealing with complex fault types in real‐time. …”
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Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…These findings underscore the necessity of intelligent fire detection systems in high-occupancy venues, demonstrating that AI-based predictive modeling can drastically improve fire response and evacuation efficiency. Future research should focus on integrating IoT-enabled emergency navigation, reinforcement learning algorithms, and real-time crowd management systems to further enhance predictive accuracy and minimize casualties. …”
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Artificial intelligence for severity triage based on conversations in an emergency department in Korea by Jae Won Seo, Sung-Joon Park, Young Jae Kim, Jung-Youn Kim, Kwang Gi Kim, Young-Hoon Yoon

“…To achieve this, artificial intelligence algorithms that consider the frequency and order of words used in the conversation were employed alongside neural network models. …”
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APPLICATION OF ARTIFICIAL NEURON NETWORK AND FUZZY INFERENCE IN THE HOUSEPLANT WATERING INTELLIGENT SYSTEM by Roman Korostenskyi, Igor Olenych

“…Consequently, the development of hardware and software tools for such systems represents a pertinent area of research in the field of smart solutions. Materials and Methods. …”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…This research highlights the transformative potential of machine learning in public sector workforce management, underscoring the role of data-driven decision-making in improving task allocation, operational efficiency, and resource utilization.…”
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The effects of limb position and grasped load on hand gesture classification using electromyography, force myography, and their combination. by Peyton R Young, Kihun Hong, Eden J Winslow, Giancarlo K Sagastume, Marcus A Battraw, Richard S Whittle, Jonathon S Schofield

“…A prominent control technique employs surface electromyography (EMG) and pattern recognition algorithms to identify specific patterns in muscle electrical activity and translate these to device commands. …”
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Corrupted Point Cloud Classification Through Deep Learning with Local Feature Descriptor by Xian Wu, Xueyi Guo, Hang Peng, Bin Su, Sabbir Ahamod, Fenglin Han

“…The experimental results show that our model outperforms existing popular algorithms when dealing with corrupted point cloud data. …”
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Fighting Evaluation Inflation: Concentrated Datasets for Grammatical Error Correction Task by Vladimir Starchenko, Darya Kharlamova, Elizaveta Klykova, Anastasia Shavrina, Aleksey Starchenko, Olga Vinogradova, Olga Lyashevskaya

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Contribution of hydrogeological, well logs and machine learning in predicting the aquifer hydraulic properties in arid regions: a case study of Nubian Sandstone aquifer, Farafra Oa... by Ahmed Nosair, Muhammad Nabih, Ahmed Bakry

“…While neutron density logs are commonly used for porosity estimation, our study uniquely employs resistivity logs to calculate porosity due to the scarcity of recorded logs in groundwater exploration. Consequently, this research aims to use conventional well log and hydrogeological data to predict T, K, and PHIE using machine learning (ML) algorithms, including random forest (RF), gradient boosting (GB), linear regression (LR), and support vector machines (SVM). …”
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Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling by Pimolkan Piankitrungreang, Kantawatchr Chaiprabha, Worathris Chungsangsatiporn, Chanat Ratanasumawong, Peemdej Chancharoen, Ratchatin Chancharoen

“…By integrating big data concepts and intelligent algorithms, the system supports continuous monitoring, anomaly detection, and process optimization. …”
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Range and angle estimation with spiking neural resonators for FMCW radar by Nico Reeb, Javier Lopez-Randulfe, Robin Dietrich, Alois C Knoll

“…Yet, most sensor systems, such as radars, do not produce suitable data for further neuromorphic processing of the data. This research presents a novel spiking neuron model for signal processing of frequency-modulated continuous wave (FMCW) radars that outperforms the state-of-the-art spectrum analysis algorithms in latency and data bandwidth. …”
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