Performance Evaluation of Neighbors-Based Learning Methods for Network Intrusion Detection System by Ngoc Thien Nguyen

“…One of the effective approaches in this field is Neighbor-Based Learning models, a group of ML algorithms that have proven useful in identifying malicious behavior in network traffic. …”
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A review of flexible robotic gripping systems by Bahadir Tarhan, Seemal Asif, Phil Webb, Marco Chacin

“…It further explores the spectrum of actuation mechanisms that empower these grippers, from traditional electric and pneumatic systems to cutting-edge soft robotics technologies that offer unprecedented adaptability and safety. The integration of sensors within grippers, enhancing their intelligence and autonomy, is also scrutinized, alongside a critical evaluation of control strategies that range from conventional PID controllers to sophisticated machine learning algorithms. …”
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Application of federated learning in predicting breast cancer by Chai Jiarui

“…Subsequently, each participant then sends the updated model parameters to the central server, where the FedAvg algorithm combines them to produce a global model. …”
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Accuracy and clinical effectiveness of risk prediction tools for pressure injury occurrence: An umbrella review. by Bethany Hillier, Katie Scandrett, April Coombe, Tina Hernandez-Boussard, Ewout Steyerberg, Yemisi Takwoingi, Vladica M Veličković, Jacqueline Dinnes

“…Only 2/19 (11%) SRs performed appropriate statistical synthesis and quality assessment. Two SRs assessing machine learning-based algorithms reported high prognostic accuracy estimates, but some of which were sourced from the same data within which the models were developed, leading to potentially overoptimistic results. …”
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Single-Cell Transcriptomics Unveils the Mechanistic Role of FOSL1 in Cutaneous Wound Healing by Jingbi Meng, Ge Zheng, Yinli Luo, Ling Ge, Zhiqing Liu, Wenhua Huang, Meitong Jin, Yanli Kong, Shanhua Xu, Zhehu Jin, Longquan Pi

“…Subsequently, we constructed Protein–Protein Interaction (PPI) networks via the STRING database. Machine learning algorithms were instrumental in identifying pivotal genes, a finding corroborated through animal modeling and Western blot analysis of tissue samples. …”
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Opportunities and Challenges of Brain-on-a-Chip Interfaces by Wenwei Shao, Weiwei Meng, Jiachen Zuo, Xiaohong Li, Dong Ming

“…Functionally, BoCIs offer a novel framework for hybrid intelligence, merging the cognitive capabilities of biological systems (e.g., learning and memory) with the computational efficiency of machines. However, critical challenges span 4 domains: optimizing neural maturation and functional regionalization, engineering high-fidelity bioelectronic interfaces for robust signal transduction, enhancing adaptive neuroplasticity mechanisms in lab-grown brains, and achieving biophysically coherent integration with artificial intelligence architectures. …”
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Automotive navigation for mobile robots: Comprehensive review by Mayar Abdullah Taleb, Gyula Korsoveczki, Géza Husi

“…This paper will give special attention to algorithms incorporating machine learning and real-time data analysis to manage dynamic obstacles better; also, it will explore the adaptability and scalability of these algorithms in simulated environments of varying complexity and size, preparing them for real-world applicability. …”
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Deriving and applying core competencies for intellectual property-based startup entrepreneurs: a data-driven approach to technology evaluation by Wongyu Lee, Jaeho Shin, Donghee Yoo

“…., the Delphi method and expert workshops), alongside machine learning algorithms to derive the key competencies. …”
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Artificial Intelligence Applied on Traffic Planning and Management for Rail Transport: A Review and Perspective by Jiamin Zhang, Jiarui Zhang

“…While many promising applications have been reported, there remains a lack of detailed review of the many AI models/algorithms and their uses and adaptations in rail TPM. …”
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Optimized window functions for spectral analysis based on digital filters by R.V. Petrosian

“…The proposed approach also shows promising potential for further development through the integration of machine learning techniques and heuristic algorithms, enabling automatic tuning of window parameters depending on analysis conditions.…”
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Design of intelligent English translation teaching system combined with bidirectional encoder representation by Shanshan Xu

“…In addition, the system integrates machine learning algorithms that analyze students' learning habits and error patterns to provide customized exercises and tutoring. …”
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Service Function Chain Migration: A Survey by Zhiping Zhang, Changda Wang

“…While machine learning enhances adaptability, it encounters limitations in data dependency and real-time performance. …”
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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…The study proposes 25 heuristic algorithms for real-time dynamic scheduling with machine eligibility restrictions. …”
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Implementation of automation tools for test analysis in the Radiotherapy Quality Assurance Programs by João Guilherme Rivera Santiago, Laura Furnari, Marcus Vinicius Saad de Paula Rodrigues, Victor Augusto Bertotti Ribeiro

“…The findings highlight the importance of conducting studies during the implementation phase of such tools to understand the algorithms used and establish appropriate usage and control measures for routine practice. …”
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Long duration multi-channel surface electromyographic signals during walking at natural pace: Data acquisition and analysis. by Francesco Di Nardo, Christian Morbidoni, Grazia Iadarola, Susanna Spinsante, Sandro Fioretti

“…The considerable duration of the signals makes this dataset particularly useful for studies where a significant volume of data is crucial, such as machine/deep learning approaches, investigations examining the variability of muscle recruitment during physiological walking, validations of the reliability of novel sEMG-based algorithms, and assembly of reference datasets for pathological condition characterization.…”
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Developing a Non-Invasive Intelligent System for Blood Glucose Level Estimation Using Reflective Optical Sensors by Mihaela MARIN, Teodora Alexandra DOBRIN, Florin Bogdan MARIN

“…Future developments may incorporate advanced optical sensors such as NIR spectroscopy or Raman technologies, alongside machine learning algorithms, to improve accuracy and extend functionality. …”
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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…Our approach not only fills a gap in current ensemble regression techniques but also provides a reliable and adaptable method for boosting prediction performance in various machine learning tasks. …”
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Development of a robust FT-IR typing system for Salmonella enterica, enhancing performance through hierarchical classification by Diego Fredes-García, Javiera Jiménez-Rodríguez, Alejandro Piña-Iturbe, Pablo Caballero-Díaz, Tamara González-Villarroel, Fernando Dueñas, Aniela Wozniak, Aiko D. Adell, Andrea I. Moreno-Switt, Patricia García

“…The IR Biotyper was used to acquire spectra from these isolates. Machine learning algorithms, including support vector machines, were trained to classify the isolates. …”
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Reinforcement Learning for Autonomous Process Control in Industry 4.0: Advantages and Challenges by Nuria Nievas, Adela Pagès-Bernaus, Francesc Bonada, Lluís Echeverria, Xavier Domingo

“…In recent years, the integration of intelligent industrial process monitoring, quality prediction, and predictive maintenance solutions has garnered significant attention, driven by rapid advancements in digitalization, data analytics, and machine learning. As traditional production systems evolve into self-aware and self-learning configurations, capable of autonomously adapting to dynamic environmental and production conditions, the significance of reinforcement learning becomes increasingly apparent. …”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…Compared with the traditional hydraulic calculation modified (THCM) models and other machine learning algorithms, the PSO-GWO-BP model has significant advantages in prediction accuracy. …”
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