Harnessing Machine Learning for Intelligent Networking in 5G Technology and Beyond: Advancements, Applications and Challenges by Kristi Dulaj, Abdulraqeb Alhammadi, Ibraheem Shayea, Ayman A. El-Saleh, Mohammad Alnakhli

“…This research investigates ML approaches in 5G networks for adaptive spectrum usage, quality of service (QoS) management, predictive maintenance, and network optimization. By leveraging ML algorithms, 5G networks can forecast user behavior, allocate resources optimally, and dynamically adjust to changing conditions, enhancing performance and dependability. …”
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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…The model uses a wrapper-based feature selection technique using machine learning algorithms to select the best features, which are then combined and fed into a Multi-Head Attention-based transformer for getting the predictions. …”
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Honeybee Colony Growth Period Recognition Based on Multivariate Temperature Feature Extraction and Machine Learning by Chuanqi Lu, Lin Li, Denghua Li, Qiuying Huang, Wei Hong

“…Finally, six machine learning algorithms, including both supervised and unsupervised learning, were utilized to identify the growth period of bee colonies. …”
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The Machine Learning-Based Task Automation Framework for Human Resource Management in MNC Companies by Suchitra Deviprasad, N. Madhumithaa, I. Walter Vikas, Archana Yadav, Geetha Manoharan

“…MNCs are now beginning to use ML algorithms in combination with Artificial Intelligence (AI) to streamline the HR processes. …”
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Comprehensive Fault Diagnosis of Three-Phase Induction Motors Using Synchronized Multi-Sensor Data Collection by Kevin Thomas, Ahasanur Rahman, Wesam Rohouma, Md. Faysal Ahamed, Fariya Bintay Shafi, Md. Nahiduzzaman, Amith Khandakar

“…The dataset, organized into ten distinct CSV files covering various operational states, provides a rich resource for developing and testing fault detection algorithms. A Random Forest classifier trained on this dataset achieved an accuracy of 99.82%, demonstrating its suitability for real-time fault diagnosis and predictive maintenance applications. …”
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Wearable sensors-based assistive technologies for patient health monitoring by Nouf Abdullah Almujally, Danyal Khan, Danyal Khan, Naif Al Mudawi, Mohammed Alonazi, Haifa F. Alhasson, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…The purpose of this study is to explore the possibilities of using advanced bio-signals for monitoring patient vital signs during daily life activities and predicting favorable and more accurate health-related solutions based on current body health-related real-time measurements.ResultsWith the help of machine learning algorithms, we have observed classification accuracy of up to 94.67% using the mHealth dataset and 95.12% on the ScientISST MOVE dataset. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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From Genomics to AI: Revolutionizing Precision Medicine in Oncology by Giulia Calvino, Juliette Farro, Stefania Zampatti, Cristina Peconi, Domenica Megalizzi, Giulia Trastulli, Sarah Andreucci, Raffaella Cascella, Claudia Strafella, Carlo Caltagirone, Federico Grifalchi, Emiliano Giardina

“…It examines their roles in identifying genetic variants, assessing cancer risk, guiding targeted therapies and immunotherapy, predicting treatment response, and enabling early detection through liquid biopsies. …”
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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…Both decision processes skillfully utilize Monte Carlo simulation and multi-objective genetic algorithms to effectively manage the uncertainty risks in the decision-making process, thereby significantly enhancing the overall resilience of the microgrid.…”
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Adopting TOGAF Framework for Sustainable and Scalable Robusta Coffee Leaf Rust Management by Thein Oak Kyaw Zaw, Kalaiarasi Sonai Muthu Anbananthen, Saravanan Muthaiyah, Baarathi Balasubramaniam, Suraya Mohammad, Yunus Yusoff, Khairul Shafee Kalid

“…The framework leverages enterprise architecture principles to integrate learning algorithms, image detection, and systematic plantation mapping within a structured approach that enhances data organization, rust severity visualization, and predictive analysis. …”
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Symmetry-Based Data Augmentation Method for Deep Learning-Based Structural Damage Identification by Long Li, Xiaoming Tao, Hui Song, Xiaolong Li, Zhilong Ye, Yao Jin, Qiuyu He, Shiyin Wei, Wenli Chen

“…These methods typically use ML algorithms to identify patterns within features extracted from data representing structural conditions, thereby inferring damage from changes in these patterns. …”
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Statistical assessment of interrelationship of marriage and divorces to fertility by A. B. Sinelnikov, O. A. Zolotareva, M. D. Khabib

“…A number of indicators complement the traditional methodology of marriage and divorce tables calculation. The algorithms for obtaining the indicators proposed for implementation (in particular, the cumulative marriage rate of divorcees, the level of divorces compensation by legal remarriages, etc.) have been prescribed, and their estimations have been made, which substantiates the scientific significance of the study. …”
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Hypothesis: the generation of T cells directed against neoepitopes employing immune-mediating agents other than neoepitope vaccines by Renee N Donahue, Jeffrey Schlom, James L Gulley, James W Hodge, Claudia Palena, Duane H Hamilton, Sofia R Gameiro

“…As with all cancer therapy modalities, neoepitope vaccine development and delivery also has some drawbacks, including the level of effort to develop a patient-specific product, accuracy of algorithms to predict neoepitopes, and with the exception of melanoma and some other tumor types, biopsies of metastatic lesions of solid tumors are often not available. …”
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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. …”
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Single cell analysis of host response to helminth infection reveals the clonal breadth, heterogeneity, and tissue-specific programming of the responding CD4+ T cell repertoire. by Ivy K Brown, Nathan Dyjack, Mindy M Miller, Harsha Krovi, Cydney Rios, Rachel Woolaver, Laura Harmacek, Ting-Hui Tu, Brian P O'Connor, Thomas Danhorn, Brian Vestal, Laurent Gapin, Clemencia Pinilla, Max A Seibold, James Scott-Browne, Radleigh G Santos, R Lee Reinhardt

“…Antigen-reactivity of the broader repertoires was predicted to be shared across both tissues and individual mice. …”
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ANALISIS KINERJA MODEL STACKING BERBASIS RANDOM FOREST DAN SVM DALAM KLASIFIKASI RUMAH TANGGA BERDASARKAN GARIS KEMISKINAN MAKANAN DI PROVINSI JAWA BARAT by Ghardapaty Ghaly Ghiffary, Nabila Tri Amanda, Rizky Ardhani, Bagus Sartono, Aulia Rizki Firdawanti

“…The stacking method is an ensemble technique in machine learning that combines predictions from several base models to improve classification accuracy. …”
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Vibration Diagnostic Methods from Methodsof Obtaining Data to Processing It Using Modern Means by Anton O. Zhuravlev, Alexey O. Polyakov, Denis A. Andrikov

“…Thus, self-diagnosis, combined with a high level of automated analytics, makes it possible to predict a malfunction with a high degree of probability, warn about the timing of its occurrence and methods of preventive elimination. …”
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A Novel Mutation of the CYP11B2 in a Saudi Infant with Primary Hypoaldosteronism by Lama Alfaraidi, Abrar Alfaifi, Rawan Alquaiz, Faten Almijmaj, Horia Mawlawi

“…Given the position of the transition at a highly conserved nucleotide and the predictions of different bioinformatic algorithms, it is likely that the mutation is the pathogenic cause of this condition. …”
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Digital Transition as a Driver for Sustainable Tailor-Made Farm Management: An Up-to-Date Overview on Precision Livestock Farming by Caterina Losacco, Gianluca Pugliese, Lucrezia Forte, Vincenzo Tufarelli, Aristide Maggiolino, Pasquale De Palo

“…The increasing integration of sensing devices with smart technologies, deep learning algorithms, and robotics is profoundly transforming the agricultural sector in the context of Farming 4.0. …”
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Identification of anaerobic bacterial strains by pyrolysis-gas chromatography-ion mobility spectrometry by Tim Kobelt, Jonas Klose, Rumjhum Mukherjee, Rumjhum Mukherjee, Martin Lippmann, Szymon P. Szafranski, Szymon P. Szafranski, Meike Stiesch, Meike Stiesch, Stefan Zimmermann

“…Preliminary experiments have demonstrated that pattern recognition algorithms can predict the genus of isolated bacteria with a precision of up to 97%.…”
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