MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

“…Leveraging regression algorithms such as Random Forest, Gradient Boosting, Light Gradient Boosting, Categorical Boosting and Extreme Gradient Boosting, we have modeled the non-linear and temporal dynamics of sensor battery degradation, thereby enabling proactive maintenance strategies, dynamic energy management, and resource allocation. …”
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Machine Learning in Public Governance: A Systematic Review of Applications, Trends and Challenges by Y. Nuruly, G. N. Sansyzbayeva, L. Z. Ashirbekova, S. K. Tazhiyeva

“…The analysis results allowed us to identify four functional areas of ML application in public administration: transparency and ethics, resource allocation and service provision, institutional design, and technical integration. …”
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Optimising management against dynamic threats: A spatially explicit approach based on integer programming by José Salgado‐Rojas, Virgilio Hermoso, Eduardo Álvarez‐Miranda

“…Employing a Warm‐start algorithmic strategy ensures rapid generation of feasible solutions, enhancing the model's practical applicability and scalability. …”
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SLAM: Sales Lead AMplification Through GenAI and ML for e-Learning Platforms by Ganesan Ramachandran, Tanmay Narang, Vallidevi Krishnamurthy

“…In the domain of sales, the accurate prediction of leads is deemed essential for optimizing resource allocation and maximizing conversion rates. …”
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Explainable machine learning models for mortality prediction in patients with sepsis in tertiary care hospital ICU in low- to middle-income countries by Saumya Diwan, Vinay Gandhi, Esha Baidya Kayal, Puneet Khanna, Amit Mehndiratta

“…Conclusions The proposed approach could provide preemptive estimations into prognostication and outcome prediction of patients with sepsis in low-resource settings. This will aid in clinical decision-making, resource allocation and research for new treatment modalities.…”
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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 anticipation of future customer conduct is a cornerstone for resource allocation in sales and marketing, enabling strategic decision-making in manufacturing operations, inventory planning, and point-of-sale scenarios. …”
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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…Achieving 82% detection accuracy in real-world applications could drastically reduce response times, minimize the damage caused by wildfires, and enhance resource allocation for firefighting efforts, emphasizing the importance of continued research in this domain.…”
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Advancements in artificial intelligence transforming medical education: a comprehensive overview by Aliasghar Khakpaki

“…However, its successful integration requires ethical frameworks, faculty training, and equitable resource allocation. A balanced approach that combines technological innovation with human-centered pedagogy is essential to preserve empathy and ethical care in healthcare.…”
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Design and Deployment of ML in CRM to Identify Leads by Alonso Yocupicio-Zazueta, Agustin Brau-Avila, Federico Cirett-Galán, Margarita Valenzuela-Galván

“…This approach enables us to drive efficiency, enhance sales outcomes, and allocate resources more effectively.…”
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ClassRoom-Crowd: A Comprehensive Dataset for Classroom Crowd Counting and Cross-Domain Baseline Analysis by Wenqian Jiang, Xiaohua Huang, Qun Zhao, Sheng Liu

“…Additionally, in day-to-day educational management, tasks such as optimizing the allocation of teaching resources and planning educational spaces heavily depend on precise crowd counting techniques. …”
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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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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

“…This paper focuses on enhancing the resilience of microgrids—localized power systems that integrate multiple energy sources—against challenges such as natural disasters, technological obstacles, and human errors. …”
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Abiotic drivers of activity in a large, free-ranging, freshwater teleost, Murray cod (Maccullochella peelii). by Jason D Thiem, Ian J Wooden, Lee J Baumgartner, Gavin L Butler, Jamin Forbes, Matthew D Taylor, Robyn J Watts

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Design and optimization of distributed energy management system based on edge computing and machine learning by Nan Feng, Conglin Ran

“…Specifically, by using machine learning algorithms for dynamic scheduling of distributed energy resources, the system can achieve an energy utilization rate 12% higher than traditional scheduling methods, and reduce energy waste by 18% in the event of fluctuations in energy demand. …”
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Improving energy efficiency for intelligent reflecting surface assisted PD-NOMA in EH relaying network by Hong Nguyen-Thi, Thuc Kieu-Xuan, Thang Le-Nhat, Anh Le-Thi

“…We also construct a Particle swarm optimization (PSO)-based program to optimize the EE depending on power allocation for NOMA users and phase shift of the IRS elements. …”
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Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial by Caio César Souza Conceição, Camila Marinelli Martins, Mayck Medeiros Silva, Hugo Caire de Castro Faria Neto, Davide Chiumello, Davide Chiumello, Davide Chiumello, Patricia Rieken Macedo Rocco, Fernanda Ferreira Cruz, Pedro Leme Silva

“…BackgroundPredicting clinical improvement after hospital admission in patients with COVID-19 is crucial for effective resource allocation. Machine-learning tools can help identify patients likely to show clinical improvement based on real-world data. …”
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Equitable hospital length of stay prediction for patients with learning disabilities and multiple long-term conditions using machine learning by Emeka Abakasanga, Rania Kousovista, Georgina Cosma, Ashley Akbari, Francesco Zaccardi, Navjot Kaur, Navjot Kaur, Danielle Fitt, Gyuchan Thomas Jun, Reza Kiani, Satheesh Gangadharan

“…Predicting the length of stay (LOS) for patients with LD and multiple long-term conditions (MLTCs) is critical for improving patient care and optimising medical resource allocation. However, there is limited research on the application of machine learning (ML) models to this population. …”
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Predictive estimations of health systems resilience using machine learning by Alessandro Jatobá, Paula de Castro-Nunes, Paloma Palmieri, Omara Machado Araujo de Oliveira, Patricia Passos Simões, Valéria da Silva Fonseca, Paulo Victor Rodrigues de Carvalho

“…This research highlights the potential of ML in predictive modeling to inform strategic health decision-making, targeting interventions and more effective resource allocation. This study provides a robust framework for evaluating resilience, offering public health managers a valuable tool to strengthen health systems in the face of emerging challenges.…”
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Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices by Muhammad Shoaib Farooq, Rizwan Pervez Mir, Atif Alvi, Kilian Tutusaus, Eduardo Garcia Villena, Fadwa Alrowais, Hanen Karamti, Imran Ashraf

“…The capacity to precisely diagnose and preemptively predict potential failures holds the potential to considerably amplify maintenance efficiency, diminish downtime, and optimize resource allocation. The wealth of information offered by telemetry data gathered from IoT devices presents an opportunity for diagnostics and prognostics applications. …”
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Robust Expansion Planning of Electric Vehicle Charging System and Distribution Networks by Yue Xiang, Ping Xue, Yanliang Wang, Lixiong Xu, Wang Ma, Miadreza Shafie-khah, Junlong Li, Junyong Liu

“…Finally, it is solved to perform distributionally robust expansion planning by the column and constraint generation algorithm. Effectiveness and scalability of the proposed planning method are illustrated by numerical case studies. …”
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