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  1. 81

    Optimization Method for Network Awareness in Different Domains of LEO Communication Constellation by DI Hang, DONG Tao, LIU Zhihui, WEI Shuotong, ZHANG Qiwei, ZHANG Dingyun

    Published 2025-06-01
    “…The heterogeneous and time-varying characteristics of network resources in LEO communication constellation, as well as the diversities of service requirements, make it difficult to allocate network resources. …”
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    Article
  2. 82

    Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

    Published 2025-02-01
    “…By integrating AI into Nigeria’s public health infrastructure, early detection and response can be improved, resource allocation optimized, and disease transmission minimized. …”
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    Article
  3. 83

    A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study. by Ilaria Amodeo, Giorgio De Nunzio, Genny Raffaeli, Irene Borzani, Alice Griggio, Luana Conte, Francesco Macchini, Valentina Condò, Nicola Persico, Isabella Fabietti, Stefano Ghirardello, Maria Pierro, Benedetta Tafuri, Giuseppe Como, Donato Cascio, Mariarosa Colnaghi, Fabio Mosca, Giacomo Cavallaro

    Published 2021-01-01
    “…The native sequences from fetal magnetic resonance imaging (MRI) will be collected. Data from different sources will be integrated and analyzed using ML and DL, and forecasting algorithms will be developed for each outcome. …”
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  4. 84

    Content-based dynamic superframe adaptation for Internet of Medical Things by Yousaf Zia, Arshad Farhad, Faisal Bashir, Kashif Naseer Qureshi, Ghufran Ahmed

    Published 2020-02-01
    “…This article presents a content-based dynamic superframe adaptation algorithm for the low-powered Internet of Medical Things devices to address the resource utilization challenges. …”
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  5. 85

    Deep Learning-Driven Geospatial Modeling of Elderly Care Accessibility: Disparities Across the Urban-Rural Continuum in Central China by Yi Yu, Tian Dong

    Published 2025-04-01
    “…Taking Changsha as a case study, this research constructs an accessibility evaluation system based on the 15-min life circle theory, utilizing multi-source data. Spatial weighting characteristics of elderly care facility locations were analyzed through machine learning algorithms, and service coverage disparities between urban districts and suburban towns were assessed under 5-, 10-, and 15-min walking thresholds. …”
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  6. 86

    Integrating Machine Learning for Enhanced Agricultural Productivity: A Focus on Bananas and Arecanut in the Context of India’s Economic Growth by B. S. Saruk, G. Mokesh Rayalu

    Published 2024-10-01
    “…Assist yield projections may provide governments and policymakers with valuable information to make well-informed choices about food security, import–export policies, and resource allocation. It facilitates national- and regional-level food supply planning. …”
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  7. 87
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  9. 89

    Two-sided Energy Storage Cooperative Scheduling Method for Transmission and Distribution Network Based on Multi-agent Attention-deep Reinforcement Learning by CHEN Shi, ZHU Yujie, LIU Yihong, XU Liuchao, TANG Guodeng

    Published 2025-01-01
    “…An improved Shapley value is used to allocate additional income, providing a cooperative incentive. …”
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    Article
  10. 90

    Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

    Published 2025-09-01
    “…Early and accurate prediction of acute kidney injury (AKI), disease severity, renal replacement therapy (RRT) requirements, and mortality risk is essential for timely identification of high-risk individuals, personalized treatment planning, and optimal allocation of healthcare resources. We aimed to develop and externally validate an interpretable multi-task machine learning (ML) model to predict four clinical outcomes in patients with rhabdomyolysis: AKI, disease severity, the need for RRT, and in-hospital mortality. …”
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  11. 91
  12. 92

    IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

    Published 2025-02-01
    “…The core of IntelliGrid AI is an advanced Q-learning algorithm that intelligently allocates energy resources. …”
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  13. 93

    The methodology for calculating the number of teaching staff using economically feasible norms by L. A. Krokhmal, Yu. A. Kovshun

    Published 2025-01-01
    “…It has been established that the planned number of teaching staff is lower than the planned staffing level, calculated based on the volume of contact work hours, which makes it possible to encourage universities to restructure their curricula without going beyond funding limits.Conclusons and Relevance:the proposed approach allowed to conduct the calculation of teaching staff in accordance with the curriculum with a standardized volume of financial resources allocated to finance the remuneration of teaching staff of a specific educational program. …”
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  14. 94

    Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector by Utsav Pandey, Sanjeet Singh

    Published 2025-04-01
    “…In the first stage, an output-oriented Data Envelopment Analysis is employed to model the interdependency between operational efficiency and service quality by assessing the allocation of the input resources for achieving these two objectives. …”
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  15. 95

    Processing streams in a monitoring cloud cluster by Alexey N. Nazarov

    Published 2020-01-01
    “…This requires to study the methodological possibilities of organization to study of parallel processing high-speed streaming services with the processing of huge amounts of bit data, and, simultaneously, to estimate the necessary computational resource. In the conditions of high dynamics of changes in the bit rate of information generation from the source, a model of the bit rate of Discretized Stream (DStream) formation is proposed, which has a common application. …”
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