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Proactive caching in cloud and D2D assisted multi-tier cellular networks

Ayaz Ahmad, Fawad Ahmad, Muhammad Suleman Khan, Adel Aldalbahi • PeerJ Computer Science (2026)

Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.4004

A review of machine learning in scheduling

Haldun Aytuğ, Siddhartha Bhattacharyya, G.J. Koehler, Jane L. Snowdon • IEEE Transactions on Engineering Management (1994)

This paper has two primary purposes: to motivate the need for machine learning in scheduling systems and to survey work on machine learning in scheduling. In order to motivate the need for machine learning in scheduling, we briefly motivate...

OPENALEX DOI: https://doi.org/10.1109/17.293383

RDDA: Rectified Discriminatory Delta-Adjust

Ziad F. Doughan, Sari S. Itani • IEEE Access (2025)

This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RD...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3641537

A diagnostic model based on clinical indicators and radiomics features for superior labral anterior and posterior lesions in the shoulder joint

Hongyu Wang, Lin Wang, Lei Shi, Fei Wang et al. • Journal of Orthopaedic Surgery (2026)

Background Superior labrum anterior and posterior (SLAP) lesions are a common cause of shoulder pain and instability. Accurate diagnosis remains challenging in clinical practice. This study aims to develop and evaluate radiomics models and ...

DOAJ Open Access (DOAJ) DOI: 10.1177/10225536261418429

Virtual CT Myelography: A Patch-Based Machine Learning Model to Improve Intraspinal Soft Tissue Visualization on Unenhanced Dual-Energy Lumbar Spine CT

Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir et al. • Information (2022)

Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurat...

DOAJ Open Access (DOAJ) DOI: 10.3390/info13090412

Incorporating snow accumulation and melting into the Xin'anjiang model using differentiable parameter learning

Zexin CHEN, Tongtiegang ZHAO • Shui kexue jinzhan (2025)

The Xin'anjiang model stands as one of the most important hydrological models. This paper develops a differentiable Xin'anjiang model coupled with the CemaNeige module(dMXAJ)under the framework of differentiable parameter learning. Specific...

DOAJ Open Access (DOAJ) DOI: 10.14042/j.cnki.32.1309.2025.02.003

Integrating BIM, Machine Learning, and PMBOK for Green Project Management in Saudi Arabia: A Framework for Energy Efficiency and Environmental Impact Reduction

Maher Abuhussain, Ali Hussain Alhamami, Khaled Almazam, Omar Humaidan et al. • Buildings (2025)

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...

DOAJ Open Access (DOAJ) DOI: 10.3390/buildings15173031

Leveraging Cloud Technology for Personalized Multiple Sclerosis Care: A Comprehensive Data Management and Visualization Approach

Jose Manuel PINILLOS RUBIO, Minerva VIGUERA MORENO • Applied Medical Informatics (2024)

This project develops a cloud-based solution for securely managing clinical data and patient-reported outcomes (PROMs) for multiple sclerosis (MS) patients. Utilizing REDCap for data collection, we incorporated clinical outcomes and PROMs f...

DOAJ Open Access (DOAJ)

Acceptance of Machine Learning for Medication Selection in Epilepsy to Inform Clinical Trial Design: Co-Design Survey Study

Madeleine J Smith, Sandra Reeder, Fiona Waugh, Shobi Sivathamboo et al. • JMIR AI (2026)

Abstract BackgroundAntiseizure medications (ASMs) are the mainstay of epilepsy treatment; however, there is currently no reliable way to predict which medication will be most effective for an individual patient. Machine learning...

DOAJ Open Access (DOAJ) DOI: 10.2196/85047

AN IMPROVED GRU BASED ON RECURRENT ATTENTION UNIT AND SELF- ATTENTION TECHNIQUE FOR TEXT SENTIMENT ANALYSIS

Dhurgham Ali Mohammed, Kalyani A. Patel • ICTACT Journal on Soft Computing (2025)

In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...

DOAJ Open Access (DOAJ) DOI: 10.21917/ijsc.2025.0518

Machine learning for real-time aggregated prediction of hospital admission for emergency patients

Zella King, Joseph Farrington, Martin Utley, Enoch Kung et al. • npj Digital Medicine (2022)

Abstract Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabi...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-022-00649-y

Machine learning in geosciences and remote sensing

David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers (2015)

Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.gsf.2015.07.003

What is Machine Learning? A Primer for the Epidemiologist

Qifang Bi, Katherine E Goodman, Joshua Kaminsky, Justin Lessler • American Journal of Epidemiology (2019)

Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well...

OPENALEX DOI: https://doi.org/10.1093/aje/kwz189

Perspectives in machine learning for wildlife conservation

Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe et al. • Nature Communications (2022)

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41467-022-27980-y PMC: 8828720

An intelligent machine learning paradigm for gyrotactic micro-organism-induced squeezing flow of Eyring–Powell hybrid nanofluids with entropy generation

A. Imran, Muna Elsadig, Jongsuk Ro • AIP Advances (2026)

A novel unsteady squeezing flow of a non-Newtonian ternary hybrid nanofluid is investigated by focusing Eyring–Powell fluid rheology in an infinite channel. The nanofluid consists of AA1072, AA1075, and ZrO2 nanoparticles suspended in blood...

DOAJ Open Access (DOAJ) DOI: 10.1063/5.0337148

Evaluation of PCA with variable selection for cluster typological domains

Silvânia Alves Braga de Castro, André Carlos Silva • REM: International Engineering Journal (2024)

Abstract The modeling of mineral deposits has been improved over the years with the incorporation of mineralogical and metallurgical information obtained from drilling samples that make up the pillars for the construction of resource models...

DOAJ Open Access (DOAJ) DOI: 10.1590/0370-44672023770071

Aerosol Optical Depth Retrieval from MODIS Using a Physically Informed Machine Learning Framework

Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing (2026)

Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs18172862