Exploring crop health and its associations with fungal soil microbiome composition using machine learning applied to remote sensing data by Mathies Brinks Sørensen, David Faurdal, Giovanni Schiesaro, Emil Damgaard Jensen, Michael Krogh Jensen, Line Katrine Harder Clemmensen

“…We associate the normalized difference vegetation index with fungal microbiomes in wheat, barley, and maize using a two-step machine learning process. The first step adjusts normalized difference vegetation index values for abiotic confounders using a random forest model trained on Lucas 2018 topsoil and ERA5 climate datasets. …”
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Self-Organizing Wireless Sensor Networks Solving the Coverage Problem: Game-Theoretic Learning Automata and Cellular Automata-Based Approaches by Franciszek Seredynski, Miroslaw Szaban, Jaroslaw Skaruz, Piotr Switalski, Michal Seredynski

“…We use the following two types of reinforcement learning machines as agents: Learning Automata (LA) and Cellular Automata (CA). …”
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From pilot project to toolkit: using lessons learned from a comprehensive university campus sexual violence activity in Kenya by Paula Tavrow, Nicole M. Maderas, Humphries Evelia, Glory Kathambi, Albert Obbuyi

“…The toolkit, a free downloadable resource, provides a step-by-step framework for SGBV project implementation that includes short videos, training curricula, and brief survey instruments.…”
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Building Bridges Instead of Putting Up Walls: An Educational Tool to Facilitate Instructors in Adopting Active Learning Methodologies for Teaching Programming by Ivanilse Calderon, Williamson Silva, Eduardo Feitosa

“…Additionally, CollabProg provides a set of practical guidelines, offering a step-by-step guide to assist instructors in adopting ALMs. …”
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Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera by Ashish Sharma, Taraprasad Das, Bryan Ong, Florian Mickael Savoy, Divya Parthasarathy Rao, Jun Kai Toh, Anand Sivaraman

“…For the fine-tuning step, the test set consisted of 238 (34% referable AMD) images. …”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

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An LSTM deep learning framework for history-based tornado prediction using meteorological data and damage assessment using NDVI anomalies by Omid Memarian Sorkhabi

“…The main goal of this research was to develop a deep learning algorithm based on history to predict this phenomenon. …”
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Enhanced detection of surface deformations in LPBF using deep convolutional neural networks and transfer learning from a porosity model by Muhammad Ayub Ansari, Andrew Crampton, Samer Mohammed Jaber Mubarak

“…Abstract Our previous research papers have shown the potential of deep-learning models for real-time detection and control of porosity defects in 3D printing, specifically in the laser powder bed fusion (LPBF) process. …”
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Exploring educational technology, online communities, and self-paced learning in enhancing graduate students' health promotion skills in physical education by Jiang Congmeng, Adjah N. Mazlan

“…Narratives were analyzed through a three-step thematic analysis to uncover relationships and insights. …”
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Digital Transformation of HOTS Assessment in Elementary School Science Learning: Technological Challenges, Human Resource Readiness, and Contribution to SDG's Achievement by Nugroho Irham, Wilujeng Insih, Pujaningsih

“…Digitalization of High Order Thinking Skills-based assessments plays a strategic role in supporting science learning in elementary schools, in line with the achievement of the Sustainable Development Goal for quality education. …”
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Deep learning-based mobile application for the enhancement of pneumonia medical imaging analysis: A case-study of West-Meru Hospital by Japheth Mumo Kimeu, Michael Kisangiri, Hope Mbelwa, Judith Leo

“…These results signify a promising step forward in empowering healthcare professionals with timely and reliable results for optimal patient management.…”
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A Multi-Stage Feature Selection and Explainable Machine Learning Framework for Forecasting Transportation CO₂ Emissions by Mohammad Ali Sahraei, Keren Li, Qingyao Qiao

“…For this reason, we proposed a multi-stage method that incorporates explainable Machine Learning (ML) and Feature Selection (FS), guaranteeing interpretability in comparison to conventional black-box models. …”
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Neuroadaptive haptics: a proof-of-concept comparing reinforcement learning from explicit ratings and neural signals for adaptive XR systems by Lukas Gehrke, Aleksandrs Koselevs, Marius Klug, Klaus Gramann

“…By demonstrating RL‐based adaptation from implicit neural signals, our proof-of-concept is a step towards seamless, low-friction personalization in XR.…”
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Toward Automated Air Leak Localization: A Machine Learning-Enhanced Ultrasonic and LiDAR-SLAM Framework for Industrial Environments by Anthony Schenck, Walter Daems, Jan Steckel

“…Automating the detection process of these air leaks can help prevent this loss of energy, as detecting and localizing them is the first necessary step in efficient maintenance. Typically ultrasonic microphone arrays are used to detect the leaks, since the escaping air causes turbulences around the leak opening. …”
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The experiences, challenges, and acceptance of e-learning as a tool for teaching during the COVID-19 pandemic among university medical staff. by Marwa Mohamed Zalat, Mona Sami Hamed, Sarah Abdelhalim Bolbol

“…Thus, it will help to develop a strategic plan for the successful implementation of e-learning and view technology as a positive step towards evolution and change.…”
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Real-time forecasting of pathological gait via IMU navigation: a few-shot and generative learning framework for wearable devices by Wenwen Zhang, Hao Zhang, Zenan Jiang, Amir Servati, Peyman Servati

“…To address these limitations, we introduce GaitMotion, a novel machine-learning framework that employs few-shot learning on a multitask dataset collected via wearable IMU sensors for real-time pathological gait analysis. …”
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A dictionary learning approach with overlap for the low dose computed tomography reconstruction and its vectorial application to differential phase tomography. by Alessandro Mirone, Emmanuel Brun, Paola Coan

“…In this scenario, we implemented a dictionary learning method with a new form of convex functional. …”
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A Novel Closed-Loop Deep Learning-Based Smart Infusion Rate Monitoring Technique for Safe Intravenous Medication Administration by Subrata Bhattacharjee, Gun Ho Kim, Hongje Lee, Kyoung Won Nam

“…Based on these results, we conclude that the proposed artificial intelligence-based smart IR status monitoring technique shows promise as a prototype for autonomous IV administration monitoring with minimal human intervention, serving as a foundational step toward clinically deployable solutions in future healthcare settings.…”
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Employability within South African businesses in the 4IR era: The impacts of abilities, self-efficacy, and work-integrated learning effectiveness by Masase Mageza-Mokhethi, Foluso Philip Adekanmbi

“…Consequently, this study found that South African employees perceive graduates’ employability as being significantly and positively influenced by their abilities (β = .802, p < .001), self-efficacy (β = .815, p < .001), and work-integrated learning (β = .864, p < .001). In the third-step model, these three factors substantially impacted graduates’ employability more than other likely combination matrices. …”
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The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS by Serap Çatlı Dinç, Aybala Nur Üçgül, Hüseyin Bora, Ertuğrul Şentürk

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