Integration of Google Earth Engine, Sentinel-2 images, and machine learning for temporal mapping of total dissolved solids in river systems by Eric Ariel L. Salas, Sakthi S. Kumaran, Robert Bennett, Eric B. Partee, Jason Brownknight, Kellsie Schrack, Bryant Willis

“…Our findings provide spatial insight into the current state of TDS as well as the success of management steps taken to manage and prevent eutrophic problems in the LMR.…”
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Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection by Md Shofiqul Islam, Khondokar Fida Hasan, Hasibul Hossain Shajeeb, Humayan Kabir Rana, Md. Saifur Rahman, Md. Munirul Hasan, AKM Azad, Ibrahim Abdullah, Mohammad Ali Moni

“…This study presents a comprehensive review of the potential of multimodal deep learning (DL) in medical diagnosis, using COVID-19 as a case example. …”
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Safety–Efficiency Balanced Navigation for Unmanned Tracked Vehicles in Uneven Terrain Using Prior-Based Ensemble Deep Reinforcement Learning by Yiming Xu, Songhai Zhu, Dianhao Zhang, Yinda Fang, Mien Van

“…Local elevation information and vehicle pose changes over consecutive time steps are used as inputs to the DRL model, enabling the UTVs to implicitly learn policies for safe navigation in complex terrains while minimizing the impact of slipping disturbances. …”
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Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…Abstract As a traditional handicraft with a long history and exquisite skills, the manufacturing process of twisted tire porcelain involves complex steps and high energy consumption. Because twisted tire porcelain has many unique patterns, it is necessary to classify porcelain according to the patterns in the production process. …”
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Deep learning for automatic brain tumour segmentation on MRI: evaluation of recommended reporting criteria via a reproduction and replication study by Justin Schneiderman, Rolf A Heckemann, Emilia Gryska, Isabella Björkman-Burtscher, Asgeir Store Jakola, Tora Dunås

“…Objectives To determine the reproducibility and replicability of studies that develop and validate segmentation methods for brain tumours on MRI and that follow established reproducibility criteria; and to evaluate whether the reporting guidelines are sufficient.Methods Two eligible validation studies of distinct deep learning (DL) methods were identified. We implemented the methods using published information and retraced the reported validation steps. …”
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Smart learning using artificial intelligence: Ways to improve the process of teaching general education subjects in higher education (China's experience) by Xiaoyu Wang, Yan Li, Jing Yan

“…In the context of the collision of traditional concepts of learning and modern technologies “artificial intelligence + learning”, a new model of smart learning has emerged. …”
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Introducing HeliEns: A Novel Hybrid Ensemble Learning Algorithm for Early Diagnosis of <i>Helicobacter pylori</i> Infection by Sultan Noman Qasem

“…The development of HeliEns involved rigorous data preprocessing steps, including data cleaning, encoding of categorical variables, and feature scaling, to ensure the dataset’s suitability for quantum machine learning algorithms. …”
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Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa by Agmasie Damtew Walle, Shimels Derso Kebede, Jibril Bashir Adem, Daniel Niguse Mamo

“…Nine supervised machine-learning algorithms were applied, following Yufeng Guo's steps for supervised learning. …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…The five most important gait parameters in the optimal model were left step height, walking speed, right step height, body sway, and step width. …”
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A Novel High Performance Object Identification Approach in Care Homes Using Gaussian Preprocessing by Sara Auweiler, Melina Mueller, Diana Puhla, Pascal Penava, Ricardo Buettner

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An Intelligent Technique for Android Malware Identification Using Fuzzy Rank-Based Fusion by Altyeb Taha, Ahmed Hamza Osman, Yakubu Suleiman Baguda

“…The suggested ANDFRF primarily consists of two steps: in the first step, five machine learning algorithms, comprising K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Logistic Regression (LR), XGbooost (XGB) and Light Gradient Boosting Machine (LightGBM), were utilized as base classifiers for the initial identification of Android Apps either as goodware or malware apps. …”
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Accelerometer Measurements: A Learning Tool to Help Older Adults Understand the Importance of Soft-Landing Techniques in a Community Walking Class by Tatsuo Doi, Ryosuke Haruna, Naoyo Kamioka, Shuzo Bonkohara, Nobuko Hongu

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ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events by Aizaz Sharif, Dusica Marijan

“…Current testing methods often rely on computationally expensive active learning techniques to identify such vulnerabilities. …”
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Multi-CNN Deep Feature Fusion and Stacking Ensemble Classifier for Breast Ultrasound Lesion Classification by Kemal PANÇ, Sümeyye SEKMEN

“…Objective: To develop and validate a robust machine learning model for classifying breast ultrasound images into benign, malignant, and normal categories, aiming to enhance diagnostic accuracy using advanced feature extraction and ensemble learning techniques. …”
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ArcticSoundsNET: BirdNET embeddings facilitate improved bioacoustic classification of Arctic species by Morgan A. Ziegenhorn, Richard B. Lanctot, Stephen C. Brown, Miles Brengle, Shiloh Schulte, Sarah T. Saalfeld, Christopher J. Latty, Paul A. Smith, Nicolas Lecomte

“…In recent years, deep learning has become a popular solution for processing large ecological monitoring datasets. …”
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Making the Implicit Explicit: An Illustration of YPAR Implementation and Lessons Learned in Partnership With Young Adults Who Have Experienced Family Member Incarceration by Michelle Abraczinskas, Britni L. Adams, Erin Vines, Shaneah Cobb, Zion Latson, Mykala Wimbish

“…To fill this gap, we provided a step-by-step implementation guide of our curriculum, stages of research, and adaptations to YPAR with young adults who experienced family member incarceration, graduated from an alternative school, and worked in the community. …”
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Strategies for teaching English spelling and reading by Daniela Sorádová

“…Learning English reading and spelling in a non-native speaking environment is generally practised through drill, repetition and learning by heart. …”
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Towards a Unified European View of Clinical Evidence: What ‘Health Technology Assessment Organizations’ Can Learn from Regulatory Experience by Karl Broich, Wiebke Löbker

“…The harmonization of pharmaceutical regulations within the European Union has been a crucial step towards ensuring high safety standards and efficient access to innovative medicines. …”
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Automated Edge Detection for Cultural Heritage Conservation: Comparative Evaluation of Classical and Deep Learning Methods on Artworks Affected by Natural Disaster Damage by Laya Targa, Carmen Cano, Álvaro Solbes-García, Sergio Casas, Ester Alba, Cristina Portalés

“…Assessing the condition of artworks is a critical step in cultural heritage conservation that traditionally involves manual damage mapping, which is time-consuming and reliant on expert input. …”
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Urban sentinel: advancing structural health monitoring for building damage measurement in districts through IoT integration and self-optimizing machine learning by Parsa Parsafar

“…This integration is still in its early stages of practical application, marking Urban Sentinel as a significant step forward in urban infrastructure management. …”
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