A deep learning-driven multi-layered steganographic approach for enhanced data security by Yousef Sanjalawe, Salam Al-E’mari, Salam Fraihat, Mosleh Abualhaj, Emran Alzubi

“…Key contributions include achieving high visual fidelity with Structural Similarity Index Metrics (SSIM) consistently above 99%, robust data recovery with text recovery accuracy reaching 100% under standard conditions, and enhanced resistance to common attacks such as noise and compression. …”
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New opportunities in management of patients with retinopathy prematurity (literature review and analysis of own data) by L. A. Katargina, E. N. Demchenko

“…The demonstrated high effect of anti-VEGF therapy in ROP is consistent with our own data. Anti-VEGF therapy opens up new possibilities in the treatment of a particular class of ROP forms. …”
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Cross-country comparative analysis of climate resilience and localized mapping in data-sparse regions by Ronald Katende

“…Yet, many LICs lack the high-resolution data needed to assess resilience at both national and local levels.MethodsThis study proposes a two-part framework to evaluate climate resilience across data sparse settings. …”
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Data and methods for assessing urban green infrastructure using GIS: A systematic review. by Xiaomian Wu, Jianquan Liu, Yukun Hou

“…This study centers on the scope, data sources, theoretical models, analyses, and objectives of GIS-based UGI assessments. …”
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A Data-Driven Intelligent Methodology for Developing Explainable Diagnostic Model for Febrile Diseases by Constance Amannah, Kingsley Friday Attai, Faith-Michael Uzoka

“…However, limitations such as dataset imbalance and exclusion of pediatric data remain. Future research will focus on refining the model, expanding the dataset, and conducting extensive clinical validation before real-world implementation. …”
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Issues with the Organic and Elemental Carbon Fractions in Recent U.S. Chemical Speciation Network Data by Philip K. Hopke, Yunle Chen, David Q. Rich, John G. Watson, Judith C. Chow

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From data on gross activity to the characterization of animal behaviour: which metrics for which purposes? by van Dixhoorn, Ingrid, Aubé, Lydiane, van Zyl, Coenraad, de Mol, Rudi, van der Werf, Joop, Lardy, Romain, Mialon, Marie-Madeleine, van Reenen, Kees, Veissier, Isabelle

“…The calculations, however, can be applied to other species and can be performed on data obtained from sensors as well as visual observations. …”
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Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data by Maksut Kulzhanov, Alexander Wagner, Abylkair Skakov, Iliyas Mukhamejan, Saya Zhorabek, Ainur B. Qumar

“…With the exponential growth of medical data and limited analytical resources, healthcare systems are increasingly adopting Artificial Intelligence (AI) and Machine Learning (ML) technologies to enhance their decision-making processes. …”
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Exploring the Perception of Landscape Elements through User-Generated Data to Support Greenspace Management by Tianchen Zheng, Quan Pan, Songyao Huai, Chenxing Wang, Yan Yan, Veerle Van Eetvelde, Tim Van de Voorde

“…Applying user-generated data and unsupervised machine learning approach, we identified the landscape elements and classified the greenspaces to extract perception rates and detect dominant elements. …”
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StarNet: Indian star gooseberries dataset for quality and maturity assessment(Mendeley Data). by Pushpa B․ R․, Manohar N․, N. Shobha Rani

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Learning Manipulation from Expert Demonstrations Based on Multiple Data Associations and Physical Constraints by Yangqing Ye, Yaojie Mao, Shiming Qiu, Chuan’guo Tang, Zhirui Pan, Weiwei Wan, Shibo Cai, Guanjun Bao

“…This article presents a novel Video to Command framework that employs multiple data associations and physical constraints. First, we introduce an object-level appearance-contrasting multiple data association strategy to effectively associate manipulated objects in visually complex environments, capturing dynamic changes in video content. …”
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A Sensor-Based Data Acquisition System for Soil Parameters to Determine Suitable Crops by Blessing Olatunde Abisoye, Eustace Manayi Dogo, Buhari Ugbede Umar, Isaac Zhiri Mamman

“…The collected data is then analyzed and visualized in through a web-based dashboard, providing farmers with information about the state of their soil. …”
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Bimodal data analysis for early detection of lameness in dairy cows using artificial intelligence by Yashan Dhaliwal, Hangqing Bi, Suresh Neethirajan

“…To address the urgent need for early detection, we introduce a novel bimodal artificial intelligence (AI) framework that leverages both facial biometric data and accelerometer-based movement metrics. Over a 21-day period, six Holstein cows were monitored to capture variations in facial expressions and locomotion, and a multimodal model was built by combining DenseNet-121 for image analysis with Long Short-Term Memory (LSTM) networks for time-series data. …”
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Class and Data-Incremental Learning Framework for Baggage Threat Segmentation via Knowledge Distillation by Ammara Nasim, Saad Mazhar Khan, Anum Abdul Salam, Arslan Shaukat, Taimur Hassan, Adeel M. Syed, Muhammad Usman Akram

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Automatic Feature Selection for Imbalanced Echocardiogram Data Using Event-Based Self-Similarity by Huang-Nan Huang, Hong-Min Chen, Wei-Wen Lin, Rita Wiryasaputra, Yung-Cheng Chen, Yu-Huei Wang, Chao-Tung Yang

“…This study used an echocardiogram dataset, visual presentations of high-frequency sound wave signals, and data of patients with heart disease who are treated using three treatment methods: catheter ablation, ventricular defibrillator, and drug control—over the course of three years. …”
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Electrophysiological Insights in Exergaming—Electroencephalography Data Recording and Movement Artifact Detection: Systematic Review by Carolina Rico-Olarte, Diego M Lopez, Bjoern M Eskofier, Linda Becker

“…Common motion artifact removal methods included visual inspection and independent component analysis. …”
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Selection and Application of the Data Transfer Operating Protocol Software Architecture for the Software-Defined Radio by Oleg V. Vorobyov, Alexey I. Rybakov

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The Abundance and Properties of Barred Galaxies out to z ∼ 4 Using JWST CEERS Data by Yuchen Guo, Shardha Jogee, Eden Wise, Keith Pritchett Jr., Elizabeth J. McGrath, Steven L. Finkelstein, Kartheik G. Iyer, Pablo Arrabal Haro, Micaela B. Bagley, Mark Dickinson, Jeyhan S. Kartaltepe, Anton M. Koekemoer, Casey Papovich, Nor Pirzkal, L. Y. Aaron Yung, Bren E. Backhaus, Eric F. Bell, Rachana Bhatawdekar, Yingjie Cheng, Luca Costantin, Alexander de la Vega, Mauro Giavalisco, Nimish P. Hathi, Benne W. Holwerda, Peter Kurczynski, Ray A. Lucas, Bahram Mobasher, Pablo G. Pérez-González, Fabio Pacucci

“…However, TNG50 simulations predict a large population of smaller bars that our data cannot robustly detect. If such bars exist, the true bar fraction at z  ∼ 2–4 may be significantly higher than our results. …”
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Comprehensive analysis of multi‐omics single‐cell data using the single‐cell analyst by Lu Pan, Bufu Tang, Xuan Zhang, Paolo Parini, Roman Tremmel, Joseph Loscalzo, Volker M. Lauschke, Bradley A. Maron, Paola Paci, Ingemar Ernberg, Nguan Soon Tan, Ákos Végvári, Zehuan Liao, Sundararaman Rengarajan, Roman Zubarev, Yuxuan Fan, Xu Zheng, Xinyue Jian, Ren Sheng, Zhenning Wang, Xuexin Li

“…It automates critical analysis steps, such as quality control, data processing, and phenotype‐specific analyses, while also offering interactive, publication‐ready visualizations. …”
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Different rs-fMRI Data Processing Methods in the Study of Vascular Cognitive Impairment by Ying GUAN, Luwen ZHU, Feng WANG, Danna CAO, Xiaoling LI, Qiang TANG

“…This article have reviewed the research on the state of rs-fMRI in the field of VCI in recent years, and summarized the commonly used rs-fMRI data processing methods and features. The application of different functional data processing methods of magnetic resonance in VCI aims to provide imaging evidence for the clinical diagnosis and treatment of VCI.…”
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