Post‐release acclimation of translocated low‐elevation, non‐migratory bighorn sheep by Justin G. Clapp, Jeffrey L. Beck, Kenneth G. Gerow

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General context and relevant public datasets available for improving pathways in Paediatric Cancer applying Artificial Intelligence. A review by Gustavo Hernández-Peñaloza, Silvia Uribe, Francisco Moreno García, Norbert Graf, Federico Álvarez

“…However, the adequate application of such techniques heavily depends on the data, which creates a set of challenges including collection, bias, and scarcity among others. …”
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Long-term reconstructed vegetation index dataset in China from fused MODIS and Landsat data by Xiangqian Li, Qiongyan Peng, Ruoque Shen, Wenfang Xu, Zhangcai Qin, Shangrong Lin, Si Ha, Dongdong Kong, Wenping Yuan

“…This dataset enables reliable annual NDVI estimates for China at a 30-m resolution and is available for reuse through an open data repository.…”
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Research on Correction Method of Water Quality Ultraviolet-Visible Spectrum Data Based on Compressed Sensing by Fengxiao Li, Bin Tang, Mingfu Zhao, Xinyu Hu, Shenghui Shi, Mi Zhou

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Optimized machine learning mechanism for big data healthcare system to predict disease risk factor by Venkata Nagaraju Thatha, Silpa Chalichalamala, Udayaraju Pamula, D. Pramodh Krishna, Manjunath Chinthakunta, Srihari Varma Mantena, Shariff Vahiduddin, Ramesh Vatambeti

“…The findings demonstrate the use of DRFBPS as a practical tool in healthcare analytics by showing the rate at which it produces accurate and reliable predictions. Additionally, its application in healthcare systems, including clinical decisions and remote patient monitoring, proves its real-world applicability in enhancing early diagnosis and preventive care measures. …”
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Urban agglomeration transportation resilience: evaluation and evolution analysis using a data-driven model by Zihao Guo, Xuanling Zhou, Cong Lu, Shixin Li, Yunlong Zhu, Yinhang Liu, Zhijian Li

“…This study proposes an innovative, data-driven approach to quantify urban transportation resilience, integrating genetic algorithms (GA), backpropagation (BP) neural networks, and the entropy weighting method. …”
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A comprehensive survey and comparative analysis of time series data augmentation in medical wearable computing. by Md Abid Hasan, Frédéric Li, Philip Gouverneur, Artur Piet, Marcin Grzegorzek

“…Recent advancements in hardware technology have spurred a surge in the popularity and ubiquity of wearable sensors, opening up new applications within the medical domain. This proliferation has resulted in a notable increase in the availability of Time Series (TS) data characterizing behavioral or physiological information from the patient, leading to initiatives toward leveraging machine learning and data analysis techniques. …”
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iVAE: an interpretable representation learning framework enhances clustering performance for single-cell data by Zeyu Fu, Chunlin Chen, Song Wang, Junping Wang, Shilei Chen

“…Abstract Background Variational autoencoders (VAEs) serve as essential components in large generative models for extracting latent representations and have gained widespread application in biological domains. Developing VAEs specifically tailored to the unique characteristics of biological data is crucial for advancing future large-scale biological models. …”
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STPam: Software for Intelligently Analyzing and Mining Spatiotemporal Processes Based on Multi-Source Big Data by Rongjun Xiong, Zeqiang Chen, Huiwen Pan, Dongyang Liu, Aiguo Sun, Nengcheng Chen

“…Analyzing and mining spatiotemporal processes refers to the extraction of geographic phenomena from spatiotemporal data and the analysis of available geographic knowledge and patterns. …”
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Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data by Bas Peters, Eldad Haber, Keegan Lensink

“…This property prevents the straightforward application of invertible networks to applications that map between different input–output dimensions, need to map to outputs with more channels than present in the input data, or desire outputs that decrease/increase the resolution compared to the input data. …”
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Statistical analysis of fatigue crack propagation data of materials from ancient portuguese metallic bridges by J.A.F.O. Correia, A.M.P. De Jesus, R. Calcada, B. Pedrosa, C. Rebelo, Luis Simoes da Silva, G. ISISE, Department of Civil Engineering

“…Residual fatigue life predictions should be based on actual fatigue data from bridge materials which is scarce due to the material specificities. …”
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Status assessment and management strategy of a large bridge based on massive real time data by Feng Zhou, Zhihao Cui

“…This study aims to enhance the understanding of the state of large-scale bridge structures by accurately analyzing the structural changes of bridges through extensive real-time monitoring data. By conducting a comparative analysis of field load test data and simulation calculations of linear models, this research seeks to provide a precise assessment of structural indices, identify potential risks, and develop appropriate preventive measures. …”
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Calculation of Sensitivity and Specificity from Partial Data for Meta-Analyses: Introducing Some Practical Methods by Reihanesadat Khatami, Mohammadsadegh Faghihi, Hannanesadat Khatami, Mahmoud Yousefifard, Seyedhesamoddin Khatami

“…This study aimed to consolidate practical methods to reconstruct sensitivity and specificity from minimal data. Methods: Our framework addresses three main situations: (1) algebraic rearrangements to compute specificity given partial metrics; (2) digitization of receiver operating characteristic (ROC) curves to obtain threshold-specific sensitivity and specificity; and (3) application of the binormal model when only AUC and prevalence are available. …”
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Comorbidities associated with a clinically-recognized delirium diagnosis in the hospital using real world data by Lay Kodama, Sarah R. Woldemariam, Alice S. Tang, Yaqiao Li, John Kornak, Isabel Elaine Allen, Eva Raphael, Tomiko T. Oskotsky, Marina Sirota

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A Data-Driven Machine Learning Framework Proposal for Selecting Project Management Research Methodologies by Otniel Didraga, Andrei Albu, Viorel Negrut, Diogen Babuc, Ovidiu Dobrican

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Validation of a Spanish-Language Scale on Data-Driven Decision-Making in Pre-Service Teachers by Fabián Sandoval-Ríos, Carola Cabezas-Orellana, Juan Antonio López-Núñez

“…This study validates a Spanish-language instrument designed to assess self-efficacy, digital competence, and anxiety in data-driven decision-making (DDDM) among pre-service teachers. …”
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Semi-Supervised Fault Diagnosis Method for Hydraulic Pumps Based on Data Augmentation Consistency Regularization by Siyuan Liu, Jixiong Yin, Zhengming Zhang, Yongqiang Zhang, Chao Ai, Wanlu Jiang

“…This study proposes a semi-supervised learning method based on data augmented consistency regularization (DACR) to address the issue of lack of labeled data in diagnostic models. …”
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Overcoming Challenges in Video-Based Health Monitoring: Real-World Implementation, Ethics, and Data Considerations by Simão Ferreira, Catarina Marinheiro, Catarina Mateus, Pedro Pereira Rodrigues, Matilde A. Rodrigues, Nuno Rocha

“…This approach ensured data privacy and aligns with ethical standards. The results reveal significant challenges in data collection and processing, including biases in video datasets, the need for high-resolution videos, and the complexities of maintaining data quality and consistency, with 42% (after adjustments) of data lost. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Modern data-intensive applications demand efficient orchestration across heterogeneous storage tiers, ranging from high-performance DRAM to cost-effective cloud storage. …”
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Managing Uncertainty in Geological Scenarios Using Machine Learning-Based Classification Model on Production Data by Byeongcheol Kang, Kyungbook Lee

“…This study, as far as we know, is the first application of CNN in which production history data are composed as a matrix form for use as an input image. …”
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