PriBeL: A primary betel leaf dataset from field and controlled environmentMendeley Data by Gauri Mane, Raghav Bhise, Rutuja Kadam, Gagandeep Kaur, Devika Verma, Rupali Chopade, Gitanjali Shinde, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

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Text-Conditioned Diffusion-Based Synthetic Data Generation for Turbine Engine Sensor Analysis and RUL Estimation by Luis Pablo Mora-de-León, David Solís-Martín, Juan Galán-Páez, Joaquín Borrego-Díaz

“…Compared to existing approaches, which rely on generative adversarial networks (GANs) or deterministic transformations, the proposed framework offers enhanced data fidelity and adaptability. This study highlights the potential of text-conditioned diffusion models for augmenting time-series datasets in industrial Prognostics and Health Management (PHM) applications.…”
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Anomaly Detection in Spatiotemporal Data from Fiber Optic Distributed Temperature Sensing for Outdoor Fire Monitoring by Haitao Bian, Xiaohan Luo, Zhichao Zhu, Xiaowei Zang, Yu Tian

“…This research underscores the potential of utilizing FO-DTS spatiotemporal data with CNN-AE for outdoor fire detection in complex scenarios and provides suggestions for mitigating environmental interference in practical applications.…”
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Proteome differences of dental stem cells between permanent and deciduous teeth by data-independent acquisition proteomics by Zhang Suping, Liu Yuqing, Dong Jin, Jiao Min, Gu Yongchun, Chen Liling, Yuan Na, Wang Jianrong, Yang Dezhao, Meng Fanwen

“…To address this gap, we employed a novel data-independent acquisition (DIA) proteomics approach to compare the protein expression profiles of DPSC and SHED. …”
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Optimizing data privacy and security measures for critical infrastructures via IoT based ADP2S technique by Zhenyu Xu, Jinming Wang, Shujuan Feng, Salwa Othmen, Chahira Lhioui, Aymen Flah, Zdenek Slanina

“…However, data loss and complexities are significant issues when handling enormous data in IoT applications. …”
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A Hybrid Method for Predicting the Bistatic Target Strength Basedon the Monostatic Scattering Sound Pressure Data by Yuhang TANG, Chenyu FAN, Yinhao LI, Changxiong CHEN, Zilong PENG

“…To predict the scattered acoustic field for underwater targets with separate transmission and reception points, a forecasting method based on limited scattered acoustic pressure data is proposed. This method represents the scattered acoustic field as the product of n acoustic scattering transfer function and a source density function. …”
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Effects of Ladder-Climbing Exercise on Mammary Cancer: Data from a Chemically Induced Rat Model by Jessica Silva, Tiago Azevedo, Inês Aires, Catarina Medeiros, Maria J. Neuparth, Fernanda Seixas, Rita Ferreira, Ana I. Faustino-Rocha, Paula A. Oliveira, José Alberto Duarte

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D-DDPM: Deep Denoising Diffusion Probabilistic Models for Lesion Segmentation and Data Generation in Ultrasound Imaging by Abdalrahman Alblwi, Saleh Makkawy, Kenneth E. Barner

“…In addition to performing segmentation, D-DDPM generates synthetic data, augmenting existing real datasets to improve data size with a diverse range of high-quality samples. …”
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Fourier coefficients-based stepwise Bayesian inversion for elastic and fracture parameters using azimuthal seismic data by Jingkun Sui, Haowen Xu, Sheng Chen, Xiaodong Zheng, Xinpeng Pan

“…Both synthetic and field data applications confirm the robustness and effectiveness of the proposed Fourier coefficients-based stepwise Bayesian inversion method for estimating elastic and fracture parameters in naturally fractured reservoirs.…”
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Effect of DEM Used for Terrain Correction on Forest Windthrow Detection Using COSMO SkyMed Data by Michele Dalponte, Daniele Marinelli, Yady Tatiana Solano-Correa

“…Preprocessing Synthetic Aperture Radar (SAR) data is a crucial initial stage in leveraging SAR data for remote sensing applications. …”
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Large-scale urban building function mapping by integrating multi-source web-based geospatial data by Wei Chen, Yuyu Zhou, Eleanor C. Stokes, Xuesong Zhang

“…Due to the limited availability of socio-economic geospatial data, it is more challenging to map building functions than building morphological information, especially over large areas. …”
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Stochastic Technique on Assigning Adaptive Minimal Code Bits to Locally Frequent Symbols in Continuous Data Stream by Taiki Kato, Shinichi Yamagiwa

“…As increasing demands for recognizing social environment and/or human activity using sensory devices and video cameras, streaming data has become one of major data types. The applications process the data stream and generate new knowledge due to recent AI technologies. …”
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Development of an IoT-based MANET for Healthcare Monitoring System Using Data Loss Aware Routing Protocol by K. Balasubramanian, S. Senthilkumar, N. Kopperundevi, S. Sivakumar

“…In this article, we suggest an optimal cluster founded data loss aware routing protocol, MANET-IoT, for healthcare monitoring systems (OCDL-HM). …”
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Triage Data-Driven Prediction Models for Hospital Admission of Emergency Department Patients: A Systematic Review by Hyun A Shin, Hyeonji Kang, Mona Choi

“…Studies were selected if they developed or validated predictive models for hospital admission using triage data from adult ED patients. Data extraction adhered to the CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), and the risk of bias was evaluated using PROBAST (Prediction model Risk of Bias Assessment Tool). …”
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Deconvolution of expression microarray data reveals 131I-induced responses otherwise undetected in thyroid tissue. by Britta Langen, Nils Rudqvist, Johan Spetz, Khalil Helou, Eva Forssell-Aronsson

“…These findings indicate that deconvolution can optimize microarray data analysis of heterogeneous sample material for biomarker screening or other clinical applications.…”
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MosaicFormer: A Novel Approach to Remote Sensing Spatiotemporal Data Fusion for Lake Water Monitors by Dongxue Zheng, Aifeng Lv

“…Testing on public benchmarks demonstrated that our method outperforms all traditional approaches, achieving robust data fusion with an overall R² of 0.77. …”
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Exploring Data Traceability Methods in Information Management Within Universities: An Action Research and Case Study Approach by Huang Chen, Zhenying Hu

“…The system is designed for ease of implementation, management, and use, and has been optimized for the unique operational needs of higher education institutions.This research adopts a combination of action research and case study methodologies, starting with small-scale trials to assess system performance before expanding the scope to gather data from broader applications. In addition, this paper introduces the concept of tiered data management for the education sector, offering valuable insights into data classification and traceability within university information systems. …”
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Super Resolution Reconstruction of Mars Thermal Infrared Remote Sensing Images Integrating Multi-Source Data by Chenyan Lu, Cheng Su

“…It optimizes the quality of existing data, increasing the resolution of the original thermal infrared images by four times. …”
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FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments by Bruno Ramos-Cruz, Francisco J. Quesada-Real, Javier Andreu-Pérez, Jessica Zaqueros-Martinez

“…One key issue is data redundancy, where identical data is stored several times because it is captured by multiple sensors. …”
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A Signal-Based Data Fusion Approach in Non-DestructiveTesting of Composite Materials in the Aerospace Industry by Tom Avikasis Cohen, Anna Brook

“…By combining multiple signals, data fusion and deep learning improve NDT reliability, offering a comprehensive understanding of material integrity. …”
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