Analysis of Receiver Operating Characteristic Curves for Cure Survival Data and Mismeasured Biomarkers by Li-Pang Chen

“…In applications, measurement errors are generally ubiquitous and ignoring measurement errors can cause unexpected bias for the estimator and lead to the wrong conclusion. …”
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Efficient Human Activity Recognition Using Machine Learning and Wearable Sensor Data by Ziwei Zhong, Bin Liu

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A Method for Automatically Locating Defects in CCTV Inspection Data of Sewer Pipes by Jun Tang, Jisheng Xia, Zhiqiang Xie, Zhaoyong Li, Yuting Zhang

“…The proposed method can be easily integrated into practical engineering applications, thereby alleviating the workload of professional technicians in obtaining the geographic locations of sewer defects in CCTV inspection data and reducing both time and labor costs associated with this process.…”
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Exploration of Large language model assisted boulder detection from Lidar data by L. Zhu, E. Hattula, J. Raninen

“…Due to the complexity of working and availability with very high-resolution data for boulder detection, few studies have explored this area. …”
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Ranking of companies in generating operating cash flows based on data envelopment analysis by Leila Negahban, Bahman Banimahd, Seyed Hosseini, Azam Shokri Cheshmeh Sabzi

“…The research method for collecting theoretical bases and research data is library studies. In this research, in order to evaluate the efficiency of pharmaceutical companies in creating operational cash flow, the Data Envelopment Analysis (DEA) model with weight limit is used. …”
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FRAME – A FRAMEwork for Objectively Measuring Fear Based on Physiological and Psychological Data by Grensing Florian, Schmücker Vanessa, Hildebrand Anne Sophie, Klucken Tim, Maleshkova Maria

“…In order to link physiological reactions with specific points in time during psychological trials, it is necessary to integrate observation data with data collected automatically by sensors, such as wearable devices. …”
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Bayesian robust symmetric regression for medical data with heavy-tailed errors and censoring. by Mehmet Ali Cengiz, Talat Şenel, Muhammed Kara

“…Bayesian symmetric regression offers a principled framework for modeling data characterized by heavy-tailed errors and censoring, both of which are frequently encountered in medical research. …”
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Analysing humanities scholars’ data seeking behaviour patterns using Ellis' model by Wenqi Li, Pengyi Zhang, Jun Wang

“…The study contributes to the conceptual growth of Ellis' model and expands its utility beyond the original information seeking contexts, indicating its potential applicability to data seeking. It also provides practical implications for system design and humanities data curation.…”
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A generic multi-lidar data batching strategy on the sensor driver level by T. Faitli, H. Hyyti, J. Hyyppä, A. Kukko, H. Kaartinen

“…Instead of traditional data batching that accumulates data packets based on the spinning angle, we propose batching based on the sampling time, which also enable us to ensure strict time alignment within the multiple lidar sources. …”
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Addressing data scarcity in nanomaterial segmentation networks with differentiable rendering and generative modeling by Dennis Possart, Leonid Mill, Florian Vollnhals, Tor Hildebrand, Peter Suter, Mathis Hoffmann, Jonas Utz, Daniel Augsburger, Mareike Thies, Mingxuan Gu, Fabian Wagner, George Sarau, Silke Christiansen, Katharina Breininger

“…To address this, we present DiffRenderGAN, a generative model that produces annotated synthetic data by integrating a differentiable renderer into a Generative Adversarial Network (GAN) framework. …”
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Harmonized Annual Averaged Traffic Data at Street Segment Level for European Cities by Xavier Bonnemaizon, Philippe Ciais, Chuanlong Zhou, Qinren Shi, Rohith Teja Mittakola, Clément Goldmann, Simon Ben Arous, Nicolas Megel, Steven J. Davis

“…To address this gap, we compiled and harmonized publicly available traffic data for 36 European cities, linking geolocalized information to road segments, spanning years from 2015 to 2024 depending on data availability. …”
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BenchMake: turn any scientific data set into a reproducible benchmark by A S Barnard

“…Benchmark data sets are a cornerstone of machine learning development and applications, ensuring new methods are robust, reliable and competitive. …”
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Context-Aware Data-Driven Intelligent Framework for Fog Infrastructures in Internet of Vehicles by Razi Iqbal, Talal Ashraf Butt, M. Omair Shafiq, Manar Wasif Abu Talib, Tariq Umar

“…These services can benefit from both variety and velocity of the generated data. This paper focuses on the data at the edge nodes to enable fog-based services that can be consumed by various IoV safety and non-safety applications. …”
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Imputation of missing data for domain mean estimation using simple random sampling by Anoop Kumar, Shashi Bhushan, Rohini Pokhrel, Amer I. Al-Omari, Ayed R.A. Alanzi, Shokrya S. Alshqaq

“…Additionally, a thorough, extensive simulation study was conducted utilizing a normally distributed population. Certain applications that contain actual data are also made available. …”
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Efficient data-driven predictive control of nonlinear systems: A review and perspectives by Xiaojie Li, Mingxue Yan, Xuewen Zhang, Minghao Han, Adrian Wing-Keung Law, Xunyuan Yin

“…In this review, we aim to provide an overview of current data-driven predictive control methods that have attributes of being computationally efficient as well as having the distinctive potential to address the above two challenges simultaneously. …”
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Electrohysterogram Data Augmentation Using Generative Adversarial Network for Pregnancy Outcome Prediction by Muhammad Omar Cheema, Zia Mohy-Ud-Din, Azhar Imran, Fawad Salam Khan, Mahmood Basil A. Al-Rawi, Mohammed A. El-Meligy, Jahan Zeb Gul

“…Analyzing electrohysterogram data, which show the electrical activity of uterine muscles, is a promising non-invasive method for classifying term and preterm pregnancies. …”
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Generative AI enables medical image segmentation in ultra low-data regimes by Li Zhang, Basu Jindal, Ahmed Alaa, Robert Weinreb, David Wilson, Eran Segal, James Zou, Pengtao Xie

“…To address this, we propose a generative deep learning framework that produces high-quality image-mask pairs as auxiliary training data. Unlike traditional generative models that separate data generation from model training, ours uses multi-level optimization for end-to-end data generation. …”
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IMpack: open source high-bandwidth data-logging inertial measurement unit by John Antolik, Daniel Harris

“… IMpack is a single-board data-logging inertial measurement unit (IMU) designed for research applications where sampling rate, compactness, and cost effectiveness are paramount. …”
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Battery System Fault Detection: A Data-Driven Aggregation and Augmentation Strategy by Zhiming Zhang, Dan Zhang, Dejun Li, Yi Liu, Jiong Yang

“…These advancements not only enable more precise battery system diagnostics but also present a generalizable paradigm for other industrial fault detection applications requiring robust performance under data constraints.…”
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Prediction of rock type from physical and mechanical properties by data mining implementations by Fatih Bayram

“…The paper’s main objective is to present the applicability of data mining algorithms in rock type determination. …”
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