A Review of AI Applications in Unconventional Oil and Gas Exploration and Development by Feiyu Chen, Linghui Sun, Boyu Jiang, Xu Huo, Xiuxiu Pan, Chun Feng, Zhirong Zhang

“…However, challenges such as data quality, model generalization, and interpretability remain significant. …”
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Advantages of trend analysis in stability studies for prediction of potential OOS result within estimated shelflife of medicinal product by Milena Nanov, Sanja Despotovska, Gordana Mitrovska, Vasilka Dubrova Koceva, Jelena Acevska

“…Identifying potential issues such as potential out-of-specification (OOS) results and ensuring data quality is often facilitated by employing objective methods for trend analysis of stability data. …”
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Absorption Efficiency Assessment and Uncertainty Measurement of the Sodium Arsenite Method for Ambient NO2 Determination by Rishu Agarwal, Shankar G. Aggarwal

“…The use of at least three absorbers/impingers (connected in series) instead of one to obtain absorption efficiency close to unity is proposed to make the reference method independent from the use of absorption efficiency factor thus ensuring the improved data quality and comparability.…”
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Enhanced Intrusion Detection in Drone Networks: A Cross-Layer Convolutional Attention Approach for Drone-to-Drone and Drone-to-Base Station Communications by Mohammad Aldossary, Ibrahim Alzamil, Jaber Almutairi

“…Preprocessing methods like weighted differential scaling and gradient-based adaptive resampling improve data quality and reduce class imbalances. Contextual attribute transformation captures the nuanced network behaviors needed for anomaly identification. …”
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Gene Selection Based Cancer Classification With Adaptive Optimization Using Deep Learning Architecture by Anju Das, N. Neelima, K. Deepa, Tolga Ozer

“…In the existing works, certain limitations, such as reduced performance due to degraded data quality, high storage space requirements, overfitting issues, and lack of robustness, can compromise overall classification accuracy. …”
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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

“…A total of 432,230 Landsat scenes were processed, enhancing data quality and accuracy. The dataset was validated using 255,000 samples across 6 geographical regions, showing strong performance in capturing spatiotemporal NDVI variations. …”
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AI-Driven precision in solar forecasting: Breakthroughs in machine learning and deep learning by Ayesha Nadeem, Muhammad Farhan Hanif, Muhammad Sabir Naveed, Muhammad Tahir Hassan, Mustabshirha Gul, Naveed Husnain, Jianchun Mi

“…By addressing challenges related to data quality and model interpretability, this review underscores the importance of continuous innovation in solar forecasting techniques to fully realize their potential. …”
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Construction and Application of Enterprise Internal Audit Data Analysis Model Based on Decision Tree Algorithm by Yuna Si

“…In order to solve many problems in traditional auditing, this paper realizes the interface of data dictionary attributes through effective domain management of multisystem data, so as to achieve the purpose of system support and effective management to improve data quality. Furthermore, the platform is extensible, which can gradually expand the data coverage and support more management fields and business systems. …”
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Fusing MODIS and AVHRR products to generate a global 1-km continuous NDVI time series covering four decades by Xiaobin Guan, Huanfeng Shen, Yuchen Wang, Dong Chu, Xinghua Li, Linwei Yue, Wei Li, Xinxin Liu, Liangpei Zhang

“…The Advanced Very High-Resolution Radiometer (AVHRR) instrument can provide the longest continuous time series since 1982, but with the drawback of coarse spatial resolution and poor data quality. To address this issue, a spatiotemporal fusion-based long-term NDVI product (STFLNDVI) since 1982 was generated in this study at a 1-km spatial resolution with monthly intervals, by fusing with the Moderate Resolution Imaging Spectroradiometer (MODIS) data. …”
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Systems science and systems thinking for public health: a systematic review of the field by Gemma Carey, Brad Crammond, Eleanor Malbon, Nicole Carey, Andrew Joyce, Alan Carey

“…The assessment of data quality was intrinsic to the goals of the review itself, and therefore, was carried out as part of the analysis.Results 4 categories of research were identified from the review, ranging from editorial and commentary pieces to complex system dynamic modelling. …”
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SAR Radiometric Cross-Calibration Based on Multiple Pseudoinvariant Calibration Sites With Extensive Backscattering Coefficient Range by Yongsheng Zhou, Xiang Chen, Qiang Yin, Fei Ma, Fan Zhang

“…It employs weighted least squares regression for the different data quality of each site. The cross-calibration experiments demonstrate an average improvement in the accuracy of 0.82 dB compared to the cross-calibration method utilizing a single PICS site.…”
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Classification of disinformation in hybrid warfare: an application of XLNet during the Russia’s war against Ukraine by Halyna Padalko, Vasyl Chomko, Sergiy Yakovlev, Plinio Pelegrini Morita

“…Results showed that accuracy initially improved with increasing data volume but declined slightly with numerous datasets, suggesting the need for balancing data quality and quantity. The proposed methodology addresses the gaps in automated disinformation detection by integrating transformer-based models with advanced preprocessing and training techniques. …”
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Classification Algorithms in Automatic Diagnosis of ECG Arrhythmias: A Review by Haibo Sun, Dan Luo, Xin Niu, Xiaoxi Zeng, Bin Zheng, Hao Liu, Jingye Pan

“…This paper summarizes the selected research results in the field of arrhythmia classification under the same database from the perspective of data quality, evaluation paradigm and performance indicators, and discusses the correlation between the specific characteristics of arrhythmia detection and different classification algorithms. …”
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Enhancing Particulate Matter Estimation in Livestock-Farming Areas with a Spatiotemporal Deep Learning Model by Dohyeong Kim, Heeseok Kim, Minseon Hwang, Yongchan Lee, Choongki Min, Sungwon Yoon, Sungchul Seo

“…Air dispersion models, commonly employed to estimate particulate matter (PM) levels, are heavily reliant on data quality, resulting in varying levels of accuracy. …”
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Fault Detection and Diagnosis in Industry 4.0: A Review on Challenges and Opportunities by Denis Leite, Emmanuel Andrade, Diego Rativa, Alexandre M. A. Maciel

“…While ML-based RT-FDD offers different benefits, including fault prediction accuracy, it faces challenges in data quality, model interpretability, and integration complexities. …”
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MMFW-UAV dataset: multi-sensor and multi-view fixed-wing UAV dataset for air-to-air vision tasks by Yang Liu, Zhihao Sun, Lele Xi, Lele Zhang, Wei Dong, Chen Chen, Maobin Lu, Hailing Fu, Fang Deng

“…MMFW-UAV contains a total of 147,417 fixed-wing UAVs images captured by multiple types of sensors (zoom, wide-angle, and thermal imaging sensors), displaying the flight status of fixed-wing UAVs of different sizes, appearances, structures, and stabilized flight velocities from multiple aerial perspectives (top-down, horizontal, and bottom-up views), aiming to cover the full-range of perspectives with multi-modal image data. Quality control processes of semi-automatic annotation, manual check, and secondary refinement are performed on each image. …”
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The Mediating Role of Emotional Intelligence in the Organisational Commitment and Turnover Intention of Clinical Nurses: A Cross‐Sectional Study by Han Lingyu, Li Ruiling, Wang Yiman, Liu Yafeng, Bai Xiaolu

“…It is important to note that the research upholds the highest standards of integrity, with a meticulous review process and a dedicated effort to maintain data quality.…”
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Addressing Data Imbalance in Crash Data: Evaluating Generative Adversarial Network’s Efficacy Against Conventional Methods by Bei Zhou, Qianxi Zhou, Zongzhi Li

“…The pivotal findings reveal that: 1) CTGAN markedly outperforms other data resampling techniques in generating superior quality synthetic data, particularly for the least represented injury severity category; 2) While CTGAN demonstrates substantial improvements over traditional data resampling methods in classification model performance, this advantage diminishes as the number of injury categories increases; 3) Surprisingly, CTGAN’s superior data quality does not result in better classification performance compared to cost-sensitive learning, especially in more complex classification scenarios. …”
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Error Characteristic Analysis and Filtering Algorithm for GNSS Time-Series Data by Hongli Zhang, Yijin Chen, Kemeng Li, Yinggang Wang

“…Using filtering methods, the data quality can be improved. Through the analysis of the experimental data in this study, it was found that the variation patterns of measurement data obtained by devices of the same accuracy during the same time period are generally consistent. …”
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DR-Z2AN: dual-recurrent neural network with a tri-channel attention mechanism for financial management prediction by Salem Knifo, Ahmad Alzubi

“…The established methods for financial management prediction have some flaws, such as the requirement of labeled data, data quality, time complexity, under fitting problems, and longer execution times. …”
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