Formal description model and conditions for detecting linked coupling faults of the memory devices by V. N. Yarmolik, D. V. Demenkovets, V. V. Petrovskaya, A. A. Ivaniuk

“…The aim of the work is to develop and analyze a formal model for describing complex linked coupling faults of memory devices and to formulate the necessary and sufficient conditions for their detection. The relevance of these studies lies in the fact that modern memory devices, characterized by a large amount of stored data and manufactured according to the latest technological standards, are distinguished by the manifestation of complex types of faults in them.Methods. …”
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Detecting Stellar Coronal Mass Ejections via Coronal Dimming in the Extreme Ultraviolet by James Paul Mason, Allison Youngblood, Kevin France, Astrid M. Veronig, Meng Jin

“…In this work, we present a tool to explore the stellar-CME detection parameter space. Our tool shows that with an instrument with performance similar to ESCAPE, setting a 600 s integration period, and integrating the spectra into bands, any star with a X-ray flux ≥2.51 × 10 ^−12 erg s ^−1 cm ^−2 should have a ≥3 σ detection even for a modest few-percent dimming profile, regardless of ISM attenuation. …”
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Iridium oxide-based biosensors: A novel method for ESBL detection and quantification by Miss Jennifer Lawrence, Professor Mark Sutton, Professor Danny O'Hare, Professor Alison Holmes, Dr Timothy Miles Rawson

“…After 2 minutes, open circuit potentials were recorded, and data analysed by plotting potential changes over time. …”
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Genetic programming support vector machine model for a wireless intrusion detection system by A. Dhoot, A. N. Nazarov, I. M. Voronkov

“…The most important requirement for such a system consists in its operation on various unbalanced sets of attack data, which use different intrusion techniques. …”
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Data anomaly repair method based on fuzzy voting and multi-segment interpolation by Yanling Lv, Qingdong Han, Shulei Xue

“…Consequently, this paper proposes a comprehensive data processing workflow, encompassing both anomaly detection and data interpolation, to preprocess data for wind farms effectively. …”
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Inception networks, data augmentation and transfer learning in EEG-based photosensitivity diagnosis by Fernando Moncada Martins, Víctor M González, José R Villar, Beatriz García López, Ana Isabel Gómez-Menéndez

“…A data augmentation (DA) technique is also applied to balance the available data set, evaluating its effects on the DL models. …”
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Seasonal and hospital settings variations in antimicrobial resistance among clinical isolates from cardiac patients: insights from a 7-Year study by Muhammad Umer Asghar, Arsalan Haseeb Zaidi, Muhammad Tariq, Noor Ul Ain

“…Abstract Background Antimicrobial resistance (AMR) is a growing global health challenge, particularly in specialized tertiary care settings. Despite its significance, data on the effects of seasonal variations, demographics, and healthcare settings on AMR in Pakistan are scarce. …”
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Convolutional kernel-based classification of industrial alarm floods by Gianluca Manca, Alexander Fay

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Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data by Bei Liu, Xiao Wang, Zhaoxin Zhang, Zhenjie Zhao, Xiaoming Wang, Ting Liu

“…Fault prediction of hydropower station is crucial for the stable operation of generator set equipment, but the traditional method struggles to deal with data with an imbalanced distribution and untrustworthiness. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Results showed outlier detection reduced extreme values, improving data distribution. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…The results were based on a set of three drilled oil wells, namely, West Kazakhstan region, Mangystau, publicly available well log dataset. …”
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Prediction of bloodstream infection using machine learning based primarily on biochemical data by Ramtin Zargari Marandi, Frederik Boetius Hertz, Jesper Qvist Thomassen, Steen Christian Rasmussen, Ruth Frikke-Schmidt, Niels Frimodt-Møller, Karen Leth Nielsen, Cameron Ross MacPherson

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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data by Maksym A. Jopek, Krzysztof Pastuszak, Sebastian Cygert, Myron G. Best, Thomas Wurdinger, Jacek Jassem, Anna J. Zaczek, Anna Supernat

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Analysis of follow-up data in large biobank cohorts: a review of methodology by Anastassia Kolde, Anastassia Kolde, Merli Koitmäe, Merli Koitmäe, Meelis Käärik, Märt Möls, Krista Fischer, Krista Fischer

“…This study focuses on key methodological challenges in genome-wide association studies (GWAS) of biobank data with time-to-event outcomes, analyzed using the Cox proportional hazards (CPH) model. …”
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Jordanian banknote data recognition: A CNN-based approach with attention mechanism by Ahmad Nasayreh, Ameera S. Jaradat, Hasan Gharaibeh, Waed Dawaghreh, Rabia Mehamad Al Mamlook, Yaqeen Alqudah, Qais Al-Na'amneh, Mohammad Sh. Daoud, Hazem Migdady, Laith Abualigah

“…The study made use of a data set from Kaggle that includes a collection of Jordanian banknotes in five different denominations. …”
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Performance of Deep Learning-Based Algorithm for Detection of Pediatric Intussusception on Abdominal Ultrasound Images by Zheming Li, Chunze Song, Jian Huang, Jing Li, Shoujiang Huang, Baoxin Qian, Xing Chen, Shasha Hu, Ting Shu, Gang Yu

“…Results. The data of pediatric intussusception were divided into a training set and validation set according to the ratio of 8 : 2, with training set (298 pediatric intussusception) and validation set (75 pediatric intussusception and 67 normal cases). …”
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Applying AI to Structured Real-World Data for Pharmacovigilance Purposes: Scoping Review by Stella Dimitsaki, Pantelis Natsiavas, Marie-Christine Jaulent

“…The included studies were “mapped” against a set of evaluation criteria, including applied AI approaches, code availability, description of the data preprocessing pipeline, clinical validation of AI models, and implementation of trustworthy AI criteria following the guidelines of the FUTURE (Fairness, Universality, Traceability, Usability, Robustness, and Explainability)-AI initiative. …”
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Hearts, Data, and Artificial Intelligence Wizardry: From Imitation to Innovation in Cardiovascular Care by Panteleimon Pantelidis, Polychronis Dilaveris, Samuel Ruipérez-Campillo, Athina Goliopoulou, Alexios Giannakodimos, Panagiotis Theofilis, Raffaele De Lucia, Ourania Katsarou, Konstantinos Zisimos, Konstantinos Kalogeras, Evangelos Oikonomou, Gerasimos Siasos

“…AI models have demonstrated remarkable success in early dis-ease detection, such as predicting heart failure from standard ECGs before symptom on-set, distinguishing genetic cardiomyopathies, and forecasting arrhythmic events. …”
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MuPETFlow: multiple ploidy estimation tool from flow cytometry data by C. Gómez-Muñoz, G. Fischer

“…Abstract Background Ploidy, representing the number of homologous chromosome sets, can be estimated from flow cytometry data acquired on cells stained with a fluorescent DNA dye. …”
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Inference of population splits and mixtures from genome-wide allele frequency data. by Joseph K Pickrell, Jonathan K Pritchard

“…While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. …”
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