On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…Recently, machine and deep learning techniques are being used widely to detect thieves by analysing the consumption patterns. While the prediction accuracy of these methods depends on the number and quality of the existing samples used for training models, the majority of previous research work focussed on data with high sampling frequencies, for example, data from smart grids. …”
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Machine learning models for reinjury risk prediction using cardiopulmonary exercise testing (CPET) data: optimizing athlete recovery by Arezoo Abasi, Ahmad Nazari, Azar Moezy, Seyed Ali Fatemi Aghda

“…Machine learning (ML) algorithms offer promising capabilities in uncovering complex patterns within this data, allowing for more accurate injury risk assessment. …”
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Decoding bacterial methylomes in four public health-relevant microbial species: nanopore sequencing enables reproducible analysis of DNA modifications by Valentina Galeone, Johanna Dabernig-Heinz, Mara Lohde, Christian Brandt, Christian Kohler, Gabriel E. Wagner, Martin Hölzer

“…We investigated distinct methylation patterns within and between species, focusing on heavily modified genes or genomic regions. …”
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High-Speed 3D Vision Based on Structured Light Methods by Leo Miyashita, Satoshi Tabata, Masatoshi Ishikawa

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Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems by Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso

“…Overall, this review outlines current innovations and future research directions essential for advancing personalized, efficient, and accessible fertility care.…”
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Design of Trabecular Bone Mimicking Voronoi Lattice-Based Scaffolds and CFD Modelling of Non-Newtonian Power Law Blood Flow Behaviour by Haja-Sherief N. Musthafa, Jason Walker

“…Designing scaffolds similar to the structure of trabecular bone requires specialised algorithms. Existing scaffold designs for bone tissue engineering have repeated patterns that do not replicate the random stochastic porous structure of the internal architecture of bones. …”
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Enhancing Latent Defect Detection in Built-In Spindle Assembly Lines Through Vibration Data Analysis by Kuo-Hao Li, Chao-Nan Wang, Yao-Chi Tang

“…The inclusion of the DBI in the k-means++ clustering algorithm facilitated an objective evaluation of cluster quality, ensuring that the selected number of clusters accurately represents the underlying data patterns. …”
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Implementation of Several Data Mining Strategies on Electronic Nose Data for Identifying Gluten in Cheese by Mohammad Nasiri-Galeh, Mahdi Ghasemi-Varnamkhasti

“…It is  not enough to make decisions and judge the data unless discovering the relationships and patterns between the data obtained to determine the relation of new data recorded by the device to the type of cheese, For this purpose, data mining and machine learning methods have been used in this research. …”
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Deploying an Educational Mobile Robot by Dorina Plókai, Borsa Détár, Tamás Haidegger, Enikő Nagy

“…The focus is on statistical analysis and identifying correlations between diverse datasets. The research utilized the PlatypOUs mobile robot platform, equipped with odometry and inertial measurement units (IMUs), to gather comprehensive motion data. …”
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Image-Based Malware Detection Using Deep CNN Models by hawraa omran musa, Muhanad Tahrir Younis

“…Deep learning (DL) presents a promising strategy for malware detection by utilizing advanced algorithms that are capable of discerning intricate patterns from extensive datasets. …”
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Machine Learning‐Assisted Simulations and Predictions for Battery Interfaces by Zhaojun Sun, Xin Li, Yiming Wu, Qilin Gu, Shiyou Zheng

“…This review highlights recent progress in ML‐assisted simulations and predictions at battery interfaces, illustrating how ML accelerates the research and development trajectory. By employing ML algorithms and machine vision, simulations of lithium dendrite growth, SEI formation, and interfacial dynamics can be performed. …”
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Global soil moisture mapping at 5 km by combining GNSS reflectometry and machine learning in view of HydroGNSS by Emanuele Santi, Davide Comite, Laura Dente, Leila Guerriero, Nazzareno Pierdicca, Maria Paola Clarizia, Nicolas Floury

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Artificial Intelligence−Driven Analysis Identifies Anterior Cruciate Ligament Reconstruction, Hip Arthroscopy and Femoroacetabular Impingement Syndrome, and Shoulder Instability as... by Henry B.G. Baird, B.S., William Allen, M.D., Mauricio Gallegos, M.D., Cody C. Ashy, M.D., Harris S. Slone, M.D., W. Michael Pullen, M.D.

“…Purpose: To use advanced topic modeling, specifically the Bidirectional Encoder Representations from Transformers Topic (BERTopic) Model, to analyze research topics in Arthroscopy: The Journal of Arthroscopic and Related Surgery (Arthroscopy). …”
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Integrated Evaluation and error decomposition of four gridded precipitation products using dense rain gauge observations over the Yunnan-Kweichow Plateau, China by Tianjian Lu, Qingquan Xiao, Hanyu Lu, Jintong Ren, Yongyi Yuan, Xiaoshan Luo, Zhijie Zhang

“…The study findings offer valuable insights into YKP precipitation, informing the development of grid-based fusion algorithms in the region’s complex terrain.…”
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An optimized ensemble model with advanced feature selection for network intrusion detection by Afaq Ahmed, Muhammad Asim, Irshad Ullah, Zainulabidin, Abdelhamied A. Ateya

“…However, these methods often fall short in detecting sophisticated and evolving threats, particularly those involving subtle variations or mutations of known attack patterns. To address this challenge, our study presents the “Optimized Random Forest (Opt-Forest),” an innovative ensemble model that combines decision forest approaches with genetic algorithms (GAs) for enhanced intrusion detection. …”
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Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses by Yuan Sun, Yan Li, Anlan Zhang, Tao Hu, Ming Li

“…Prognostic gene sets were screened using machine learning algorithms to construct a risk model, which was externally validated via GEO database. …”
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Abnormal eye movement, brain regional homogeneity in schizophrenia and clinical high-risk individuals and their associated gene expression profiles by Zhaobin Chen, Yangpan Ou, Yudan Ding, Ying Wang, Huabing Li, Feng Liu, Ping Li, Dongsheng Lv, Yong Liu, Bing Lang, Jingping Zhao, Wenbin Guo

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Design, assembly, alignment and application of a versatile, open-source, single-pixel microscope by Samuel I. Zapata-Valencia, Heberley Tobón-Maya, Luis Ordoñez, Andrea Farina, Jesús Lancis, Enrique Tajahuerce

“…Abstract Single-pixel microscopy (SPM) is an emerging imaging technique in which a sample is illuminated with a series of micro-structured light patterns, typically generated by a digital micromirror device (DMD). …”
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A Review of Optimization Scheduling for Active Distribution Networks with High-Penetration Distributed Generation Access by Kewei Wang, Yonghong Huang, Yanbo Liu, Tao Huang, Shijia Zang

“…This paper provides a comprehensive review of research in this domain over the past decade. Initially, it analyzes the voltage impact patterns and control principles in distribution networks under varying levels of renewable energy penetration. …”
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Integration of geospatial techniques and machine learning in land parcel prediction by Nekkanti Haripavan, Subhashish Dey, Chimakurthi Harika Mani Chandana

“…The integration of geospatial techniques and machine learning algorithms has revolutionized our ability to analyze and predict changes in land parcels. …”
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