An open paradigm dataset for intelligent monitoring of underground drilling operations in coal mines by Pengzhen Zhao, Xichao Wang, Shuainan Yu, Xiangqing Dong, Baojiang Li, Haiyan Wang, Guochu Chen

“…The results indicate the proposed dataset highlights areas for improvement in algorithmic models and fills the data gap in the coal mining, providing valuable resources for developing coal mine safety monitoring.…”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah, Seifeddine Bouallegue, Ridha Bouallegue

“…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …”
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Integrating artificial intelligence into thermodynamics: A new paradigm for sustainable future by Marwan Al-Raeei

“…By integrating machine learning algorithms and statistical techniques into predictive modeling, we demonstrate that it is possible to develop highly accurate models that forecast performance based on historical data. …”
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Enhancing Visitor Forecasting with Target-Concatenated Autoencoder and Ensemble Learning by Ray-I Chang, Chih-Yung Tsai, Yu-Wei Chang

“…Regression models, on the other hand, face challenges when dealing with high-dimensional data. …”
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Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review by Yasmin Abdelaal, Michaël Aupetit, Abdelkader Baggag, Dena Al-Thani

“…Post hoc methods such as Shapley Additive Explanations have gained traction for their adaptability in explaining complex algorithms visually. However, user evaluation remains an area in which improvement is needed, and involving users in the development process can contribute to more transparent and reliable artificial intelligence models in health care applications. …”
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AI-powered Somatic Cancer Cell Analysis for Early Detection of Metastasis: The 62 principal Cancer Types by Sandile Buthelezi, Solly Matshonisa Seeletse, Taurai Hungwe, Vimbai Mbirimi-Hungwe

“…Background: Early detection of metastasis is critical in improving survival outcomes in cancer patients, with artificial intelligence offering advanced tools for predictive analytics. …”
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Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…The rapid development of deep learning technology, especially the introduction of self-attention Transformer models, has greatly improved the accuracy of cloud detection tasks while achieving efficient processing of large-scale remote sensing images. …”
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Bridging Plant Biotechnology and Additive Manufacturing: A Multicriteria Decision Approach for Biopolymer Development by Aarthi S., Raja S., Maher Ali Rusho, Simon Yishak

“…The research consolidates knowledge from recent developments in genetic modification, enzymatic polymerization, and artificial intelligence (AI)–based computational modeling to demonstrate improved polymer characteristics, such as improved tensile strength, improved interlayer adhesion, and improved thermal resistance. …”
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The Role of Time in Facial Dynamics and Challenges in Automatic Emotion Recognition (2019–2024) by Williams Contreras-Higuera, Lucrezia Crescenzi-Lanna

“…It also addresses the limitations of current models, including cultural biases and the need for large, diverse datasets. …”
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Investigation of the impact of service parameters on the degree of passenger satisfaction based on the application of the apparatus of neural networks by S. S. Pastukhov, K. V. Stel’Mashenko

“…Based on the analysis of the advantages and disadvan-luation models has been identified and justified. These models could tages of various methodological approaches to the search for ways be used to guide management to implement several areas of service to increase the quality of service existing in the marketing practice of improvement at the same time, and also to make efficient decisions in the passenger complex, the need for further development of such the context of possible synergies between the multiple aspects of the robust nonparametric mechanisms for constructing predictive va-service being investigated in their impact on customer satisfaction. …”
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Assessing the Risk of Artificial Intelligence Impact on Decision-Making Automation in Digital Businesses by Mioara Chirita, George Chirita

“…The results indicate strong governance structures, open algorithmic audits, and flexible regulatory laws as ways for companies to reduce these risks. …”
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A review on multi-fidelity hyperparameter optimization in machine learning by Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

“…Tuning hyperparameters effectively is crucial for improving the performance of machine learning models. …”
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Joint Channel Assignment and Routing in Multiradio Multichannel Wireless Mesh Networks: Design Considerations and Approaches by Omar M. Zakaria, Aisha-Hassan A. Hashim, Wan H. Hassan, Othman O. Khalifa, M. Azram, Lalitha B. Jivanadham, Mistura L. Sanni, Mahdi Zareei

“…Multiradio wireless mesh network is a promising architecture that improves the network capacity by exploiting multiple radio channels concurrently. …”
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Advanced Wildfire Prediction in Morocco: Developing a Deep Learning Dataset From Multisource Observations by Ayoub Jadouli, Chaker El El Amrani

“…Our best-performing models achieve an accuracy of up to 90%, significantly improving upon traditional approaches. …”
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SurfILE: An Open-Source Python Package for Surface Topography Analysis by Andrea Giura, Massimo Zucco, Luigi Ribotta

“…There are also freely available tools, including open-source options, that provide a variety of algorithms and methods. The rapid growth of investigations aimed at better understanding the effects of the microscale phenomena requires the improved traceable calibration of samples, the development of new methodologies and measuring techniques, and the specification of new mathematical models and processing techniques. …”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…The study considers the creation of ensembles combining different Convolutional Neural Network (CNN) models and transformer architectures to understand whether different optimization algorithms can result in more robust and efficient classification across various plankton datasets. …”
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MASIP: A Methodology for Assets Selection in Investment Portfolios by José Purata-Aldaz, Juan Frausto-Solís, Guadalupe Castilla-Valdez, Javier González-Barbosa, Juan Paulo Sánchez Hernández

“…This paper proposes a Methodology for Assets Selection in Investment Portfolios (MASIP) focused on creating investment portfolios using heuristic algorithms based on the Markowitz and Sharpe models. …”
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The classification method of donkey breeds based on SNPs data and machine learning by Dekui Li, Dekui Li, Xiaolong Hu, Yongdong Peng

“…A method for accurately classifying donkey breeds has been developed by integrating single nucleotide polymorphism (SNPs) data with machine learning algorithms. The approach includes preprocessing donkey genomic sequencing data, addressing data imbalance with the Synthetic Minority Over-sampling Technique (SMOTE), and utilizing an improved Leave-One-Out Cross-Validation (LOOCV) for dataset partitioning. …”
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Lessons from a Space Lab: An Image Acquisition Perspective by Leo Pauly, Michele Lynn Jamrozik, Miguel Ortiz del Castillo, Olivia Borgue, Inder Pal Singh, Mohatashem Reyaz Makhdoomi, Olga-Orsalia Christidi-Loumpasefski, Vincent Gaudillière, Carol Martinez, Arunkumar Rathinam, Andreas Hein, Miguel Olivares-Mendez, Djamila Aouada

“…The use of deep learning (DL) algorithms has improved the performance of vision-based space applications in recent years. …”
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Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining by Xinfeng Zhao, Binghui Dong, Shengwen Dong, Wuyi Ming

“…The review systematically compares the advantages and disadvantages of traditional methods and AI models in terms of nonlinear modeling capabilities, adaptability, and generalization. …”
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