Novel application of unsupervised machine learning for characterization of subsurface seismicity, tectonic dynamics and stress distribution by Mohammad Salam, Muhammad Tahir Iqbal, Raja Adnan Habib, Amna Tahir, Aamir Sultan, Talat Iqbal

“…Employing a diverse range of clustering algorithms, with particular emphasis on Fuzzy C-Means (FCM), our research meticulously dissects the intricate physical processes that govern a complex tectonic zone. …”
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Planning and layout of tourism and leisure facilities based on POI big data and machine learning. by Shifeng Wu, Jiangyun Wang, Yinuo Jia, Jintian Yang, Jixiu Li

“…Drawing on POI and demographic data, and considering the distribution patterns of existing tourism and leisure facilities, this research applies machine learning to quantitatively simulate the optimal siting of such amenities. …”
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Artificial Intelligence in Radiology and Medical Imaging in Romania: Current Applications and Future Perspectives by Ioana Andreea GHEONEA

“…In lung imaging, deep learning algorithms have improved the identification and segmentation of pulmonary nodules, aiding in early lung cancer detection. …”
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Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las... by Jingyi Liu, Yuxuan Cai, Xiwei Shen

“…Over the past two decades, research on residential segregation and environmental justice has evolved from spatial assimilation models to include class theory and social stratification. …”
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Blood biomarker discovery for autism spectrum disorder: A proteomic analysis. by Laura Hewitson, Jeremy A Mathews, Morgan Devlin, Claire Schutte, Jeon Lee, Dwight C German

“…Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and social interaction and restricted, repetitive patterns of behavior, interests, or activities. Given the lack of specific pharmacological therapy for ASD and the clinical heterogeneity of the disorder, current biomarker research efforts are geared mainly toward identifying markers for determining ASD risk or for assisting with a diagnosis. …”
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Layer-by-Layer Multifractal Scanning of Optically Anisotropic Architectonics of Blood Plasma Films: Fundamental and Applied Aspects by Alexander Ushenko, Natalia Pavlyukovich, Oksana Khukhlina, Olexander Pavlyukovich, Mykhaylo Gorsky, Iryna Soltys, Alexander Dubolazov, Yurii Ushenko, Olexander Salega, Ivan Mikirin, Jun Zheng, Zhebo Chen, Lin Bin

“…In the proposed model, algorithms were developed to relate the real and imaginary parts of the complex elements of the Jones matrix to the theziograms of linear and circular birefringence. …”
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Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

“…This study addresses these challenges by integrating human-inspired metaheuristics with non-parametric machine-learning techniques to enhance groundwater potential prediction. This research introduces a novel approach combining human-based metaheuristics—Teaching Learning Based Optimization (TLBO) and Cultural Algorithms (CA)—with non-parametric Decision Tree (DT) models. …”
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La Teoría del andamiaje como herramienta de construcción del pensamiento matemático by Cesar Orlando Vargas Mantilla, Sonia Maritza Mendoza Lizcano, Wlamyr Palacios Alvarado

“…Therefore, it is necessary to analyze the teaching-learning processes, and more specifically, the construction of mathematical thinking, from an innovative and agile perspective that breaks with traditional learning patterns of repeating algorithms and implementing formulas. …”
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Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

“…Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. …”
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Identification Method of Dynamic Propagation Process of Rock Fracture Based on Ground Penetrating Radar by CHEN Jun, ZHANG Bo, ZHUANG Xingyue, SONG Zhishu, ZHENG Jun

“…However, challenges remain in addressing the heterogeneity of fracture fillings, the dynamic coupling effects in multi-fracture systems, and the rapid interpretation of large-scale monitoring data. Future research should focus on developing advanced algorithms to suppress interference from non-uniform fillings, resolve dynamic coupling mechanisms, and improve the accuracy of vertical trajectory inversion. …”
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Application of Machine Learning Techniques for Bearing Fault Diagnosis by Sarra Eddai, Nabih Feki, Ahmed Ghorbel, Abdelkhalak El Hami, Mohamed Haddar

“…Machine learning enhances machine diagnostics through advanced data analysis, pattern recognition, and fault prediction. This study investigates the application of machine learning algorithms for bearing fault detection. …”
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Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision by Sang Wha Kim, Adams Hei Long Yuen, Hyun Woo Kim, Seyoung Lee, Sung Bin Lee, Young Min Lee, Won Joon Jung, Cherry Tsz Ching Poon, Dasol Park, Sangyun Kim, Sang Guen Kim, Jung Woo Kang, Jun Kwon, Su Jin Jo, Sib Sankar Giri, Hyunjung Park, Jong-pil Seo, Deok-Soo Kim, Byung Yeop Kim, Se Chang Park

“…The processed scans were reconstructed using bone reconstruction algorithms to enable precise craniofacial measurements. …”
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Enhanced gait tracking measures for individuals with stroke using leg-worn inertial sensors by Francesco Lanotte, Shusuke Okita, Megan K. O’Brien, Arun Jayaraman

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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

“…Our results show that the Random Forest algorithm achieved the highest accuracy with 98 %.This research shows how machine learning techniques embedded in learning analytics could expand the functionalities of VLEs toward greater personalization and effectiveness, with every student receiving the best educational experience that suits their learning styles.…”
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Macro-Modelling of Rib-Knitted Tubular Parts by Tetiana Ielina, Liudmyla Halavska, Nataliia Ausheva

“… The aim of the research was to improve the process of knitted products design. …”
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Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding by Huan Liang, Xiao Liang, Man Zheng, Shoudong Wang

“…Conclusions This research elucidates the complex relationship between KLRD1 and AS, underscoring its potential as a novel biomarker for diagnosing and monitoring the disease.…”
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Artificial Neural Network for Air Pollutant Concentration Predictions Based on Aircraft Trajectories over Suvarnabhumi International Airport by Patcharin Kamsing, Chunxiang Cao, Wuttichai Boonpook, Sornkitja Boonprong, Min Xu, Pisit Boonsrimuang

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A Hardware Accelerator for Real-Time Processing Platforms Used in Synthetic Aperture Radar Target Detection Tasks by Yue Zhang, Yunshan Tang, Yue Cao, Zhongjun Yu

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Review: Multiobject tracking in livestock − from farm animal management to state-of-the-art methods by M.H. Nidhi, K. Liu, K.J. Flay

“…The use-cases, datasets, and algorithms of MOT applied to livestock were thoroughly examined. …”
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