Urban tourism management based on artificial neural networks analysis and data mining by Xin Cui

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Reinforcement Learning for Mitigating Malware Propagation in Wireless Radar Sensor Networks with Channel Modeling by Guiyun Liu, Hao Li, Lihao Xiong, Yiduan Chen, Aojing Wang, Dongze Shen

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Exploring Trends and Variability of Water Quality over Lake Titicaca Using Global Remote Sensing Products by Vann Harvey Maligaya, Analy Baltodano, Afnan Agramont, Ann van Griensven

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Artificial intelligence technology in ophthalmology public health: current applications and future directions by ShuYuan Chen, Wen Bai, Wen Bai

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Adaptive weighted multi-view subspace clustering method for recognizing urban functions from multi-source social sensing data by Qiliang Liu, Zexin Lu, Weihua Huan, Chong Fan

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Robotic irrigation complex for crop cultivation in irrigated areas by M. G. Zagoruiko, D.  A. Soloviev, N. F. Ryzhko, S. N. Ryzhko

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Interchangeability of hunts as a factor of sustainability of hunting use by S. P. Matveytchuk, I. A. Grebnev

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Identification of line status changes using phasor measurements through deep learning networks by N. E. Gotman, G. P. Shumilova

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CONTROL RESEARCH AND AUTOMATION OF STOCHASTIC DEVIATIONS IN ORGANISATIONAL MANAGEMENT PRODUCTION PROCESS SYSTEMS by R. B. Aghajanyan, D. O. Baizhanova, M. V. Markosyan

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Using a Camera System for the In-Situ Assessment of Cordon Dieback due to Grapevine Trunk Diseases by Julie Tang, Olivia Yem, Finn Russell, Cameron A. Stewart, Kangying Lin, Hiranya Jayakody, Matthew R. Ayres, Mark R. Sosnowski, Mark Whitty, Paul R. Petrie

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Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning by Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu

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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh, Abdulrahman Alassi, Nader Meskin, Mohammed A. Al-Hitmi, Ahmed M. Massoud

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Intra-Technology Enhancements for Multi-Service Multi-Priority Short-Range V2X Communication by Ihtisham Khalid, Vasilis Maglogiannis, Dries Naudts, Adnan Shahid, Ingrid Moerman

“…To bridge this gap, we propose intelligent Multi-Attribute Decision-Making algorithms for adaptive AC selection in ITS-G5 and RRI adjustment in C-V2X PC5, tailored to the varying priorities of active V2X services. …”
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Interactive Mitigation of Biases in Machine Learning Models for Undergraduate Student Admissions by Kelly Van Busum, Shiaofen Fang

“…Because these issues are intrinsically subjective and context-dependent, creating trustworthy software requires human input and feedback. (1) Introduction: This work introduces an interactive method for mitigating the bias introduced by machine learning models by allowing the user to adjust bias and fairness metrics iteratively to make the model more fair in the context of undergraduate student admissions. (2) Related Work: The social implications of bias in AI systems used in education are nuanced and can affect university reputation and student retention rates motivating a need for the development of fair AI systems. (3) Methods and Dataset: Admissions data over six years from a large urban research university was used to create AI models to predict admissions decisions. …”
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Machine Learning‐Enhanced Optimization for High‐Throughput Precision in Cellular Droplet Bioprinting by Jaemyung Shin, Ryan Kang, Kinam Hyun, Zhangkang Li, Hitendra Kumar, Kangsoo Kim, Simon S. Park, Keekyoung Kim

“…In this study, a high‐throughput cellular droplet bioprinter is designed, capable of printing over 50 cellular droplets simultaneously, producing the large dataset required for effective machine learning training. Among the five algorithms evaluated, the multilayer perceptron model demonstrates the highest prediction accuracy, while the decision tree model offers the fastest computation time. …”
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Ethical Challenges and Opportunities of AI in End-of-Life Palliative Care: Integrative Review by Abel García Abejas, David Geraldes Santos, Fabio Leite Costa, Aida Cordero Botejara, Helder Mota-Filipe, Àngels Salvador Vergés

“…While AI shows promise for improving efficiency and personalization, consolidated real-world examples of efficiency and equity remain scarce. Key risks include algorithmic bias, cultural insensitivity, and the potential for reduced patient autonomy. …”
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Precision Medicine in Hematologic Malignancies: Evolving Concepts and Clinical Applications by Rita Khoury, Chris Raffoul, Christina Khater, Colette Hanna

“…Complementary tools such as liquid biopsy and minimal residual disease (MRD) monitoring have improved diagnosis, risk stratification, and therapeutic decision making. We discuss major molecular targets and personalized strategies across hematologic malignancies: <i>FLT3</i> and <i>IDH1/2</i> in acute myeloid leukemia (AML); Philadelphia chromosome–positive and Ph-like subtypes in acute lymphoblastic leukemia (ALL); <i>BCR-ABL1</i> in chronic myeloid leukemia (CML); <i>TP53</i> and <i>IGHV</i> mutations in chronic lymphocytic leukemia (CLL); molecular subtypes and immune targets in diffuse large B-cell lymphoma (DLBCL) and other lymphomas; and B-cell maturation antigen (BCMA) in multiple myeloma. …”
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Classification of Heart Failure Using Machine Learning: A Comparative Study by Bryan Chulde-Fernández, Denisse Enríquez-Ortega, Cesar Guevara, Paulo Navas, Andrés Tirado-Espín, Paulina Vizcaíno-Imacaña, Fernando Villalba-Meneses, Carolina Cadena-Morejon, Diego Almeida-Galarraga, Patricia Acosta-Vargas

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Prediction of the Cause of Fundus-Obscuring Vitreous Hemorrhage Using Machine Learning by Jinsoo Kim, Bo Sook Han, Joo Eun Ha, Min Seon Park, Soonil Kwon, Bum-Joo Cho

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Deep learning radiomics based on MRI for differentiating tongue cancer T - staging by Zhaoyi Lu, Bowen Zhu, Hang Ling, Xi Chen

“…ResNet18 and ResNet50 algorithms were employed to build deep learning models (deep learning radiomics (DLR) resnet18 / DLRresnet50), compared with a radiomics model (Rad) based on 17 optimized features. …”
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