Integrating AI detection and language models for real-time pest management in Tomato cultivation by Yavuz Selim Şahin, Nimet Sema Gençer, Hasan Şahin

“…Traditional pest detection methods are labor-intensive and prone to errors, necessitating the exploration of advanced techniques. …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by Rahmat Rizky, Munirul ula, Zara Yunizar

“…Implemented in Jupyter Notebook, the research explores the strengths of each method in analyzing market fluctuations and price trends. …”
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Complete blood count in neonatal Intensive care Unit (NICU): Performance comparison between POCT Sight OLO® and Sysmex XN-9100™ hematology analyzers by Francesca Nencini, Alessandro Bonari, Sara Ciullini Mannurita, Alessandra Mongia, Francesca Romano, Maria Garieri, Edda Russo, Silvia Sastrucci, Graziella Marrani, Martina Tonelli, Stefano Salti, Niccola Funel, Amedeo Amedei, Carlo Dani, Alessandra Fanelli

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Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography by Jonathan Bouvette, Hsuan-Fu Liu, Xiaochen Du, Ye Zhou, Andrew P. Sikkema, Juliana da Fonseca Rezende e Mello, Bradley P. Klemm, Rick Huang, Roel M. Schaaper, Mario J. Borgnia, Alberto Bartesaghi

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Debriefing Methodologies in Nursing Simulation: An Exploratory Study of the Italian Settings by Sonia Lomuscio, Emanuele Capogna, Stefano Sironi, Marco Sguanci, Sara Morales Palomares, Giovanni Cangelosi, Gaetano Ferrara, Stefano Mancin, Antonio Amodeo, Anne Destrebecq, Mauro Parozzi, Susy Dal Bello

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Model Biokinetika Sistem Kontak Stabilisasi Lumpur Air Lindi Berdasarkan Pengaruh Fosfor dan Variasi Waktu Detensi Unit Kontak by Muhammad Faiz Kahendran, Owen Jacob Notonugroho, Chusnul Arif, Ariani Dwi Astuti, Allen Kurniawan

“…Based on research results, the percent removal of COD efficiency in each HRT contact tank of 2, 3, and 4 hours, were 26.9%; 35.1%; and 46.5%, respectively. …”
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A Comparative Analysis of Option Pricing Models Under Jump Dynamics, Skewness, and Non-Normal Kurtosis by Hossein Nasrollahi, Mohammad Reza Haddadi

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Automated Seedling Contour Determination and Segmentation Using Support Vector Machine and Image Features by Samsuzzaman, Md Nasim Reza, Sumaiya Islam, Kyu-Ho Lee, Md Asrakul Haque, Md Razob Ali, Yeon Jin Cho, Dong Hee Noh, Sun-Ok Chung

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A Hybrid Model of Feature Extraction and Dimensionality Reduction Using ViT, PCA, and Random Forest for Multi-Classification of Brain Cancer by Hisham Allahem, Sameh Abd El-Ghany, A. A. Abd El-Aziz, Bader Aldughayfiq, Menwa Alshammeri, Malak Alamri

“…However, manual examination of brain MRI scans is prone to errors and heavily depends on radiologists’ experience and fatigue levels. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…These faults can arise from a variety of factors, including environmental conditions, manufacturing defects, installation errors, and wear and tear of the components. Fault diagnosis in solar PV systems involves the detection, identification, and rectification of faults or abnormalities that can occur due to various reasons. …”
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Replace government healthcare with patient-controlled health care by Deane Waldman

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The Impacts of Different PBL Schemes on the Simulation of PM2.5 during Severe Haze Episodes in the Jing-Jin-Ji Region and Its Surroundings in China by Tian Li, Hong Wang, Tianliang Zhao, Min Xue, Yaqiang Wang, Huizheng Che, Chao Jiang

“…In this study, three schemes [Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrère (Boulac)] were employed in the Weather Research and Forecasting/Chemistry (WRF-Chem) model to simulate the severe haze that occurred in February 2014 in the Jing-Jin-Ji region and its surroundings. …”
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Identifying preferential flow from soil moisture time series: Review of methodologies by John R. Nimmo, Inge Wiekenkamp, Ryoko Araki, Jannis Groh, Nitin K. Singh, Octavia Crompton, Briana M. Wyatt, Hoori Ajami, Daniel Giménez, Daniel R. Hirmas, Pamela L. Sullivan, Matthias Sprenger

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Advanced AI techniques for classifying Alzheimer’s disease and mild cognitive impairment by Sophie Tascedda, Sophie Tascedda, Sophie Tascedda, Pierfrancesco Sarti, Pierfrancesco Sarti, Veronica Rivi, Claudia Savia Guerrera, Giuseppe Alessio Platania, Mario Santagati, Filippo Caraci, Filippo Caraci, Johanna M. C. Blom, Johanna M. C. Blom

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On the risks of good intentions and poor evidence – comment on “Back to the future? Conservative grassland management can preserve soil health in the changing landscapes of Uruguay... by J. Paruelo, J. Paruelo, J. Paruelo, L. López-Mársico, P. Baldassini, P. Baldassini, F. Lezama, B. Bazzoni, L. Staiano, A. Nuñez, A. Guido, C. Ríos, A. Tommasino, F. Gallego, F. Pezzani, G. Camba Sans, A. Quincke, S. Baeza, G. Piñeiro, G. Piñeiro, W. Baethgen

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Rainfall estimation in the West African Sahel: comparison and cross-validation of top-down vs. bottom-up precipitation products in Burkina Faso by Roland Yonaba, Axel Belemtougri, Tazen Fowé, Lawani Adjadi Mounirou, Elias Nkiaka, Moctar Dembélé, Akpoti Komlavi, Serigne M’backé Coly, Mahamadou Koïta, Harouna Karambiri

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Digital twin manifesto for the pathology laboratory by Albino Eccher, Fabio Pagni, Massimo Dominici, Luca Reggiani Bonetti, Stefano Marletta, Enrico Munari, Giorgio Cazzaniga, Anil V Parwani, Vincenzo L’Imperio, Angelo Paolo Dei Tos

“…The framework highlights measurable gains such as up to 90% reduction in labeling errors, 20–30% improvements in slide quality, and 30–50% reductions in diagnostic turnaround time. …”
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Time Series Prediction Method of Clean Coal Ash Content in Dense Medium Separation Based on the Improved EMD-LSTM Model by Kai Cheng, Xiaokang Zhang, Keping Zhou, Chenao Zhou, Jielin Li, Chun Yang, Yurong Guo, Ranfeng Wang

“…SSA optimizes LSTM parameters (learning rate, hidden layers, epochs) to minimize prediction errors. Results demonstrate the EMD-IMF1-LSTM-SSA model achieves superior accuracy (RMSE: 0.0099, MAE: 0.0052, MAPE: 0.047%) and trend consistency (NSD: 12), outperforming baseline models. …”
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A hybrid statistical-machine learning approach for experimental analysis of biogas production in a waste to energy plant using a vacuum evaporator systems by Vakkar Ali, Praveen Pachauri, Azhar Equbal, Osama Khan, Mohd Parvez, Haidar Howari, Taufique Ahamad, Ashok Kumar Yadav, Brahmdeo Yadav

“…Also, the percentage errors came out to be minimum for machine learning model of around 5.3 %, 5 % and 4.7 % for energy efficiency, equipment durability and process throughput respectively. …”
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A quantum-resilient lattice-based security framework for internet of medical things in healthcare systems by Zeyad Ghaleb Al-Mekhlaf, Murtaja Ali Saare, Jalal Mohammed Hachim Altmemi, Mahmood A. Al-Shareeda, Badiea Abdulkarem Mohammed, Gharbi Alshammari, Reem alrashdi, Yasser A. Alkhabra, Ibrahim Alreshidi

“…This paper proposes a quantum-resistant healthcare security framework based on lattice-based cryptographic primitives such as Learning With Errors (LWE), Ring-LWE (RLWE), and Short Integer Solution (SIS). …”
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