Fluvial bedload transport modelling: advanced ensemble tree-based models or optimized deep learning algorithms? by Khabat Khosravi, Aitazaz A. Farooque, Sayed M. Bateni, Changhyun Jun, Dorsa Mohammadi, Zahra Kalantari, James R. Cooper

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An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…Conclusively, the proposed investigation provides insightful AI, ML and CFD-proposed analysis of blood-based nano-particles which can improve imaging techniques, provide tailored drug delivery, reduce hyperthermia, improve blood flow, and show potential for application in medicine.Highlights Artificial intelligence and machine learning-based CFD simulation of the blood-mediated tri-hybrid nano-fluid flow is presented.An improved finite difference scheme (the Keller-Box method), is utilized to numerically evaluate the problem.The LMA-ANN forecasts with an absolute error range of [Formula: see text] to [Formula: see text] relative to the actual data.Regression scores equal to 1 indicate a strong correlation between forecasts and actual data.…”
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Distributed Consensus Gossip-Based Data Fusion for Suppressing Incorrect Sensor Readings in Wireless Sensor Networks by Martin Kenyeres, Jozef Kenyeres, Sepideh Hassankhani Dolatabadi

“…In this paper, WSNs are modeled as random geometric graphs with various connectivity, and the performance of the algorithms is evaluated using two metrics (specifically, the mean square error (MSE) and the number of sent messages required for an algorithm to be completed). …”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…According to the results, the simultaneous application of Q and SC lag time values as inputs has led to the best SL estimates by XGB-MPA, with XGB-MPA9 (RMSE = 103.7 ton/day; NSE = 0.96) exhibiting the lowest error rates. …”
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Aerodynamic energy consumption analysis of divided evacuated tube transportation system by Ziwei Zhang, Yingxue Wang, Guanqing Wang, Feilong Li, Dengke Wang, Jianjun Luo

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Classification of Review Text using Hybrid Convolutional Neural Network and Gated Recurrent Unit Methods by Fiqih Fathor Rachim, Auli Damayanti, Edi Winarko

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Automatic differential kinematics of serial manipulator robots through dual numbers by Luis Antonio Orbegoso Moreno, Edgar David Valverde Ramírez

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ANALISIS PENGARUH ANGKA KEMATIAN BAYI TERHADAP ANGKA HARAPAN HIDUP DI PROVINSI JAWA TIMUR BERDASARKAN ESTIMATOR LEAST SQUARE SPINE by Anies Yulinda W, Trias Novia L., Melati Tegarina, Nur Chamidah

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Implementation of Mamdani Method Fuzzy System in Determining Final Semester Grades of UIN Walisongo Semarang Students by Arif Rezky Aprilianto, Budi Cahyono, Mohamad Tafrikan

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Automated System for OEE Management in the Industrial Sector by Diego Gomez, Sofia Pantoja, Enoc Acosta, David Arrieta, Sebastián Gutiérrez

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ENHANCED COASTLINE EXTRACTION AND EROSION ANALYSIS USING UNET AND DEXINED MODELS by Yan Wang, Adisorn Sirikham, Jessada Konpang, Chunguang Li

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ENHANCED COASTLINE EXTRACTION AND EROSION ANALYSIS USING UNET AND DEXINED MODELS by Yan Wang, Adisorn Sirikham, Jessada Konpang, Chunguang Li

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The First Moon Bistatic SAR Imaging Experiment Based on FAST Radio Telescope by Yan Yin, Jinghai Sun, Jitong Duan, Xiaochen Wang, Mingyuan Li, Xinan Yue, Lijia Huang, Peng Jiang, Chibiao Ding

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KEKELIRUAN-KEKELIRUAN DALAM MEMAHAMI KONSEP-KONSEP TEORETIS HALEY TENTANG METAFORA: SEBUAH KAJIAN METALINGUAL by Joko Kusmanto, Anni Holila Pulungan

“…The results of data analysis and discussion indicate that there are conceptual errors in the application of Haley's metaphorical theory in the six data sources. …”
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Quality Control Automation for Student Driven Digitization Workflows by Corinne Chatnik, James Gaskell

“…While they do a great job, the infrequency of their work hours and lack of experience results in errors in digitization and metadata. Many of these errors are difficult to catch during quality control checks because they are so minute, such as a missed counted page number here, or a transposed character in a filename there. …”
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How Effective are SETA Programs Anyway: Learning and Forgetting in Security Awareness Training by David Sikolia, David Biros, Tianjian Zhang

“…Prevalent security threats caused by human errors necessitate security education, training, and awareness (SETA) programs in organizations. …”
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PENGGUNAAN BAHASA ILMIAH PADA PENULISAN SKRIPSI: PROBLEMATIKA DAN ALTERNATIF SOLUSINYA (Studi Kasus Mahasiswa Jurusan Pendidikan Agama Islam IAIN Syekh Nurjati Cirebon) by Tati Sri Uswati

“…Based on the analysis of data errors, word formation found 31 errors, 61 errors word choice, sentence drafting error 62, 11 arrangement error of reasoning, and the application of rule 105 spelling errors. …”
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Analysis of Land Surface Performance Differences and Uncertainty in Multiple Versions of MODIS LST Products by Ruoyi Zhao, Wenping Yu, Xiangyi Deng, Yajun Huang, Wen Yang, Wei Zhou

“…The error assessment includes cross-comparisons between product versions and evaluations of the absolute errors generated. …”
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Bounds on Worst-Case Deadline Failure Probabilities in Controller Area Networks by Michael Short

“…Industrial communication networks like the Controller Area Network (CAN) are often required to operate reliably in harsh environments which expose the communication network to random errors. Probabilistic schedulability analysis can employ rich stochastic error models to capture random error behaviors, but this is most often at the expense of increased analysis complexity. …”
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Interlanguage development among the learners of Indonesian language in Paris by Mahriyuni Mahriyuni, Isda Pramuniati, Dedi Rahmad Sitinjak

“…The main goal is to look at the several kinds of grammatical, syntactic, and lexical errors that appear in their written sentences. This research attempts to determine how learners' native language affects their learning of Indonesian by concentrating on typical mistakes in prepositional usage, adverbial application, word/phrase organization, vocabulary selection, and spelling/capitalization. …”
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