Relevant bibliographies by topics / Runway ML

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Runway ML'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Runway ML"

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Kanjanasurat, I., W. Jungsuwadee, A. Lasakul, and C. Benjangkaprasert. "Comparison of logistic regression and random forest algorithms for airport’s runway assignment." Journal of Physics: Conference Series 2497, no. 1 (2023): 012016. http://dx.doi.org/10.1088/1742-6596/2497/1/012016.

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Abstract Various automation systems are currently developed using machine learning techniques. It is used to predict and decide on numerous complex tasks in order to reduce the likelihood of human error. Logistic regression is one of the most widely employed machine learning (ML) algorithm. In this study, the accuracy of logistic regression was compared to that of random forest for the assignment of Suvarnabhumi Airport runways to arriving aircraft. The accuracy of the logistic regression model was determined to be 82%, while the accuracy of the random forest model was 77%. Logistic regression
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Suryanto, Suryanto, and Nurokhman Nurokhman. "Evaluasi Properti Marshall Terhadap Mutu Aspal Beton Lapangan Pada Runway Bandara Yogyakarta International Airport." CivETech 4, no. 1 (2022): 59–72. http://dx.doi.org/10.47200/civetech.v4i1.1106.

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Pada pekerjaan runway Bandara YIA dengan lapis perkerasan aspal beton ACBC dan lapisan aus ACWC merupakan konstruksi penting dalam mendukung beban pesawat untuk landing dan take off yang harus sesuai spesifikasi yang telah ditentukan. Dalam penentuan kadar aspal yang akan berpengaruh pada kepadatan lapisan ACBC dan lapisan ACWC telah dilakukan pengujian Marshall di laboratorium untuk mendapatkan formula yang tepat agar hubungan kadar aspal dan kepadatan lapisan laston sesuai yang diharapkan. Studi bertujuan mengetahui hasil parameter pepada ngujian Marshall lapisan ACBC dan lapisan ACWC di lab
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Cornejo-Bueno, Sara, David Casillas-Pérez, Laura Cornejo-Bueno, et al. "Persistence Analysis and Prediction of Low-Visibility Events at Valladolid Airport, Spain." Symmetry 12, no. 6 (2020): 1045. http://dx.doi.org/10.3390/sym12061045.

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This work presents an analysis of low-visibility event persistence and prediction at Villanubla Airport (Valladolid, Spain), considering Runway Visual Range (RVR) time series in winter. The analysis covers long- and short-term persistence and prediction of the series, with different approaches. In the case of long-term analysis, a Detrended Fluctuation Analysis (DFA) approach is applied in order to estimate large-scale RVR time series similarities. The short-term persistence analysis of low-visibility events is evaluated by means of a Markov chain analysis of the binary time series associated
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Kao, Dina, Eoin Lalor, Gurpal Sandha, et al. "A Randomized Controlled Trial of Four Precolonoscopy Bowel Cleansing Regimens." Canadian Journal of Gastroenterology 25, no. 12 (2011): 657–62. http://dx.doi.org/10.1155/2011/486084.

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BACKGROUND: The ideal bowel cleansing regimen for colonoscopy has yet to be determined.OBJECTIVE: To compare the cleansing efficacy, and patient tolerability and safety of four bowel preparation regimens.METHODS: A total of 834 patients undergoing outpatient colonoscopy were randomly assigned to one of four regimens: 4 L polyethylene glycol (PEG); 2 L PEG + 20 mg bisacodyl; 90 mL of sodium phosphate (NaP); or two sachets of a commercially available bowel cleansing solution (PSMC) + 300 mL of magnesium citrate (M). The primary outcome measure was cleansing efficacy, which was scored by blinded
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Duong, Nguyen Hong. "Application of Artificial Intelligence and 3D Printing in Visual Arts - Innovation and Sustainable Development." Journal of Lifestyle and SDGs Review 5, no. 6 (2025): e06471. https://doi.org/10.47172/2965-730x.sdgsreview.v5.n06.pe06471.

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Objective: This study explores the integration of Artificial Intelligence (AI) and 3D printing in visual arts to promote creative innovation and sustainable development. It investigates how these technologies optimize design, reduce material waste, and improve education, contributing to SDG 4 and SDG 9. Theoretical Framework: The research is grounded in theories of digital creativity, sustainable design, and interdisciplinary art pedagogy. It situates AI and 3D printing within the context of Industry 4.0 and the creative economy, emphasizing their transformative potential in art, education, an
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Boulis, Nicholas M., Vikas Bhatia, Theodore I. Brindle та ін. "Adenoviral nerve growth factor and β-galactosidase transfer to spinal cord: a behavioral and histological analysis". Journal of Neurosurgery: Spine 90, № 1 (1999): 99–108. http://dx.doi.org/10.3171/spi.1999.90.1.0099.

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Object. The present study characterizes the time course and loci of gene expression induced by the administration of adenoviral vectors into spinal cord. Although a marked inflammatory response to these vectors occurred, no effect on spinal cord function was seen in the 1st postoperative week. The expression of transgenic genes delivered by viral vectors is being exploited throughout the nervous system. The present study utilized adenoviral vectors containing the Rous sarcoma virus (RSV) promoter and a nuclear localization signal to achieve transgenic expression in mammalian spinal cord. Metho
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Al-kahtani, M. S. M., Han Zhu, Yasser E. Ibrahim, S. I. Haruna, and S. S. M. Al-qahtani. "Study on the Mechanical Properties of Polyurethane-Cement Mortar Containing Nanosilica: RSM and Machine Learning Approach." Applied Sciences 13, no. 24 (2023): 13348. http://dx.doi.org/10.3390/app132413348.

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Polymer-modified cement mortar has been increasingly used as a runway/road pavement repair material due to its improved bending strength, bonding strength, and wear resistance. The flexural strength of polyurethane–cement mortar (PUCM) is critical in achieving a desirable maintenance effect. This study aims to evaluate and optimize the flexural strength of PUCM involving nano silica (NS) using a central composite design/response surface methodology (CCD/RSM) to design and establish statistical models. The PU binder and NS were utilized as input parameters to evaluate the responses, such as com
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Khattak, Afaq, Jianping Zhang, Pak-Wai Chan, Feng Chen, and Hamad Almujibah. "Explainable Boosting Machine: A Contemporary Glass-Box Strategy for the Assessment of Wind Shear Severity in the Runway Vicinity Based on the Doppler Light Detection and Ranging Data." Atmosphere 15, no. 1 (2023): 20. http://dx.doi.org/10.3390/atmos15010020.

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Pilots commonly undergo training to effectively manage instances of wind shear (WS) during both the landing and takeoff stages. Nevertheless, in exceptional circumstances, there may be instances of severe wind shear (SWS) surpassing a magnitude of 30 knots, leading to adverse effects on the operation of taking off and landing aircraft. This phenomenon can lead to the execution of aborted landing maneuvers and deviations from the intended glide path. This study utilized the explainable boosting machine (EBM), an advanced machine learning (ML) model known for its transparency, to predict the sev
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Khudazarov, Ravshan Saparovich. "USING ARTIFICIAL INTELLIGENCE IN MODELING MATHEMATICAL ACTIVITIES IN THE HIGHER EDUCATION SYSTEM AS A TOOL FOR CREATIVELY ORGANIZING THE EDUCATIONAL PROCESS." Multidisciplinary Journal of Science and Technology 5, no. 5 (2025): 1337–41. https://doi.org/10.5281/zenodo.15528134.

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&nbsp;This scientific article explores the methods of using artificial intelligence (AI), a new computer system widely applied across various fields due to technological advancements, for modeling mathematical activities in the higher education system. Additionally, it provides insights into the potential of leveraging AI to transform the educational process from traditional (primitive) learning to a creative learning approach.<strong></strong>
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Coman, Paul T., Andrew Weng, Jason Ostanek, Eric C. Darcy, Donal P. Finegan, and Ralph E. White. "Modeling of Li-ion Battery Thermal Runaway: Insights into Modeling and Prediction." Electrochemical Society Interface 33, no. 3 (2024): 63–68. http://dx.doi.org/10.1149/2.f09243if.

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This article discusses the dual challenges of modeling and predicting thermal runaway (TR) in li-ion batteries. It explores the current challenges of TR modeling, the methods for progressing from single cells to battery packs, and future directions involving the use of probabilistic methods and ML/AI to tackle this multifaceted issue. Accurate prediction of TR events remains a major challenge, especially because of the cell-to-cell variability, but also due to parametrization, which requires complex experimentation or exhaustive experimental data for training data-driven ML models. Continued r
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Dissertations / Theses on the topic "Runway ML"

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SOCHOROVÁ, Šárka. "Občanské elity, obecní samospráva a kultura města Telč." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-252398.

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This dissertation is dealing with the town of Telč and its way of living in the first half of the 20th century. The research is focused on the thorough analysis of local authorities from the social and occupational point of view, territorial origin and location of residence its various fellows. The main purpose of this is to idicate the changes which coincided with the influence of nationwide political, social and economic changes. The illustration of six Telč´s families with various professions charts their share which affected the social, cultural and public life of the town. The aim is to g
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Conference papers on the topic "Runway ML"

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Nieduzak, Tymon B., Tianyi Zhou, Eleonora M. Tronci, Luke B. Demo, and Maria Q. Feng. "Machine Learning Predictive Algorithm for Self-Sensing Electric Vehicle Battery Enclosure." In ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/smasis2024-140078.

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Abstract Electric Vehicles (EVs) are a favorable and rapidly growing tactic for reducing carbon emissions. However, the most commonly used power source in EVs, Lithium-Ion Batteries (LIBs), can pose a significant safety risk in the form of thermal runaway. This is a fast-acting and dangerous failure mode that may lead to fires and explosions. To address this issue, the authors’ previous work developed a self-sensing composite battery enclosure with embedded micro-temperature sensors to provide LIB condition monitoring. The prior work produced extensive experimental and simulation results, char
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Dunlap, Christy, Hari Pandey, Jackson Marsh, Ethan Weems, and Han Hu. "Remote Thermal Measurements With Regression of Acoustic Emissions." In ASME 2023 Heat Transfer Summer Conference collocated with the ASME 2023 17th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/ht2023-106939.

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Abstract Real-time thermal monitoring and regulation are critical to the mitigation of thermal runaways and device failures in two-phase cooling systems. Compared to conventional approaches that rely on the Joule effect, thermal gradient or transverse thermoelectric effect, acoustic emission (AE)-based remote sensing is more promising for robust and non-intrusive thermal monitoring. Nevertheless, due to the high stochasticity and noise of acoustic signals, existing implementations of AE in thermal systems have been limited to qualitative state monitoring. In this paper, we present a technology
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