determination of dust using remote sensing techniques and numerical simulation by Razieh Pilehvaran, Zahra Rastgu, Sara Karami, Behrooz Moradpour

“…At the first step, in order to detect and observe the intensity of the dust concentration over the study area, the MODIS AOD product from the Deep blue and Dark target algorithms has been analyzed using the ENVI software, and the generated images have been displayed in the ArcGIS software. …”
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High-throughput image-based monitoring of cell aggregation and microspheroid formation. by Thomas Deckers, Toon Lambrechts, Stefano Viazzi, Gabriella Nilsson Hall, Ioannis Papantoniou, Veerle Bloemen, Jean-Marie Aerts

“…Studies on monolayer cultures and whole-animal models for the prediction of the response of native human tissue are associated with limitations. …”
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Data-driven modelling of a commercial cold storage system using subspace system identification by Adesola Temitope Bankole, Muhammed Bashir Mu’azu, Habeeb Bello-Salau, Zaharuddeen Haruna

“…The proposed model is stable, robust and suitable for testing linear control algorithms.…”
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Optimizing Stroke Classification with Pre-Trained Deep Learning Models by Serra Aksoy, Pinar Demircioglu, Ismail Bogrekci

“…Methods: The study utilized advanced deep learning algorithms, specifically ConvNeXt Base, to analyze large datasets of medical imaging data, focusing on MRI scans. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…As a result, the efficient allocation of public security resources based on spatio-temporal crime prediction models has become a critical concern for urban management. …”
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Deep Learning in Power Systems: A Bibliometric Analysis and Future Trends by Seyed Mahdi Miraftabzadeh, Andrea Di Martino, Michela Longo, Dario Zaninelli

“…Advancements in deep learning enable sophisticated algorithms to learn from vast data sets, driving innovation and efficiency in power systems. …”
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Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis by Ahmed Alfakeeh, Mhd Saeed Sharif, Abin Daniel Zorto, Thiago Pillonetto

“…The study revealed that data balancing and augmentation on the ensemble machine learning algorithms boost the efficacy of clinical predictive models and can help clinics decide which data types are most important when examining patients and diagnosing sepsis early through intelligent human-machine interface.…”
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On Complexities of Impact Simulation of Fiber Reinforced Polymer Composites: A Simplified Modeling Framework by M. Alemi-Ardakani, A. S. Milani, S. Yannacopoulos

“…Different numerical algorithms have been developed over the past decades for impact modeling of composites, yet a considerable gap often exists between predicted and experimental observations. …”
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Fuzzy AHP Based Optimal Design Building-Attached Photovoltaic System for Academic Campus by Mega Ardisa Hapsari, Subiyanto Subiyanto

“…Several algorithms have been developed for building-attached photovoltaic system (BAPV) planning in educational institute based on PV capacity. …”
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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…Given that lung cancer is a leading cause of cancer-related deaths globally and NSCLC accounts for the majority of lung cancer cases, understanding the relationship between TME and metabolic pathways in NSCLC is crucial for developing new treatment strategies.MethodsFinally, machine learning algorithms were employed to construct a risk signature with strong predictive power across multiple independent cohorts. …”
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The structural pathway of interleukin 1 (IL-1) initiated signaling reveals mechanisms of oncogenic mutations and SNPs in inflammation and cancer. by Saliha Ece Acuner Ozbabacan, Attila Gursoy, Ruth Nussinov, Ozlem Keskin

“…In the reconstructed pathway there are 104 interactions between proteins whose three dimensional structures are experimentally identified; only 15 have experimentally-determined structures of the interacting complexes. By predicting the protein-protein complexes throughout the pathway via the PRISM algorithm, the structural coverage increases from 15% to 71%. …”
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Effects of Polypropylene Waste Addition as Coarse Aggregates in Concrete: Experimental Characterization and Statistical Analysis by D. C. Naveen, K. Naresh, B. S. Keerthi Gowda, Madhu Sudana Reddy G, C. Durga Prasad, Ragavanantham Shanmugam

“…The Levenberg–Marquardt algorithm was used in predicting the mechanical properties using the ANN. …”
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Resolving the conformational ensemble of a membrane protein by integrating small-angle scattering with AlphaFold. by Samuel Eriksson Lidbrink, Rebecca J Howard, Nandan Haloi, Erik Lindahl

“…Several strategies have recently been developed to drive the machine learning algorithm AlphaFold2 (AF) to sample multiple conformations, but it is more challenging to a priori predict what states are stabilized in particular conditions and how the transition occurs. …”
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Crowdsourced data leaking user's privacy while using anonymization technique by Naadiya Mirbahar Mirbahar, Kamlesh Kumar, Asif Ali Laghari, Mansoor Ahmed Khuhro

“…Five supervised standard learning algorithm classifiers have been utilized to predict the user identity i.e., Extra Tree, Bagging, Decision Tree, Nearest Neighbor (KNN), and Random Forest Tree classifiers. …”
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Method of automatic coregistration of digital remote sensing images from different sources by A.N. Borisov, V.V. Myasnikov, V.V. Sergeev

“…To achieve a universal and robust solution in the latter stages, the best-known algorithms were compared: SIFT, SAR-SIFT, RIFT, and the trainable RoMa. …”
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Enhancing Engineering and Architectural Design Through Virtual Reality and Machine Learning Integration by Ali Shehadeh, Odey Alshboul

“…The results indicate a reduction in design clashes by 16% and iterative revisions by 15%, culminating in a 12% decrease in overall project timelines. …”
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Monocular vision guided deep reinforcement learning UAV systems with representation learning perception by Zhihan Xue, Tad Gonsalves

“…In recent years, numerous studies have applied deep reinforcement learning (DRL) algorithms to vision-guided unmanned aerial systems. …”
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Technics and Contingency by Alan Díaz Alva

“…However, I will also propose that we can read them as complementary propositions that account for the ontological productivity of computational media and operations, allowing us to theorise a form of computational contingency independent from the tendencies towards algorithmic closure and determinism present in contemporary technical systems.   …”
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STUDY ON THE USE OF COMPUTER BASED INFORMATION SYSTEMS IN PRODUCTION MANAGEMENT by Mirela PLESA (CHIRIACESCU)

“…These changes ultimately lead to a reduction in the amount of food available to humans and animals, to starvation, a phenomenon that still affects millions of people today.…”
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Numerical Reduced Variable Optimization Methods via Implicit Functional Dependence with Applications by Christopher Gunaseelan Jesudason

“…This work is more general than the reduction schemes for conditional linear parameters since it covers the nonconditional case as well and has potentially wide applicability.…”
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