Advanced machine learning artificial neural network classifier for lithology identification using Bayesian optimization by Saâd Soulaimani, Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, Abdelhalim Miftah, Mohammed S. Fnais, Biraj Kanti Mondal

“…This technique utilizes the capability of Bayesian optimization to utilize past classification outcomes to enhance the lithology models performance based on physical parameters calculated from well log data. …”
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MECHANISMS OF MANTLE‐CRUST INTERACTION AT DEEP LEVELS OF COLLISION OROGENS (CASE OF THE OLKHON REGION, WEST PRIBAIKALIE) by A. G. Vladimirov, A. S. Mekhonoshin, S. V. Khromykh, E. I. Mikheev, A. V. Travin, N. I. Volkova, T. B. Kolotilina, Yu. A. Davydenko, E. V. Borodina, V. V. Khlestov

“…Considering petrology, the deep mafic chamber under the layer of granulite facies is evidenced by metamorphic magma mingling, as well as pipe‐shaped intrusions characterized by the specific morphology, internal structure and bulk rock compositions. …”
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MULTIMODAL APPROACH TO THE STUDY OF SPECIALIZED TEXTS IN TECHNICAL DISCOURSE by Yuliia V. Polycheva, Volodymyr I. Vetokhin

“…Given that, a distinctive feature of multimodal technical discourse is the presence of accompanying drawings or / and explanatory drawings, which demonstrate all the geometric parameters and other information concerning the manufacturing processes of the product. From an extralinguistic point of view, it is not the language that is considered, but a drawing, a table, a diagram as a whole, creating an image and representing encrypted data, the correct analysis of which reveals a large layer of technical information. …”
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Structural, physical, optical, mechanical, and radiation shielding investigation of tantalum pentoxide doped Germanate-Tellurite-Borate based glass system by M.I. Sayyed, M.H.A. Mhareb, M.Kh. Hamad, Abed Jawad Kadhim, Kawa M. Kaky, Yasser Maghrbi

“…Moreover, the half-value layer (HVL) at 0.05 MeV is reduced from about 0.15 cm for the Ta0.5 sample to 0.14 cm for the Ta2.5 sample. …”
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Methodology for assessing the stability and evaporation of volatile substances from the soil by Kochetova Zh. Yu., Shishkin A. V., Velikanov A. V.

“…The permissible concentration of volatile matter is experimentally established, at which its entry into the air does not exceed the permissible standards for atmospheric air. This process is associated with certain difficulties caused, first of all, by the complexity of modeling the emission of toxicants from soils in laboratory conditions, and the duration of the process. …”
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Structural Build-Up of Cement Pastes: A Comprehensive Overview and Key Research Directions by Mahmoud Hayek, Youssef El Bitouri, Kamal Bouarab, Ammar Yahia

“…The advancement of modern concretes, such as printable concrete, fluid concrete with adapted rheology, and ultra-high-performance concrete, has increased the importance of understanding structural build-up in cement-based materials. This process, which describes the time-dependent evolution of rheological properties, is a key factor to ensure the stability of concrete by influencing segregation, bleeding, formwork pressure, numerical modeling, and multi-layer casting. …”
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Research on Diffusion Patterns of Gas Produced by Energy Storage Lithium Batteries due to Thermal Runaway by LIU Li, SHI Mengzhao, XU Dongyang, TANG Wenbing, HU Yue, JIANG Fengbing

“…In addition, the smoke layer spreads from the battery compartment to the ground within only 50 seconds.…”
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AI-Based Prediction of Warpage in Organic Substrates by Jingyi Zhao, Meiying Su, Rui Ma

“…Through material preparation, substrate manufacturing, and comprehensive characterization testing, process-matched material parameters and warpage data were obtained. …”
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HP_FLAP: homomorphic and polymorphic federated learning aggregation of parameters framework by Mohammad Moshawrab, Mehdi Adda, Abdenour Bouzouane, Hussein Ibrahim, Ali Raad

“…The framework is evaluated using multiple models, including logistic regression, Gaussian Naive Bayes, Stochastic Gradient Descent, and Multi-Layer Perceptron, demonstrating HP_FLAP’s ability to enhance both security and privacy in FL environments.…”
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Structural Properties of Wire-Mesh-Reinforced Straw Concrete Sandwich Panels for Sustainable Construction by Guoliang Guo, Chun Lv, Jie Liu, Yu Zhang

“…The FGC was sprayed on the SWM to make the SCSP layer work together. The loading process of the SCSP could be divided into three stages: elastic working state, cracking state, and failure state. …”
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A Machine Learning-Based Ransomware Detection Method for Attackers’ Neutralization Techniques Using Format-Preserving Encryption by Jaehyuk Lee, Jinwook Kim, Hanjo Jeong, Kyungroul Lee

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Human AI collaboration for unsupervised categorization of live surgical feedback by Rafal Kocielnik, Cherine H. Yang, Runzhuo Ma, Steven Y. Cen, Elyssa Y. Wong, Timothy N. Chu, J. Everett Knudsen, Peter Wager, John Heard, Umar Ghaffar, Anima Anandkumar, Andrew J. Hung

“…We propose a Human-AI Collaborative Refinement Process that uses unsupervised machine learning (Topic Modeling) with human refinement to discover feedback categories from surgical transcripts. …”
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A machine learning framework to measure Water Drop Penetration Time (WDPT) for soil water repellency analysis by Danxu Wang, Emma Regentova, Venkatesan Muthukumar, Markus Berli, Frederick C. Harris, Jr.

“…It consists of an electronically controlled mechanism to release a water drop, and a video camera to record the water penetration process. The latter is modeled as an “action” in video and Temporal Action Localization (TAL) analytics is used for predicting the WDPT and assessing the SWR level.…”
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Parameter sensitivity and data uncertainty assessment of the cradle-to-gate environmental impact of state-of-the-art passive daytime radiative cooling materials by N. Adams, K. Allacker

“…The study investigates three key sources of input uncertainty: (1) parameter sensitivity, analyzing variations in production processes; (2) Monte Carlo analysis, assessing uncertainty within Ecoinvent datasets used for RC material modeling; and (3) pedigree matrix evaluation, incorporating an additional layer of uncertainty where data are incomplete. …”
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On Knowledge-Based Forecasting Approach for Predicting the Effects of Oil Spills on the Ground by D. Kalibatiene, A. Burmakova, V. Smelov

“…It consists of components for modelling geological environment (i.e., geological layers, oil spill form, the oil migration with groundwater), forecasting component for an oil spill and pollution mitigation component. …”
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GIS Copilot: towards an autonomous GIS agent for spatial analysis by Temitope Akinboyewa, Zhenlong Li, Huan Ning, M. Naser Lessani

“…Recent advancements in generative artificial intelligence (AI), particularly Large Language Models (LLMs), offer promising capabilities for spatial analysis. …”
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Partially Binarized Deep MUSIC for Multiple Target Angle Estimation Using Wireless Sensor Array Systems by Jongsung Kang, Joonhyeon Jun, Jaehyun Park, Hyungju Kim, Byung Jang Jeong

“…By modeling the noisy backhaul link as a binarized feedforward layer, we developed a new neural network architecture suitable for AoA estimation using wireless sensor array systems, and we trained it using a straight-through gradient estimator. …”
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Supply Chain Data Analytics for Digital Twins: A Comprehensive Framework by Vasileios Xiros, Jose M. Gonzalez Castro, Francisco Fernandez-Pelaez, Babis Magoutas, Konstantinos Christidis

“…In this work we present a comprehensive modular, scalable and secure analytics architecture, designed to expand the available components in commercial solutions by providing an intelligent layer to Digital Twins. Our approach integrates with the latest standards for international data spaces, interoperability and process models in distributed environments where multiple actors engage in co-opetition. …”
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Inorganic carbon assimilation by planktonic community in Santos Basin, Southwestern Atlantic Ocean by Deborah S. Kutner, Jeff S. Bowman, Flávia M. P. Saldanha-Corrêa, Mateus G. Chuqui, Pedro M. Tura, Daniel L. Moreira, Frederico P. Brandini, Camila N. Signori

“…Rates were analyzed using statistical tests to verify spatial differences between groups of samples and generalized linear models to identify correlations with environmental variables (temperature, salinity, density, mixed layer depth, dissolved oxygen, nitrite, nitrate, silicate, phosphate, turbidity, CDOM, and phycoerythrin and chlorophyll-a concentrations). …”
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Research of Surface Wear Resistance of Aluminum Alloy Modified with Minerals using Sclerometry Method by A. V. Skazochkin, G. G. Bondarenko, P. Żukowski

“…Also, measurements of the hardness and elastic modulus of the surface of the modified sample were performed taking into account the features of measuring the mechanical parameters of thin layers.The obtained parameters of the modified surface of the aluminum alloy can be further used to build models of the processes of friction and wear of the surface modified by ultrafine particles of minerals. …”
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