Machine Learning-Based Detection of Archeological Sites Using Satellite and Meteorological Data: A Case Study of Funnel Beaker Culture Tombs in Poland by Krystian Kozioł, Natalia Borowiec, Urszula Marmol, Mateusz Rzeszutek, Celso Augusto Guimarães Santos, Jerzy Czerniec

“…This study aimed to develop predictive models for assessing archeological site visibility in satellite imagery by integrating vegetation indices and meteorological data using machine learning techniques. The research focused on megalithic tombs associated with the Funnel Beaker culture in Poland. …”
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A high-gain THz microstrip patch antenna designed for IoT and 6G communications with predicted efficiency using machine learning approaches by Md Sharif Ahammed, Redwan A. Ananta, Jun-Jiat Tiang, Mouaaz Nahas, Narinderjit Singh Sawaran Singh, Md. Ashraful Haque

“…This dataset comprises six features based on the geometric and material parameters of the antenna. The implementation of various machine-learning techniques, including Extreme Gradient Boosting (XGB) regression, yielded outstanding outcomes. …”
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One techno-economic analysis to rule them all: Instant prediction of hydrothermal liquefaction economic performance with a machine learned analytic equation by Muntasir Shahabuddin, Nikolaos Kazantzis, Andrew R Teixeira, Michael T. Timko

“…The most accurate model consists of three terms and requires 6 adjustable parameters to predict independently published values of MFSP (N = 28) to within an average value of ± 20.4%. …”
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An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

“…The geospatial approaches namely, Inverse Distance Weighted (IDW) has been implemented to draw the interpolated maps for different water quality parameters. Water samples were collected from 19 different sites to evaluate 20 water quality indicators during the pre-monsoon (PRM) season. …”
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Precision hole-machining of SiCf/SiC composite using single-layer brazed diamond core drill dressed by pulsed laser by Ning QIAN, Jingyuan HE, Honghua SU, Yuting SUN, Lama ANGGEI, Wenfeng DING, Jiuhua XU

“…ObjectivesThe single-layer brazed diamond core drill generally exhibits poor protrusion height uniformity of grains, making it difficult to control the hole diameter and the accuracy when machining SiCf/SiC composites. Pulsed laser is used to dress the core drill to improve grain height uniformity, thereby enhancing hole accuracy on SiCf/SiC composite.MethodsFirstly, a pulsed laser dressing platform for the single-layer brazed diamond core drill is developed, and the influence of laser dressing parameters on grain height uniformity and morphology is revealed. …”
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Development and validation of a machine learning-based model to predict survival in patients with cirrhosis after transjugular intrahepatic portosystemic shuntResearch in context by Binlin Da, Huan Chen, Wei Wu, Wuhua Guo, Anru Zhou, Qin Yin, Jun Gao, Junhui Chen, Jiangqiang Xiao, Lei Wang, Ming Zhang, Yuzheng Zhuge, Feng Zhang

“…Summary: Background: Although numerous prognostic scores have been developed for patients with cirrhosis after Transjugular intrahepatic portosystemic shunt (TIPS) placement over years, an accurate machine learning (ML)-based model remains unavailable. …”
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Comparative flank wear and produced chips types analysis of CNMG 120408 indexable cutting inserts after machining hardened 1.6582 steel by Karel Šramhauser, Pavel Kraus, Pavel Černý, Pavel Kříž, František Špalek, Roman Horký, Tomáš Zoubek, Vladimír Vochozka

“…The experiment concludes that the thickness of the coating layers alone does not have a direct effect on the overall lifetime of the tool, and the approximate lifetime of the cutting edge cannot be predicted based on the parameters of the coating layers. When choosing a cutting tool, the manufacturer should carry out a test series for the specific material to be machined, despite the declaration of the composition and thickness of the coating layers. …”
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Effect of Surface Roughness on Characteristics of Textured Hydrodynamic Bearings by Hongtao Wang, Shaolin Zhang, Shuai Yang

“…On this basis，the static and dynamic characteristic parameters under different eccentricities and speeds are calculated and the influence of the surface roughness on the pressure distribution and instability threshold speed of textured hydrodynamic bearings are analyzed. …”
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Ontology-conformal recognition of materials entities using language models by Sai Teja Potu, Rachana Niranjan Murthy, Akhil Thomas, Lokesh Mishra, Natalie Prange, Ali Riza Durmaz

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Optimization of Wear Behaviour on Mg-TiO2 Nanocomposite Using Taguchi Grey Relational Analysis by Radhakrishnan Ganesh, K. Kannapiran, R. Saranraj, G. Praburam

“…n this research, the dry sliding wear behaviour of the Mg-TiO2 nanocomposite is analyzed by conducting a wear test using a pin-on-disc wear testing machine under normal atmospheric conditions. The process parameters considered during the test are the weight fraction of TiO2 nanoparticles, normal load, and sliding speed. …”
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Comparative Analysis of Wear Models for Accurate Wear Predictions by Guntis Springis, Irina Boiko

“…Moreover, classical wear models do not fully account for material fatigue effects and 3D surface texture parameters, which are critical for solving complex engineering problems. …”
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Cosmology with One Galaxy: Autoencoding the Galaxy Properties Manifold by Amanda Lue, Shy Genel, Marc Huertas-Company, Francisco Villaescusa-Navarro, Matthew Ho

“…Previous studies have demonstrated that machine learning can be used to infer the cosmological parameter Ω _m from the internal properties of even a single randomly selected simulated galaxy. …”
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Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen by Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho

“…The results of this study indicate that parameter optimization with PSO can improve the performance of sentiment analysis on the subjects studied. …”
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Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms by Rafael Pires de Lima, Yue Chen, Youzuo Lin

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Investigation mechanical properties and on surface roughness during WEDM machining of nano Cr2C3-MoS2 hybrid metal matrix composites by Ramesh Vellaichamy, Pugazhenthi Rajagopal, A. Geetha Selvarani, Itha Veeranjaneyulu, J. Immanuel Durai Raj, E. Balaji, Mamdooh Alwetaishi, S. Baskar, Krishna Moorthy Sivalingam, P. V. Elumalai

“…Abstract The study aims to identify a suitable machining parameter during Wire Cut Electrical Discharge Machining (WEDM) of duralumin reinforced with varying amounts of particulates. …”
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Performance Investigation of Coated Carbide Tools in Milling Procedures by Paschalis Charalampous

“…This study presents an investigation of the cutting tool’s performance under varying machining parameters via the generation of an experimental dataset that was obtained through laboratory-controlled milling operations. …”
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Vertical two-phase flow regimes in an annulus image dataset - Texas A&M universityMendeley Data by Kaushik Manikonda, Chinemerem Obi, Aarya Abhay Brahmane, Mohammad Azizur Rahman, Abu Rashid Hasan

“…Designed to support research in fluid dynamics, machine vision, and computational modeling, the dataset offers valuable resources for developing machine vision models for accurate regime detection and differentiation, enhancing the fidelity of computational fluid dynamics simulations, and facilitating the estimation of critical flow parameters. …”
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Personnel Potential for Ensuring Food Security in the Post-War Five Years (1946—1950): Experience of Irkutsk Region by K. K. Vasilyeva, O. R. Ochirov

“…The presence and level of technical and general material base for training and retraining of machine operators, specialists and other workers have been studied. …”
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Updimensioning strategy derived from synthetic equiaxed grain structures for approximating 3D grain size distributions from 2D visualizations with 1D parameters by Kevin Gillespie, Algirdas Baskys, Ian Pong, Jean-Francois Croteau

“…The procedure requires larger sample sizes to lower variance and a deeper analysis which could become more practical with machine learning (ML) models for grain boundary segmentation, which synthetic grain structures can help train. …”
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Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM) by Lei Wang, Jinghang Li, Wenbo Zhang, Yu Li

“…Finally, the quantitative analysis model of WLSSVM is reconstructed by using the optimized parameters, and the nine parameters of buried depth of coal seam, gas content of coal seam, coal thickness, interlayer lithology, production rate of working face, length of working face, inclination of coal seam, gas content of adjacent layer, and thickness of adjacent layer are used as the main influencing factors. …”
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