Study of the level of noise load when cutting natural stone with a disc diamond tool by S.S. Iskov, A.O. Kryvoruchko, O.L. Herasymchuk, S.I. Bashynskyi, N.M. Ostafiichuk

“…Changes in the level of noise load during granite sawing with a diamond disk tool of various types were studied when adjusting the operating parameters of disk stone-cutting machines, in particular, when changing the feed rate and cutting depth in 1 pass. …”
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Study on User Fraud Identification of PV Expansion Based on a Bottom-Up Approach of a DELM Algorithm Improved by SSA for a Power Distribution Network by Wang Jinpeng, Wei Haojie, Dou Shunyao, Jeremy-Gillbanks, Zhao Xin

“…Next, a Sparrow Search Algorithm (SSA) was applied to optimize the weight parameters of the Deep Extreme Learning Machine (DELM). …”
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Investigation of Ground Vibration of Full-Stone Foundation under Dynamic Compaction by Jiawen Wu, Linjian Ma, Jun Shi, Yangyang Sun, Jiewei Ke, Dan Wang

“…However, the three parameters, namely, PGV, PGA, and average frequency, remain stable roughly when they reach a threshold of test tamping times. …”
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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

“…The AOA optimizes the model’s learnable parameters by utilizing the distribution patterns of four mathematical operators, further enhanced by logistic and cubic mappings, to avoid local optima. …”
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Mobile detection of cataracts with an optimised lightweight deep Edge Intelligent technique by Dipta Neogi, Mahirul Alam Chowdhury, Mst. Moriom Akter, Md. Ishan Arefin Hossain

“…This research has developed a machine learning model that can work with Edge devices like smartphones. …”
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Current Situation and Prospect of Fluid Identification in Non-Resistivity Logging by YUAN Lixin, WU Hongliang, FENG zhou, TIAN Han, WANG Kewen, LIU Peng

“…Directly inverting fluid characterization parameters using Stoneley waves. Conducting substantial experiments and simulations to improve the theory of chlorine yield correction and form a stable chloride ion fluid identification method. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…To address the aforementioned issues, this work proposed a machine-learning technique that uses phases to detect Bone scintigraphy. …”
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GDPR and Large Language Models: Technical and Legal Obstacles by Georgios Feretzakis, Evangelia Vagena, Konstantinos Kalodanis, Paraskevi Peristera, Dimitris Kalles, Athanasios Anastasiou

“…We discuss issues such as the transformation of personal data into non-interpretable model parameters, difficulties in ensuring transparency and accountability, and the risks of bias and data over-collection. …”
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In-situ production of Ti6Al4V single tracks from a blend of CP-Ti and spheroidized Al-V master alloy powders by Ramosena Lekhetho, Dzogbewu Thywill, du Preez Willie

“…The identification of these machine parameters signposts the possibility to produce high-quality Ti6Al4V parts from this powder blend.…”
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Assessing and Forecasting Natural Regeneration in Mediterranean Landscapes After Wildfires by Paraskevi Oikonomou, Vassilia Karathanassi, Vassilis Andronis, Ioannis Papoutsis

“…To predict vegetation regrowth, two time series models (ARMA, VARIMA) and two machine learning-based ones (random forest, XGBoost) were tested. …”
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Techno-Economic Analysis of Lignin-Containing Micro- and Nano-Fibrillated Cellulose for Lightweight Linerboard Packaging by Heather Starkey, Maria Gonzalez, Hasan Jameel, Lokendra Pal

“…This study developed the first model to evaluate changes in steam consumption and other process parameters on a paper machine when incorporating lignin-containing micro- and nano-fibrillated cellulose (LMNFC) as a dry-strength additive, as well as its economic effects. …”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques.…”
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Disassembly Plan Representation by Hypergraph by Abboy Verkuilen, Mirjam Zijderveld, Niels de Buck, Jenny Coenen

“…First requirements from small and medium-sized remanufacturing companies have been collected and compared with available frameworks for modeling product topology, parameters, and (dis)assembly process rationale. Based on this, the disassembly hypergraph is presented as a concept for recording ‘resource-agnostic disassembly guides’ in (machine-readable) product models to determine required disassembly actions and tools ‘smartly’. …”
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State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model by Jun Chen, Yan Liu, Jun Yong, Cheng Yang, Liqin Yan, Yanping Zheng

“…This paper presents a novel SOH estimation method that integrates Particle Swarm Optimization (PSO) with an Extreme Learning Machine (ELM) to improve prediction accuracy. Health Indicators (HIs) are first extracted from the battery’s charging curve, and correlation analysis is conducted on seven indirect HIs using Pearson and Spearman coefficients. …”
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Predicting the Tensile Strength of Plant Leaves Based on GA-SVM by Wei Chang, Meihong Liu, Yayu Huang, Junjie Lei, Kai Wu

“…A genetic algorithm (GA) is then applied to optimize the structural parameters of the support vector machine (SVM), establishing a GA-SVM-based predictive model for the tensile strength of plant leaves. …”
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The Study of Tribological Characteristics of YSZ/NiCrAlY Coatings and Their Resistance to CMAS at High Temperatures by Dastan Buitkenov, Zhuldyz Sagdoldina, Aiym Nabioldina, Cezary Drenda

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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

“…Compressive strength (CS) and slump flow (SL) are two of the most essential parameters in High-Performance Concrete (HPC), which directly affect its structural capacity, durability, and workability. …”
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Dielectric constant prediction in polymers: A chemical structure based approach by S. Sharifi, S. Bonardd, L.A. Miccio

“…In this work, we describe a machine learning-based approach for estimating the dielectric constant of polymers by using their chemical structure. …”
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Constitutive Model and Hot Processing Map of Ni-Cr-Fe Heat-resistant Alloy for Advanced Ultra-Supercritical Boilers by Gao　Pei, Huang　Guijun

“…Thermal compression deformation experiments on Ni-Cr-Fe heat-resistant alloy for advanced ultra-supercritical boilers were conducted using a Gleeble-3500 thermal simulator testing machine over a temperature range of 950 ℃–1 250 ℃， strain rates of 0.01 s⁻¹-10 s⁻¹， and a strain of 0.7. …”
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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

“…By adjusting the key parameters of the Convolutional Neural Network (CNN) with IGWO, the prediction accuracy is significantly enhanced. …”
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