Fluid-Structure-Interaction in butterfly valves for hydropower: A numerical and experimental study by M. Berger, L. Zingerle, Ch Mayerl, T. Senfter, M. Pillei

“…The numerical results are validated through 2D/2C Particle Image Velocimetry (PIV) measurements of the flow field and Digital Image Correlation (DIC) for non-invasive deformation analysis. A mean absolute error of approximately 10 % between CFD and experimental data confirms the model’s reliability under operating conditions, while larger deviations at extreme angles highlight the limitations of 2D measurement techniques. …”
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Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…In order to address challenges such as the large computational workload, tedious training process, and multiple influencing factors associated with predicting earthquake casualties, this study proposes a Support Vector Machine (SVM) model utilizing Principal Component Analysis (PCA) and Bayesian Optimization (BO). The original data are first subjected to dimensionality reduction using PCA, with principal components contributing cumulatively to over 80% selected as input variables for the SVM model, while earthquake casualties are designated as the output variable. …”
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Feasibility of EfficientDet-D3 for Accurate and Efficient Void Detection in GPR Images by Sung-Pil Shin, Sang-Yum Lee, Tri Ho Minh Le

“…Traditional methods of analyzing ground-penetrating radar (GPR) data are labor-intensive and error-prone. This study presents a novel approach using the EfficientDet-D3 deep learning model for automated void detection in GPR images. …”
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Cross-validation of methods for the quantitative determination of phenazepam and its active metabolite in human blood plasma at various extractions by A. I. Platova, I. I. Kuzmin, D. V. Ivaschenko, I. I. Miroshnichenko

“…Cross-validation was performed at the end of the experiment using data from study samples. The Bland – Altman analysis was used to evaluate accuracy and precision. …”
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Carbon emission prediction method for expressway construction period based on PSO-BP neural network by Quansheng ZHAO, Fei LI, Feng′ai GUO, Jianyou YU, Shizhao XU, Yunpeng HU, Xiaomeng CHU

“…The 12 key indicators, including route length, subgrade length, pavement length, tunnel length, bridge and culvert length, interchange length, excavation volume, filling volume, diesel consumption, cement consumption, crushed stone consumption and steel consumption, were refined from the four dimensions of project length, construction, energy consumption and material consumption using the analytic hierarchy process (AHP). The data from 36 highway projects were used as empirical samples for model training, and a comparative analysis was conducted based on error indicators. …”
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Automated Fixed-Point Precision Optimization for FPGA Synthesis by Ines Winandy, Arnaud Dion, Florent Manni, Pierre-Loic Garoche, Dorra Ben Khalifa, Matthieu Martel

“…The distinguishing feature of our technique lies in its formal approach to error analysis: it systematically propagates numerical errors through computations to infer variable-specific fixed-point formats that guarantee user-specified accuracy bounds. …”
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A Hybrid STL-Deep Learning Framework for Behavioral-Based Intrusion Detection in IoT Environments by Abdullah AlHayan, Jalal Al-Muhtadi

“…The methodology involved principal component analysis (PCA) for dimensionality reduction and careful hyperparameter tuning. …”
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VAS value set still has its own application value compare with TTO value set of EQ-5D-3L in Chinese population by Lin Zhuo, Siyuan Gao, Rui Jin, Lang Zhuo, Xiuying Wang

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Optimal Parameter Extraction of PEM Fuel Cell Using a Hybrid Weighted Mean of Vectors and Nelder-Mead Simplex Method by Rahul Khajuria, Mahipal Bukya, Ravita Lamba, Rajesh Kumar

“…An optimization problem is framed and a sum of squared error (SSE) based objective function is formulated between estimated and experimental voltages. …”
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Preliminary Assessment of Geometric Variability Effects Through a Viscous Through-Flow Model Applied to Modern Axial-Flow Compressor Blades by Arnaud Budo, Jules Bartholet, Thibault Le Men, Koen Hillewaert, Vincent E. Terrapon

“…On the one hand, the TF simulations are fed with the exact radial distribution of the correlation parameters using RANS input data in order to isolate the modeling error from correlation empiricism. …”
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An improved MP-NMO correction method based on multiparameter fitting and its application by Xiaohui YANG, Pengfei YU, Jiawei ZHANG

“…ConclusionsThe results of this study provide a technical method for the high-fidelity processing of seismic data from structurally complex areas. This method is especially applicable to the analysis and anisotropic inversion of AVO/amplitude versus frequency (AVF) attributes.…”
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Modelling the Spatial Distribution of <i>Dosidicus gigas</i> in the Southeast Pacific Ocean at Multiple Temporal Scales Based on Deep Learning by Mingyang Xie, Bin Liu, Xinjun Chen, Wei Yu, Jintao Wang, Jiawen Xu

“…With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (<i>Dosidicus gigas</i>). …”
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Forest attribute maps: a support for small area estimation of forest disturbances by Ankit Sagar, Cédric Vega, Olivier Bouriaud, Christian Piedallu, Jean-Pierre Renaud

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An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms by Burhanettin Ozdemir, Ishak Pacal

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Predicting Sugar Yield From Sugarcane Using Machine Learning for Jaggery Production by Kathirvel Narayanasamy, Ilayaraja Venkatachalam

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Spatio-temporal scale identification of LUCC based on remote sensing images in Shenyang Economic Zone by Yue Wang, Xingrong Lu, Guohong Chen

“…However, current methodologies often suffer from subjectivity, experimental errors, and limitations in spatial representation, as they typically rely on statistical data. …”
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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

“…In addition, the SSA-BPNN model shows a high goodness of fit (R) and a good fit with the experimental data. The SSA-BPNN model underwent standard statistical validation tests, effectively predicting the erosion rate of coiled tubing with a high coefficient of determination and low errors, demonstrating a robust consistency between predicted and actual values. …”
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A tiered NARX model for forecasting day-ahead energy production in distributed solar PV systems by Sameer Al-Dahidi, Mohammad Alrbai, Bilal Rinchi, Loiy Al-Ghussain, Osama Ayadi, Ali Alahmer

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Computer Vision-Based Safety Monitoring of Mobile Scaffolding Integrating Depth Sensors by Muhammad Sibtain Abbas, Rahat Hussain, Syed Farhan Alam Zaidi, Doyeop Lee, Chansik Park

“…The qualitative analysis further confirms substantial improvements in worker position detection and safety compliance using 3D data over 2D approaches. …”
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Day-Ahead Electricity Price Forecasting Based on Hybrid Regression Model by Ali Najem Alkawaz, Abdallah Abdellatif, Jeevan Kanesan, Anis Salwa Mohd Khairuddin, Hassan Muwafaq Gheni

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