An Integrated Hybrid-Stochastic Framework for Agro-Meteorological Prediction Under Environmental Uncertainty by Mohsen Pourmohammad Shahvar, Davide Valenti, Alfonso Collura, Salvatore Micciche, Vittorio Farina, Giovanni Marsella

“…Machine learning models, including random forest and multi-layer perceptron (MLP), were hybridized to improve the prediction accuracy for both proxy yield and wind components (U and V that represent the east–west and north–south wind movement). …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…The KAN model with a 10-neuron mid-layer achieved an overall accuracy of 88.89%, outperforming the SNN results with a maximum accuracy of 87.84 for a model with 20 & 20-neuron hidden layers.…”
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Integrated Imager and 3.22 <italic>&#x03BC;</italic>s/Kernel-Latency All-Digital In-Imager Global-Parallel Binary Convolutional Neural Network Accelerator for Image Processing by Ruizhi Wang, Cheng-Hsuan Wu, Makoto Takamiya

“…This prototype achieved a latency of <inline-formula> <tex-math notation="LaTeX">$3.22~\mu \text{s}$ </tex-math></inline-formula>/kernel on the first layer convolution at a power supply of 1 V and a clock frequency of 35.7 MHz. …”
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Partial-Net: A Method for Data Gaps Reconstruction on Mars Images by Depei Gu, Dingruibo Miao, Jianguo Yan, Zhigang Tu, Jean-Pierre Barriot

“…The mask self-updating mechanism is applied simultaneously following the partial convolution of each layer, effectively tracking the shape of the mask and reconstructing missing areas during forward propagation. …”
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Graph-Based COVID-19 Detection Using Conditional Generative Adversarial Network by Imran Ihsan, Azhar Imran, Tahir Sher, Mahmood Basil A. Al-Rawi, Mohammed A. Elmeligy, Muhammad Salman Pathan

“…These reconstructed features serve as input to a classification module, comprising a multi-layer neural network, GCN, adept at processing graph-structured data, alongside conventional machine learning classifiers such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), and Random Forest (RF), facilitating categorization of chest X-ray images into COVID-19, pneumonia, and normal cases. …”
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Data-driven insights of flow over heated elliptic cylinders: Machine learning and CFD perspectives on non-Newtonian forced convection by Anika Tahsin Meem, Md. Zhangir Hossain, Hasina Akter, Md. Mamun Molla

“…To alleviate the computational cost of high-fidelity CFD simulations, surrogate machine learning (ML) models — Random Forest, XGBoost, Support Vector Regression (SVR), and Multi-Layer Perceptron (MLP) – are trained to predict CD, CL, and q′′¯. …”
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Construction and validation of a predictive model for meningoencephalitis in pediatric scrub typhus based on machine learning algorithms by Yonghan Luo, Wenrui Ding, Xiaotao Yang, Houxi Bai, Feng Jiao, Yan Guo, Ting Zhang, Xiu Zou, Yanchun Wang

“…Six predictive models—Logistic Regression, K-Nearest Neighbors, Naive Bayes, Multi-layer Perceptron(MLP), Random Forest, and XGBoost—were constructed using the training set and evaluated for performance, with validation conducted on the test set. …”
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Adjunctive antihypertensive therapy of primary glaucoma with a fixed combination drug of 1% brinzolamide and 0.5% timolol: efficacy and safety by S. Yu. Petrov, O. M. Kalinina, L. V. Yakubova, S. M. Kosakyan, L. V. Vasilenkova, O. M. Filippova, A. N. Zhuravleva, O. I. Markelova

“…The target points were intraocular pressure (IOP), visual acuity, perimetric indices (MD, PSD), mean retinal nerve fiber layer thickness, minimal neuroretinal rim width, retinal nerve fiber layer thickness in the macula, ganglion cell layer thickness in the macula, inner plexiform layer thickness, as well as the number of adverse events. …”
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Mapping clay fraction oxides in Brazil using Earth observation strategy by Jorge Tadeu Fim Rosas, José A.M. Demattê, Nícolas Augusto Rosin, Raul Roberto Poppiel, Nélida E.Q. Silvero, Merilyn Taynara Accorsi Amorim, Heidy S. Rodríguez-Albarracín, Letícia Guadagnin Vogel, Bruno dos Anjos Bartsch, José João Lelis Leal de Souza, Lucas de Carvalho Gomes, Danilo César de Mello

“…The best predictions were observed for Fe2O3 in the 0–20 cm layer (RMSE = 49.8 g.kg−1, RPIQ = 1.82, and R2 = 0.62), while the worst predictions were for SiO2 in the 80–100 cm layer (RMSE = 65.3 g.kg−1, RPIQ = 1.50 and R2 = 0.22). …”
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A comprehensive review on uncertainty modeling methods in modern power systems by Zhaoyuan Wang, Siqi Bu, Jiaxin Wen, Can Huang

“…In recent years, modern power systems integrated with renewable energy sources and communication technologies have been rapidly developed. However, the randomness and intermittency of renewable energy sources, together with the unexpected disturbances in the vulnerable cyber layer, introduce uncertainties into power systems, which pose huge threats to the stable operation of modern power systems and should be carefully considered. …”
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Nanoparticles Induced Biomimetic Remineralization of Acid-Etched Dentin by Venu Babu Devalla, B Srinidhi.v, S Pushpa, Taufin Neha, Sai naveen Pilli, Pakalapti Dharma Rayudu

“…After 30 days remineralization period, the samples were evaluated for micro tensile bond strength, hybrid layer morphology, and mineral composition of the hybrid layer. …”
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Air Traffic Simulation Framework for Testing Automated Air Traffic Control Solutions by Rebeka Anna Jáger, Géza Szabó

“…The framework consists of a two-layer structure: a traffic simulation layer for generating and updating aircraft positions, and an upper layer for managing control agents and traffic commands. …”
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On the Training Algorithms for Artificial Neural Network in Predicting the Shear Strength of Deep Beams by Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran

“…The ANN structure consists of an input layer with 9 neurons corresponding to 9 input parameters, a hidden layer of 10 neurons, and an output layer with 1 neuron representing the shear strength of RC deep beams. …”
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Chemical attributes and microbial activity of soil cultivated with cassava under different cover crops by Fernando S. Araújo, Josué R. Barroso, Lucas de O. Freitas, Mauro S. Teodoro, Zigomar M. de Souza, Jose L. R. Torres

“…The concentrations of soil Ca and K were greater in the fallow coverage and C. juncea areas in the 0-0.10 m soil layer; however, these nutrients differ in the soil layer below (0.10-0.20 m). …”
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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

“…In this study, we compared two different random selection patterns: SLG disperse random selection (DSLG) and SLG parallel random selection (PSLG). …”
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Enhancing burned area monitoring with VIIRS dataset: A case study in Sub-Saharan Africa by Boris Ouattara, Michael Thiel, Barbara Sponholz, Heiko Paeth, Marta Yebra, Florent Mouillot, Patrick Kacic, Kwame Hackman

“…The algorithm encompasses several steps, including pre-processing individual scenes, creating cloud-free composites, generating binary reference data for burned and non-burned areas, conducting a supervised classification using random forest, and performing region shaping. The VIIRS-BA final product, which includes three confidence levels (low, moderate, and high) known as the uncertainty layer, is compared to four other burned area products. …”
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Impact of microgravity on retinal neuroimmune responses and visual dysfunction in rats by Jin-Shuo Liu, Nai-Qin Yan, Ying-Yan Mao, Chen Xin, Da-Peng Mou, Xin-Xiao Gao, Jia Guo, Ning-Li Wang, Si-Quan Zhu

“…OCT and histological analyses revealed subtle photoreceptor layer damage: while the inner nuclear layer (INL) thickness remained relatively unchanged, the outer nuclear layer (ONL) thinned significantly, and the nerve fiber layer-ganglion cell layer complex thickness (NFL-GCL) complex initially thickened before later thinning. …”
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Thermography and physiology of stress in dairy calves in outdoor holding pens covered with geosynthetics by Jéssica C. D. Campos, Roberta Passini, Kaio F. M. do Nascimento

“…The geosynthetics studied can be used as roofing material for outdoor holding pens, with the geocomposite drainage layer being the most indicated for tropical regions.…”
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Data-driven cultural background fusion for environmental art image classification: Technical support of the dual Kernel squeeze and excitation network. by Chenchen Liu, Haoyue Guo

“…The DKSE module adopts various techniques such as dilated convolution, L2 regularization, Dropout, etc. in the multi-layer convolution process. Firstly, dilated convolution is introduced into the initial layer of the model to enhance the original art image's feature capture ability. …”
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Comparative evaluation of table egg quality of local and pure breed laying hens in response to storage period length by Metin PETEK, Tuğba KAHRAMAN

“…This study was made to investigate the fresh and stored egg quality characteristics of local and pure-breed layer chickens. The eggs were randomly collected from a commercial farm that raised different free-range layer flocks such as local Atak-S, commercial Nick Brown, pure-breed Sussex laying hen, and a local cross-breed hen, all of 50 weeks of age. …”
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