H-ConvLSTM to Estimate Reference Evapotranspiration From Air Temperature and Relative Humidity by Abdul Haris, M. Marimin, Sri Wahjuni, Budi Indra Setiawan

“…These three algorithms have been extensively evaluated and validated due to their ability to predict and estimate ETo data using temperature (T), relative humidity (RH), and solar radiation (Rs) as variables. …”
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Domain Adaptation and Fine-Tuning of a Deep Learning Segmentation Model of Small Agricultural Burn Area Detection Using High-Resolution Sentinel-2 Observations: A Case Study of Pun... by Anamika Anand, Ryoichi Imasu, Surendra K. Dhaka, Prabir K. Patra

“…Subsequent fine-tuning using annotated data from Punjab improved the model’s ability to detect small burn patches, demonstrating higher accuracy than the baseline Normalized Burn Ratio (NBR) Index method. …”
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Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns by Junfeng Sun, Yong Fang, Hu Luo, Zhigang Yao, Long Xiang, Jianfeng Wang, Yubo Wang, Yifan Jiang

“…The ability to predict tunnel deformation holds great significance for ensuring the reliability, safety, and sustainability of tunnel structures. …”
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Predicting steady degradation in ship power system: A deep learning approach based on comprehensive monitoring parameters by Xingshan Chang, Xiaojian Xu, Bohua Qiu, Muheng Wei, Xinping Yan, Jie Liu

“…During the SD process, YC2Model exhibits high predictive accuracy, an ability to capture changes in degradation mechanisms and robust adaptability to degradation trends. …”
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Search Guidance Network Assisted Dynamic Particle Swarm Optimization Algorithm by LIU Zhi, SONG Wei

“…The learning target of each input particle is selected based on the hidden layer of SGN, and its acceleration coefficient is adjusted in the output layer to guide the search of particles. …”
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Evaluation of the performance of three pulse oximeters at different probe positions in awake rabbits. by Giulia Maria De Benedictis, Barbara Contiero, Daniele Bovo, Vincenzo De Rosa, Martina Cardinali, Francesca Zanusso

“…The Edan devices showed superior ability to detect reliable values of SpO2 and PR compared to the Masimo in rabbits. …”
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Composite Metal Oxide Nanopowder-Based Fiber-Optic Fabry–Perot Interferometer for Protein Biomarker Detection by Ulpan Balgimbayeva, Zhanar Kalkozova, Kuanysh Seitkamal, Daniele Tosi, Khabibulla Abdullin, Wilfried Blanc

“…The biosensor has demonstrated an impressive ability to detect biomarkers in a wide range of concentrations, from 1 aM to 100 nM. …”
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Development and validation of odour identification tests for olfactory assessment in Singapore by Xinni Xu, Margaret Ru Xiang Zhang, Terese Huiying Low, Yew Kwang Ong

“…Both tests had good test-retest reliability (Pearson’s correlation coefficient of 0.88 with P < 0.001 for SS-Sg; and at 0.90 with P < 0.001 for Scentsor). …”
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Stripe-Patterned Al/PDMS Triboelectric Nanogenerator for a High-Sensitive Pressure Sensor and a Novel Two-Digit Switch with Surface-Edge Enhanced Charge Transfer Behavior by Chung-Yu Yu, Chia-Chun Hsu, Chin-An Ku, Chen-Kuei Chung

“…A triboelectric nanogenerator (TENG) holds significant potential as a self-powered pressure sensor due to its ability to convert mechanical energy into electrical energy. …”
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Novel FTLRNN with Gamma Memory for Short-Term and Long-Term Predictions of Chaotic Time Series by Sanjay L. Badjate, Sanjay V. Dudul

“…Static multi layer perceptron (MLP) model is also attempted and compared against the proposed model on the performance measures like mean squared error (MSE), Normalized mean squared error (NMSE), and Correlation Coefficient (r). The standard back-propagation algorithm with momentum term has been used for both the models.…”
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Modeling study of the magnetocaloric behavior of La₀.₆₇Ca₀.₃₃Mn₀.₉₈Ni₀.₀₂O₃ alloys using artificial neural networks by Kawther Laajimi, Emna Ammar Elhadjamor, Radhouane Laajimi, Mehdi Rahmani, Mohamed Hichem Gazzah

“…The model showed outstanding performance with a coefficient of determination (R²) of 0.999241 and a root mean square error (MSE) of 0.003472. …”
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Effect of Drying Method on Selected Physical and Functional Properties of Powdered Black Soldier Fly Larvae by Radosław Bogusz, Małgorzata Nowacka, Ewa Gondek, Murat Delman, Karolina Szulc

“…The FTIR spectrum of the CD-dried powder showed lower absorption at key wavenumbers for the protein (1625 and 1350–1200 cm⁻¹), indicating lower denaturation and less ability to bind water and water vapor. The mathematical modeling of the water vapor adsorption kinetics of insect powders via the second Fick’s law for transient diffusion showed that this equation is suitable for adjusting the experimental data based on the high coefficient of determination (0.997–0.999) and the low root mean square (2.50–3.34%). …”
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Quantifying cross-country ski–snow friction using real-time kinematic positioning by Kalle Kalliorinne, Joakim Sandberg, Gustav Hindér, Hans-Christer Holmberg, Matej Supej, Roland Larsson, Andreas Almqvist

“…While the sled was running on a classic ski track with natural height variations, altitude and velocity data were recorded for quantification of the coefficient of friction (COF), both for accelerating and decelerating motion, employing a model based on Newton’s second law. …”
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Spatial Ecology of a Resident Avian Predator During the Non-Breeding Period in Managed Habitats of Southeastern Europe by Draženko Z. Rajković, Daliborka Stanković, Jelena Šeat, Dejan S. Stevanović, Miona V. Andrejević Stošović, Stefan Skorić

“…Also, adult and heavier males have smaller core area and home ranges than juvenile and lightweight individuals. The Bhattacharyya coefficient showed minor home range overlap in tagged males. …”
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Экологическая пластичность коллекционных образцов озимой тритикале по зимостойкости by T. A. Babaytseva, E. N. Poltorydyadko, E. V. Kuznetsova

“…The factor ‘conditions’ (42%) and the interaction of the factors ‘conditions-variety’ had a dominating effect on the changing ability of the winter triticale samples. There have been determined significant differences in winter tolerance variability among the collection samples, the coefficient of the variability ranged from 6.9% to 48.9%. …”
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Harnessing Multiple Level Features to Improve Segmentation Performance of Deep Neural Network: A Case Study in Magnetic Resonance Imaging of Nasopharyngeal Cancer by Rongzhi Mao, Liangxu Xie, Xiaohua Lu, Jialu Pei, Xiaojun Xu, Shan Chang

“…The improved generalization ability suggests that harnessing multi-level features in deep neural networks can improve segmentation performance.…”
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To Evaluate the Effectiveness of Plasmapheresis as a Method for the Graft Disease Prevention in Patients with Keratoplasty by S. N. Sakhnov, V. V. Myasnikova, K. I. Melkonyan, S. V. Kravchenko

“…At the same time, the patients of the Main group who underwent plasmapheresis had the best graft survival rates: during the observation period, there were no cases of graft disease (in both subgroups).Conclusion: the obtained data indicate the ability of plasmapheresis, performed in the perioperative period, to prevent the development of graft disease in patients with keratoplasty.…”
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Estimating Subsurface Thermohaline Structure in the Tropical Western Pacific Using DO-ResNet Model by Xianmei Zhou, Shanliang Zhu, Wentao Jia, Hengkai Yao

“…In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE), and coefficient of determination (R²) were employed to evaluate the model’s performance. …”
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ANALYSIS OF THE RELATIONSHIP BETWEEN WATER QUALITY AWARENESS AND DRINKING WATER CONSUMPTION BEHAVIOR (CASE STUDY: MAJENE CITY AND CAMPALAGIAN VILLAGE, WEST SULAWESI) by Musafira Musafira, Nur Hilal A. Syahrir, Putri Indi Rahayu

“…SEM-PLS was employed for its ability to analyze latent variables and handle small sample sizes effectively. …”
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Multitask semantic change detection guided by spatiotemporal semantic interaction by Yinqing Wang, Liangjun Zhao, Yueming Hu, Hui Dai, Yuanyang Zhang

“…In particular, on the Landsat-SCD dataset, the F1 score (F1scd) reaches 91.64%, and the separation Kappa coefficient improves by 17.68%. These experimental results fully demonstrate the significant advantages of STGNet in improving semantic change detection accuracy, robustness, and generalization capability.…”
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