Geographically Aware Air Quality Prediction Through CNN-LSTM-KAN Hybrid Modeling with Climatic and Topographic Differentiation by Yue Hu, Yitong Ding, Wenjing Jiang

“…Comparative experiments demonstrated superior performance with a 23.6–59.6% reduction in Root-Mean-Square Error (RMSE) relative to baseline LSTM models, along with consistent outperformance over CNN-LSTM hybrids. …”
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Separating the albedo-reducing effect of different light-absorbing particles on snow using deep learning by L.-A. Chevrollier, A. Wehrlé, J. M. Cook, N. Pirk, L. G. Benning, A. M. Anesio, M. Tranter

“…Among these 180 surfaces, the albedo reduction due to light-absorbing particles was highly variable and reached up to 0.13, 0.21, and 0.25 for red algal blooms, mineral dust, and dark particles respectively. …”
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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…These models offer superior performance in handling large datasets, noise reduction, and feature extraction, making them ideal for this application. …”
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Combustion Control of Ship’s Oil-Fired Boilers Based on Prediction of Flame Images by Chang-Min Lee

“…Given its ease of application to existing ships, it is expected to contribute to sustainable air pollution reduction across the maritime environment.…”
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Study on Multiobjective Path Optimization of Plant Protection Robots Based on Improved ACO‐DWA Algorithm by Jing Niu, Chuanyan Shen, Lipeng Zhang, Guanghao Gao, Jiahao Zheng

“…Simulation results on Matlab R2021 show that this improved algorithm has an average of 28%, 16% and 37% reduction in three indicators of the travel path, the number of detours, and the calculation time, respectively. …”
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Impact of PM_2.5 Pollution on Solar Photovoltaic Power Generation in Hebei Province, China by Ankun Hu, Zexia Duan, Yichi Zhang, Zifan Huang, Tianbo Ji, Xuanhua Yin

“…Our analysis reveals that elevated PM_2.5 concentrations substantially attenuate solar irradiance, resulting in PV power losses reaching up to a 48.2% reduction in PV power output during severe pollution episodes. …”
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Urban Fire Spatial–Temporal Prediction Based on Multi-Source Data Fusion by Haiyu Xiang, Lizhi Wu, Zidong Guo, Shaoyun Ren

“…Extensive evaluations on real-world datasets from Anci and Guangyang Districts demonstrate that UFSTP achieves a 16.2% average reduction in Mean Absolute Error (MAE) for time prediction and a 3.3% average improvement in top-1 hit rate for regional prediction over state-of-the-art baselines. …”
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Distributed Relative Pose Estimation for Multi-UAV Systems Based on Inertial Navigation and Data Link Fusion by Kun Li, Shuhui Bu, Jiapeng Li, Zhenyv Xia, Jvboxi Wang, Xiaohan Li

“…The experimental results demonstrate that the system achieves a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>76</mn><mo>%</mo></mrow></semantics></math></inline-formula> reduction in positioning error compared to using data link measurements alone. …”
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A fast and fully automated system for segmenting retinal blood vessels in fundus images by Alqassab Ans Ibrahim Mahameed, Luque-Nieto Miguel-Ángel

“…Manual segmentation is time-consuming and prone to human error, leading to inconsistent results. Additionally, existing automated methods often struggle with low-quality images or variations in illumination, hindering their effectiveness. …”
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A Fast Multi-Scale of Distributed Batch-Learning Growing Neural Gas for Multi-Camera 3D Environmental Map Building by Chyan Zheng Siow, Azhar Aulia Saputra, Takenori Obo, Naoyuki Kubota

“…The experimental results show that the proposed method can extract topological features enough to integrate point cloud data sets, and it runs 14 times faster than the previous GNG method with a 23% reduction in the quantization error. Finally, this paper discuss the advantage and disadvantage of the proposed method through numerical comparison with other methods, and explain future works to improve the proposed method.…”
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Experimental and simulation study on fracture conductivity of acid-fracturing in Dengying Formation of Sichuan Basin by CHEN Xiang, WANG Guan, LIU Pingli, DU Juan, WANG Ming, CHEN Weihua, LI Jinlong, LIU Jinming, LIU Fei

“…As closure stress increases, different acids and combinations exhibit distinct patterns of conductivity reduction, with potential for two rapid decline phases. …”
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Unveiling the drivers of climate change: the impact of economic indicators, renewable energy consumption and human development through a panel ardl approach by Abhinav Pal, Zamurd Ali, Shagufta Tariq Khan, Chandan Kumar Tiwari, Mohd. Abass Bhat

“…These findings contribute to the understanding of the dynamics between economic growth, human development and emission reduction pathways in Asia.…”
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Tripability Analysis of Casing Strings in Directional Wells Using the Continuous Beam-Column and Buckling Theory by Gang Wang, Gang Liu, Kai Wang, Yichen Li, Yinan Hu

“…Through finite element method verification, the prediction was in line with the actual casing running operation and the improved model has the smallest prediction error, i.e., 6.58%, compared with the existing models. …”
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Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…Gas emission in the working face is influenced by a variety of factors. Dimensionality reduction methods, such as Principal Component Analysis, can reduce computational resources but may alter the original feature structure, leading to a loss of some detailed information in the dataset. …”
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Wireless Sensor Networks for Urban Development: A Study of Applications, Challenges, and Performance Metrics by Sheeja Rani S., Raafat Aburukba, Khaled El Fakih

“…Additionally, the proposed method obtains 36%, 30%, 46%, 35%, and 32% reduction in energy consumption, computation cost, execution time, error rate, and computational overhead, respectively, compared to conventional methods.…”
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Solar Wind Data Assimilation in an Operational Context: Use of Near‐Real‐Time Data and the Forecast Value of an L5 Monitor by Harriet Turner, Matthew Lang, Mathew Owens, Andy Smith, Pete Riley, Mike Marsh, Siegfried Gonzi

“…This suggests that an operational solar wind DA scheme would provide significant forecast improvement, with reduction in the mean absolute error of solar wind speed around 46% over forecasts without DA. …”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…The MLPNN monitors the mean squared error (MSE) and disruptive inputs throughout training and validation, revealing consistent MSE reduction over recovery periods. …”
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Effects of mindfulness meditation on human impulsivity: a systematic review and meta-analysis by Eric W. Tsang, Junling Gao, Chi Ngai Lo, Nicholas T. Trapp, Aaron D. Boes, Hinhung Sik

“…Neurophysiological findings showed a significant reduction in event-related potential amplitudes related to impulsivity, including N200, Error-Related Negativity (ERN), and P300 components (Cohen’s d = −0.65, 95% CI [−1.01, −0.08]). …”
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Participant motivators and perceptions of risks and benefits in adult Phase 2/3 COVID-19 vaccine clinical trials by Bettina Wunderlich, Brittany Feijoo, Rupali Limaye, Lawrence H. Moulton, Kawsar Talaat

“…While limited by low response rate and recall error, this study suggests that in future emergency situations, messaging should be prioritized to improve understanding of trials and vaccines.…”
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Multivariate forecasting of dengue infection in Bangladesh: evaluating the influence of data downscaling on machine learning predictive accuracy by Mahadee Al Mobin

“…Comparative analysis reveals that downscaling provided a $$28.5\%$$ 28.5 % improvement in accuracy and an $$89.3\%$$ 89.3 % reduction in mean absolute percentage error (MAPE) over non-downscaled data which has been proven to be statistically significant using the Wilcoxon signed rank test, illustrating the substantial advantages of employing downscaling for effective DENV forecasting. …”
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