A Data-Driven Method for Deriving the Dynamic Characteristics of Marginal Carbon Emissions for Power Systems by Bing Fang, Jiayi Zhang, Shuangyin Chen, Li Li, Shanli Wang, Mingzhe Wen

“…However, the existing research has normally considered the average carbon emissions as the indicator for the operation and planning of power systems. …”
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A Novel FECAM-iTransformer Algorithm for Assisting INS/GNSS Navigation System during GNSS Outages by Xinghong Kuang, Biyun Yan

“…While there has been considerable research into using neural networks to replace the GNSS signal output during such interruptions, these approaches often lack targeted modeling of sensor information, resulting in poor navigation stability. …”
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Sensitivity of WRF model parameterizations in simulating extreme rainfall over complex terrain – case of July 2020 over the Poyang Lake basin, China by Jinru Wu, Jianzhong Lu, Xiaoling Chen

“…In recent years, the Weather Research and Forecasting (WRF) model has been used to obtain reliable rainfall with higher spatial and temporal resolutions. …”
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Dynamic Spatial Small-Target Simulation System with Long-Exit Pupil Distance by Yi Lu, Xiping Xu, Ning Zhang, Yaowen Lv, Hua Geng

“…Experimental validation shows that the system’s star position error is better than −3.94″, and the angular distance error between stars does not exceed −7.69″. …”
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Experience of neuronet diagnosis and prediction of peptic ulcer disease by results of risk factors’ analysis by V. A. Lazarenko, A. E. Antonov, V. K. Markapuram, K. Awad

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Transformer-Based Models for Probabilistic Time Series Forecasting with Explanatory Variables by Ricardo Caetano, José Manuel Oliveira, Patrícia Ramos

“…Models leveraging these variables achieve up to 12.4% reduction in Normalized Root Mean Squared Error (NRMSE) and 2.9% improvement in Mean Absolute Scaled Error (MASE) compared to models that rely solely on past sales. …”
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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

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Leveraging deep learning for risk prediction and resilience in supply chains: insights from critical industries by Waleed Abdu Zogaan, Nouran Ajabnoor, Abdullah Ali Salamai

“…In the food and automotive sectors, the GRU model had the lowest mean absolute error and mean squared error, while the ANN model performed best in predicting electricity demand. …”
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Estimation of characteristics of supported object on vibration isolator using air suspensions by Kenta NAKANO, Hiroshi YAMAMOTO, Terumasa NARUKAWA

“…The estimation error of the moment of inertia is 24% at maximum regardless of the center of gravity of the supported object.…”
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SentiTSMixer: A Specific Model for Sales Forecasting Using Sentiment Analysis of Customer by Partha Ghosh, Subhashis Das, Subhankar Roy, Ankur Bhattacharjee, Agostino Cortesi, Soumya Sen

“…Experimental results on various types of Amazon data show that, depending on the dataset and the specific error detection techniques used, the proposed model delivers a reduction in error ranging from 65% to 99% compared to established models.…”
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Optimizing relay node selection in cooperative wireless body area networks with modified POA by A. Hena Rubavathy, S. Sundar

“…In the realm of Wireless Body Area Networks (WBANs), cooperative communications emerge as a crucial research focus, lauded for their capacity to mitigate fading and optimize spectral efficiency. …”
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Predicting Crown-width of Dominant Trees on Teak Plantation from Clonal Seed Orchards in Ngawi Forest Management Unit, East Java by Ronggo Sadono

“…AbstractThis study aims to determine the model of crown width development of the dominant teak tree planted using seeds from clonal seed orchards. The research was carried out in Ngawi Forest Management Unit on the good quality teak compartment having stands age from 6 to 15 years old. …”
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Optimization of thermal conductivity in coir fibre-reinforced PVC composites using advanced computational techniques by Saksham Anand, Venkatachalam Gopalan, Shenbaga Velu Pitchumani

“…Abstract This research focuses on enhancing the thermal conductivity of coir fibre-reinforced polyvinyl chloride (PVC) composites using advanced optimization techniques. …”
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Prediction of the remaining useful life of a milling machine using machine learning by Abbas Al-Refaie, Majd Al-atrash, Natalija Lepkova

“…Several ML algorithms were applied and the results were evaluated using five measures involving Accuracy, Mean Absolute Error (MAE), Mean Squared Error (MSE), R-squared, and R-squared adjusted. …”
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Simulation and Empirical Studies of Long Short-Term Memory Performance to Deal with Limited Data by Khusnia Nurul Khikmah, Kusman Sadik, Khairil Anwar Notodiputro

“…This research is proposed to determine the performance of time series machine learning in the presence of noise, where this approach is intended to forecast time series data. …”
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A comparison of relative survival and cause‐specific survival methods to measure net survival in cancer populations by Nupur Makkar, Quinn T. Ostrom, Carol Kruchko, Jill S. Barnholtz‐Sloan

“…Both are valid methodologies for estimating net survival and are used widely in medical research. In these analyses, we compare CSS to RS at selected cancer sites. …”
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Crowdsourced Indoor Positioning: Integrating 5G NR and WiFi Technologies by P. Ye, L. Chen

“…Indoor positioning technology is a key area of research in location-based services. Crowdsourced WiFi and mobile communication signal fingerprinting are critical for achieving large-scale indoor positioning for consumers. …”
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Pointer Meter Reading Recognition Based on YOLOv11-OBB Rotated Object Detection by Xing Xu, Liming Wang, Chunhua Deng, Bi He

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Forecasting Day-Ahead Electricity Demand in Australia Using a CNN-LSTM Model with an Attention Mechanism by Laial Alsmadi, Gang Lei, Li Li

“…The results show a significant reduction in both Mean Absolute Error and Mean Absolute Percentage Error, confirming the model’s effectiveness. …”
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Physics-data hybrid dynamic model of a multi-axis manipulator for sensorless dexterous manipulation and high-performance motion planning by Wu-Te Yang, Jyun-Ming Liao, Pei-Chun Lin

“…Meanwhile, the physics-based and data-driven based dynamic models are studied in this research to select the best model for planning. The physics-based model is constructed using the Lagrangian method, and the loss terms include inertia loss, viscous loss, and friction loss. …”
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