Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy by Sun Chao, Hu Runze, Liu Niansong, Ding Jianjun

“…After comparing various optimized BP neural network models, the performance of the WOA-BP temperature compensation was the most outstanding, with an R2 of 97.89%, MAE of 1.4868, RMSE of 2.0416, and a convergence speed after 15 iterations, reducing detection errors and thus achieving precise detection of low-concentration mixed gases.…”
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Quantification of 3D Kinematic Measurements for Knee Flexion and Tibial Rotation Using an IMU-Based Sensor and Ultrasound Imaging System: A Cadaveric Study by Hamid Rahmatullah Bin Abd Razak, Nicolas Chua, Kah Weng Lai

“…Knee rotational stability is crucial for anterior cruciate ligament (ACL) procedures, yet, current clinical assessments are subjective and lack precision. …”
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Impact of modified parameterizations in CLM5.0 on soil hydrothermal dynamics in permafrost regions of the Qinghai–Tibet Plateau by Shu-Hua Yang, Lin Zhao, Guo-Jie Hu, Jian-Jun Cao, Qing Huang, Tong-Hua Wu, Xiao-Dong Wu, Yu-Xin Zhang, Yi-Zhen Du, Dong-Liang Li, Jian Chen, Ren Li

“…However, the inadequate representation of soil water‒heat transport processes in current land surface models (LSMs) introduces large uncertainty in simulating permafrost dynamics, particularly on the Qinghai–Tibet Plateau (QTP). …”
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A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy by Ilyas Nurmemet, Yilizhati Aili, Yang Xiang, Aihepa Aihaiti, Yu Qin, Bilali Aizezi

“…Effective soil salinity monitoring is crucial for sustainable land management in arid regions. Most current studies face limitations by relying solely on single-source data. …”
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Calibration of SUMO Microscopic Simulation for Heterogeneous Traffic Condition: The Case of the City of Khulna, Bangladesh by Md. Mynul Hossain Chowdhury, Tanmoy Chakraborty

“…The calibration process is done by minimizing the root mean square error (RMSE) of queue, and travel time, and combining both of them between observation and calibrated model. …”
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PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments by Shiji Hai, Xitai Na, Zhihui Feng, Jinshuo Shi, Qingbin Sun

“…To address this, this paper proposes a Predictive-Estimative Nonlinear Control (PENC) framework. This framework optimizes the UAV-gimbal system’s control inputs in real-time to ensure the target remains within the camera’s field of view (FOV) despite obstacles, while simultaneously using historical target state measurements to accurately estimate its current state. …”
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A High-resolution Soil Organic Carbon Map for Great Britain by Salar Mahmood, Beccy Wilebore, Rhosanna Jenkins, Katherine J. Willis, Marc Macias-Fauria, Shibu M. Ebrahim

“…Soil carbon sequestration represents 25% of all natural climate solutions to carbon. Current SOC maps for Great Britain (GB) are limited due to their coarse resolution (0.5–1 km). …”
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Estimation of Evaporation Rate Using Advanced Methods by Mohammed Falah Allawi, Uday Hatem Abdulhameed, Mohammed Freeh Sahab, Sadeq Oleiwi Sulaiman

“…Several applications of water resources, including hydrological, hydraulic, and an optimal agricultural irrigation system, depend heavily on accurate estimation of evaporation losses. …”
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3D Reconstruction of Asphalt Pavement Macro-Texture Based on Convolutional Neural Network and Monocular Image Depth Estimation by Xinliang Liu, Chao Yin

“…An innovative multi-scale feature fusion CNN model was developed based on an encoder–decoder architecture, along with an optimized training strategy for model parameters. For performance evaluation, multiple metrics were employed, including root mean square error (RMSE = 0.491), relative error (REL = 0.102), and accuracy at different thresholds (δ = 1/2/3: 0.931, 0.979, 0.990). …”
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Addressing underestimated carbon monoxide emissions in Taiwan using CMAQ and impacts on local ozone concentration by Chieh-Sen Tsai, Ping-Chieh Huang, Hsin-Chih Lai, John C. Lin, Hui-Ming Hung

“…With the minimum root mean square error (RMSE) analysis between simulation and observation, the optimal emission correction factors are estimated as 2, 4, and 3.6 for northern, central, and southern Taiwan, respectively. …”
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A Hybrid Approach for Forecasting Occupancy of Building’s Multiple Space Types by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Ahsan Raza Khan, Kamran Arshad, Khaled Assaleh, Naeem Iqbal Ratyal, Ahmed Zoha

“…Researchers are currently working on two key issues in building management systems. …”
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Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…Based on the outcomes of RMSE, R2, Adjusted R2, MAPE, AIC and BIC, the GB and Cat B outperformed the AB model.For the purpose to achieve consistent and favourable outcomes in irrigation forecasting with surface water suitability, the current research suggests merging modelling approaches from Cat B, GB, and AB. …”
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IMAGE QUALITY ANALYSIS OF AN INDUSTRIAL INSTANT NON-SCANNING TOMOGRAPHY SYSTEM WITH DIFFERENT COLLIMATORS by Alexandre França Velo, Alexandre Gimenes Alvarez, Margarida Mizue Hamada, Carlos Henrique de Mesquita

“…The greatest impact of the computed tomography (CT) applications currently occurs in medicine. In industry there is much interest of using CT in order to know the interior of: (i) industrial objects; (ii) machines and their means of production. …”
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Enhanced household energy consumption forecasting using multivariate long short-term memory (LSTM) networks with weather data integration by Aditya Pai H, Kritika Kumari Mishra, Mahesh T R, J V Muruga Lal Jeyan, Anu Sayal

“…This study introduces a TinyML-optimized multivariate LSTM model designed for resource-constrained environments, leveraging self-supervised learning to enhance predictive accuracy with minimal computational overhead. …”
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Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm by Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

“…Key variables were selected through correlation analysis, missing values were interpolated using K-means clustering, and model parameters were systematically optimized via grid search and cross-validation. Among the algorithms tested, LightGBM achieved the best performance (R² = 0.992, RMSE = 0.297), demonstrating both robustness and efficiency. …”
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Short-Term Load Forecasting for Electrical Power Distribution Systems Using Enhanced Deep Neural Networks by Shewit Tsegaye, Sanjeevikumar Padmanaban, Lina Bertling Tjernberg, Kinde Anlay Fante

“…The rationale for using enhanced Deep Neural Networks (DNNs) in the power distribution system for short-term load forecasting (STLF) originates from a thorough analysis of current trends, the emergence of the state-of-the-art use cases and approaches. …”
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A CNN deep learning approach to scour depth estimation around complex bridge piers in steady flow environments by Ngoc Thi Huynh, Anh Thu Thi Phan, Tan Tai Trieu, Ho-Hong-Duy Nguyen, Thanh Nhan Nguyen

“…Results show that the proposed 1D CNN model significantly outperforms traditional approaches, achieving higher coefficient of determination (R 2  = 0.85) values and lower root mean squared error (RMSE = 0.1125), mean absolute error (MAE = 0.1078), and scatter index (SI = 0.1149). …”
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Towards Real-Time Spatial Distance Monitoring of Power Transmission Lines Using LiDAR Point Clouds and Visual Imaging by Li Zhendong, Wang Feiran, Han Geng, Guo Xinyang, Shi Zhaoyang

“…Spatial distance estimation had a low Mean Absolute Error (MAE) of 0.16 meters and Root Mean Square Error (RMSE) of 0.23 meters. The rate of safety violations detected never exceeded 4% among all object pairs. …”
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Surfactant representation using COSMO screened charge density for adsorption isotherm prediction using Physics-Informed Neural Network (PINN) by Achmad Anggawirya Alimin, Kattariya Srasamran, Wanutchaya Yuenyong, Ampira Charoensaeng, Bor-Jier Shiau, Uthaiporn Suriyapraphadilok

“…Abstract Predicting surfactant adsorption using the currently available isotherm model is limited to one or two independent variables: equilibrium concentration and temperature. …”
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Development and application of the 3-PGCj model for predicting stand growth of Japanese cedar (Cryptomeria japonica) plantations by Hung-En Li, Ching-Chu Tsai, Kai-Chih Yin, Yen-Jen Lai, Su-Ting Cheng

“…The results revealed higher planting densities led to earlier attainment of the maximum mean annual increment and current annual increment, key for optimizing management decisions like thinning and rotation ages. …”
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