Simulation of urban development in the City of Rome: Framework, methodology, and problem solving by Simone Di Zio, Armando Montanari, Barbara Staniscia

“…In Italy’s case, the implementation of the UrbanSIM model involved the territory of Rome, including the municipalities of Rome and Fiumicino. …”
Get full text

Comparison of Deep and Machine Learning Approaches for Quebec Tree Species Classification Using a Combination of Multispectral and LiDAR Data by Omid Reisi Gahrouei, Jean-François Côté, Philippe Bournival, Philippe Giguère, Martin Béland

“…The results indicated that Dense Convolution Network (DenseNet) achieved the best overall accuracy of 78%, outperforming machine learning methods by 5%. In addition, the models’ performance was independently assessed using permanent and temporary ground sample plots, acknowledging the superiority of DenseNet in terms of overall accuracy (73%) in predicting the dominant species. …”
Get full text

Mapping the global distribution of livestock. by Timothy P Robinson, G R William Wint, Giulia Conchedda, Thomas P Van Boeckel, Valentina Ercoli, Elisa Palamara, Giuseppina Cinardi, Laura D'Aietti, Simon I Hay, Marius Gilbert

“…The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). …”
Get full text

Assessing climate risks from satellite imagery with machine learning: A case study of flood risks in Jakarta by Jeasurk Yang, Donghyun Ahn, Junbeom Bahk, Sungwon Park, Nurrokhmah Rizqihandari, Meeyoung Cha

“…Results confirm that our model can assess climate risks in a granular scale and further capture potential risks in the marginalized areas (e.g., slums) that were previously hard to predict. …”
Get full text

Gaze Estimation Based on a Multi-Stream Adaptive Feature Fusion Network by Changli Li, Enrui Tong, Kao Zhang, Nenglun Cheng, Zhongyuan Lai, Zhigeng Pan

“…The concatenated high-dimensional and fused low-dimensional features are processed through fully connected layers to predict the final gaze direction. Extensive experiments on the EYEDIAP, MPIIFaceGaze, and Gaze360 datasets validate the superiority of the proposed method.…”
Get full text

Using electro-inductive sensor to trace moving and non-moving objects tracked by S. S. Kolmogorova, S. V. Biryukov

“…The research carries out a spatial model of path tracking using the dynamic parameters of the object's position, as well as the path of motion of electric field source. …”
Get full text

Investigation of the dynamic charge transport behaviours under electron beam irradiation of advanced insulation materials for aerospace applications by Guangyu Sun, Xiong Yang, Wentong An, Kun Huang, Xiaogang Qin, Baipeng Song, Guanjun Zhang

“…The model reveals the spatial–temporal evolutions of the current, charge density, and electric field distribution. …”
Get full text

Estimating the impact of interventions against COVID-19: From lockdown to vaccination. by James Thompson, Stephen Wattam

“…Our model predicts far fewer cases and deaths than the equivalent equation-based SEIR model. …”
Get full text

Pan-cancer analysis uncovered the prognostic and therapeutic value of disulfidptosis by Yiwei Zhang, Zihua Li, Hengli Lu, Zongrui Jiang, Yixian Song, Zhanhui Ye, Chenzheng Gu, Kequan Chen, Anquan Shang

“…The nomogram based on the DRGs Score model could accurately predict the prognosis of patients with pan-cancer. …”
Get full text

Tier‐1 and Tier‐2A Scenario Parameterisation and Example Calculations ‐ In Support of the Revision of the Guidance Document on Persistence in Soil under Council Directive 91/414/EE... by European Food Safety Authority

“…The aim of this scheme is to assess such Predicted Environmental Concentrations (PEC), chosen to be the 90th spatial percentile, resulting from the use of the plant protection product. …”
Get full text

Evolution Law of Longitudinal Deformation Curve and Release Coefficient of Viscoelastic Rock by WANG Jiachen, MENG Lingzan, ZHANG Dingli, LU Song, WEN Ming

“…Empirical formulas are fitted for the longitudinal deformation curve, including time, spatial, and spatiotemporal factors. The research conclusion can provide a more convenient method for predicting the deformation of soft rock tunnels.…”
Get full text

Network control energy reductions under DMT relate to serotonin receptors, signal diversity, and subjective experience by S. Parker Singleton, Christopher Timmermann, Andrea I. Luppi, Emma Eckernäs, Leor Roseman, Robin L. Carhart-Harris, Amy Kuceyeski

“…Using receptor distribution and pharmacokinetic information, we recapitulate DMT’s effects on global control energy trajectories, demonstrating control models can predict pharmacological effects on brain dynamics.…”
Get full text

Estimates of Effective Number of Breeders Identify Drivers of Decline in Mid‐Atlantic Brook Trout Populations by Zachary L. Robinson, Jason A. Coombs, Mark Hudy, Keith H. Nislow, Andrew R. Whiteley

“…Our results are consistent with presently observed and predicted future impacts of climate change on populations of this cold‐water fish. …”
Get full text

A novel fusion of Sentinel-1 and Sentinel-2 with climate data for crop phenology estimation using Machine Learning by Shahab Aldin Shojaeezadeh, Abdelrazek Elnashar, Tobias Karl David Weber

“…The spatio-temporal analysis of the model predictions demonstrates its transferability across different spatial and temporal context of Germany. …”
Get full text

Study of Shale Gas Source Rock S-Wave Structure Characteristics via Dense Array Ambient Noise Tomography in Zhangjiakou, China by Si Chen, Zhanwu Lu, Haiyan Wang, Qingyu Wu, Wei Cai, Guowei Wu, Guangwen Wang

“…Employing a binary stratigraphic model, the study predicted shale content based on the velocity structure, with predictions exhibiting a moderate correlation (correlation coefficient of 0.58) with empirical data. …”
Get full text

Explainable artificial intelligence with temporal convolutional networks for adverse weather condition detection in driverless vehicles by Samah Alzanin

“…The CapsNet model is employed for feature extraction to recognize spatial hierarchies and capture intricate patterns from complex visual data. …”
Get full text

Ecological network construction and land degradation risk identification in the Yellow River source area by Haoxiang Zhang, Qian Song, Shiru Wang, Jianyun Zhao, Wenming Gao

“…Based on ordered weighted average operator, morphological spatial pattern analysis, ecological sensitivity, circuit theory, CA-Markov model, kernel density analysis, and other methods, this study aims to consider the positive and negative connections of the network thus constructing the ecological and risk network and predicting the potential risk areas in the future. …”
Get full text

Investigation on the early pressure load characteristics of bubbles in near-field underwater explosion with condensed-phase CL-20 explosive detonation by Yi Hao, Zhenxin Sheng, Bo Yan, Teng Xie, Lunping Zhang, Haibin Mao, Jun Yu

“…Validation against 1D detonation wave tests confirms the accuracy of our burn model. Numerical simulations of cylindrical and spherical CL-20 charges under near-field conditions show good agreement with the experimental data, highlighting the model’s precision in predicting shock wave propagation and interface motion. …”
Get full text

Study on the Risk of Urban Population Exposure to Waterlogging in Huang-Huai Area Based on Machine Learning Simulation Analysis—A Case Study of Xuzhou Urban Area by Shuai Tong, Jiuxin Wang, Jiahui Qin, Xiang Ji, Zihan Wu

Get full text

Enhanced Blood Loss Quantification Using a Novel Multi-Wavelength Imaging Approach by Ara Abigail E. Ambita, Laura T. David, Catherine Sim Co, Prospero C. Naval

“…Lastly, an individualized interpretation for each surgical test gauze is provided, a useful tool to understand how the machine learning model predicts the absorbed blood volume.…”
Get full text