Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data by Netra R. Regmi, Nina D.S. Webb, Jacob I. Walter, Joonghyeok Heo, Nicholas W. Hayman

“…Results showed that the approach mapped ∼84% of observed landforms when covariates were at 2 m resolution to ∼89% when they were at 10 m resolution. However, predicted maps showed that the 2 m resolution covariates performed better at capturing accurate landform boundaries and details of small-sized landforms such as stream channels and ridges. …”
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Modeling microbial drug-resistance: from mathematics to pharmacoeconomics by Yu. M. Gomon, M. A. Arepyeva, Yu. E. Balykina, A. S. Kolbin, A. A. Kurylev, M. A. Proskurin, S. V. Sidorenko

“…The proposed mathematical model allows one to predict the changes in microbial  drug-resistance and choose the optimal algorithm of AMA consumption able to restrain the growth of drug-resistance.…”
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Can vegetation breakpoints in Eastern Mongolia rangeland be detected using Sentinel-1 coherence time series data? by Shuxin Ji, Ganzorig Gonchigsumlaa, Sugar Damdindorj, Tserendavaa Tseren, Densmaa Sharavjamts, Amartuvshin Otgondemberel, Enkh-Amgalan Gurjav, Munguntsetseg Puntsagsuren, Batnaran Tsabatshir, Tumendemberel Gungaa, Narantsetseg Batbold, Lukas Drees, Bayarchimeg Ganbayar, Dulamragchaa Orosoo, Bayartsetseg Lkhamsuren, Badamtsetseg Ganbat, Myagmarsuren Damdinsuren, Gantogoo Gombosuren, Batnyambuu Dashpurev, Thanh Noi Phan, Nandintsetseg Dejid, Thomas Müller, Lukas Lehnert

“…In drier and less intensively used areas, the predicted pattern agrees less with the known movements. …”
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Objective dairy cow mobility analysis and scoring system using computer vision–based keypoint detection technique from top-view 2-dimensional videos by Shogo Higaki, Guilherme L. Menezes, Rafael E.P. Ferreira, Ariana Negreiro, Victor E. Cabrera, João R.R. Dórea

“…In addition, the study determined the potential of a machine learning classification model to predict mobility scores based on the newly extracted mobility variables. …”
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Red cell distribution width and renal outcome in patients with non-dialysis-dependent chronic kidney disease. by Sayoko Yonemoto, Takayuki Hamano, Naohiko Fujii, Karin Shimada, Satoshi Yamaguchi, Ayumi Matsumoto, Keiichi Kubota, Nobuhiro Hashimoto, Tatsufumi Oka, Masamitsu Senda, Yusuke Sakaguchi, Isao Matsui, Yoshitaka Isaka

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The prognostic significance of long noncoding RNAs in bladder cancer: A meta-analysis. by Yuexin Xia, Zhiyuan Liu, Weijian Yu, Shihang Zhou, Linnan Shao, Wenqian Song, Ming Liu

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Visualising fibre path and generating G-code for melt electrowriting of tubular scaffolds using Grasshopper software by Kelly L. O’Neill, Taite McLoughlin, Georgia Van der Linden, Ignacio Lopez Buson, Naomi C. Paxton, Mary Polites, Paul D. Dalton

“…This visual prototyping platform through Rhinoceros and Grasshopper offers a new method in predicting fibre paths and incorporating scaffold design parameters, meeting the need for diverse tubular scaffolds in different fields. …”
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Understanding the evolutionary processes and causes of groundwater drought using an interpretable machine learning model by Zhiyuan Gan, Xianjun Xie, Chunli Su, Weili Ge, Hongjie Pan, Liangping Yang

“…We employed machine learning models and the Shapley Additive Explanation (SHAP), a game theory-based interpretability method, to understand and predict the evolution of groundwater drought by evaluating eight models with SHAP analysis in the West Liao River Plain (WLRP), with a semi-arid climate. …”
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Impact of Climate Change on the Distributional Potential of the Endemic Species Tamarix dubia Bunge and Conservation Implications for the Irano‐Turanian Region by Habibollah Ijbari, Jamil Vaezi, Maryam Behroozian, Hamid Ejtehadi

“…Under both future scenarios, we predicted a decrease in the suitable habitat range of T. dubia in the period 2041–2060. …”
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IDI diesel engine performance and exhaust emission analysis using biodiesel with an artificial neural network (ANN) by K. Prasada Rao, T. Victor Babu, G. Anuradha, B.V. Appa Rao

“…For the ANN modeling standard back propagation algorithm was found to be the optimum choice for training the model. …”
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A Real-Time Safety-Based Optimal Velocity Model by Awad Abdelhalim, Montasir Abbas

“…Then, we analyze the driver behavior to predict the shape of the underlying TTC-based desired velocity function. …”
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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
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Bamboo bio composite: A renewable and sustainable sound absorber for acoustic comfort in indoor settings by Hassan Irvani, Hassan Asilian Mahabadi, Ali Khavanin, Ali Safari Variani, Mohammad Javad SheikhMozafari

“…Furthermore, the impedance tube results exhibited noteworthy concordance with the predictions of the JCA model. Conclusively, the findings of this research underscore the potential of natural bamboo fiber-based composites as promising sound absorbers for effective sound control in indoor environments.…”
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Knowledge-guided self-learning control strategy for mixed vehicle platoons with delays by Jingyao Wang, Huinian Wang, Jian Song, Xingyu Chen, Jinghua Guo, Keqiang Li, Xunrui Li, Bowen Huang

“…This helps autonomous vehicles predict traditional vehicles’ trajectories. Secondly, to tackle delayed current state information, the study incorporates previous control instructions into the state representation of the soft actor-critic algorithm. …”
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A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders by Jorge Magalhães, Tomás Jorge, Rúben Silva, António Guedes, Diogo Ribeiro, Andreia Meixedo, Araliya Mosleh, Cecília Vale, Pedro Montenegro, Alexandre Cury

“…Abstract Wayside monitoring is a promising cost-effective alternative to predict damage in the rolling stock. The main goal of this work is to present an unsupervised methodology to identify out-of-roundness (OOR) damage wheels, such as wheel flats and polygonal wheels. …”
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A damage model that can be coupled with constitutive behavior prior to necking for SGAFC 780 steel by Seong Jin Lee, Taek Jin Jang, Hyunho Shin, Yongwon Ju, Sangho Bae, Jong-Bong Kim

“…They also predicted damage contours that reasonably correspond to the moments and locations of cracks observed during the tensile fracture tests. …”
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UAV-Based SAR-Imaging of Objects From Arbitrary Trajectories Using Weighted Backprojection by Alexander Grathwohl, Julian Kanz, Christina Bonfert, Christian Waldschmidt

“…Based on this model, the expected signal-to-clutter ratio (SCR) of any point target in a single measurement can be predicted. This allows weighting of the contributions with the goal of maximizing target contrast in the synthetic aperture radar (SAR) image. …”
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Investigating the Short-Circuit Problem Using the Planarity Index of Complex q-Rung Orthopair Fuzzy Planar Graphs by Abrar Hussain, Ahmed Alsanad, Kifayat Ullah, Zeeshan Ali, Muhammad Kamran Jamil, Mogeeb A. A. Mosleh

“…Some advantages of the projected study over the previous study are observed, and some future study is predicted.…”
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Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

“…The diffusion coefficient extracted from the moisture ratio function was used to assess the drying kinetics, while SEC was used to evaluate the energy efficiency of the EHD dehydrator under different parameter settings. To predict and control performance, an artificial neural network (ANN) model was developed, achieving a high R-value of 0.9781. …”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

“…Subsequently, a convolutional neural network is constructed based on the simulation data to predict the energy consumption and riding comfort under complex operation scenarios. …”
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