Fire spread simulations using Cell2Fire on synthetic and real landscapes by Minho Kim, Cristobal Pais, Marta C. Gonzalez

“…As wildfires have emerged into a global phenomenon with far-reaching impacts on the natural and built environments, FSM simulations provide crucial information to better understand and predict fire behavior in various landscapes. In this study, we tested Cell2Fire, a recently developed cellular automata-based FSM, against benchmarking models used in the U.S., Canada, and Chile. …”
Get full text

Cheby-KANs: Advanced Kolmogorov–Arnold Networks for Applying Geometric Deep Learning in Quantum Chemistry Applications by Amgad Abdallah Mahmoud, Andreas Pester, Maha M. Muttardi, Frederic Andres, Shihori Tanabe, Nicolas Greneche, Hesham H. Ali

“…In this work, we present an enhanced version of the Kolmogorov–Arnold network (KAN) algorithm, called Cheby-KAN, that offers a more efficient, more reliable, and faster alternative to conventional KANs. …”
Get full text

Research on an intelligent coagulant dosing system based on alum floc image recognition by FU Yuan, LEI Zhifeng, CUI Dongfeng, GUO Zhongquan, CAI Bohan, XIAO Yan, ZHOU Aijiao*

“…The system combines the YOLOv5 alum floc recognition algorithm and the Linear Regression dosing decision algorithm. …”
Get full text

Optimizing TCP Performance in Multi-AP Residential Broadband Connections via Minislot Access by Domenico Giustiniano, Eduard Goma, Alberto Lopez Toledo, George Athanasiou

“…We then introduce a simple analytical model that accurately predicts the TCP round-trip time (RTT) with a multi-AP TDMA policy and propose a resource allocation algorithm to reduce the observed TCP RTT with a very low computational cost. …”
Get full text

Experimental validation of the analytical modelling of a digitally created duffing acoustic nonlinear oscillator at low amplitudes by Morell Maxime, Collet Manuel, Gourdon Emmanuel, Ture Savadkoohi Alireza, De Bono Emanuele

“…Despite the several assumptions of the model, the analytical modelling is validated by the experiment, showing that the model is able to predict the two-degree-of-freedom system.…”
Get full text

Behaviour recognition of housed sheep based on spatio-temporal information by Lina Zhang, Bin Zhao, Chunming He, Fan Yang, Jue Zhang

“…Therefore, monitoring the behavior of sheep is helpful to predict the health status of sheep and thus safeguard the production performance of sheep. …”
Get full text

Hybrid model for wind power estimation based on BIGRU network and error discrimination‐correction by Yalong Li, Ye Jin, Yangqing Dan, Wenting Zha

“…Abstract Accurate estimation of wind power is essential for predicting and maintaining the power balance in the power system. …”
Get full text

Oncological alertness in the practice of a primary care dentist by V. V. Shkarin, Y. A. Makedonova, O. Yu. Afanasyeva, A. V. Poroshin, L. A. Devyatchenko

“…In most cases, it is not possible to accurately predict the probability of malignancy, however, at a clinical appointment, the most important aspect is to identify both risk factors and initial signs of the development of the pathological process in the absence of complaints from the patient.  …”
Get full text

SAGE2Splice: unmapped SAGE tags reveal novel splice junctions. by Byron Yu-Lin Kuo, Ying Chen, Slavita Bohacec, Ojvind Johansson, Wyeth W Wasserman, Elizabeth M Simpson

“…To test this hypothesis, we have developed an algorithm, SAGE2Splice, to efficiently map SAGE tags to potential splice junctions in a genome. …”
Get full text

The implementation of random survival forests in conflict management data: An examination of power sharing and third party mediation in post-conflict countries. by Andrew B Whetten, John R Stevens, Damon Cann

“…Further, the RSF, a previously under-used method for analyzing political science time-to event data, provides a novel approach for ranking of peace agreement criteria importance in predicting peace agreement duration. Our findings demonstrate a scenario exhibiting the interpretability and performance of RSF for political science time-to-event data. …”
Get full text

Landing attitude analysis and control of bouncing robots by WU Zhe, ZHOU Zupeng, YANG Quan

“…Finally, a prototype was built to verify the feasibility of using the momentum wheel to change the attitude of the bouncing robot.ResultsThe designed attitude control mechanism based on three orthogonal momentum wheels combined with the integral sliding mode control algorithm can effectively control the attitude of the robot after bouncing, and the proposed robot landing stability criterion can effectively predict the stability of the robot through the current robot state.…”
Get full text

DNFE: Directed network flow entropy for detecting tipping points during biological processes. by Xueqing Peng, Rui Qiao, Peiluan Li, Luonan Chen

“…Furthermore, the numerical simulations for 100-node and 1000-node gene regulatory networks illustrate the method's application for large-scale data. The DNFE method predicts active transcription factors, and further identified "dark genes", which are usually overlooked with traditional methods.…”
Get full text

Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

“…The results show that the maximum error between the calculation results of the developed numerical model and the experimental results is 3.87%, and the maximum error between the predicted values of the trained surrogate model and the true values is 0.15%. …”
Get full text

X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…The model effectively incorporates both spatial and temporal correlations in network traffic data, which improves its detection capability. The model predictions are explained using the XAI techniques. …”
Get full text

Hyperspectral Imaging Combined with Deep Learning for the Early Detection of Strawberry Leaf Gray Mold Disease by Yunmeng Ou, Jingyi Yan, Zhiyan Liang, Baohua Zhang

“…Overall, the fused feature-based model can reduce the dimensionality of the classification data and effectively improve the predicting accuracy and precision of the classification algorithm.…”
Get full text

In-silico and in-vitro morphometric analysis of intestinal organoids. by Sandra Montes-Olivas, Danny Legge, Abbie Lund, Alexander G Fletcher, Ann C Williams, Lucia Marucci, Martin Homer

“…Developing tools to assess and predict the behaviour of these systems may produce a more robust and standardised biological model to perform accurate clinical studies. …”
Get full text

Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser

“… # Conclusions Utilization of machine learning to predict NASH allows for wider recognition, timely intervention, and targeted treatments to improve or mitigate disease progression and could be used as an initial screening tool.…”
Get full text

Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model by Xinxiao Li, Yanyan Li, Shushuo Xu, Penghao Wang, Meng Hu, Haibin Li, Yongbin Wang

“…To assess how well the BSTS algorithm performs predictions, we split the observations into various training and testing ranges. …”
Get full text

Artificial intelligence in personalized cardiology treatment by Abbas Mohammadi, Sheida Shokohyar

“…Personalized medicine customizes interventions according to individual characteristics, with artificial intelligence (AI) playing a key role in analyzing complex data to improve diagnostic accuracy, predict outcomes, and optimize therapies. AI can identify patterns in imaging and biomarkers, facilitating the earlier detection of medical conditions. …”
Get full text

Sequential Multidimensional Scaling with Kalman Filtering for Location Tracking by Lan Anh Trinh, Nguyen Duc Thang, Dang Viet Hung, Tran Cong Hung

“…In this paper, we propose a solution to attenuate noise effects to MDS by combining MDS with a Kalman filter. A model is built to predict the noise distribution with regard to additive noises to the distance measurements following the Gaussian distribution. …”
Get full text