From word models to executable models of signaling networks using automated assembly by Benjamin M Gyori, John A Bachman, Kartik Subramanian, Jeremy L Muhlich, Lucian Galescu, Peter K Sorger

“…Abstract Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. …”
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Probabilistic Routing Based on Two-Hop Information in Delay/Disruption Tolerant Networks by Xu Wang, Rongxi He, Bin Lin, Ying Wang

“…Probabilistic routing protocol using history of encounters and transitivity (PRoPHET) is an efficient history-based routing protocol specifically proposed for DTNs, which only utilizes the delivery predictability of one-hop neighbors to make a decision for message forwarding. …”
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Historical Reconstruction of Astronaut Cancer Risk: Context for Recent Solar Minima by Tony C. Slaba

“…., sunspot number records and radionuclide yields from ice cores and/or tree rings) combined with model predictions have also been used to infer that the Sun may be entering into a quiet period similar to the Dalton or Gleissberg minima when GCR fluences reached historically high levels. …”
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Machine learning discovery of the dielectric properties of strontium-containing condensed matter by Dongyang Huang, Jiaxing Fu, Chenghao Yu

“…Traditional theoretical predictions or first-principles calculations of dielectric constants are often challenging and require significant time and computational resources. …”
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An explainable and federated deep learning framework for skin cancer diagnosis. by Shuvo Biswas, Sajeeb Saha, Muhammad Shahin Uddin, Rafid Mostafiz

“…To ensure model interpretability, an XAI-based algorithm named Local Interpretable Model-Agnostic Explanations (LIME) was used to explain the predictions of the proposed framework. …”
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Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification by Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah

“…The study applied these algorithms to analyze the most influential variables affecting HDI. …”
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Adaptive Kalman Filter Fusion Positioning Based on Wi-Fi and Vision by Shuxin Zhong, Li Cheng, Haiwen Yuan, Xuan Li

“…In the experimental section, the real trajectory data and the predicted trajectory data generated using different positioning methods are compared. …”
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Classifying software security requirements into confidentiality, integrity, and availability using machine learning approaches by Taghreed Bagies

“…Our results revealed that SVM with the sentence-transformer technique outperformed all classifiers by 87% accuracy in predicting a type of security dimension.…”
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COVID-19 Pandemic Forecasting Using CNN-LSTM: A Hybrid Approach by Zuhaira M. Zain, Nazik M. Alturki

“…Furthermore, we demonstrated that the suggested model produced satisfactory predicting results even with a small amount of data.…”
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Research of Large Inflow Angles BEMT-Based Analytical–Numerical Performance Evaluation Model by Carlos Sosa Henríquez, Martynas Lendraitis

“…Drawing upon the theoretical framework presented by Stahlhut, the algorithm enables a more complex understanding of proprotor dynamics, facilitating accurate predictions of the loads at each blade section. …”
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ANN-Based Maximum Power Tracking for a Grid-Synchronized Wind Turbine-Driven Doubly Fed Induction Generator Fed by Matrix Converter by Mohamed A. Alarabi, Sedat Sünter

“…To address this, an artificial neural network (ANN) is adopted to predict the optimal shaft speed, ensuring maximum power point tracking (MPPT) for a wind energy-driven DFIG connected to a matrix converter (MC). …”
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Unraveling the Drivers of ESG Performance in Chinese Firms: An Explainable Machine-Learning Approach by Hyojin Kim, Myounggu Lee

“…This study develops an explainable artificial intelligence framework using SHAP and permutation feature importance (PFI) methods to predict the ESG performance of Chinese firms. We analyze comprehensive ESG data of 1608 Chinese listed companies over 13 years (2009–2021), integrating financial and non-financial determinants traditionally examined in isolation. …”
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A numerical framework for enhancing the seismic resilience of urban infrastructure in clayey basins using finite element modeling and AI optimization by Kaveh Dehghanian

“…AI-based sensitivity analysis has singled out key parameters influencing seismic resilience; real earthquake data validates model predictions. This study provides a systemic approach toward enhancing the seismic resilience of urban infrastructure in clayey basins, with information applicable for earthquake risk mitigation and infrastructure design.…”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…A hybrid ensemble approach is then proposed, integrating the predictions of the three optimized CNN-LSTM models to reduce error and enhance forecasting stability. …”
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A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things. by Umhara Rasool Khan, Javaid A Sheikh, Aqib Junaid, Shazia Ashraf, Altaf A Balkhi

“…In this article, regression-based Machine learning (ML) techniques are used to facilitate the design of Horse shoe shaped patch antenna to predict the frequency of operation, radiation efficiency and Specific Absorption Rate (SAR) values to accelerate its design process for on-body applications. …”
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Making JavaScript Render Decisions to Optimize Security-Oriented Crawler Process by Onur Aktas, Ahmet Burak Can

“…Addressing this crucial gap, our study introduces an innovative approach to predict the necessity of JavaScript rendering, thereby enhancing the effectiveness and efficiency of security-oriented web crawlers. …”
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Energy-Efficient and Fault-Tolerant Control of a Six-Axis Robot Based on AI Models by Patryk Nowak, Zoran Pandilov

“…Specifically, a genetic algorithm is used to generate learning data for the selection of the optimal kinematic configuration of the robot, and a multilayer perceptron is utilized to predict the parameters of the defined reward function. …”
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Intelligent design and synthesis of energy catalytic materials by Linkai Han, Zhonghua Xiang

“…We provide the illustrations of predicting the properties of catalytic materials with ML assistance in different material types. …”
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Vehicle Pose Estimation Method Based on Maximum Correntropy Square Root Unscented Kalman Filter by Shuyu Liu, Ying Guo

“…The method first generates an estimate of the predicted state and covariance matrix through the Unscented Transform (UT), and then obtains the square root matrix of the covariance through Cholesky and QR decomposition to replace the original covariance, effectively preserving the positive definiteness of the covariance and improving the accuracy of the algorithm. …”
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DIGITAL TWINS AND THEIR APPLIANCE IN TRANSPORT ECONOMICS by O. N. Rimskaya, I. V. Anokhov

“…The consequence of this is the emergence of digital twins that allow modeling and predicting the behavior of both individual processes and enterprises as a whole.The aim of the article is to investigate the process of digitalization in the transport industry. …”
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