Strategic Implementation of Super-Agents in Heterogeneous Multi-Agent Training for Advanced Military Simulation Adaptability by Huseyin Oktay Altun, Huseyin Furkan Ceran, Korkut Kutay Metin, Tolga Erol, Emre Fisne

“…Optimizing Heterogeneous Multi-Agent Training (HMAT) through scenario-specific adjustments to the Proximal Policy Optimization (PPO) algorithm, we tackle the complexity of tactical simulations. …”
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The future of precision orthopaedics: personalized data-driven practice by Deiary F. Kader, Andrew Coppola, Aditya Vijay, Andreas Fontalis, Fares S. Haddad

“…However, challenges related to data quality, algorithm transparency, ethical considerations, and infrastructure development must be addressed to ensure robust and equitable implementation. …”
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Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System by Hongseok Jang, Yeonho Lee, Hongseok Lee, Youngtaek Cha, Sungjoon Choi, Jongkyu Park

“…The ERMS, mounted on a mobile crane, continuously monitors the ground conditions in real time and predicts the likelihood of ground subsidence to prevent accidents. …”
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Computational modelling and optimization of porous plates for mandibular fracture fixation accounting for bone healing by Ali Mehboob, Imad Barsoum, Hassan Mehboob, Abdelhak Ouldyerou, Rashid K. Abu Al-Rub

“…The healing process was predicted using a mechano-regulation algorithm. Conventional plate showed excessive interfragmentary strain (IFS) of approximately 1.4 and 0.6 in the 0.5 mm and 2.0 mm fracture gaps, respectively, which resulted in delayed healing. 2 MPP bone plates exhibited improved biomechanical performance with less stress in the bone plates and improved micromovement at the fracture site, promoting early bone union. …”
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Mammography in 2022, from Computer-Aided Detection to Artificial Intelligence Applications by Filippo Pesapane, Chiara Trentin, Marta Montesano, Federica Ferrari, Luca Nicosia, Anna Rotili, Silvia Penco, Mariagiorgia Farina, Irene Marinucci, Francesca Abbate, Lorenza Meneghetti, Anna Bozzini, Antuono Latronico, Alessandro Liguori, Giuseppe Carrafiello, Enrico Cassano

“…Objective: During the last decades, advances in computing power, structured data, and algorithm development, developed a technology based on Artificial intelligence (AI) which is currently applied in medicine. …”
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Advanced water quality assessment using machine learning: Source identification and probabilistic health risk analysis by Amin Mohammadpour, Ehsan Gharehchahi, Mohammad Golaki, Majid Amiri Gharaghani, Fahime Ahmadian, Soroush Abolfathi, Mohammad Reza Samaei, Md Galal Uddin, Agnieszka I. Olbert, Amin Mousavi Khaneghah

“…The Extremely Randomized Trees (ExT) algorithm demonstrated strong predictive capability for RMS-WQI, with sensitivity analysis identifying electrical conductivity (EC) and chloride (Cl−) as the most influential parameters. …”
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Crop choice advisory for the West African Sudan Savanna based on soil type and presowing rainfall forecasts: A machine learning residual model approach by Toshichika Iizumi, Kohtaro Iseki, Kenta Ikazaki, Toru Sakai, Shintaro Kobayashi, Benoit Joseph Batieno

“…Using the random forest (RF) algorithm, residual models were developed for cowpea, groundnut, soybean, maize, millet, and sorghum cultivated at three locations in Burkina Faso. …”
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The adaptive dynamic programming signal control system for person in a connected vehicle environment by Zongyuan Wu, Shiming LI, Gen LI, Ben Waterson, Luyao Zhu, Decai Wang

“…Leveraging Connected Vehicle (CV) data, this study proposes a novel Person-Based Adaptive Control Algorithm (PB-ACA) to minimize average person delay at isolated urban intersections. …”
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Fusion of Medium- and High-Resolution Remote Images for the Detection of Stress Levels Associated with Citrus Sooty Mould by Enrique Moltó, Marcela Pereira-Sandoval, Héctor Izquierdo-Sanz, Sergio Morell-Monzó

“…The data were used to evaluate the performance of a Random Forest classifier in predicting intensity levels through cross-validation. …”
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Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in BrazilResearch in context by Rejane Santos-Silva, Pilar Tavares Veras Florentino, Thiago Cerqueira-Silva, Vinicius de Araújo Oliveira, Juracy Bertoldo Junior, George C.G. Barbosa, Gerson O. Penna, Viviane S. Boaventura, Pablo I. Pereira Ramos, Manoel Barral-Netto, Izabel Marcilio

“…We assessed EWS timeliness, sensitivity, and positive predictive value (PPV) against fixed-incidence dengue outbreak thresholds. …”
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The Immune‐Related Gene CD48 Is a Prognostic Biomarker Associated With the Breast Cancer Tumor Microenvironment by Yi Zhao, Hengheng Zhang, Wenwen Wang, Guoshuang Shen, Miaozhou Wang, Zhen Liu, Jiuda Zhao, Jinming Li

“…Conclusions CD48 may serve as an effective biomarker for predicting BCa patient prognosis and a potential immune‐related therapeutic target.…”
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Assessing the Spatial Benefits of Green Roofs to Mitigate Urban Heat Island Effects in a Semi-Arid City: A Case Study in Granada, Spain by Francisco Sánchez-Cordero, Leonardo Nanía, David Hidalgo-García, Sergio Ricardo López-Chacón

“…Green roofs (GRs) may minimize land surface temperature (LST) by modifying albedo. This research predicts, assesses, and measures the impact of reducing the LST by applying green roofs in buildings by using a Random Forest algorithm and different remote sensing methods. …”
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The Water Table Model (WTM) (v2.0.1): coupled groundwater and dynamic lake modelling by K. L. Callaghan, K. L. Callaghan, K. L. Callaghan, A. D. Wickert, A. D. Wickert, A. D. Wickert, R. Barnes, J. Austermann

“…However, we currently lack the capacity to simulate and predict these terrestrial water changes across the full range of relevant spatial (watershed to global) and temporal (monthly to millennial) scales. …”
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AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks by Xingchen Yu, Jiawen Zhao, Zhenxiu Xu, Junrong Wei, Qi Wang, Feng Shen, Xiaozeng Yang, Zhonglong Guo

“…For the optimization algorithm, we opted for the Adam optimizer and utilized the cross-entropy loss function. …”
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Bayesian inference of radial impurity transport in the pedestal of ASDEX Upgrade discharges using charge-exchange spectroscopy by T. Gleiter, R. Dux, F. Sciortino, T. Odstrčil, D. Fajardo, C. Angioni, J. Buchner, R.M. McDermott, T. Hayward-Schneider, G.F. Harrer, M. Faitsch, M. Griener, R. Fischer, E. Wolfrum, U. Stroth, the ASDEX Upgrade Team

“…This supports the hypothesis of additional transport associated with the predicted high-n ballooning-unstable region and the observed quasi- coherent mode.…”
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Berg Balance Scale Scoring System for Balance Evaluation by Leveraging Attention-Based Deep Learning with Wearable IMU Sensors by Zhangli Lu, Huiying Zhou, Honghao Lyu, Haiteng Wu, Shaohua Tian, Geng Yang

“…The key limitations included: a limited generalizability to severely impaired patients who were unable to walk independently, and the inability to predict the score of individual tasks.…”
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Chemical Composition, Chemometric Analysis, and Sensory Profile of <i>Santolina chamaecyparissus L.</i> (<i>Asteraceae</i>) Essential Oil: Insights from a Case Study in Serbia and... by Biljana Lončar, Mirjana Cvetković, Milica Rat, Jovana Stanković Jeremić, Jelena Filipović, Lato Pezo, Milica Aćimović

“…Chemometric analysis proved effective in predicting the oil’s composition, and sensory evaluation revealed a herbal aroma with earthy, woody, and camphoraceous notes. …”
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Modeling saturation exponent of underground hydrocarbon reservoirs using robust machine learning methods by Abhinav Kumar, Paul Rodrigues, A. K. Kareem, Tingneyuc Sekac, Sherzod Abdullaev, Jasgurpreet Singh Chohan, R. Manjunatha, Kumar Rethik, Shivakrishna Dasi, Mahmood Kiani

“…A well-known outlier detection algorithm is applied on the gathered data to assess the data reliability before model development. …”
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Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach by Dan Ben Ami, Kobi Cohen, Qing Zhao

“…In this paper, we present a novel multi-armed bandit (MAB)-based approach for client selection to minimize the training latency without harming the ability of the model to generalize, that is, to provide reliable predictions for new observations. We develop a novel algorithm to achieve this goal, dubbed Bandit Scheduling for FL (BSFL). …”
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Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation by Sixuan Wu, Yuanbin Tang, Qihong Pan, Yaqin Zheng, Yeru Tan, Junfan Pan, Yuehua Li

“…In addition, a machine learning model constructed based on Stepglm[backward] with the random forest algorithm achieved the highest C-index (0.999) and screened eight core genes, among which ST14 was noted for its excellent predictive ability. …”
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