A Methodology to Characterize an Optimal Robotic Manipulator Using PSO and ML Algorithms for Selective and Site-Specific Spraying Tasks in Vineyards by Roni Azriel, Oded Degani, Avital Bechar

“…This prediction served as decision support in selecting which configurations should be tested in the simulation, thereby reducing computational time. The integration of machine learning models in the proposed methodology resulted in an average runtime reduction of 59% while maintaining an average manipulability index score in comparison to the original approach, which did not include the XGBoost model. …”
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Efficient management of neonatal sepsis diagnosis using predictive analytics methods: a scoping review by KVKL Narasimha Rao, Pradeep Kumar Dadabada, Sanjita Jaipuria

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Unsupervised detection of high-frequency oscillations in intracranial electroencephalogram: promoting a valuable automated diagnostic tool for epilepsy by Wenjing Chen, Tongzhou Kang, Md Belal Bin Heyat, Jamal E. Fatima, Yuanning Xu, Dakun Lai

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Temporal and spatial variations of urban surface temperature and correlation study of influencing factors by Lei Ding, Xiao Xiao, Haitao Wang

“…This study investigates the influence of three-dimensional urban form characteristics on LST, using ECOSTRESS sensor data and four machine learning models. Six urban morphology variables—building density (BD), mean building height (MH), building volume (BVD), gross floor area (GFA), floor area ratio (FAR), and sky view factor (SVF)—are analyzed across different seasons and times of day. …”
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Prediction and Assessment of Myocardial Infarction Risk on the Base of Medical Report Text Collection by Margaryta Prazdnikova

“…This underscores the significant potential of leveraging textual data and machine learning methods in medical diagnostics. Moreover, the reduction in false predictions highlights the model's reliability and suitability for practical application. …”
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Nonlinear compressive reduced basis approximation for PDE’s by Cohen, Albert, Farhat, Charbel, Maday, Yvon, Somacal, Agustin

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Towards a minimum universal features set for IoT DDoS attack detection by Osama Ebrahem, Salah Dowaji, Suhel Alhammoud

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Landslide Susceptibility Evaluation Based on the Combination of Environmental Similarity and BP Neural Networks by Ruiting Wang, Wenfei Xi, Guangcai Huang, Zhiquan Yang, Kunwu Yang, Yongzai Zhuang, Ruihan Cao, Dingjie Zhou, Yijie Ma

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Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality by Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

“…We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. …”
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Short-Term Load Forecasting in Distribution Substation Using Autoencoder and Radial Basis Function Neural Networks: A Case Study in India by Venkataramana Veeramsetty, Prabhu Kiran Konda, Rakesh Chandra Dongari, Surender Reddy Salkuti

“…The input dataset dimensionality is reduced using autoencoder to build a light-weight machine learning model to be deployed on edge devices. …”
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Decoding Humor-Induced Amusement via Facial Expression Analysis: Toward Emotion-Aware Applications by Gabrielle Toupin, Arthur Dehgan, Marie Buffo, Clément Feyt, Golnoush Alamian, Karim Jerbi, Anne-Lise Saive

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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

“…A stacking ensemble model is developed with support vector machine (SVM), K-nearest neighbors (KNN), and extreme learning machine (ELM) to enhance forecast accuracy. …”
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Skin Microbiome alterations in heroin users revealed by full-length 16S rRNA sequencing by Ruiyang Tao, Xiang Wang, Xiaoyuan Zhen, Ruocheng Xia, Kaiqin Chen, Han Zhang, Yu Deng, Suhua Zhang

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Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers by Wentong Li, Yiyi Zhang, Chuanhong Li, Mingyang Jiang, Dong Wang, Luomeng Chao, Luomeng Chao, Luomeng Chao, Yuxia Yang

“…PPI network analysis identified HSP90AA1, HSPA1B, and DNAJB1 as core hub genes (degree centrality >20). Machine learning validation demonstrated their combined exceptional diagnostic efficacy (AUC=0.963, F1 = 0.88). …”
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Two-decade spatiotemporal variations in ground-level ozone over Ontario, Canada by Zhou Zang, Jane Liu, Erjia Ge, Yi Zhang

“…Understanding long-term trends and spatially explicit details of O3 is important for supporting air quality management in Ontario.MethodWe construct a high-resolution (daily, 10 km) dataset of maximum daily 8-hour average O3 (MDA8 O3) over Ontario from 2004 to 2023, through a two-step machine learning model. The model has incorporated our hypothesis that accounting for transboundary influences can enhance the accuracy of O3 estimation.ResultsValidation against in-situ measurements confirms the hypothesized high accuracy of the dataset (R2 = 0.82, RMSE = 4.99 ppb), outperforming the traditional model and two existing datasets. …”
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A new classification algorithm for low concentration slurry based on machine vision by Chuanzhen Wang, Xinyi Wang, Andile Khumalo, Fengcheng Jiang, Jintao Lv

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Location, Location, Location: The Power of Neighborhoods for Apartment Price Predictions Based on Transaction Data by Christopher Kmen, Gerhard Navratil, Ioannis Giannopoulos

“…This study leverages a decade-long dataset of 83,527 apartment transactions in Vienna, Austria, to train machine learning models using XGBoost. Unlike most prior research, the extended time span of the dataset enables predictions for multiple future years, providing a more robust long-term prediction. …”
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Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments by Uzair Khan, Mohd Tariq, Arif I. Sarwat

“…The increasing interests and recent advancements in artificial intelligence and machine learning have significantly accelerated the development of novel techniques for the state estimation of batteries in electrified vehicles’ battery management systems (BMSs). …”
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An AI-Based Framework for Characterizing the Atmospheric Fate of Air Pollutants Within Diverse Environmental Settings by Nataša Radić, Mirjana Perišić, Gordana Jovanović, Timea Bezdan, Svetlana Stanišić, Nenad Stanić, Andreja Stojić

“…This study introduces a novel artificial intelligence (AI) modeling framework that combines machine learning algorithms optimized through metaheuristics with explainable AI to capture complex interactions among pollutant concentrations, meteorological data, and socio-economic indicators. …”
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AI-Powered Forecasting of Environmental Impacts and Construction Costs to Enhance Project Management in Highway Projects by Joon-Soo Kim

“…To address this, our study proposes a machine learning-based predictive framework utilizing artificial neural networks (ANNs) and deep neural networks (DNNs), enhanced by autoencoder-driven feature selection. …”
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