Artificial intelligence for severity triage based on conversations in an emergency department in Korea by Jae Won Seo, Sung-Joon Park, Young Jae Kim, Jung-Youn Kim, Kwang Gi Kim, Young-Hoon Yoon

“…To verify the robustness of the models, we performed tenfold cross-validation. Based on the area under the receiver operating characteristic curve (AUROC) values, the support vector machine achieved the best performance among the term frequency-inverse document frequency-based conventional machine learning models with an AUROC of 0.764 (95% CI 0.019). …”
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Laser powder bed fusion dataset for relative density prediction of commercial metallic alloys by Germán Omar Barrionuevo, Iván La Fé-Perdomo, Jorge A. Ramos-Grez

“…This dataset offers a valuable resource for researchers to benchmark their results, better understand key factors influencing RD, and validate models or explore new machine-learning approaches tailored to L-PBF.…”
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Application of ai driven system for estimation of orders in the printing industry by Kostaryev D., Tkachenko V., Sizova N.

“…Initially designed for IT project evaluation, the system was enhanced with machine learning and data mining to deliver automated, transparent, and accurate order assessment. …”
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Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture by Saha Laboni, Dubey Ahilya

“…The proposed AI solutions are integrated platform of machine learning algorithms and sensor data, predictive analytics for the purpose to generate a water efficient irrigation framework reacts dynamically to the crops' needs and environmental conditions. …”
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Comparison of sample preparation methods for higher heating values in various sugarcane varieties using near-infrared spectroscopy by Kantisa Phoomwarin, Khwantri Saengprachatanarug, Jetsada Posom, Seree Wongpichet, Kittipong Laloon, Arthit Phuphaphud

“…The integration of NIR spectroscopy with machine learning presents a practical and scalable approach for accelerating the evaluation of sugarcane clones, offering significant advantages in terms of time efficiency, cost reduction, and sample throughput.…”
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Research Concept and Prospects of Key Technologies for Intelligent Perception, Early Warning, and Prevention of Bank Collapse Risks in the Middle and Lower Reaches of the Yangtze R... by Jinyou LU, Yinjun ZHOU, Caiyun DENG, Chao GUO, Lingyun LI

“…It develops a multi-scale universal model and a dynamic early warning technology system using coupled simulation, statistical analysis, and machine learning in prediction and early warning. …”
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The Relationship Between Surface Meteorological Variables and Air Pollutants in Simulated Temperature Increase Scenarios in a Medium-Sized Industrial City by Ronan Adler Tavella, Daniele Feijó das Neves, Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti, Flavio Manoel Rodrigues da Silva Júnior

“…This study utilized five years of daily meteorological data (from 1 January 2019 to 31 December 2023) to model atmospheric conditions and two years of daily air pollutant data (from 21 December 2021 to 20 December 2023) to simulate how pollutant levels would respond to annual temperature increases of 1 °C and 2 °C, employing a Support Vector Machine, a supervised machine learning algorithm. …”
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Prediction of Carbonate Reservoir Porosity Based on CNN-BiLSTM-Transformer by Yingqiang Qi, Shuiliang Luo, Song Tang, Jifu Ruan, Da Gao, Qianqian Liu, Sheng Li

“…Compared with traditional machine learning and deep learning models, the improved model better captures domain-specific information, resulting in an R² increase of 0.23 and reductions in RMSE and MAE by 0.016 and 0.014, respectively. …”
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Bibliometric analysis of financial management research issues in the information technologies field by O.Yu. Polchanov

“…Modern approaches to financial management are increasingly based on advanced computing techniques, such as machine learning and blockchain. The transformation of management approaches challenges traditional risk reduction systems, investment analysis and corporate governance. …”
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Research on the Maximum Regenerative Energy Commutation Control Strategy of a Dual-Mode Synergistic Energy Recovery Pump-Controlled Grinder by Bo Yu, Gexin Chen, Keyi Liu, Guishan Yan, Yaou Zhang, Yinping Liu

“…Machine learning models were compared for predicting the peak time of total recovered energy, with a neural network (NN) demonstrating superior accuracy (R² ≈ 0.99997). …”
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Adaptive high frequency data streaming for Soft Real-Time Industrial AI: A scalable microservices based architecture with dynamic downsampling by Telmo Fernández De Barrena, Alcides Fernandes, Juan Luis Ferrando, Ander García, Hugo Landaluce, Ignacio Angulo

“…This paper presents a novel IoT architecture wherein an Edge server dynamically down-samples sensor data before transmission to a Fog (central) server equipped with upsampling, feature extraction, machine learning (ML) inference, and network latency analysis services. …”
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Optical Versus Electronic Implementation of Probabilistic Graphical Inference and Experimental Device Demonstration Using Nonlinear Photonics by Masoud Babaeian, Patrick Keiffer, Mark A. Neifeld, Ratchaneekorn Thamvichai, Robert A. Norwood, Pierre-A. Blanche, John Wissinger, N. Peyghambarian

“…The probabilistic inference model has been widely used in various areas, such as error-control coding, machine learning, speech recognition, artificial intelligence, and statistics. …”
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Genome-wide DNA methylation patterns in Daphnia magna are not significantly associated with age by Ruoshui Liu, Marco Morselli, Lev Y. Yampolsky, Leonid Peshkin, Matteo Pellegrini

“…Our results showed no significant global differences in DNA methylation levels between young, mature, and old individuals, nor any age-related clustering in dimensionality reduction analyses. Attempts to construct an epigenetic clock using machine learning models did not yield accurate age predictions, likely due to the overall low DNA methylation levels and lack of robust age-associated methylation changes. …”
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A Study on the Spatial Perception and Inclusive Characteristics of Outdoor Activity Spaces in Residential Areas for Diverse Populations from the Perspective of All-Age Friendly Des... by Biao Yin, Lijun Wang, Yuan Xu, Kiang Chye Heng

“…Guided by the principles of all-age friendly and inclusive design, this study innovatively integrates eye-tracking and multi-modal physiological monitoring technologies to collect both subjective and objective perception data of different age groups regarding outdoor activity spaces in residential areas through human factor experiments and empirical interviews. Machine learning methods are utilized to analyze the data, uncovering the differentiated response mechanisms among diverse groups and clarifying the inclusive characteristics of these spaces. …”
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Impact of the COVID-19 pandemic on dengue in Brazil: Interrupted time series analysis of changes in surveillance and transmission. by Kirstin Oliveira Roster, Tiago Martinelli, Colm Connaughton, Mauricio Santillana, Francisco A Rodrigues

“…In this study, we estimated the gap between expected and observed dengue cases in each Brazilian state from March to April 2020 using an interrupted time series design with forecasts from machine learning models. We then decomposed the gap into the contributions of pandemic-induced changes in disease surveillance and transmission dynamics, using proxies for care availability and care seeking behavior. …”
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AI in Agriculture: Advanced Smart Irrigation for Enhanced Crop Yields by Rahman F.

“…The proposed smart irrigation system will leverage machine learning algorithms, predictive analytics, as well as other AI technologies and real time data in the soil moisture, weather conditions, crop health and water usage. …”
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Detecting microcephaly and macrocephaly from ultrasound images using artificial intelligence by Abraham Keffale Mengistu, Bayou Tilahun Assaye, Addisu Baye Flatie, Zewdie Mossie

“…Conclusion Deep learning models can enhance prenatal diagnosis workflows, especially in resource-constrained settings. …”
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Mapping Windthrow Severity as Change in Canopy Cover in a Temperate Eucalypt Forest by Nina Hinko-Najera, Paul D. Bentley, Samuel Hislop, Alison C. Bennett, Jamie E. Burton, Thomas A. Fairman, Sacha Jellinek, Julio C. Najera Umana, Lauren T. Bennett

“…We assessed percentage canopy cover from high-resolution aerial images of 455 randomly selected plots in disturbed and undisturbed areas to train a model and machine learning framework to predict landscape scale canopy cover from Sentinel-2 images. …”
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A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

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Domain- and Language-Adaptable Natural Language Interface for Property Graphs by Ioannis Tsampos, Emmanouil Marakakis

“…However, existing solutions are typically limited to high-resource languages; are difficult to adapt to evolving domains with limited annotated data; and often depend on Machine Learning (ML) approaches, including Large Language Models (LLMs), that demand substantial computational resources and advanced expertise for training and maintenance. …”
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