Estimativa do balanço de radiação por sensoriamento remoto de diferentes usos de solo no sudoeste da Amazônia brasileira / Estimative of radiation balance by remote sensing of diff... by Luiz Carlos Da Silva, José Maurício Cunha, Nadja Gomes Machado, Milton César Costa Campos, Marcelo Sacardi Biudes

“…The net radiation and biophysical parameters (NDVI, leaf area index, albedo and radiometric temperature) were estimated by the SEBAL algorithm, using images from the Landsat TM sensor 5 in July of 2009, 2010 and 2011. …”
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A simple yet effective approach for predicting disease spread using mathematically-inspired diffusion-informed neural networks by ByeongChang Jeong, Yeon Ju Lee, Cheol E. Han

“…GCNs are a recent deep learning algorithm designed to learn spatial relationship from graph-structured data. …”
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Analysis of Public Sentiment Towards LGBT on Twitter Social Media using Naïve Bayes Method by Yudhi Franata, Rizal, Rizki Suwanda

“…The classification model achieved an accuracy of 57%, precision of 52%, recall of 100%, and an F1-score of 68%. While the Naïve Bayes approach proved capable in sentiment classification, the model's accuracy could be further enhanced through improved data preparation or the application of more advanced algorithms.…”
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Improved Phase Diversity Wavefront Sensing with a Deep Learning-Driven Hybrid Optimization Approach by Yangchen Wang, Ming Wen, Hongcai Ma

“…The deep learning model provides an initial estimate of wavefront aberrations, which is further refined by the L-BFGS optimization algorithm to achieve high-precision reconstruction. …”
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Slax: a composable JAX library for rapid and flexible prototyping of spiking neural networks by Thomas M Summe, Siddharth Joshi

“…Alternative learning rules and algorithms could help further develop models and systems across the spectrum of performance, bio-plausibility, and complexity. …”
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Targeted molecular generation with latent reinforcement learning by Ragy Haddad, Eleni E. Litsa, Zhen Liu, Xin Yu, Daniel Burkhardt, Govinda Bhisetti

“…Proximal policy optimization is a state-of-the-art policy gradient algorithm capable of operating in continuous high-dimensional spaces in a sample-efficient manner. …”
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Super Twisted Sliding Mode Observer for Enhancing Ventilation Drive Performance by Prince, Byungun Yoon

“…The STSMO leverages the super twisted algorithm, a second-order SM technique, to minimize chattering while ensuring finite-time convergence and high resilience. …”
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Risk averse reproduction numbers improve resurgence detection. by Kris V Parag, Uri Obolski

“…An E>1generates timely resurgence signals (upweighting risky groups), while an E<1ensures local outbreaks are under control. …”
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Disentangling Multiannual Air Quality Profiles Aided by Self-Organizing Map and Positive Matrix Factorization by Stefano Fornasaro, Aleksander Astel, Pierluigi Barbieri, Sabina Licen

“…Currently, vast quantities of data are collected at high frequencies, and researchers must navigate multiannual, multisite datasets trying to identify possible pollutant sources while addressing the presence of noise and sparse missing data. …”
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Coal Combustion Warning System Based on TDLAS and Performance Research by Zhitao Xie, Guanyu Lin, Jianing Wang, Xi Wang, Weijia Li, Pengbo Li, Hengyuan Kong

“…Through the temperature compensation algorithm and normalized signals, the impact of factors such as ambient temperature and environmental noise is reduced, effectively improving the signal-to-noise ratio and accuracy. …”
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Dynamic Modeling of a Kaplan Hydroturbine Using Optimal Parametric Tuning and Real Plant Operational Data by Hong Wang, Sunil Subedi, Wenbo Jia

“…To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. …”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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Energy efficiency maximization in MIMO links aided by metasurfaces with global reflection constraints by Ayşegül Ilay Tunalı, Robert Kuku Fotock, Alessio Zappone, Giorgio Taricco, Giuseppa Alfano, Hakan Ali Çırpan

“…The two algorithms are compared, showing that the codebook-based method achieves performance with only a limited gap compared to the more complex sequential fractional programming algorithm. …”
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An integrated and cooperative architecture for multi-intersection traffic signal control by Qiang Wu, Jianqing Wu, Bojian Kang, Bo Du, Jun Shen, Adriana Simona Mihăiţă

“…However, relevant studies are usually independent of the urban traffic simulation environment, collaborative TSC algorithms and traffic signal communication. In this paper, we propose (1) an integrated and cooperative Internet-of-Things architecture, namely General City Traffic Computing System (GCTCS), which simultaneously leverages an urban traffic simulation environment, TSC algorithms, and traffic signal communication; and (2) a general multi-agent reinforcement learning algorithm, namely General-MARL, considering cooperation and communication between traffic lights for multi-intersection TSC. …”
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LSTM-JSO framework for privacy preserving adaptive intrusion detection in federated IoT networks by Shaymaa E. Sorour, Mohammed Aljaafari, Amany M. Shaker, Ahmed E. Amin

“…The framework dynamically optimizes hyperparameters using the Joint Strategy Optimization (JSO) algorithm, ensuring efficient model adaptation across heterogeneous IoT networks. …”
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Exploring dose–response variability and relative severity assessment in STZ-induced diabetes male NSG mice by Steven R. Talbot, Miriam Heider, Martin Wirth, Anne Jörns, Ortwin Naujok

“…In this pilot study the dose–response relationship of STZ in male NSG mice was investigated and additionally animal suffering was charted by applying the novel ‘Relative Severity Assessment’ algorithm. By this we successfully explored an STZ dose that reliably induced diabetes while reduced stress and pain to the animals to a minimum using evidence-based and objective parameters rather than criteria that might be influenced by human bias.…”
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Predominance Preferential Selection for Minimizing Surplus Parts in the Selective Assembly of a Flow Production System by Kanghyeon Shin, Hyobin Son, Kyohong Jin

“…This paper presents the Predominance Preferential Selection (PPS) algorithm, an advanced approach to optimizing selective assembly in flow production systems. …”
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Unmanned aerial vehicle image stitching based on multi‐region segmentation by Weidong Pan, Anhu Li, Xingsheng Liu, Zhaojun Deng

“…Compared to several popular image stitching algorithms in real experiments, the proposed method can essentially prevent the seamline from crossing significant ground objects to ensure the integrity of structural objects while achieving satisfactory accuracy and efficiency during the UAV image stitching process.…”
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DISEASES OF THE CARDIOVASCULAR SYSTEM – PREVENTIVE AND EDUCATIONAL ACTIVITIES WITHIN THE COUNTY PROGRAM OF PROPHYLAXIS AND PREVENTION OF HEALTH “TOGETHER FOR THE HEART” AMONG THE I... by Anna Ślifirczyk

“…The reduction of those risk factors minimizes the probability of disease, while in ill patients it causes a milder course of ailments and fewer complications (Kosobudzki, Bortkiewicz, 2012). …”
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Advanced heart disease classification based on multi-channel heart sound coupling features. by Yu Fang, Dongbo Liu, Zijian Guo, Hongxia Leng, Xing Liu, Xiaochen Wu

“…When applied to clinical congenital heart disease datasets, the proposed method achieved a classification accuracy of 95.6%, while on the PhysioNet heart sound challenge dataset, it reached an accuracy of 98.3%. …”
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