Exploring Multiscale Causal Interventions for Burned Area Estimation by A. Mustofa Irawan, A. Mustofa Irawan, M. Vall-llossera, M. Vall-llossera, C. López-Martínez, C. López-Martínez, A. Camps, A. Camps, A. Camps, G. Portal, M. Pablos, A. Alonso-González

“…Understanding complex causal interactions between local, continental, and global drivers remains a significant challenge in wildfire prediction systems. This study implements a causal inference framework combining the Peter-Clark momentary conditional independence (PCMCI) algorithm with <em>do</em>-calculus interventions to analyse land-atmosphere feedback mechanisms influencing wildfire dynamics across South Asia (India, Pakistan, Myanmar, and adjacent regions). …”
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Semi-supervised multi-task learning based framework for power system security assessment by Muhy Eddin Za’ter, Amir Sajadi, Bri-Mathias Hodge

“…Additionally, this framework incorporates a confidence measure for its predictions, enhancing its reliability and interpretability. …”
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Fuzzy-Logic-Based Energy Optimized Routing for Wireless Sensor Networks by Haifeng Jiang, Yanjing Sun, Renke Sun, Hongli Xu

“…Simulation results show that the algorithm effectively extends the network lifetime and has achieved energy efficiency and energy balance together, compared with similar algorithms.…”
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Investigating the Role of Code Smells in Preventive Maintenance by Junaid Ali Reshi, Satwinder Singh

“…Code smells, which are indicators of the software quality have not been put to an extensive study for as to determine their role in the prediction of defects in the software. This study aims to investigate the role of code smells in prediction of non-faulty classes. …”
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Pinna anthropometry in sex estimation: a machine learning-based approach by Emre Söylemez, Suna Tokgöz Yılmaz

“…We aimed to investigate the feasibility of sex prediction using anthropometric measurements of the pinna in machine learning. …”
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Enhancing Pest Detection: Assessing Tuta absoluta (Lepidoptera: Gelechiidae) Damage Intensity in Field Images through Advanced Machine Learning by Edwin Lewıs, Atilla Erdinç, Yavuz Selim Şahin, Alperen Kaan Bütüner, Hilal Erdoğan

“…The performance of the DTs algorithm, as evidenced by a high precision and an accuracy rate of 0.98 and 0.99 respectively, testifies to its robust predictive and classification abilities. …”
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Circadian phase resetting via single and multiple control targets. by Neda Bagheri, Jörg Stelling, Francis J Doyle

“…Through sensitivity analysis, we identify additional control targets whose individual and simultaneous manipulation (via a model predictive control algorithm) out-perform the open-loop light-based phase recovery dynamics by nearly 3-fold. …”
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Cheby-KANs: Advanced Kolmogorov&#x2013;Arnold Networks for Applying Geometric Deep Learning in Quantum Chemistry Applications by Amgad Abdallah Mahmoud, Andreas Pester, Maha M. Muttardi, Frederic Andres, Shihori Tanabe, Nicolas Greneche, Hesham H. Ali

“…In this work, we present an enhanced version of the Kolmogorov&#x2013;Arnold network (KAN) algorithm, called Cheby-KAN, that offers a more efficient, more reliable, and faster alternative to conventional KANs. …”
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Improving medical machine learning models with generative balancing for equity and excellence by Brandon Theodorou, Benjamin Danek, Venkat Tummala, Shivam Pankaj Kumar, Bradley Malin, Jimeng Sun

“…Abstract Applying machine learning to clinical outcome prediction is challenging due to imbalanced datasets and sensitive tasks that contain rare yet critical outcomes and where equitable treatment across diverse patient groups is essential. …”
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Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data by Qinkai Han, Zhentang Wang, Tao Hu

“…After comparing the regression accuracy of several popular algorithms in the MRA, the random forest is adopted for feature selection and regression prediction. …”
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Human Pose Estimation and Event Recognition via Feature Extraction and Neuro-Fuzzy Classifier by Muhammad Hanzla, Naif S. Alshammari, Shuaa S. Alharbi, Wasim Wahid, Nouf Abdullah Almujally, Ahmad Jalal, Hui Liu

“…Key point features are characterized through the degree of freedom, human landmark detection via the HSV algorithm, and angular point analysis using the media pipe algorithm. …”
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Optimization of drilling parameters to minimize delamination in CNT-filled GFRP composites using machine learning by Aveen K P, Ullal Vignesh Nayak, K M Pranesh Rao, Shivaramu H T, V Londhe Neelakantha, Shashikumar C M

“…A machine learning based multi-output random forest regression model with hyper parameter tuning was used to predict the T, F, and delamination factor (Fd). The algorithm showed that the most important parameter that influenced delamination was speed (s) followed by the feed rate (f) and filler content respectively. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…A multiple linear regression model was developed to estimate instantaneous fuel consumption (in L/100 km) using the gear predicted by the KNN algorithm and other relevant variables. …”
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A Novel Method of Parameter Identification for Lithium-Ion Batteries Based on Elite Opposition-Based Learning Snake Optimization by Wuke Li, Ying Xiong, Shiqi Zhang, Xi Fan, Rui Wang, Patrick Wong

“…Traditional evolutionary algorithms often fail to balance global and local search. …”
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Analysis of the Radiological Anatomy of the Proximal Femur after the Intramedullary Nailing of Trochanteric Fractures by Boris A. Maiorov, Igor G. Belenkiy, Gennadii D. Sergeev, Ivan A. Endovitskiy, Mariya A. Sergeeva, David A. Isakhanyan

“…To improve the quality of surgical treatment, it is worth paying an increased attention to the quality of the achieved reduction, implant selection, technical peculiarities of the fixation of types A2 and A3 fractures, improvement of preoperative planning algorithms, as well as development of criteria for intraoperative radiological assessment of the quality of the restoration of the proximal femur anatomy.…”
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Digital processing of images of nano-dimensional elements on nanostructured material surface using the ImageJ software by H. T. Dinh, N. V. Lushpa, K. V. Chernyakova, I. A. Vrublevsky

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Sparse wavelet decomposition in problems of vibration-based diagnostics of rotary equipment by Y. P. Aslamov, A. P. Aslamov, I. G. Davydov, A. V. Borsuk

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Data processing of non-stationary capillary viscometer for blood by V. G. Leshchenko, M. V. Goltsev, D. V. Mansurov, V. A. Mansurov

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Targets Spatial Coordinates Calculation in Angle-Difference Rangefinder Passive Location Complexes by Numerical Iterative Methods by A. A. Dmitrenko, S. Y. Sedyshev

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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. Predictive models were developed for both annual averages and seasonal variations. …”
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