Marine soundscape forecasting: A deep learning-based approach by Shashidhar Siddagangaiah

“…The deep-learning forecasting models produced more accurate predictions in the mid (500–3000 Hz) (MAE ∼0.4–1) and high (3000–24,000 Hz) (MAE ∼1.5–3) frequency ranges, where seasonal acoustic activity from fish and shrimp strongly influenced sound levels. …”
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Analysis and Validation of Autophagy-Related Gene Biomarkers and Immune Cell Infiltration Characteristic in Bronchopulmonary Dysplasia by Integrating Bioinformatics and Machine Lea... by Xiao S, Ding Y, Du C, Lv Y, Yang S, Zheng Q, Wang Z, Zheng Q, Huang M, Xiao Q, Ren Z, Bi G, Yang J

“…Finally, we searched the drug targets of these hub genes, and established a nomogram model for predicting the risk of BPD.Results: There were 73 the differentially expressed and autophagy-related genes (DE-ARGs) by overlapping the DEGs in GSE8586 and ARGs. …”
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Formation of a heterogeneous group of UAVS with a reasonable number of false and real drones by Volodymyr Prymirenko, Andrii Demianiuk, Roman Shevtsov, Serhii Bazilo, Andrey Pilipenko, Mykola Vovchanskyi

“…The availability of the developed mathematical model, algorithm, and program code makes it possible to predict the possible results of the combat use of heterogeneous groups of UAVs based on the initial parameters and to substantiate recommendations for a possible composition of such groups.…”
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Estimating Winter Canola Aboveground Biomass from Hyperspectral Images Using Narrowband Spectra-Texture Features and Machine Learning by Xia Liu, Ruiqi Du, Youzhen Xiang, Junying Chen, Fucang Zhang, Hongzhao Shi, Zijun Tang, Xin Wang

“…Aboveground biomass (AGB) is a critical indicator for monitoring the crop growth status and predicting yields. UAV remote sensing technology offers an efficient and non-destructive method for collecting crop information in small-scale agricultural fields. …”
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Operation strategy analysis for the passenger and freight shared transportation system by Zuoning Jia, Siyuan Yang, Kun An, Wanjing Ma

“…A customized heuristic algorithm is developed, incorporating a vector clustering method, a matching technique, and parallel computation. …”
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Construction of a minimizing sequence for the problem of cooling of the given segments of the rod with phase constraint by A.I. Egamov

“…The possibility of its reduction to a finite shortened system was demonstrated for the resulting countable system of differential equations. …”
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Machine learning in Alzheimer’s disease genetics by Matthew Bracher-Smith, Federico Melograna, Brittany Ulm, Céline Bellenguez, Benjamin Grenier-Boley, Diane Duroux, Alejo J. Nevado, Peter Holmans, Betty M. Tijms, Marc Hulsman, Itziar de Rojas, Rafael Campos-Martin, Sven van der Lee, Atahualpa Castillo, Fahri Küçükali, Oliver Peters, Anja Schneider, Martin Dichgans, Dan Rujescu, Norbert Scherbaum, Jürgen Deckert, Steffi Riedel-Heller, Lucrezia Hausner, Laura Molina-Porcel, Emrah Düzel, Timo Grimmer, Jens Wiltfang, Stefanie Heilmann-Heimbach, Susanne Moebus, Thomas Tegos, Nikolaos Scarmeas, Oriol Dols-Icardo, Fermin Moreno, Jordi Pérez-Tur, María J. Bullido, Pau Pastor, Raquel Sánchez-Valle, Victoria Álvarez, Mercè Boada, Pablo García-González, Raquel Puerta, Pablo Mir, Luis M. Real, Gerard Piñol-Ripoll, Jose María García-Alberca, Eloy Rodriguez-Rodriguez, Hilkka Soininen, Sami Heikkinen, Alexandre de Mendonça, Shima Mehrabian, Latchezar Traykov, Jakub Hort, Martin Vyhnalek, Nicolai Sandau, Jesper Qvist Thomassen, Yolande A. L. Pijnenburg, Henne Holstege, John van Swieten, Inez Ramakers, Frans Verhey, Philip Scheltens, Caroline Graff, Goran Papenberg, Vilmantas Giedraitis, Julie Williams, Philippe Amouyel, Anne Boland, Jean-François Deleuze, Gael Nicolas, Carole Dufouil, Florence Pasquier, Olivier Hanon, Stéphanie Debette, Edna Grünblatt, Julius Popp, Roberta Ghidoni, Daniela Galimberti, Beatrice Arosio, Patrizia Mecocci, Vincenzo Solfrizzi, Lucilla Parnetti, Alessio Squassina, Lucio Tremolizzo, Barbara Borroni, Michael Wagner, Benedetta Nacmias, Marco Spallazzi, Davide Seripa, Innocenzo Rainero, Antonio Daniele, Fabrizio Piras, Carlo Masullo, Giacomina Rossi, Frank Jessen, Patrick Kehoe, Tsolaki Magda, Pascual Sánchez-Juan, Kristel Sleegers, Martin Ingelsson, Mikko Hiltunen, Rebecca Sims, Wiesje van der Flier, Ole A. Andreassen, Agustín Ruiz, Alfredo Ramirez, EADB, Ruth Frikke-Schmidt, Najaf Amin, Gennady Roshchupkin, Jean-Charles Lambert, Kristel Van Steen, Cornelia van Duijn, Valentina Escott-Price

“…Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. …”
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Developing a Sleep Algxorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study by Jeffrey M Cochran

“…ACC and ECG features were derived for each 5-minute window. The algorithm that most accurately predicted sleep parameters against PSG data was compared to commercially available wearable devices to further benchmark model performance. …”
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Carreau’s Rheological Model and A.N. Tikhonov’s Regularization Method: Parametric Identification Based on a CFD model by Anatoly A. Khvostov, Gazibeg O. Magomedov, Victor I. Ryazhskih, Aleksey V. Kovalev, Aleksey A. Zhuravlev, Magomed G. Magomedov

“…The error for the viscosity prediction did not exceed 14.07%. Conclusion. The parametric identification algorithm made it possible to evaluate the rheological parameters of structured liquid media with Carreau's rheological law in cases that lack experimental information on the behavior of the medium at limiting shear rates. …”
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Incidence, Disease Spectrum, and Outcomes of Tuberculous Meningitis in South African Children: The Initial Impact of COVID-19 by Victoria E. Namukuta, Mariette Smith, Danite Bester, Magriet van Niekerk, Regan Solomons, Ronald van Toorn, Hendrik Simon Schaaf, James A. Seddon, Helena Rabie, Mary-Ann Davies, Anneke C. Hesseling, Karen du Preez

“…An innovative surveillance algorithm was used to identify all possible TBM episodes using integrated electronic health data. …”
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AI-Assisted Pump Operation for Energy-Efficient Water Distribution Systems by Niuosha Hedaiaty Marzouny, Rebecca Dziedzic

“…The LLM-assisted framework was compared with a genetic algorithm optimization. The results demonstrated that the proposed method outperformed the GA, achieving an energy reduction of 66.98%.…”
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Panoramic video coding based on spherical distortion with spatio-temporal dependency by Xu YANG, Ce ZHU, Hongwei GUO, Lei LUO

“…The planar coding distortion, which affects objective quality, and spherical distortion, which affects subjective quality, as well as existing independent rate-distortion optimization techniques that fail to consider the temporal propagation of spherical distortion and its impact on coding performance, result in coding performance degradation.To address these issues, a spatio-temporal dependent spherical distortion model was proposed for optimizing panoramic video coding.Firstly, a spatial mapping model was proposed to map spherical distortions to coding distortions, aiming to align subjective and objective quality assessments.Secondly, a temporal propagation model for spherical distortions was introduced to enhance the overall coding performance of all coding units in the propagation chain.Finally, the coding parameters were adjusted by computing the weights for spatial mapping and temporal propagation of spherical distortions.Experimental results demonstrate that, under low-delay encoding configurations, compared to the VTM14.0, a state-of-the-art video coding benchmark, the proposed algorithm achieves an average bitrate savings of 7.4% (up to 22.1%) and reduction in coding time of 9%.…”
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Optimized actuator design for flapping-wing robots: A multi-objective approach to mimic natural flapping dynamics by Peiqi Li, Zhiwei Ai, Mufan Zhang

“…The optimization utilized the NSGA-II algorithm. Additionally, a virtual prototype with rigid-flexible coupling was created for simulation assessments pre- and post-optimization. …”
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ECG Paper Digitization and R Peaks Detection Using FFT by Ibraheam Fathail, Vaishali D. Bhagile

“…We used the fast Fourier transform (FFT) algorithm to calculate R peaks and calculate the heart rate. …”
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Characteristic changes the bending moments in shell of soil-steel structures by Czesław Machelski

“…The examples show a favorable reduction of bending moments in shells with a regular arc. …”
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Speaker Model Clustering to Construct Background Models for Speaker Verification by Gökay DİŞKEN, Zekeriya TÜFEKCİ, Ulus ÇEVİK

“…Then, the $k$-means algorithm with the Euclidean distance measure is applied to the speaker models. …”
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Decomposition pipeline for large-scale portfolio optimization with applications to near-term quantum computing by Atithi Acharya, Romina Yalovetzky, Pierre Minssen, Shouvanik Chakrabarti, Ruslan Shaydulin, Rudy Raymond, Yue Sun, Dylan Herman, Ruben S. Andrist, Grant Salton, Martin J. A. Schuetz, Helmut G. Katzgraber, Marco Pistoia

“…Our pipeline includes three main components: preprocessing of correlation matrices based on random matrix theory, modified spectral clustering based on Newman's algorithm, and risk rebalancing. Our empirical results show that our pipeline consistently decomposes real-world portfolio optimization problems into subproblems with a size reduction of approximately 80%. …”
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Reinforcement Learning-driven Mechanism Study of Ecological Compensation to Suppress Carbon Lock-in by Yongxin Zhou

“…Specifically, RL-MEC-CL, in a continuous action space, leverages an actor-critic architecture with experience replay and target networks to optimize compensation strategies adaptively, balancing carbon reduction benefits, sequestration enhancement, and policy costs. …”
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Fault diagnosis technology for three-level inverter based on ICEEMDAN-FE and SVM by CAO Ruijun, GUO Qiyi

“…Second, the characteristics of the α-β phase voltage were extracted by the ICEEMDAN algorithm to generate the intrinsic modal functions (IMFs) at multiple scales. …”
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Technics and Contingency by Alan Díaz Alva

“… This text aims to explore the relationship between technics and contingency within a context where computational technologies often have the effect of domesticating the latter, leading to its statistical reduction within the realm of the probable. I will argue that the post-prosthetic and non-correlational character of these technologies prompts us to pursue a line of inquiry that calls for a different understanding of contingency. …”
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