A Novel Audio Copy Move Forgery Detection Method With Classification of Graph-Based Representations by Beste Ustubioglu, Gul Tahaoglu, Arda Ustubioglu, Guzin Ulutas, Muhammed Kilic

“…The trained model was evaluated using five different datasets, demonstrating that this approach generally outperforms existing methods in terms of detection accuracy. …”
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A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification by Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan

“…Through an intensive comparison with present algorithms assessed in variety of performance evaluating metrics the present study emphasize the exceptional ability of proposed approach to accurately classify the different MI categories from the EEG signals and which is a great contribution to the field of BCI research field.…”
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Sagittal Plane Kinematic Deviations and Spatio-Temporal Gait Characteristics in Children with Idiopathic Toe Walking: A Comparative Analysis Using Statistical Parametric Mapping by Rocio Pozuelo-Calvo, Almudena Serrano-Garcia, Yolanda Archilla-Bonilla, Angel Ruiz-Zafra, Manuel Noguera-Garcia, Kawtar Benghazi-Akhlaki, Miguel Membrilla-Mesa, Carla DiCaudo, Jose Heredia-Jimenez

“…While spatio-temporal parameters often remain within normal ranges, subtle but clinically significant kinematic deviations may underlie compensatory mechanisms that sustain gait functionality. This study aims to evaluate spatio-temporal and sagittal plane kinematic differences between children with ITW and typically developing peers using Statistical Parametric Mapping (SPM). …”
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Towards an optimization of catheter guidance in vascular surgery: A comparative analysis of the contribution of reinforcement learning by Cheima Bouden

“…We compare different RL approaches within simulated vascular environments, focusing on their success rates, operational efficiency, and adaptability to varied clinical scenarios. …”
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A novel ensemble model for multi-temporal forest vegetation classification: integrating spectral-temporal features and topographic constraints by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang

“…Outputting and integrating the results of multiple classifiers provides insights into the model’s classification mechanism, results proved the effectiveness of the feature extraction module and the differences among the integration strategies. The Simpson index was employed for visual evaluation, overcoming sample labelling limitations, and the influence of elevation and slope on vegetation was analysed, highlighting the necessity for topographic features in mountainous areas.…”
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Mapping the landscape of Artificial intelligence for serious games in Health: An enhanced meta review by Xiya Tao, Nicolás Sáenz-Lechón, Martina Eckert

“…Game control algorithms adapt the game environment and difficulty, while user assessment algorithms gather information about the player's state, such as performance, mood, or physiological data, to evaluate the treatment progress. …”
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Structural-methodical model of computer program for control of theoretical knowledge of cadets by V. V. Bulgakov

“…Basically, readymade computer programs are used, which are universal and are intended for wide application, without taking into account the specifics of Universities.Research and development of structural and methodological model was carried out with the use of theoretical analysis of the provisions of pedagogy on the problems of control, evaluation and analysis of the level of theoretical knowledge, methods of theory of algorithms and decision-making, methods of synthesis and analysis of information processes. …”
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Simulation-Based E-Learning Framework for Entrepreneurship Education and Training by Constanţa-Nicoleta Bodea, Radu Ioan Mogoş, Maria-Iuliana Dascălu, Augustin Purnuş, Narcisa Georgeta Ciobotar

“…Using this e-learning framework, the students can learn how to choose relevant characteristics/aspects for a type of business and how important is each of them according specific criteria; how to set realistic values for different characteristics/aspects of the business, how a business scenario can be changed in order to fit better to the business context and how to assess/evaluate business scenarios.…”
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Cladistics with geometric morphometric data: The variability of the calvarium in the genus Homo by Margaux Simon-Maciejewski, Giorgio Manzi, Valéry Zeitoun, Aurélien Mounier

“…This study tests two different protocols to analyse 23 operational taxonomic units (OTUs) representing the genera Pongo, Gorilla, Pan, Australopithecus and Homo, in order to evaluate the phylogenetic information derived from geometric morphometric data. …”
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Ecological niche models as a tool for estimating the distribution of plant communities by Mayra Flores-Tolentino, Enrique Ortiz, José Luis Villaseñor

“…The use of widely distributed species in the definition of communities results in models with greater overestimation. It is important to adapt the available information and knowledge about the object of study, to properly integrate them into the different algorithms that allow us to obtain an approximation of what happens with the species or communities. …”
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In-Process Monitoring of Inhomogeneous Material Characteristics Based on Machine Learning for Future Application in Additive Manufacturing by André Jaquemod, Marijana Palalić, Kamil Güzel, Hans-Christian Möhring

“…The algorithms are trained to recognize patterns, anomalies, or deviations from expected behavior, which can aid in evaluating the effect of detected defects on the machining process and the resultant component quality. …”
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Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…This work aims to fill this gap by systematically evaluating the performance of metaheuristic algorithms in optimizing hyperparameters and discussing advanced techniques such as parallel computing to adapt metaheuristic algorithms for use in hyperparameter optimization with high-dimensional hyperparameter search space.…”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Results We introduce novel acquisition functions for experiment design in gene expression data, leveraging active learning in both Essential Graph and Graphical Model spaces. We evaluate scalable structure learning algorithms within an active learning framework to optimize intervention selection. …”
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Lateral shear interferometry for shape accuracy measurements of 3D-printed micro-optics by Zhao Yanqiu, Wang Lunwei, Siegle Leander, Giessen Harald

“…This unprecedented level of accessibility and adaptability holds immense promise for diagnostic and therapeutic interventions in the realm of cardiovascular medicine and beyond. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah, Seifeddine Bouallegue, Ridha Bouallegue

“…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …”
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A Data-Driven Model for the Energy and Economic Assessment of Building Renovations by Giuseppe Piras, Francesco Muzi, Zahra Ziran

“…The proposed methodology aims to provide a digital approach that is replicable and adaptable to different territorial realities and useful for strategic planning of energy transformation in the building sector.…”
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An Autonomic Nervous System Model Applied to the Analysis of Orthostatic Tests by Virginie Le Rolle, Alfredo I. Hernández, Pierre-Yves Richard, Guy Carrault

“…One of the clinical examinations performed to evaluate the autonomic nervous system (ANS) activity is the tilt test, which consists in studying the cardiovascular response to the change of a patient's position from a supine to a head-up position. …”
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A deep multiple self-supervised clustering model based on autoencoder networks by Ling Zhu, Zijin Liu, Guangyu Liu

“…The experimental results show that the model performs significantly better than various common clustering algorithms on datasets of different types in multiple fields. …”
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A Hybrid Proactive Caching System in Vehicular Networks Based on Contextual Multi-Armed Bandit Learning by Qiao Wang, David Grace

“…Specifically, the paper proposes a distributed Hybrid cMAB Proactive Caching System where RSUs act as independent learners that implement two parallel online reinforcement learning-based mobility prediction algorithms between which they can adaptively finalize their predictions for the next RSU. …”
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Identification of reference genes for RT-qPCR in the Antarctic moss Sanionia uncinata under abiotic stress conditions. by Mira Park, Soon Gyu Hong, Hyun Park, Byeong-Ha Lee, Hyoungseok Lee

“…In this report, 11 traditionally used and 6 novel candidate reference genes were selected from transcriptome data of S. uncinata and the expression stability of these genes was evaluated under various abiotic stress conditions using three statistical algorithms; geNorm, NormFinder, and BestKeeper. …”
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