Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment by Aleš Procházka, Daniel Martynek, Marie Vitujová, Daniela Janáková, Hana Charvátová, Oldřich Vyšata

“…Individual physiotherapy is crucial in treating patients with various pain and health issues, and significantly impacts abdominal surgical outcomes and further medical problems. …”
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A double-layer ensemble framework for rubber plantation mapping using multi-source data in the google earth engine: a case study of the southwestern border region of China by Hui Wang, Jie Li, Jinliang Wang, Yuncheng Deng, Shupeng Gao, Jing Zou, An Chen, Haichao Xu

“…To address these issues, we propose a double-layer ensemble framework for rubber plantation extraction using multi-source data in the Google Earth Engine. …”
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Scalable Semantic Adaptive Communication for Task Requirements in WSNs by Hong Yang, Xiaoqing Zhu, Jia Yang, Ji Li, Linbo Qing, Xiaohai He, Pingyu Wang

“…The experimental results show that the proposed SSAC is more robust than traditional and other semantic communication algorithms in image classification tasks, and achieves scalable compression rates without sacrificing classification performance, while improving the bandwidth utilization of the communication system.…”
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Performance Evaluation of Micro and Small Industries in East Java Province, Indonesia Using SMA and DEA: A Case Study by Erni Puspanantasari Putri, Erwin Widodo, Jaka Purnama, Bonifacius Raditya Sri Pramana Putra, Agatha Hannabel Avnanta Puteri

“…Micro- and small-scale industries (MSIs) are the pillars of Indonesia’s national economy. MSIs face several issues as their businesses grow. Performance evaluation is one way to identify MSI’s effectiveness. …”
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Generalized cross-entropy for learning from crowds based on correlated chained Gaussian processes by J. Gil-González, G. Daza-Santacoloma, D. Cárdenas-Peña, A. Orozco-Gutiérrez, A. Álvarez-Meza

“…Through extensive simulated and real-world experiments, CCGP-GCE demonstrated superior classification performance, outperforming state-of-the-art multilabeler models in terms of both accuracy and expert reliability estimation. …”
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An interpretable dynamic ensemble selection multiclass imbalance approach with ensemble imbalance learning for predicting road crash injury severity by Kamran Aziz, Feng Chen, Mahmood Ahmad, Muhammad Salman Khan, Mohanad Muayad Sabri Sabri, Hamad Almujibah

“…Abstract Accurate prediction of crash injury severity and understanding the seriousness of multi-classification injuries is vital for informing authorities and the public. …”
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Nuclear Accidents: Consequences for Human, Society and Energy Sector by L. A. Bolshov, R. V. Arutyunyan, I. I. Linge, I. L. Abalkina

“…The development of regulations on criteria for the classification of radioactive waste and the issues of remediation of radioactively contaminated areas are discussed as the examples.…”
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A.R. Luria's contribution to studies of the brain organization of language by A. Ardila, T. V. Akhutina, Yu. V. Mikadze

“…The paper discusses differences between these two books and also linguistic issues, which received much attention in his later publication. …”
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Land surface temperature assessment in relation to land-use/land-cover (A case study: Isfahan City, Central Iran) by Sayyad Asghari Saraskanrood, Bahareh Asadi, Ehsan Ghale

“…Most of critical issues such as increase in pollution levels, sudden climatic changes and the rise of temperature in the urban area, leading to the formation of Urban Heat Islands (UHI), have been resulted from urbanization. …”
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Uncertainty Quantification and Monte Carlo Simulations to Enhance SDG 11.3.1 Monitoring by J. R. Santillan, J. R. Santillan, M. Dorozynski, C. Heipke

“…While this metric is valuable for guiding urban planning, it could be affected by variability in Earth Observation (EO) data products, especially differences in built-up area definitions and classification errors that lead to data quality issues. …”
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Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…It demonstrates how addressing these issues enhances the reliability and applicability of predictive models. …”
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Heterogeneous appetite patterns in depression: computational modeling of nutritional interoception, reward processing, and decision-making by Yuuki Uchida, Yuuki Uchida, Takatoshi Hikida, Manabu Honda, Yuichi Yamashita

“…Overall, this study findings emphasize the importance of integrating interoception and homeostasis into decision-making frameworks to enhance subtype classification and facilitate the development of effective therapeutic strategies.…”
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Research on Indoor Object Detection and Scene Recognition Algorithm Based on Apriori Algorithm and Mobile-EFSSD Model by Wenda Zheng, Yibo Ai, Weidong Zhang

“…Experiments show that the method achieves stable performance, effectively detects occluded objects, and accurately extracts category and location information. (2) To improve classification stability in indoor scene recognition, this paper proposes a naive Bayes-based method. …”
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STA-AgriNet: A Spatio-Temporal Attention Framework for Crop Type Mapping from Fused Multi-Sensor Multi-Temporal SITS by Jayakrishnan Anandakrishnan, Venkatesan Meenkaski Sundaram, Prabhavathy Paneer

“…The high-resolution multispectral optical data can deliver essential spatial-spectral characteristics; however, these are typically impeded by unfavorable weather and obstructions, resulting in poor classification. Recent advancements in multisensor data fusion techniques have focused on integrating optical data with auxiliary synthetic aperture radar (SAR) data to mitigate misclassification issues. …”
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Transformative bioprinting: 4D printing and its role in the evolution of engineering and personalized medicine by Vidhi Mathur, Prachi Agarwal, Meghana Kasturi, S. Varadharajan, Elsa Sanatombi Devi, Kirthanashri S. Vasanthan

“…Section 4 shifts focus to commercial advancements, presenting a classification of 4D bioprinters available in the market. …”
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Physiological signal-based mental stress detection using hybrid deep learning models by Nandini Modi, Yogesh Kumar, Kapil Mehta, Neelam Chaplot

“…These spectrograms are then processed by CNN layers to extract spatial patterns, followed by MLP layers for mental stress state classification. Experimental results demonstrates that the hybrid CNN-MLP model achieves superior classification accuracy of 99.45% for training and 99.99% for validation outperforming other conventional models such as Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN) and Transformers. …”
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Minimizing Model Size of CNN-Based Vehicle Make Recognition for Frontal Vehicle Images by Wiput Puisamlee, Rathachai Chawuthai

“…Issues included larger models and longer processing times. …”
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Improved Intelligent Condition Monitoring with Diagnostic Indicator Selection by Urszula Jachymczyk, Paweł Knap, Krzysztof Lalik

“…In this study, a predictive maintenance (PdM) system focused on feature selection for the detection and classification of simulated defects in wind turbine blades has been developed. …”
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Enhanced detection of Mpox using federated learning with hybrid ResNet-ViT and adaptive attention mechanisms by V. Maheskumar, R. Vijayarajeswari

“…This system ensures decentralized training across healthcare facilities, preserving data privacy while improving classification performance. The Monkeypox Skin Lesion Dataset (MSLD), consisting of 3192 augmented images, is utilized for training and testing. …”
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Towards AI-Assisted Mapmaking: Assessing the Capabilities of GPT-4o in Cartographic Design by Abdulkadir Memduhoğlu

“…The model showed proficiency in classification and symbolization tasks but occasionally deviated from theoretical expectations. …”
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