Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review by Dhekre Saber Saleh, Mohd Shahizan Othman

“…By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. …”
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Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…Recent research has explored machine learning-based approaches using smartphone accelerometers to classify intoxicated gait patterns. While neural network approaches have emerged, due to the significant challenges with collecting intoxicated gait data, gait datasets are often too small to utilize such approaches. …”
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Movement Disorders and Smart Wrist Devices: A Comprehensive Study by Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

“…Epilepsy and seizure detection are also research topics of interest, while there are few papers analyzing gait disorders, Huntington’s Disease, ataxia, or Tourette Syndrome. …”
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Ensemble stacked model for enhanced identification of sentiments from IMDB reviews by Komal Azim, Alishba Tahir, Mobeen Shahroz, Hanen Karamti, Annia Almeyda Vazquez, Angel Rojas Vistorte, Imran Ashraf

“…The suggested ensemble RRLS model performs better than other learning algorithms and achieves a 90% accuracy rate, outperforming current methods. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…This success has led to the development of several advanced sharpness-based algorithms aimed at addressing the limitations of SAM, such as Adaptive SAM, Surrogate-Gap SAM, Weighted SAM, and Curvature Regularized SAM. …”
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A Novel Hybrid Analysis Method of LLC Resonant Converter for High Accuracy and Low Computational Burden by Su-Seong Park, Rae-Young Kim

“…This paper proposes an analysis model that can estimate the efficiency of the converter and the temperature of component parts with high accuracy while requiring a relatively low computational burden when analyzing LLC resonant converters. …”
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Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation by K. Radha, Yepuganti Karuna

“…Our goal is to generate multiple realistic retinal fundus images based on tubular structured annotations while simultaneously creating binary masks from the retinal fundus images. …”
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An analytic research and review of the literature on practice of artificial intelligence in healthcare by Salma Mizna, Suraj Arora, Priyanka Saluja, Gotam Das, Waled Abdulmalek Alanesi

“…Addressing ethical and security considerations is crucial for the successful integration of AI in healthcare while upholding patient safety and legal standards. …”
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Factors influencing the spatial distribution of police stops and their efficacy in crime prevention and control by Zhuoying Fan, Xuewei Zhang, Guangwen Song, Chunxia Zhang

“…The space is partitioned using hierarchical clustering after applying the XGBoost and SHAP algorithms to determine the factors related to police stops. …”
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AI Act as EU Legislator’s Response to Challenges of Artificial Intelligence Development by Monika Wyszomirska

“…In this article, the author analyses the main challenges of AI regulation, highlighting the difficulties of defining AI, protecting human rights, ensuring algorithmic transparency, and balancing the innovation of this technology with human and environmental safety. …”
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Fostering non-intrusive load monitoring for smart energy management in industrial applications: an active machine learning approach by Lukas Fabri, Daniel Leuthe, Lars-Manuel Schneider, Simon Wenninger

“…We compare three disaggregation algorithms with a benchmark model by efficiently selecting a subset of training data through three query strategies that identify the data requiring labeling. …”
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Enhanced gap-filling for satellite-derived crop monitoring using temperature-driven reconstruction techniques by Flavian Tschurr, Lukas Valentin Graf, Achim Walter, Helge Aasen

“…Our approach requires fewer satellite observations compared to traditional remote sensing time series algorithms, making it suitable for agricultural areas with high cloud cover. …”
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High-Level Implicit Enumerations for Quadratic Periodic Train Timetabling with Prioritized Cross-Line Operations by Congcong Zou, Hongxia Lv, Miaomiao Lv, Shaoquan Ni, Qinglun Zhong

“…The results demonstrate that our proposed method can efficiently achieve flexible while recoverable operational times for the cross-line services and the proposed implicit enumeration algorithms significantly outperform the direct linearization, which increases the search space significantly due to the considerable dimensionality of the periodic decision variables involved. …”
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Hankel Tensor Subspace Representation for Remotely Sensed Image Fusion by Fei Ma, Qiang Qu, Feixia Yang, Guangxian Xu

“…Exactly, traditional matrix-factorization-based algorithms often result in the loss of cubic structure knowledge in hyperspectral data, while deep neural networks are susceptible to noise accumulation and lack of large-scale labeled data. …”
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Empirical Evaluation and Analysis of YOLO Models in Smart Transportation by Lan Anh Nguyen, Manh Dat Tran, Yongseok Son

“…You Only Look Once (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. …”
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Automated attendance management with RFID and geospatial visualization by Jilbert C. Bati-On, Kyle P. Kuizon, Krischel Ann Y. Catulpos, Johnloyd B. Bonghanoy, Jose Jr. Costillas Agoylo

“…Conclusion: The integration of genetic algorithms and facial recognition in a web-based scheduling system demonstrated improvements in efficiency, accuracy, and data security. …”
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Conic curve encryption and digital signature based on complex number theory for cybersecurity applications by Ahmed Kamal, H. A. El-Kamchochi, Adel El-Fahar, Esam A. A. Hagras

“…Abstract Secure image transmission requires robust algorithms to ensure authentication, integrity, non-repudiation, and confidentiality. …”
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A mechanism for the emergence of low-dimensional structures in brain dynamics by Claudio Runfola, Spase Petkoski, Hiba Sheheitli, Christophe Bernard, Anthony R. McIntosh, Viktor Jirsa

“…These range from linear algorithms to more intricate non-linear methods for manifold extraction. …”
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Time-of-Flight Camera Intensity Image Reconstruction Based on an Untrained Convolutional Neural Network by Tian-Long Wang, Lin Ao, Na Han, Fu Zheng, Yan-Qiu Wang, Zhi-Bin Sun

“…This experimental demonstration effectively reduces the noise and direct ambient light generated by the ToF camera itself, while opening up the potential application of ToF cameras in challenging environments, such as scattering media or underwater.…”
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Understanding acceptance and resistance toward generative AI technologies: a multi-theoretical framework integrating functional, risk, and sociolegal factors by Priyanka Shrivastava

“…Results revealed that functional factors significantly enhanced acceptance while reducing resistance, whereas risk factors amplified resistance and negatively influenced acceptance. …”
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