Wireless body area network: Architecture and security mechanism for healthcare using internet of things by Arun Kumar, Ritu Dewan, Wisam Subhi Al-Dayyeni, Bharat Bhushan, Jayant Giri, Sardar MN Islam, Ahmed Elaraby

“…Internet of Things (IoT) enabled wireless body area network (WBAN) is a novel technology that combines medical, wireless, and non-medical devices for healthcare management applications. Indoor healthcare institutions, such as hospitals, may employ IoT devices to manage medical equipment, maintain inventory, and monitor patients. …”
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A Data-Driven Approach for Predicting Remaining Useful Life of Semiconductor Devices Based on Machine Learning and Synthetic Data Generation: A Review and Case Study on SiC MOSFETs by Yarens J. Yarenscruz, Fernando Castano, Alberto Villalonga, Madhav Mishra, Rodolfo E. Haber

“…Predicting the remaining useful life of electronic components is a crucial aspect for predictive maintenance and system reliability across multiple fields and applications. Data-driven approaches, particularly those methods based on machine learning, are currently being used due to their ability to model complex degradation patterns without the need for explicit physical modeling. …”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…Permanent Magnet Synchronous Machines (PMSMs) are extensively utilized for their ability to deliver accurate position control, and the equivalent circuit characteristics of these machines are essential in several applications, particularly in formulating the control strategy. …”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…The qualitative and quantitative evaluation results show that MCSP is superior to two classical cost calculation methods and shows good transferability and applicability in the popular disparity estimation algorithms, which can significantly enhance the definition of the edges of the ground objects and improve the quality of the disparity estimation in the shadow occlusion areas.…”
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HI4HC and AAAAD: Exploring a hierarchical method and dataset using hybrid intelligence for remote sensing scene captioning by Jiaxin Ren, Wanzeng Liu, Jun Chen, Shunxi Yin

“…Many existing methods and datasets lack a fine-grained description of key geographical elements, fail to capture the full diversity of spatial relations, and are limited in their applicability to real-world geospatial scenarios. To address these shortcomings, we propose HI4HC (hybrid intelligence for remote sensing scene hierarchical captioning), a novel method that combines deep learning algorithms with expert knowledge to generate hierarchical captions for remote sensing scenes. …”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). …”
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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…Through systematic analysis of 11 key studies across multiple international databases, we evaluated various AI architectures, including machine learning algorithms and deep learning networks, applied to qEEG data for AD detection. …”
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SYSTEM FOR CONTROLLING ELECTRIC DRIVE OF ASPHALT CONCRETE MIXING PLANT by A. S. Surmak, I. F. Kuzmitsky, I. O. Orobey

“…Block diagram of the system is presented and algorithm of its operation is given in the paper. In addition to improvement of the finished product quality the application of the system makes it possible to reduce bitumen consumption used for production of asphalt concrete.…”
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River total dissolved gas prediction using a hybrid greedy-stepwise feature selection and bidirectional long short-term memory model by Khabat Khosravi, Salim Heddam, Changhyun Jun, Sayed M. Bateni, Dongkyun Kim, Essam Heggy

“…These findings demonstrate that GSFST-BiLSTM provides a robust and transferable framework for TDG prediction, with the potential for broader application pending further validation.…”
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Machine learning for predicting all-cause mortality of metabolic dysfunction-associated fatty liver disease: a longitudinal study based on NHANES by Xueni Wang, Huihui Chen, Luqiao Wang, Wenguang Sun

“…Conclusions Machine learning has a promising application in predicting all-cause mortality in MAFLD individuals. …”
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Analysis of the Current State of Digitalization İmplementation in the Banking System of Azerbaijan by K. N. Atayev

“…Furthermore, the article thoroughly explores existing cybersecurity strategies, types of threats, and their potential impact on the financial system, serving as a significant indicator of the application of a risk-based approach.Results. The process of digitalization in the banking sector of the Republic of Azerbaijan has evolved progressively since the 1990s and has ultimately led to the establishment of high-level digital banking services. …”
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Optimizing Superior Seed Bunches: A New Approach to Artificial Pollination with Machine Learning Models by Yabani Yabani, Retna Astuti Kuswardani

“…Overall, the model evaluation showed an increase in quantitative output while strengthening production quality and efficiency. …”
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Tomografía geoeléctrica: dos ejemplos en la Sabana de Bogotá by Briceno Guarupe Luis Alberto, Sanín Camilo Ernesto

“…This geophysic tool is very useful in shallow applications (100 m depth), and where high resolution and quality are needed.…”
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Investigation of deep learning image fusion techniques for medical imaging by Angayarkanni Veeraputhiran, Muthukumar Balamurugan, Varun P. Gopi

“…Experiments on the fusion of MRI and PET medical images are being conducted to evaluate performance, algorithm stability, and other parameters. …”
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Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…Conventional CT scans, such as those of the cervical spine, have so far lacked the resolution to reliably evaluate dental structures or implants. This study evaluates the diagnostic utility of PCCT for visualizing peri-implant structures in routine clinical photon-counting CT acquisitions and assesses the influence of metal artifact reduction (MAR) algorithms on image quality. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…Secondly, the scarcity of high quality datasets and the unnaturalness of recommendation systems pose pressing issues. …”
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A Complementary Approach for Securing and Anti-Counterfeiting of Valuable Documents Based on Encryption of Computer-Generated Hologram by Zakaria E. Ahmed, Rania M. Abdelazeem, Yasser A. Attia, Tawfik A. Khattab, Claas Falldorf, Ralf B. Bergmann, Mostafa Agour

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Transfer learning based feature selection for feedforward neural network for speech emotion classifier by D. V. Krasnoproshin, M. I. Vashkevich

“…To evaluate the quality of the model, unweighted average recall (UAR) was used. …”
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Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment by Xiaohui Gong

“…Based on this, this study studies the innovation of the teaching model of national vocal music in colleges and universities based on the deep recurrent neural network algorithm and designs the teaching quality evaluation model based on the deep recurrent neural network algorithm. …”
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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…Wet lab experiments validated the role of KRT6B in NSCLC, demonstrating that KRT6B expression is elevated and it stimulates the proliferation of cancer cells.DiscussionThese observations not only enhance our understanding of metabolic reprogramming and its biological functions in NSCLC but also provide new perspectives for early detection, prognostic evaluation, and targeted therapy. However, future research should further explore the specific mechanisms of these metabolic pathways and their application potentials in clinical practice.…”
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