Artificial Intelligence (AI) in Neurofeedback Therapy Using Electroencephalography (EEG), Heart Rate Variability (HRV), and Galvanic Skin Response (GSR): A Review by Teddy Marcus Zakaria, Armein Zainal R. Langi, Muhamad Sophian Nazaruddin, Isa Anshori

“…These directions include the development of robust AI algorithms, the integration of NFT with emerging technologies such as virtual reality, ethical and societal implications, and AI-powered NFT applications. …”
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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

“…In addition to monitoring temperature, humidity, and air quality, IoT sensors may help prevent the spread of sickness. …”
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A New Efficient Approach to Model Stiff Biogeochemical Reactive Transport Scenarios Across Groundwater Systems by Xiaochuang Bu, Heng Dai, Songhu Yuan, Ming Ye, Zhenxue Dai, Mohamad Reza Soltanian, Zhang Wen, Alberto Guadagnini

“…Overall, our approach offers a robust and efficient solution for modeling stiff biogeochemical processes in groundwater systems. Its successful application to diverse reaction networks highlights its potential for broad implementation in environmental and engineering contexts, paving the way for accurate and computationally feasible groundwater quality assessments.…”
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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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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

“…Each model is trained and evaluated at one station and validated at the second station to assess transferability and generalization capability. …”
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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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Outliers and anomalies in training and testing datasets for AI-powered morphometry—evidence from CT scans of the spleen by Yuriy Vasilev, Yuriy Vasilev, Anastasia Pamova, Tatiana Bobrovskaya, Anton Vladzimirskyy, Anton Vladzimirskyy, Olga Omelyanskaya, Elena Astapenko, Artem Kruchinkin, Novik Vladimir, Kirill Arzamasov, Kirill Arzamasov

“…There are no universally accepted methods for evaluating outliers or anomalies in such datasets. This can cause errors in machine learning and compromise the quality of end products. …”
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Transformed L1 Regularization for Sparse Photoacoustic Tomography by Xueyan Liu, Lu Wang, Xin Wang, Ziqi Hao, Xiaolong Hu

“…In this study, a transform L1 (TL1) regularization model was proposed to improve the quality of PAT images, which was evaluated by numerical simulation and tissue phantom experiments. …”
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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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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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Advanced control parameter optimization in DC motors and liquid level systems by Serdar Ekinci, Davut Izci, Mohammad H. Almomani, Kashif Saleem, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu, Laith Abualigah

“…Furthermore, a new performance indicator, ZLG, is introduced to comprehensively evaluate control quality. The MGO-based approach consistently achieves lower ZLG values, showcasing its adaptability and robustness in dynamic system control and parameter optimization. …”
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Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
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Building Consumption Data Systems Driven by AI Plus Expert for Scientific and Technical Literature Information Resources by Guanghui YE, Kai TU, Lina HU, Li HAN, Zhiming FENG

“…Furthermore, the paper deconstructs and analyzes the risks associated with the involvement of AI in the construction of consumer-end data systems, including four types of risks: machine algorithm risks, annotation content risks, annotation data risks and application risks. …”
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Before hands disappear: Effect of early warning visual feedback method for hand tracking failures in virtual reality. by Mucahit Gemici, Vrushank Phadnis, Anil Ufuk Batmaz

“…However, current hand tracking algorithms are prone to errors, which can disrupt the user experience and hinder task performance. …”
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Three-dimensional linkage analysis with digital PCR for genome integrity and identity of recombinant adeno-associated virus by Tam Duong, Michele Firmo, Chien-Ting Li, Bingnan Gu, Peng Wang

“…In this study, we focus on evaluating our 3D linkage mathematical model by performing DNA mixing experiments and a case study using multiple rAAV samples. …”
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A 3D reconstruction platform for complex plants using OB-NeRF by Sixiao Wu, Changhao Hu, Boyuan Tian, Yuan Huang, Shuo Yang, Shanjun Li, Shengyong Xu

“…Finally, Object-Based NeRF we proposed is utilized for the fine-scale reconstruction of plants. The OB-NeRF algorithm introduced a new ray sampling strategy that improved the efficiency and quality of target plant reconstruction without segmenting the background of images. …”
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Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization by Amandeep Kaur, Shalli Rani, Mohammad Shabaz

“…This study presents exceptional quantitative performance across various evaluation metrics: a UIQM score of 3.71 (indicating image quality), a PSNR of 28.4 dB (reflecting signal fidelity), an SSIM of 0.88 (representing structural similarity), and a perceptual LPIPS score of 0.082. …”
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Learning new surgical techniques in low and middle income countries, approval processes, and the impact of artificial intelligence by Long Cong Duy Tran, Long Cong Duy Tran, Helal Metwalli, Helal Metwalli, Dat Tien Le, Dat Tien Le, Samuel Amo-Afful, Samuel Amo-Afful, Mario Salib Todry Gerges, Mario Salib Todry Gerges, Hajer Hatim Hassan Ahmed, Hajer Hatim Hassan Ahmed, Dinh Thi Kim Quyen, Dinh Thi Kim Quyen, Abdelrahman Gamil Gad, Abdelrahman Gamil Gad, Phillip Tran, Nguyen Tien Huy, Nguyen Tien Huy, Nguyen Tien Huy

“…Recently, artificial intelligence (AI) has emerged as a reliable solution, providing applicable, Quantitative methods for skill development, competency evaluation and regulatory supervision. …”
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AN INTELLIGENT POSTOPERATIVE CHRONIC PAIN PREDICTION SYSTEM (I-POCPP) by Elif Kartal, Fatma Önay Koçoğlu, Zeki Özen, İlkim Ecem Emre, Gürcan Güngör, Pervin Sutaş Bozkurt

“…Objective: Postoperative Chronic Pain (POCP) affects the quality of patients’ lives. Machine learning and its applications provide significant contributions to pain research. …”
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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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