ID3RSNet: cross-subject driver drowsiness detection from raw single-channel EEG with an interpretable residual shrinkage network by Xiao Feng, Xiao Feng, Zhongyuan Guo, Zhongyuan Guo, Sam Kwong

“…First, a base feature extractor is employed to extract the essential features of EEG frequencies; to enhance the discriminative feature learning ability, the residual shrinkage building unit with attention mechanism is adopted to perform adaptive feature recalibration and soft threshold denoising inside the residual network is further applied to achieve automatic feature extraction. …”
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Instance Assignment Coverage Feature for Operation Control of SAT Solver by Zhihui Li, Shuwei Chen, Guanfeng Wu, Yang Xu

“…The CoverT metric provided unique insight into the characteristics of the instance structure, allowing dynamic adaptation of branching heuristics in our proposed Deep Restart-Enhanced Conflict-Driven Clause Learning algorithm framework (DR-CDCL). Experimental validation in 2021–2023 SAT Competition benchmarks demonstrated statistically significant improvements: 14 additional solved instances for satisfiable cases (352 $$\rightarrow $$ → 366, $$p<0.05$$ p < 0.05 via McNemar’s test). 7.3% reduction in average runtime for SAT instances under the 5000 s timeout threshold. …”
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Application of IRSA-BP neural network in diagnosing diabetes. by Wan-Hua Zhang, Zi-Xun Zhang

“…Within the healthcare sector, the application of machine learning is gaining prominence, notably enhancing the efficiency and precision of diagnostic procedures. …”
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Research on Seismic Signal Denoising Model Based on DnCNN Network by Li Duan, Jianxian Cai, Li Wang, Yan Shi

“…The DnCNN framework, which integrates batch normalization with residual learning, is adept at swiftly identifying and eliminating noise from seismic signals through its residual learning capabilities. …”
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Associative experiment as a means of tracking dynamics of secondary language personality development as exemplified by the stimulus word “nation” by Vera V. Koroleva, Ekaterina T. Polyanskaya

“…Furthermore, the prospects of associative experiment application for methodological purposes are noted, particularly for tracking the level of secondary language personality formation in learning groups and adjusting the language learning trajectory.…”
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Automated image transcription for perinatal blood pressure monitoring using mobile health technology. by Nasim Katebi, Whitney Bremer, Tony Nguyen, Daniel Phan, Jamila Jeff, Kirkland Armstrong, Paula Phabian-Millbrook, Marissa Platner, Kimberly Carroll, Banafsheh Shoai, Peter Rohloff, Sheree L Boulet, Cheryl G Franklin, Gari D Clifford

“…Overall, our results demonstrate that the device-specific model with transfer learning and the device independent model outperformed the device-specific model without transfer learning. …”
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Explainable handcrafted features for mitotic event detection and classification by Panason Manorost, Thomas Deckers, Veerle Bloemen, Jean Marie Aerts

“…In the new method, traditional image processing, such as thresholding and cell tracking, is employed to select the candidate events. …”
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Effects of a long term faculty development program on improvement in quality of MCQs: an impact evaluation study by Rukhsana Ayub, Faiza Kiran, Nadia Shabnam, Ayesha Rauf, Fozia Fatima

“…The objective of this study was to evaluate the impact of this focused training, at Kirkpatrick level II, on learning of item writing skills by the participants. …”
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TableStructureFormer: an improved masked-attention mask transformer model with long-distance feature aggregation and deep detail supervision for table structure recognition by Chenglong Yu, Weibin Li, Zixuan Zhu, Wei Li, Jianchao Du, Shiwei Zhang

“…When the position matching thresholds are 0.50 and 0.75, the average accuracy (AP) is 91.50% and 86.32%, respectively, indicating excellent spatial perception ability. …”
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An algorithm to Detect Overlapping Red Blood Cells for Sickle Cell Disease Diagnosis. by Mabirizi, Vicent, Kawuma, Simon, Safari, Yonasi

“…The algorithm uses canny edge and double threshold machine learning techniques and takes overlapping red blood cell images as inputs to detect if these cells are sickle cell anemic. …”
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Optimizing Satellite Imagery Datasets for Enhanced Land/Water Segmentation by Marco Scarpetta, Luisa De Palma, Attilio Di Nisio, Maurizio Spadavecchia, Paolo Affuso, Nicola Giaquinto

“…This paper presents an automated procedure for optimizing datasets used in land/water segmentation tasks with deep learning models. The proposed method employs the Normalized Difference Water Index (NDWI) with a variable threshold to automatically assess the quality of annotations associated with multispectral satellite images. …”
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Swi4-dependent SWI4 transcription couples cell size to cell cycle commitment by Pooja Goswami, Abhishek Ghimire, Carleton Coffin, Jing Cheng, Jasmin Coulombe-Huntington, Ghada Ghazal, Yogitha Thattikota, María Florencia Guerra, Mike Tyers, Sylvain Tollis, Catherine A. Royer

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Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol by Bruno Bonnechère, Dominique Hansen, Kim Daniels, Sharona Vonck, Jolien Robijns, Annemie Spooren

“…All measurements align with the Behaviour Change Wheel framework, assessing capability, opportunity and motivation. Machine learning will analyse data, employing unsupervised learning (eg, hierarchical clustering) to identify PA behaviour patterns and supervised learning (eg, recurrent neural networks) to predict behavioural influences. …”
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Variational Autoencoder Based Anomaly Detection in Large-Scale Energy Storage Power Stations by Tuo Ji, Pinghu Xu, Dongliang Guo, Lei Sun, Kangji Ma, Yanan Wang, Xuebing Han

“…Currently, station monitoring primarily relies on preset fixed threshold-based alerts combined with manual supervision. …”
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The influence of particular entrance exam score on enrolment and graduation at the University of Criminal Investigation and Police Studies by Janković Radivoje, Kukić Filip, Koropanovski Nenad

“…The research suggests that implementing a minimum score threshold for various exam components could potentially enhance learning efficiency and graduation rates at the UCIPS.…”
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A Comparative Study of Customized Algorithms for Anomaly Detection in Industry-Specific Power Data by Minsung Jung, Hyeonseok Jang, Woohyeon Kwon, Jiyun Seo, Suna Park, Beomdo Park, Junseong Park, Donggeon Yu, Sangkeum Lee

“…This study compares and analyzes statistical, machine learning, and deep learning outlier-detection methods on real power-usage data from the metal, food, and chemical industries to propose the optimal model for improving energy-consumption efficiency. …”
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Bridging the digital divide: mapping Internet connectivity evolution, inequalities, and resilience in six Brazilian cities by Nicolò Gozzi, Niccolò Comini, Nicola Perra

“…Additionally, we investigate the impact of Internet quality on access to critical online services, focusing on e-learning. Our analysis shows that nearly 13% of catchment areas around educational facilities have Internet speeds below the threshold required for e-learning, with disadvantaged areas experiencing more significant challenges. …”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…Convolutional Neural Networks (CNNs) are a class of deep learning algorithms most commonly applied. They are particularly powerful for tasks involving data recognition, classification, and analysis due to their ability to automatically and adaptively learn spatial hierarchies of features. …”
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Encouraging arm use in stroke survivors: the impact of smart reminders during a home-based intervention by Laura Mayrhuber, Sebastian D. Andres, Mathilde L. Legrand, Andreas R. Luft, Franziska Ryser, Roger Gassert, Janne M. Veerbeek, Jannie van Duinen, Anne Schwarz, Karmen Franinovic, Christoph Rickert, Erik Schkommodau, Jeremia P. O. Held, Chris Awai Easthope, Olivier Lambercy

“…Abstract Background Upper limb impairment post-stroke often leads to a predominant use of the less affected arm and consequent learned disuse of the affected side, hindering upper limb outcome. …”
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Defective Intracortical Inhibition as a Marker of Impaired Neural Compensation in Amputees Undergoing Rehabilitation by Guilherme J. M. Lacerda, Lucas Camargo, Fernanda M. Q. Silva, Marta Imamura, Linamara R. Battistella, Felipe Fregni

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