Augmenting brain-computer interfaces with ART: An artifact removal transformer for reconstructing multichannel EEG signals by Chun-Hsiang Chuang, Kong-Yi Chang, Chih-Sheng Huang, Anne-Mei Bessas

“…We performed comprehensive validations using a wide range of open datasets from various BCI applications, employing metrics like mean squared error and signal-to-noise ratio, as well as sophisticated techniques such as source localization and EEG component classification. …”
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Developing a Model of Wisdom Based on Successful Intelligence and Psychological Well-Being in Students: The Mediating Role of Creativity by Rasool Kordnoghabi, Saeed Veisi

“…Finally, a root mean square error of approximation (RMSEA) of 0.058 was obtained, whereby RMSEA values ≤0.08 indicate an acceptable fit.  …”
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Untethered Autonomous Holonomic Mobile Micromanipulator for Operations in Isolated Confined Spaces by Ryosuke Kinoshita, Rintaro Minegishi, Chihiro Sekine, Yohei Tsukui, Yuta Sunohara, Yuko Nishimura, Shogen Sekiguchi, Ohmi Fuchiwaki

“…The micromanipulator can autonomously position a single object with a positioning error of 0.18 ± 0.51 mm and an angular deviation of −0.4° ± 1.2°, utilizing image recognition, machine learning, and visual feedback. …”
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LightSTATE: A Generalized Framework for Real-Time Human Activity Detection Using Edge-Based Video Processing and Vision Language Models by Anik Debnath, Yong-Woon Kim, Yung-Cheol Byun

“…Human activity detection plays a vital role in applications such as healthcare monitoring, smart environments, and security surveillance. …”
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Exploring Machine Learning's Potential for Estimating High Resolution Daily Snow Depth in Western Himalaya Using Passive Microwave Remote Sensing Data Sets by Srinivasarao Tanniru, Dhiraj Kumar Singh, Kamal Kant Singh, RAAJ Ramsankaran

“…(b) In general, with an increase in SD, the mean absolute error of SD retrievals has increased in all SD products/models. …”
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Scale-invariant total decay width Γ(H → b b ¯ $$ b\overline{b} $$ ) using the novel method of characteristic operator by Jiang Yan, Xing-Gang Wu, Jian-Ming Shen, Xu-Dong Huang, Zhi-Fei Wu

“…The PMC scale is fixed up to N3LL-accuracy, Q * = 55.2916 GeV and a scale-invariant total decay width is obtained, Γ H → b b ¯ = 2.3819 − 0.0231 + 0.0230 $$ \Gamma \left(H\to b\overline{b}\right)={2.3819}_{-0.0231}^{+0.0230} $$ MeV, whose errors are squared averages of the ones associated with ∆α s (M Z ) = ±0.0009, ∆M H = 0.11 GeV, Δ m ¯ b m ¯ b $$ \Delta {\overline{m}}_b\left({\overline{m}}_b\right) $$ = ±0.007 GeV, and the uncalculated N5LO contributions ∆Γ = ±0.0001 MeV predicted via Bayesian analysis with the degree-of-belief DoB = 95.5%.…”
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Decoding wisdom: Evaluating ChatGPT's accuracy and reproducibility in analyzing orthopantomographic images for third molar assessment by Ana Suárez, Stefania Arena, Alberto Herranz Calzada, Ana Isabel Castillo Varón, Victor Diaz-Flores García, Yolanda Freire

“…Professional oversight is essential to prevent diagnostic errors. Further refinement and specialized training of AI models are needed to enhance their performance and ensure safe integration into dental practice, especially in patient-facing applications.…”
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Transformer-based travel time estimation method for plateau and mountainous environments by Guangjun Qu, Kefa Zhou, Rui Wang, Dong Li, Yingpeng Lu, Zhihong Lv, Dequan Zhao, Aijun Zhang, Qing Zhang

“…Current research and applications related to TTE primarily focus on urban environments. …”
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Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…This study not only evaluates the CVA6 architecture but also introduces a novel, scalable methodology for design space exploration, applicable to a wide range of SoC designs. A high-accuracy CVA6 model was developed using the gem5 simulator, achieving less than 5% error in the RISC-V microbenchmark suite and MiBench suite in both the system simulation (bare metal mode) and the full system (FS) modes. …”
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Predicting the Evolution of Extreme Water Levels With Long Short‐Term Memory Station‐Based Approximated Models and Transfer Learning Techniques by Samuel Daramola, David F. Muñoz, Paul Muñoz, Siddharth Saksena, Jennifer Irish

“…LSTM‐SAM incorporates a transfer learning approach applicable to target (tide‐gage) stations along the U.S. …”
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π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing by Xiang Zhang, Tianze Ling, Zhi Jin, Sheng Xu, Zhiqiang Gao, Boyan Sun, Zijie Qiu, Jiaqi Wei, Nanqing Dong, Guangshuai Wang, Guibin Wang, Leyuan Li, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Fuchu He, Wanli Ouyang, Cheng Chang, Siqi Sun

“…Current deep learning models often rely on autoregressive generation, which suffers from error accumulation and slow inference speeds. In this work, we introduce π-PrimeNovo, a non-autoregressive Transformer-based model for peptide sequencing. …”
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Nonlinear Model Predictive Yaw Moment Control Through Electric Axle and Friction Brake Torque Distribution by Carmine Caponio, Gaetano Tavolo, Davide Tavernini, Ahu Ece Hartavi Karci, Javad Ahmadi, Basilio Lenzo, Giulio Reina, Giacomo Mantriota, Pietro Perlo, Aldo Sorniotti

“…With respect to benchmarking rule-based controllers, the results show that the NMPCs bring significant reductions of the yaw rate errors and friction brake power losses, while increasing the exit speed in acceleration-during-cornering conditions.…”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…The outcomes of our study are particularly noteworthy, with the model demonstrating remarkably low Mean Squared Error (MSE) values across all data clusters, ranging from 0.011 to 0.072. …”
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Wireless Channel Prediction Using Artificial Intelligence With Imperfect Datasets by Gowhar Javanmardi, Ramiro Samano Robles

“…Emerging vehicular applications will operate in complex settings with potentially abrupt and quick propagation changes. …”
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High-Resolution Eye-Tracking System for Accurate Measurement of Short-Latency Ocular Following Responses: Development and Observational Study by Aleksandar Miladinović, Christian Quaia, Simone Kresevic, Miloš Ajčević, Laura Diplotti, Paola Michieletto, Agostino Accardo, Stefano Pensiero

“…Head motion compensation was successfully tested, showing a displacement error of less than 5 μm. Finally, robust OFRs were detected in 16 children during recording sessions lasting less than 5 minutes. …”
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A Modified Regular Perturbation Model for the Single-Span Fiber Transmission Using Learnable Methods by Shuhong He, Zhongya Li, Sizhe Xing, An Yan, Yingjun Zhou, Jianyang Shi, Chao Shen, Ziwei Li, Zhixue He, Wei Chen, Nan Chi, Junwen Zhang

“…When transmitting a dual-polarization signal with a launch power of 13 dBm, the modified regular perturbation (MRP) model proposed in the paper can reduce the fitting errors by more than 75% compared to the standard RP model after transmitting through a 120 km standard single-mode fiber.…”
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A Regional Gravimetric and Hybrid Geoid Model in Northern Greece from Dedicated Gravity Campaigns by Georgios S. Vergos, Dimitrios A. Natsiopoulos, Elisavet G. Mamagiannou, Eleni A. Tzanou, Anastasia I. Triantafyllou, Ilias N. Tziavos, Dimitrios Ramnalis, Vassilios Polychronos

“…The determination of physical heights is of key importance for a wide spectrum of geoscientific applications and, in particular, for engineering projects. …”
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Integrating experimental and theoretical investigations of porous graphite materials with scanning electron microscope image processing by Muhammad Punhal Sahto, Wang Wei, Muhammad Fawad Jamil, Awais Mehmood, Mariyam Sattar, Asif Raza, Mujib Ur Rahman, Mumtaz A. Qaisrani

“…Accurate determination of fractal dimension (FD) and permeability of porous graphite materials (PGM) is essential for applications like porous aerostatic bearings (PABs). …”
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Beyond N-Grams: Enhancing String Kernels With Transformer-Guided Semantic Insights by Nazar Zaki, Reem Alderei, Mahra Alketbi, Alia Alkaabi, Fatima Alneyadi, Nadeen Zaki

“…We propose and evaluate four innovative kernel-based methods namely Attention-Augmented Kernel, Error Pattern Analysis, Transformer-Guided N-gram Selection, and a Custom Kernel Function each designed to uniquely capture semantic and structural distinctions of text. …”
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Retrieval of Total Precipitable Water Under All‐Weather Conditions From Himawari‐8/AHI Observations Using the Generative Diffusion Model by Haixia Xiao, Feng Zhang, Renhe Zhang, Feng Lu, Miao Cai, Lingxiao Wang

“…Specifically, when compared to radiosonde TPW, TPWDiff‐CB yields a correlation coefficient (R) of 0.98 and a root mean square error of 4.51 mm under all‐weather condtions. The model demonstrates exceptional performance, maintaining near‐identical accuracy under both cloudy and clear‐sky conditions. …”
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