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

“…Our approach offers a holistic, end-to-end denoising solution that simultaneously addresses multiple artifact types in multichannel EEG data. We enhanced the generation of noisy-clean EEG data pairs using an independent component analysis, thus fortifying the training scenarios critical for effective supervised learning. …”
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Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…This work aims to investigate on IMU recorded data (i) the influence of environmental factors and biometric measurements, (ii) their repeatability, (iii) the correlation with judge evaluations, and (iv) their predictive value.Material and methodsThe Equisense Motion S® was used to collect phenotypes on 135 horses, Bardigiano (101) and Murgese (34) and the data analysis was conducted using R (v.4.1.2). …”
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Wind Turbine Fault Detection Through Autoencoder-Based Neural Network and FMSA by Welker Facchini Nogueira, Arthur Henrique de Andrade Melani, Gilberto Francisco Martha de Souza

“…The methodology comprises five main stages: (i) the identification of failure modes and their observable symptoms using FMSA, (ii) the acquisition and preprocessing of SCADA monitoring data, (iii) the development of dedicated autoencoder models trained exclusively on healthy operational data, (iv) the implementation of an anomaly detection strategy based on the reconstruction error and a persistence-based rule to reduce false positives, and (v) evaluation using performance metrics. …”
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The potential of drone observations to improve air quality predictions by 4D-Var by H. Erraji, P. Franke, A. Lampert, T. Schuldt, R. Tillmann, A. Wahner, A. C. Lange

“…On both days, a significant improvement in the vertical distribution of <span class="inline-formula">O₃</span> and <span class="inline-formula">NO</span> is noticed in the analysis compared to the reference simulation without data assimilation. …”
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Iron Deposition and Functional Connectivity Differences in Females With Migraine Without Aura: A Comparative Study of Headache Sides by Yan Zhang, Mingxian Bai, Zhenliang Xiong, Qin Zhang, Lihui Wang, Xianchun Zeng

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Image Generation and Lesion Segmentation of Brain Tumors and Stroke Based on GAN and 3D ResU-Net by Mingkang Sun, Xiang Li, Weiye Sun

“…For example, in T1<inline-formula> <tex-math notation="LaTeX">$\to $ </tex-math></inline-formula> Flair conversion, the generative multi-modal image analysis model based on perceptual loop consistency had an average peak signal-to-noise ratio of <inline-formula> <tex-math notation="LaTeX">$23.951~\pm ~2.735$ </tex-math></inline-formula>, an average structural similarity of <inline-formula> <tex-math notation="LaTeX">$0.873~\pm ~0.046$ </tex-math></inline-formula>, and an average root mean square error of <inline-formula> <tex-math notation="LaTeX">$16.998~\pm ~6.184$ </tex-math></inline-formula>. …”
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Integrating analytical statistical models, sequential pattern mining, and fuzzy set theory for advanced mobile app reliability assessment by Олександр Шматко, Олексій Коломійцев, Володимир Федорченко, Ірина Михайленко, Вячеслав Третяк

“…The application of the methodology is demonstrated by studying software error reports and conducting a comprehensive statistical analysis of them. …”
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Evolutionary Neural Simulation of Import Substitution in the Radio Electronics Industry in the Regions Using Adaptive Network-Based Fuzzy Inference System by Sergei Yashin, Egor Koshelev, Alexey Ivanov, Sergei Borisov, Diyor Karimov, Ivan Babkin

“…Similarly, the analysis showed the result on the new 2023 data compared to the conventional ANFIS (MAPE=20.88% for target 1 and MAPE=14.03% for target 2) as well as Lavenberg-Marquardt method (MAPE=40.3% for target 1), respectively. …”
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Efficient adsorption of methylene blue (MB) by an eco-friendly chitosan derivative adsorbent: An RSM and ANN modeling study by E. Igberase, I.G. Mkhize

“…One neuron was employed as the output layer, which corresponds to the removal efficiency of MB, and variables, including adsorbent dosage, pH, contact time, and MB concentration, were taken into consideration as the input layer feed data. Statistical metrics such as average relative errors (ARE), coefficient of determination (R2), mean squared error (MSE), Pearson's Chi-square (χ2), root means square errors (RMSE), and the sum of squares of errors (SSE) were used to measure the RSM and ANN models. …”
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Interpretable Deep Learning Model for Grape Leaf Disease Classification Based on EfficientNet with Grad-CAM Visualization by Castaka Agus Sugianto, Dini Rohmayani, Jhoanne Fredricka, Mohamed Doheir

“…Each image has a resolution of 300 × 300 pixels with a 24-bit color depth, ensuring sufficient detail for analysis. To enhance model performance, data augmentation and hyperparameter tuning were applied. …”
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Estimation of the Relative Chlorophyll Content of Pear Leaves Based on Field Spectrometry in Alaer, Xinjiang by Yufen Huang, Zhenqi Fan, Hongxin Wu, Ximeng Zhang, Yanlong Liu

“…ViewSpecPro 6.2 software was employed to smooth the ground spectral data. Traditional mathematical transformations and the discrete wavelet transform were used to process the spectral data, then correlation analysis was employed to extract the sensitive bands, and partial least squares regression (PLS) was used to establish a model for estimating the chlorophyll content of pear tree leaves. …”
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Network intrusion detection based on relative mutual K-nearest neighbor density peak clustering by Chunhua Ren, Changyuan Wang, Yang Yu, Wanan Yang, Ruiqi Guo

“…Firstly, in the stage of local density calculation, the relative mutual K-nearest neighbor method is used instead of the traditional truncation distance method to more accurately characterize the local density distribution by considering the mutual neighborhood relationship between data points. Secondly, in the remaining point allocation stage, the fuzzy allocation strategy of the mutual K-nearest neighbor effectively avoids the error propagation problem caused by chain allocation in traditional density peaks clustering algorithm (DPC). …”
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Prognosis of air quality index and air pollution using machine learning techniques by Mostafa M. Abdelmalek, Hatem Mahmoud, Hassan Shokry

“…The findings highlight the value of ML in enhancing air quality prediction and monitoring, offering accurate tools for hourly data analysis and potential real-time application. …”
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Effects of mouldboard shape and operational parameters on soil-ridger dynamics: An experimental and discrete element modelling approach by Avdhoot Walunj, Saurabh Shinde, Sachin Nalawade, Pranav Pawase, Zhiwei Zeng

“…Ridge and furrow profile indicated that mouldboard shape, speed, and depth collectively shaped soil topography. The average relative error between experimental and DEM data for furrow width, furrow depth, ridge height, and draft force ranged between 2.75% and 17.26%, demonstrating close agreement. …”
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Research on Mechanical Properties of Non-Directly Welded Reinforced Casings Under High Stress Ratio by Yiwei Fang, Yuming Li, Kuntao Xing, Zhe Liu

“…These models allowed for a comprehensive analysis of the numerical results alongside the experimental data, taking into account the thermal effects of welding. …”
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The Influence of Freeze–Thaw Process on the Dynamic Changes in Body Weight and Metal in Groundwater of Seasonal Frozen Lakes: Experimental Study and Model Simulation by Hui Zhang, Shengnan Zhao, Xiaohong Shi, Jinda Zhang, Zhimou Cui, Jingyi Wang

“…Based on a large amount of measured lake heavy metal data, MATLAB 2022b software is used to model data fitting and optimization identification, and wavelet analysis and 24 h sliding average method are used for verification analysis to describe the variation process of heavy metal concentration in ice water with depth and time. …”
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Thematic Curriculum and Pupils’ Academic Performance: A case study of Kitumba Sub-County, Kabale District. by Bibian, Kemigisha

“…The collected data was then cross checked for completeness and error omission. …”
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Development and psychometric evaluation of E-Learning Assessment Scale in Higher Education by Sevil Çiçek Özdemir, Ayten Şentürk Erenel, Şengül Yaman Sözbir, Sıdıka Pelit Aksu, Canan Uçakcı Asalıoğlu

“…The item pool of the scale was created grounded on the applicable literature. The data were estimated using descriptive statistics, explanatory and confirmational factor analysis (CFA), Pearson correlation analysis, t-test for dependent variables and Cronbach alpha coefficient. …”
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Dietary factors and predominant eye diseases in sub-Saharan African populations: A systematic review protocol. by Isaiah Osei Duah Junior, Kwadwo Owusu Akuffo, Josephine Ampong, David Owiredu, Bridget Senya Boateng, Anthony Danso-Appiah

“…Evidence linking diet and ocular diseases is growing, yet variations persist, with a paucity of data in sub-Saharan Africa. The proposed review will systematically synthesize evidence on dietary factors associated with predominant eye disorders (cataracts, refractive error, glaucoma, diabetic retinopathy, age-related macular degeneration, and dry eye disease) in the sub-Saharan African population. …”
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Nonlinear Autoregressive Neural Network and Extended Kalman Filters for Prediction of Financial Time Series by Ghassane Benrhmach, Khalil Namir, Abdelwahed Namir, Jamal Bouyaghroumni

“…Obtaining the method with the least prediction error is one of the difficult problems of financial market and investment analysts. …”
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