Evaluating the Impact of Replay-Based Continual Learning on Long-Term sEMG Pattern Recognition in Instance-Incremental Learning by Yuto Okawa, Suguru Kanoga, Takayuki Hoshino, Shin-Nosuke Ishikawa

“…Although regularization-based CL methods have proven effective in ensuring robust sEMG pattern recognition in instance-IL scenarios, the effectiveness of replay-based CL methods in instance-IL remains uncertain, particularly regarding the optimal sample number for replay. This study compared two replay-based CL methods—experience replay (ER) and averaged gradient episodic memory (A-GEM) with two regularization-based CL methods (synaptic intelligence (SI) and learning without forgetting (LwF))—to update a backbone model. …”
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An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

“…The implementation of algorithms based on convolutional neural networks (CNNs) has seen significant growth in the automation of disease identification. …”
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An Enhanced Deep Learning Approach to Potential Purchaser Prediction: AutoGluon Ensembles for Cross-Industry Profit Maximization by Hashibul Ahsan Shoaib, Md Anisur Rahman, Jannatul Maua, Ashifur Rahman, M. F. Mridha, Pankoo Kim, Jungpil Shin

“…The proposed AutoGluon-based ensemble integrates neural networks with boosted trees, stacking, and bagging to maximize the Expected Maximum Profit Criterion (EMPC) and deliver consistent predictive performance across datasets. …”
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Forecasting Weather using Deep Learning from the Meteorological Stations Data : A Study of Different Meteorological Stations in Kaski District, Nepal by Supath Dhital, Kapil Lamsal, Sulav Shrestha, Umesh Bhurtyal

“…Stochastic Gradient Descent and Adam optimizer are used to optimize the LSTM model. Among all the models prepared, Root Mean Square Error (RMSE) values range from 0.58 to 4.08 for the precipitation model and from 0.16 to 0.82 for the air temperature model, and Mean Absolute Error (MAE) values range from 0.21 to 2.87 for the precipitation model and from 0.12 to 0.64 for air temperature model were the values of the final model that indicates better accuracy for air temperature. …”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Classical keypoint matching methods find the extreme pose transitions between cameras present in a CVGL configuration challenging to operate in, while deep neural networks demonstrate superb capacity in this area. …”
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The Impact of Research-Based Learning and Institutional Support on Student Research Productivity at Madrasah Aliyah Negeri in Jakarta, Indonesia by Farida Hanun, Onok Yayang Pamungkas, Suprapto Suprapto, Achmad Dudin, Wakhid Kozin, Lisa'diyah Ma'rifataini

“…However, problems in optimizing research learning, as well as the lack of structural support from madrasas, still affect the level of student involvement in scientific research. …”
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Leveraging Extended Windows in End-to-End Deep Learning for Improved Continuous Myoelectric Locomotion Prediction by Yuzhou Lin, Yuyang Zhang, Wenjuan Zhong, Wenxuan Xiong, Zhen Xi, Yi-Feng Chen, Mingming Zhang

“…We systematically evaluate six window lengths paired with three prediction horizons (model forecasts 50 ms to 150 ms ahead) in a continuous locomotion task involving eight modes and 16 transitions. The optimal configuration (1000 ms window with 150 ms horizon) achieved subject-average accuracies of 96.93% (steady states) and 97.50% (transient states), maintaining 95.03% and 85.53% respectively in real-time simulations. …”
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Rapid human movement and dengue transmission in Bangladesh: a spatial and temporal analysis based on different policy measures of COVID-19 pandemic and Eid festival by Jahirul Islam, Wenbiao Hu

“…Through the selection of an optimal Seasonal autoregressive integrated moving average model, we observed that the closure of public transport (β = − 1.66, P < 0.10) and restrictions on internal movement (β = − 2.13, P < 0.10) were associated with the reduction of dengue incidence. …”
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YOLOv9-Based Human Face Detection and Counting Under Human-Animal Faces, Complex Imaging Environments, and Image Qualities by Sivaranjini Perikamana Narayanan, M. Sabarimalai Manikandan, Linga Reddy Cenkeramaddi

“…Despite the advancements in deep learning networks, accurate and reliable detection is still a challenging task in the presence of different kinds of objects, animal faces, and image characteristics. …”
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YOLOv8-eRFD-AP: A Novel Domain Generalization Model for UAV-Based Insulator Inspection Under Adverse Weather Conditions by Badr-Eddine Benelmostafa, Rita Aitelhaj, Hicham Medromi

“…The model achieves a mean average precision at 0.5 intersection over union (mAP@0.5) of 92.0%, exceeding the second-best model by 2.7% under clear weather. …”
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Electrochemical Sensors Based on Single-Wall Carbon Nanotubes in Voltammetric Ascorbic Acid Tests by Natalia V. Ivanova, Elizaveta A. Martynova, Anna I. Vershinina, Maksim V. Lomakin, Galina O. Eremeeva, Olesya R. Gordaya, Sergey D. Shandakov

“…Fibers were produced from a solvent by wet-pulling of single-wall carbon nanotubes networks. Thin films of randomly oriented single-wall carbon nanotube bundles were deposited downstream of a floating aerosol CVD reactor, which included a high temperature furnace with a quartz tube. …”
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Development of Low-Cost Monitoring and Assessment System for Cycle Paths Based on Raspberry Pi Technology by Salvatore Bruno, Ionut Daniel Trifan, Lorenzo Vita, Giuseppe Loprencipe

“…The continuous monitoring of road networks is required to ensure the timely scheduling of optimal maintenance activities. …”
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A hybrid deep learning framework for global irradiance prediction using fuzzy C-Means, CNN-WNN, and Informer models by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Wissem Dimassi, Salah Hannachi

“…Artificial intelligence (AI) is revolutionizing solar energy forecasting, enabling precise irradiance prediction for electric solar vehicles (ESVs) to optimize energy efficiency and extend driving range.This study introduces a novel AI-powered hybrid deep learning framework that synergistically combines fuzzy C-means (FCM) clustering, convolutional neural networks (CNNs), wavelet neural networks (WNNs), and an Informer model to achieve superior accuracy. …”
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Revised methodology for CO₂ and CH₄ measurements at remote sites using a working standard-gas-saving system by M. Sasakawa, N. Tsuda, T. Machida, M. Arshinov, D. Davydov, A. Fofonov, B. Belan

“…The Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) is made up of this system, which was installed across nine different sites in Siberia. …”
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Utilizing plasma biochemical indicators to improve prediction of economic traits in crossbred duck population by Jian Hu, Mengdie Wang, Linxi Zhu, Chengming Han, Qinglei Yang, Zhenlin Liu, Jing Song, Zhengkui Zhou, Shuisheng Hou, Wentao Cai

“…GBLUP outperformed pedigree BLUP, with an average reliability improvement of 0.024, though Bayesian models offered incremental gains for specific traits (e.g., +0.165 for CHE under BayesN). …”
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Algoritmo genético permutacional para el despliegue y la planificación de sistemas de tiempo real distribuidos by Ekain Azketa, J. Javier Gutiérrez, Marco Di Natale, Luís Almeida, Marga Marcos

“…Besides deploying and scheduling tasks and messages, the algorithm can minimize the number of the used computers, the utilization of computing and networking resources and the average worst-case response times of the applications. …”
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Working time distribution and administrative burden in Austrian community health nursing: A cross-sectional survey by Raimund M. Kovacevic, Doris A. Behrens, Walter Hyll

“…Results: Our analysis shows that 92% of the community health nurses in Austria work in non-urban areas. On average, they have one client contact every five working hours, lasting around 75 minutes. …”
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Analysing cold-climate urban heat islands using personal weather station data by Jonathon Taylor, Charles H. Simpson, Jaana Vanhatalo, Hasan Sohail, Oscar Brousse, Clare Heaviside

“…Urban heat islands (UHI) modify building heating and cooling loads and public exposure to non-optimal temperatures, topics of increasing importance given climate change. …”
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Machine learning algorithms to predict stroke in China based on causal inference of time series analysis by Qizhi Zheng, Ayang Zhao, Xinzhu Wang, Yanhong Bai, Zikun Wang, Xiuying Wang, Xianzhang Zeng, Guanghui Dong

“…Participants This study employed a combination of Vector Autoregression (VAR) model and Graph Neural Networks (GNN) to systematically construct dynamic causal inference. …”
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Research on emulsion concentration detection technology based on interpretable machine learning methods by Jiaxu Kang, Jianwei Li, Meng Wang, Xinwei Guo, Dinghao Liu, Chao Qu, Chengbin Guo

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