Advancements in image classification for environmental monitoring using AI by Jinjing Zhu, Ling Li

“…MABEC-Net integrates multi-scale feature extraction, which enables the model to analyze both fine-grained local textures and broader environmental patterns. Spatial and channel attention mechanisms are incorporated to dynamically adjust feature importance, allowing the model to focus on key visual information while minimizing noise.In addition to the network architecture, we propose the Adaptive Environmental Training Strategy (AETS), a robust training framework designed to improve model generalization across diverse environmental datasets. …”
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Comparative Analysis of Data Visualization and Deep Learning Models in Air Quality Forecasting by Bihter Daş, Damla Mengus

“…This study utilizes air pollution data from the Continuous Monitoring Center of the Ministry of Environment, Urbanization, and Climate Change in Turkey to predict various pollutants using three advanced deep learning approaches: LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), and RNN (Recurrent Neural Network). Missing data in the dataset were imputed using the K-Nearest Neighbor (K-NN) algorithm to ensure data completeness. …”
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Regional differences and distributional dynamic evolution of science and technology innovation driven green development efficiency in Chinese agriculture by Lingling Wang, Min Li, Panpan Zhang

“…This study assesses the spatiotemporal efficiency of ASTI in promoting green agricultural development across 30 Chinese provinces, aiming to uncover persistent regional disparities and dynamic evolution patterns.MethodsConstructing an evaluation model and indicator system for science, technology and innovation driven green development in agriculture, applying the network Slack-Based Measure (SBM) model to measure the level of efficiency, and analyzing regional differences and dynamic features through the Theil index, kernel density estimation and spatial Markov methods.Results and discussionThis study explores the regional differences and distributional dynamic evolution of the efficiency of Agricultural science and technology innovation (ASTI) driven green development in China. …”
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Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

“…Although existing studies have attempted to combine acoustic and visual information, most adopt simple feature-level fusion strategies, which fail to fully explore the complementary advantages of the two modalities under different environmental conditions and lack dynamic evaluation mechanisms for modal reliability. To address these problems, we propose the Adaptive Cross-modal Attention Fusion Network (ACAF-Net), a cross-modal complementarity learning framework with a two-stage attention fusion mechanism: (1) a cross-modal enhancement stage that enriches individual representations through Low-rank Bilinear Pooling and learnable fusion weights; (2) an adaptive attention fusion stage that dynamically weights acoustic and visual features based on complementarity and environmental reliability. …”
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Identifying Socio-Technical Risks in Open-Source Software for Scholarly Communications: Tools, Metrics, and Opportunities for Libraries to Support Sustainable Development by Pierre Lasou, Tomasz Neugebauer, Pamela Carson

“…While all aspects of OSS projects may be evaluated at the project or network/ecosystem level, addressing the actors, software, or orchestration (Linåker et al., 2022), community evaluation that looks at the interaction patterns between project contributors is the practical focus of this research paper since there are multiple human factors that librarians who may not be software developers can impact. …”
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Antimicrobial Analysis of an Antiseptic Made from Ethanol Crude Extracts of P. granatum and E. uniflora in Wistar Rats against Staphylococcus aureus and Staphylococcus epidermidis by Thaís Honório Lins Bernardo, Regina Célia Sales Santos Veríssimo, Valter Alvino, Maria Gabriella Silva Araujo, Raíssa Fernanda Evangelista Pires dos Santos, Max Denisson Maurício Viana, Maria Lysete de Assis Bastos, Magna Suzana Alexandre-Moreira, João Xavier de Araújo-Júnior

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SEM Deep Learning Multiclass Noise Level Classification With Data Augmentation by Kai Liang Lew, Kok Swee Sim, Shing Chiang Tan

“…Three different SEM datasets are used, namely the NFFA-EUROPE dataset, EPFL CVLab EM dataset, and Biofilms SEM dataset. The proposed network achieved the highest evaluation in accuracy (92.76%), precision (92.77%), recall (92.76%), and F1 score (92.74%), as well as the shortest training time in the NFFA-EUROPE dataset. …”
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Analysis of hot spots and trends in urban resilience research based on CiteSpace by Dong Yanan, Wang Fei

“…This study integrates bibliometric knowledge graphs with the theory of discipline evolution dynamics, employing CiteSpace software to analyze international literature data since 1990, revealing the research stages and evolution patterns. The findings show that: (1) International research has consistently grown since the 1990s, forming a research framework centered around ecological construction and sustainable development, with a core author network demonstrating close collaboration; (2) The evolution of the discipline exhibits a gradient development, with research entering a mature stage and a multi-dimensional research paradigm emerging; (3) Current research primarily focuses on ecological construction and sustainable development, with a strong emphasis on empirical studies, while also showing signs of maturation as it diversifies into various directions. …”
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Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision by Chenglong Fan, Guanglin Yang, Cheng Li, Jiwen Cheng, Shaohua Chen, Hua Mi

“…Methods In this study, the expression patterns of glycolysis-related genes (GRGs) were first analyzed using the GSE30122, GSE30528, and GSE96804  datasets, followed by an evaluation of the immune landscape in DN. …”
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A systematic review on sleep stage classification and sleep disorder detection using artificial intelligence by Tayab Uddin Wara, Ababil Hossain Fahad, Adri Shankar Das, Md Mehedi Hasan Shawon

“…The Neural Network algorithms are the most popular, having 47 % of the total usage. …”
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Novel dual gland GAN architecture improves human protein localization classification using salivary and pituitary gland inspired loss functions by Hanaa Salem Marie, Moatasem M. Draz, Waleed Abd Elkhalik, Mostafa Elbaz

“…This paper introduces a novel approach that employs two complementary loss functions within a Generative Adversarial Network (GAN) framework for processing images from the Human Protein Atlas dataset. …”
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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction by Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas

“…A genetic algorithm-based hyperparameter optimization method reduces the computational load on edge nodes by efficiently exploring different configurations and using only the most promising ones for edge nodes’ cross-validation. The evaluation results demonstrate a significant improvement in average prediction accuracy and better capturing of energy patterns compared to the federated averaging approach. …”
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Enhancing Creativity and Validation in Explanatory Deep Learning-Based Symbolic Music Generation: A Hybrid Approach With LSTM and Genetic Algorithms by Ahmad Zainul Fanani, Arry Maulana Syarif, Ika Novita Dewi, Abdul Karim

“…The LSTM network produces initial compositions, and the GA module ensures compliance with musical rules, enhancing both explainability and creativity. …”
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Physics-Informed Learning Framework for Lower Limb Kinematic Prediction With Sparse Sensors and Its Application in Chronic Stroke by Yan Guo, Yusuke Sekiguchi, Wen Zeng, Satoru Ebihara, Dai Owaki, Mitsuhiro Hayashibe

“…Kinematic evaluation of gait is critical for biomechanical analysis and disease diagnosis. …”
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Research on load labeling method for big data in novel power system by ZHANG Ximing, XU Huan, YANG Qiuyong

“…Unique evaluation indicators are also identified to measure the performance of the composite dataset. …”
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Diagnosis of depression based on facial multimodal data by Nani Jin, Renjia Ye, Peng Li

“…We use spatiotemporal attention module to enhance the extraction of visual features and combine the Graph Convolutional Network (GCN) and the Long and Short Term Memory (LSTM) to analyze the audio features. …”
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Unravelling interdisciplinary interactions and researcher migration across the evolution of perovskite solar cell research through comprehensive bibliometrics by Jun-Seok Yeo, A-Ram Kim

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Rehabilitation and Motion Symmetry Analysis With a TACX Smart Cycling Trainer Using Computational Intelligence by Hana Charvatova, Daniel Martynek, Alexandra Molcanova, Ales Prochazka

“…The research objectives include analysis of motion patterns, evaluation of motion symmetry under varying loads, and examination of heart rate responses to load variations. …”
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A comparison of floating catchment area parameters with applications to a dataset of clinics enrolled in a statewide child and adolescent psychiatric consultation program by Jocelyn Hunyadi, Jocelyn Hunyadi, Lara S. Savas, Kehe Zhang, Kehe Zhang, Jeanette E. Deason, Ryan Ramphul, Melissa F. Peskin, Erica L. Frost, Cici Bauer, Cici Bauer

“…Our study aims to (a) perform a comparative analysis of 2SFCA input parameters on patterns of spatial accessibility and (b) identify a 2SFCA method to guide evaluation of equitable allocation of scarce mental health resources for children and adolescents in Texas.MethodsWe used the Texas Child Psychiatry Access Network (CPAN) data to assess county-level, regional patterns in access to pediatric psychiatric care, and to identify areas to expand CPAN to mitigate access-related disparities. …”
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Social behavior in ASD males: The interplay between cognitive flexibility, working memory, and functional connectivity deviations by Shi Yu Chan, Jasmine Si Min Chuah, Pei Huang, Ai Peng Tan

“…These normative charts were then applied to ASD males (n = 418) to calculate individual deviation scores (z-scores) that reflect the degree of rsFC atypicality. Deviations in rsFC patterns among the default mode network (DMN), ventral attention network (VAN), frontoparietal network (FPN), and somatomotor network (SMN) were associated with distinct dimensions of social behavior. …”
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