Early signs of strong El Niño–Southern Oscillation episodes by Wenxiu Zhong, Arnold Sullivan, Gian Luca Eusebi Borzelli, Ziguang Li

“…Additionally, we find that the spatial standard deviations of the sea surface temperature anomaly in Niño-3 and Niño-4 region, rapidly decrease in the first half of ENSO developing year. This feature is fundamentally distinct from that in neutral years, suggesting that the cycle of ENSO persistence goes beyond the SPB and sea surface temperature anomalies in those two Niño regions are the most predictable.…”
Get full text

Anomaly Detection and Business Process Orchestration for Low-Code Platform in Power System Based on Deep-Cross Model With Data Balancing by Jin Huang, Ming Sheng Xu, Chang Ming Zhu, Guo An Wang

“…Third, we implement a hierarchical feature interaction mechanism that enables both explicit and implicit learning of high-order patterns, resulting in a 35% improvement in anomaly pattern recognition over traditional deep learning approaches. …”
Get full text

Versatility Evaluation of Landslide Risk with Window Sizes and Sampling Techniques Based on Deep Learning by Fudong Ren, Koichi Isobe

“…Unlike conventional methods that often require manual feature selection and engineering, CNNs automate feature extraction, enabling a more nuanced understanding of complex patterns. …”
Get full text

Assessing training needs and influencing factors among personnel at centers for disease control and prevention in northeast China: a cross-sectional study framed by SDT and TPB usi... by Kexin Wang, Peng Wang, Min Wei, Yanping Wang, Huan Liu, Ruiqian Zhuge, Qunkai Wang, Nan Meng, Yiran Gao, Yuxuan Wang, Lijun Gao, Jingjing Liu, Xin Zhang, Mingli Jiao, Qunhong Wu

“…When formulating training plans, priority should be given to how to improve on-job training satisfaction and design a more targeted competency patterns tailored training curriculum. Moreover, organizational incentives aimed at motivating trainees and integrating career development goals into training program design are important. …”
Get full text

Computational characterization of modes of transcriptional regulation of nuclear receptor genes. by Yogita Sharma, Chandra Sekhar Reddy Chilamakuri, Marit Bakke, Boris Lenhard

“…We find that nuclear receptor genes involved in developmental roles show strong evidence of long-range mechanism of transcription regulation with distinct cis-regulatory content they feature clusters of highly conserved non-coding elements distributed in regions spanning several Megabases, long and multiple CpG islands, bivalent promoter marks and statistically significant higher enrichment of enhancer mark around their gene loci. …”
Get full text

Estimating comprehensive growth index for drip-irrigated spring maize in junggar basin via satellite imagery and machine learning by Mingjie Ma, Jinghua Zhao, Tingrui Yang, Feng Liu, Yingying Yuan, Shijiao Ma, Zikang Chang

“…Additionally, the study generated field-scale CGI spatiotemporal distribution maps, revealing the temporal and spatial variation patterns of crop growth. In summary, this study provides an efficient method for monitoring the growth of drip-irrigated spring maize in Northwest China, offering valuable guidance for precision agriculture management and sustainable development.…”
Get full text

A mobile hybrid deep learning approach for classifying 3D-like representations of Amazonian lizards by Arthur Gonsales da Silva, Arthur Gonsales da Silva, Roger Pinho de Oliveira, Caio de Oliveira Bastos, Caio de Oliveira Bastos, Elena Almeida de Carvalho, Bruno Duarte Gomes

“…In this study, we present the development of a hybrid machine learning-based tool suitable for deployment on mobile devices. …”
Get full text

Extraction of <i>Suaeda salsa</i> from UAV Imagery Assisted by Adaptive Capture of Contextual Information by Ning Gao, Xinyuan Du, Min Yang, Xingtao Zhao, Erding Gao, Yixin Yang

“…In this paper, for <i>Suaeda salsa</i>, which is a weak target with a sparse distribution and inconspicuous features, relying on the high-resolution and spatial information-rich features of UAV imagery, we establish an adaptive contextual information extraction deep learning semantic segment model (ACI-Unet), which can solve the problem of recognizing <i>Suaeda salsa</i> from high-precision UAV imagery. …”
Get full text

Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…Feature selection using the ANOVA method identified 10 key features from a total of 17: seq, stddev, N_IN_Conn_P_SrcIP, min, state_number, mean, N_IN_Conn_P_DstIP, drate, srate, and max. …”
Get full text

Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

Get full text

Optimization of CNN Activation Functions using Xception for South Sulawesi Batik Classification by Aswan Aswan, Eva Yulia Puspaningrum, Billy Eden William Asrul

“…The results demonstrate that selecting an optimal activation function substantially enhances convolutional neural network classification of complex batik patterns. The findings offer practical guidance for development of resource aware batik identification systems in support of cultural digitization and education initiatives.…”
Get full text

A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…The CNN model is adjusted for different convolutional layers and fully connected layers to identify patterns and features in brain tumor pictures using an enhanced salp swarm algorithm (SSA) with kernel extreme learning machine (KELM). …”
Get full text

Preparation of Porous F-WO3/TiO2 Films with Visible-Light Photocatalytic Activity by Microarc Oxidation by Chung-Wei Yeh, Kee-Rong Wu, Chung-Hsuang Hung, Hao-Cheng Chang, Chuan-Jen Hsu

Get full text

MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…In the modern era of computers, numerous disciplines are witnessing the development of massive data volumes. Statistics are important in healthcare engineering because they provide insights into various diseases and match patient data. …”
Get full text

TableBorderNet: A Table Border Extraction Network Considering Topological Regularity by Jing Yang, Shengqiang Zhou, Xialing Li, Yuchun Huang, Honglin Jiang

“…The framework captures structural context by guiding convolutional feature extraction along explicit row and column directions, enabling more accurate delineation of table borders. …”
Get full text

Bangla Character Detection Using Enhanced YOLOv11 Models: A Deep Learning Approach by Mahbuba Aktar, Nur Islam, Chaoyu Yang

“…A key limitation lies in the absence of robust detection frameworks capable of accommodating the script’s complex visual patterns and nuances. To address this gap, we propose an enhanced object detection model based on the YOLOv11 architecture, incorporating a ResNet50 backbone for improved feature extraction. …”
Get full text

Personality typology, emotional needs, and romantic relationship stability in Chinese college students: A cultural perspective on MBTI dynamics by Jiaxin Li, Gu Fang, Yiyang Li

“…Structural equation modeling further indicated that gender and personality interactions influence emotional stability, with distinct patterns observed among NT, SJ, and SP types. A U-shaped pattern of emotional stability across academic years was identified, with freshmen showing the highest levels, declining in juniors, and slightly recovering in seniors. …”
Get full text

A Comprehensive Review of EEG-Based Seizure Detection Techniques by Goldwyn Sudhakar Jebaraj, Konguvel Elango

“…By discussing the pros and cons of different methods, current limitations, and ethical considerations, this review seeks to help new researchers develop better EEG-based seizure classification and prediction systems with real-world impact for patients.…”
Get full text

Unsupervised Binary Classifier-Based Object Detection Algorithm with Integrated Background Subtraction Suitable for Use with Aerial Imagery by Gabija Veličkaitė, Ignas Daugėla, Ivan Suzdalev

“…Unlike conventional supervised models, SARGAS is trained in a partially unsupervised manner, learning to recognize feature patterns without requiring labeled data. The algorithm achieved a recall of 93%, demonstrating strong detection capability even under challenging conditions. …”
Get full text

Interpretable Deep Learning for Diabetic Retinopathy: A Comparative Study of CNN, ViT, and Hybrid Architectures by Weijie Zhang, Veronika Belcheva, Tatiana Ermakova

“…The models are assessed based on classification accuracy and interpretability, applying Grad-CAM and Attention-Rollout to analyze decision-making patterns. Results indicate that hybrid models outperform both standalone CNNs and ViTs, achieving a better balance between local feature extraction and global context awareness. …”
Get full text