A multi-module enhanced YOLOv8 framework for accurate AO classification of distal radius fractures: SCFAST-YOLO by Yu Wang, Haifu Sun, Tiankai Jiang, JunFeng Shi, JunFeng Shi, Qin Wang, Qin Wang, Hongwei Yang, Hongwei Yang, Yusen Qiao

“…Secondly, we develop the C2f-Faster-EMA module that preserves fine-grained spatial details through optimized information pathways and statistical feature aggregation. …”
Get full text

Unsupervised machine learning-based multi-attributes analysis for enhancing gas channel detection and facies classification in the serpent field, offshore Nile Delta, Egypt by Shaimaa A. El-Dabaa, Farouk I. Metwalli, Ali Maher, Amir Ismail

“…Seismic attribute analysis can enhance the tracking of subtle stratigraphic features. It is challenging to investigate these subtle features, including channel systems, with conventional-amplitude seismic data. …”
Get full text

Eccentric Compression Behavior of Coral Aggregate Geopolymer Concrete Columns Reinforced with Stainless-Steel Rebars by Haiwen Xu, Jiasheng Jiang, Chao Yang

Get full text

Direct-Write Ion Beam Lithography by Alexandra Joshi-Imre, Sven Bauerdick

“…Indeed, the capability of easily creating three-dimensional patterns and shaping objects by milling and deposition is probably the most recognized feature of ion beam lithography (IBL) and micromachining. …”
Get full text

Symmetry-Based Data Augmentation Method for Deep Learning-Based Structural Damage Identification by Long Li, Xiaoming Tao, Hui Song, Xiaolong Li, Zhilong Ye, Yao Jin, Qiuyu He, Shiyin Wei, Wenli Chen

“…These methods typically use ML algorithms to identify patterns within features extracted from data representing structural conditions, thereby inferring damage from changes in these patterns. …”
Get full text

A Data Model and Method Framework for Cyberspace Map Visualization by Zheng Zhang, Chenghu Zhou, Minjie Chen, Yibing Cao, Shaojing Fan

“…The experimental results showed that the proposed data model and method framework can be effectively applied to represent the distribution and relations of cyberspace features and help reveal the interaction patterns between cyberspace and geographic space.…”
Get full text

Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…To ensure the models’ decision-making is compatible with clinical decisions and common practices, we applied explainability techniques such as SHAP to reveal the patterns learned by the models. These patterns were found to be clinically plausible. …”
Get full text

Windows Malware Detection via Enhanced Graph Representations with Node2Vec and Graph Attention Network by Nisa Vuran Sarı, Mehmet Acı, Çiğdem İnan Acı

“…The increasing complexity of malware poses significant challenges in cybersecurity due to the inability of existing methods to understand detailed and contextual relationships in modern software behavior. Therefore, developing innovative detection frameworks that can effectively analyze and interpret these complex patterns has become critical. …”
Get full text

Ensemble of deep learning and IoT technologies for improved safety in smart indoor activity monitoring for visually impaired individuals by Mesfer Al Duhayyim

“…Furthermore, the ResNet50 model is employed for feature extraction to capture complex spatial patterns in visual data. …”
Get full text

Centripetal Trend in Comments to News in Social Networks by Nikolay D. Golev, Maria A. Sushkina

“…The patterns of their correlation showed how the self-developing nature of communication created new linguistic phenomena. …”

Experimental and discrete element method study on the mechanical properties of hole-fracture sandstone by Peijie Lou, Peijie Lou, Peijie Lou, Peijie Lou, Lichen Sun, Cheng Pan, Penghui Ji, Huan Liu

Get full text

Landscapes of Trade by Merten Nefs

“…These include the seemingly ubiquitous growth pattern of DCs in the Netherlands, the dominant and increasingly challenged policy narrative of the Netherlands as a ‘gateway to Europe’, and the public-private actor network that appears to fall short of adequate DC planning and development. …”
Get full text

Logging identification of karstified Jurassic conglomerate aquifer in the Zhuxianzhuang coal mine: implications for water abundance heterogeneity and mining risk mitigation by Zhu Guanyu, Zhu Guanyu, Jiang Bo, Jiang Bo, Li Ming, Li Ming, Song Yu, Song Yu, Cheng Guoxi, Cheng Guoxi

“…The Jurassic conglomerate aquifer in the coal seam roof of Zhuxianzhuang Coal Mine in the Huaibei Coalfield exhibits significant karst and water-rich heterogeneity, and its geological patterns remain poorly understood. This study systematically investigates the lithology, stratigraphy, structural characteristics, karst features, and hydrogeological conditions of the Jurassic conglomerate aquifer. …”
Get full text

Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance With EDA and Multi-Channel CNN by Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, I Gede Juliana Eka Putra

“…The MCNN architecture effectively captures local patterns in text using multiple filter sizes, enabling comprehensive feature extraction with low computational overhead. …”
Get full text

GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence by Mohd Anjum, Ashit Kumar Dutta, Ali Elrashidi, Sana Shahab, Asma Aldrees, Zaffar Ahmed Shaikh, Abeer Aljohani

“…To address these limitations, this research proposes GraphFedAI, a novel framework that integrates adaptive session-based graph modeling, Pearson correlation-guided feature selection, interpolation-aware graph neural network (GNN) training, and federated learning to enable robust, scalable, and privacy-preserving DDoS detection in heterogeneous Internet of Things (IoT) networks.The framework represents the IoT network as dynamic graphs where communication patterns among devices are modeled as edges that evolve over time. …”
Get full text

HCAP: Hybrid cyber attack prediction model for securing healthcare applications. by Mohanad Faeq Ali, Mohammed Shakir Mohmood, Ban Salman Shukur, Rex Bacarra, Jamil Abedalrahim Jamil Alsayaydeh, Masrullizam Mat Ibrahim, Safarudin Gazali Herawan

“…The gathered information is processed with the help of Principal Component-Recursive Feature Elimination (PC-RFE), which eliminates the irrelevant features. …”
Get full text

Quantitative analysis of communication dynamics in agile software teams through multimodal analytics by Diego Miranda, Rene Noel, Jaime Godoy, Carlos Escobedo, Cristian Cechinel, Roberto Munoz

“…Abstract Effective collaboration in agile software development depends on communication, cooperation, and coordination. …”
Get full text

Conceptualizing resilience in public health: a philosophical approach by Jishnu Pawan K., Mala Ramanathan

“…Results The critical evaluation of existing literature led to the identification of two patterns by which resilience has been conceptualized across disciplines. …”
Get full text

Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…This method leverages TCN's causal and dilated convolution operations to capture long-term sequential features, BiLSTM's bidirectional information processing to ensure the completeness of sequence information, and the SEAttention mechanism to assign adaptive weights to features, effectively enhancing the focus on key features. …”
Get full text

Geographically Aware Air Quality Prediction Through CNN-LSTM-KAN Hybrid Modeling with Climatic and Topographic Differentiation by Yue Hu, Yitong Ding, Wenjing Jiang

“…Air pollution poses a pressing global challenge, particularly in rapidly industrializing nations like China where deteriorating air quality critically endangers public health and sustainable development. To address the heterogeneous patterns of air pollution across diverse geographical and climatic regions, this study proposes a novel CNN-LSTM-KAN hybrid deep learning framework for high-precision Air Quality Index (AQI) time-series prediction. …”
Get full text