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

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

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

“…Abstract Background The initial inquiry into the concept revealed its usage as a boundary object and how this facilitated its interdisciplinary utilization. The same feature enabled the shift to literature within other disciplines and then identify its conceptualization in them. …”
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

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

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

Identification of Inequities in Green Visibility and Ways to Increase Greenery in Neighborhoods: A Case Study of Wuhan, China by Xiaohua Guo, Chang Liu, Shibo Bi, Yuling Tang

“…The rapid increase in urban population density driven by urban development has intensified inequity in urban green space distribution. …”
Get full text

Personalized prediction of negative affect in individuals with serious mental illness followed using long-term multimodal mobile phenotyping by Christian A. Webb, Boyu Ren, Habiballah Rahimi-Eichi, Bryce W. Gillis, Yoonho Chung, Justin T. Baker

“…Abstract Heightened negative affect is a core feature of serious mental illness. Over 90% of American adults own a smartphone, equipped with an array of sensors which can continuously and unobtrusively measure behaviors (e.g., activity levels, location, and phone usage patterns) which may predict increases in negative affect in real-time in individuals’ daily lives. …”
Get full text

Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

Get full text

A sustainability trilogy approach for drought risk prevention: Case study in Indonesia by Ramli Akhmad, Sumarmi Sumarmi, I. Komang Astina, Satti Wagistina

“…Drought presents a major challenge to agriculture and rural livelihoods, particularly in countries like Indonesia, which feature diverse topography and unpredictable rainfall patterns. …”
Get full text

Hybrid GIS-Transformer Approach for Forecasting Sentinel-1 Displacement Time Series by Lama Moualla, Alessio Rucci, Giampiero Naletto, Nantheera Anantrasirichai, Vania Da Deppo

“…This study presents a deep learning-based approach for forecasting Sentinel-1 displacement time series, with particular attention to irregular temporal patterns—an aspect often overlooked in previous works. …”
Get full text

MetaTrans-FSTSF: A Transformer-Based Meta-Learning Framework for Few-Shot Time Series Forecasting in Flood Prediction by Jiange Jiang, Chen Chen, Anna Lackinger, Huimin Li, Wan Li, Qingqi Pei, Schahram Dustdar

Get full text

NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides by Chengzhi Xie, Yijie Wei, Xinwei Luo, Huan Yang, Hongyan Lai, Fuying Dao, Juan Feng, Hao Lv

“…While various machine learning and deep learning approaches have been explored, their limitations in feature representation and model integration hinder the effective discovery of novel AIPs. …”
Get full text

Acute Liver Injury Is Independent of B Cells or Immunoglobulin M. by James A Richards, Martina Bucsaiova, Emily E Hesketh, Chiara Ventre, Neil C Henderson, Kenneth Simpson, Christopher O C Bellamy, Sarah E M Howie, Stephen M Anderton, Jeremy Hughes, Stephen J Wigmore

“…<h4>Discussion</h4>IgM deposition appears to be common feature of both human and murine sterile liver injury. …”
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

“…Using the Routers, BrightKite, and Cables datasets, we developed a web-based CMV system and generated a statistical map, a node-link map, an edge bundling map, a flow map, and a feature distribution map. …”
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

Flash Flood Regionalization for the Hengduan Mountains Region, China, Combining GNN and SHAP Methods by Yifan Li, Chendi Zhang, Peng Cui, Marwan Hassan, Zhongjie Duan, Suman Bhattacharyya, Shunyu Yao, Yang Zhao

“…The SHAP model was then applied to quantify the impact of all the inducing factors on the regionalization results by Dink-Net. The newly developed framework captured the spatial interactions of the inducing factors and characterized the spatial distribution patterns of the factors. …”
Get full text

Geografia dell’automazione industriale. L’impatto dell’uso dei robot sulle localizzazioni manifatturiere by Lucia Simonetti

“…Robotics seems to be able to slow down (at least in some industrial sectors) the pace of offshoring, but it does not seem to be able to lead to the reshoring of activities to developed economies. And while labour-cost differentials still remain a key feature in firms’ decisions of where to locate manufactures, especially of goods with a high labour content, demand factors, such as the size and growth of local markets, are progressively becoming major determinants.…”
Get full text