IoT-Edge Hybrid Architecture with Cross-Modal Transformer and Federated Manifold Learning for Safety-Critical Gesture Control in Adaptive Mobility Platforms by Xinmin Jin, Jian Teng, Jiaji Chen

“…This research presents an IoT-empowered adaptive mobility framework that integrates high-dimensional gesture recognition with edge-cloud orchestration for safety-critical human–machine interaction. …”
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A Deep Reinforcement Learning Framework for Last-Mile Delivery with Public Transport and Traffic-Aware Integration: A Case Study in Casablanca by Amine Mohamed El Amrani, Mouhsene Fri, Othmane Benmoussa, Naoufal Rouky

“…A custom-built environment is developed, utilizing public transportation nodes as transshipment nodes for standardized packets of goods, combined with a realistic simulation of traffic conditions through the integration of the travel time index (TTI) for Casablanca. …”
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Machine Learning-Enhanced Model-Based Optical Proximity Correction Framework With Convolutional Neural Network-Based Variable Threshold Method Near the Diffraction Limit by Jinhao Zhu, Liwan Yue, Ying Li, Xianhe Liu, Qiang Wu, Qi Wang, Yanli Li

“…This study proposes a Machine Learning (ML)-enhanced MBOPC framework that employs a convolutional neural network (CNN) to predict mask edge imaging thresholds, thereby mitigating modeling deviations caused by complex lithographic conditions in the 28 nm technology node under immersion lithography. …”
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Lessons learned deploying an oyster farm monitoring auto-sustainable wireless sensor network and trial of a temperature and relative humidity–based transmission power control schem... by César Ortega-Corral, José Jaime Esqueda Elizondo, Oscar Ricardo Acosta Del Campo, Luis E Palafox, Leocundo Aguilar, Ricardo Guerra-Frausto, Florencio López Cruz, Roberto A Reyes, Jesús Enrique López-Montoya, Carlos Chávez

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A graph neural network simulation of dispersed systems by Aref Hashemi, Aliakbar Izadkhah

“…We present a graph neural network (GNN) that accurately simulates a multidisperse suspension of interacting spherical particles. …”
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Advanced intrusion detection in internet of things using graph attention networks by Aamir S. Ahanger, Sajad M. Khan, Faheem Masoodi, Ayodeji Olalekan Salau

“…Common Internet of Things safety features like encryption, authentication, and access control frequently fall short of meeting their desired functions. In this paper, we present a novel perspective to IoT security by using a Graph-based (GB) algorithm to construct a graph that is evaluated with a graph-based learning Intrusion Detection System (IDS) incorporating a Graph Attention Network (GAT). …”
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Strategy-Switch: From All-Reduce to Parameter Server for Faster Efficient Training by Nikodimos Provatas, Iasonas Chalas, Ioannis Konstantinou, Nectarios Koziris

“…However, the abundance of available data presents a challenge when training neural networks on a single node. …”
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Fault Detection System for Smart City Distribution Networks: A Long Short-Term Memory-Based Approach by A. Herrada, C. Orozco-Henao, Juan Diego Pulgarín Rivera, J. Mora-Flórez, J. Marín-Quintero

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Automatic Acne Detection Model Based on Improved YOLOv7 by Delong Zhang, Chunyang Jin, Zhidong Zhang, Xiyuan Cao, Chenyang Xue

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Social Network Analysis: A Novel Paradigm for Improving Community Detection by Rodrigo Hernández, Inmaculada Gutiérrez, Javier Castro

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Recognition of Human Activities Based on Ambient Audio and Vibration Data by Marcel Koch, Thomas Pfitzinger, Fabian Schlenke, Fabian Kohlmorgen, Roland Groll, Hendrik Wohrle

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Graph Contrastive Pre-training for Anti-money Laundering by Hanbin Lu, Haosen Wang

“…Abstract Anti-money laundering (AML) is vital to maintaining financial markets, social stability, and political authority. At present, many studies model the AML task as the graph and leverage graph neural network (GNN) for node/edge classification. …”
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A Novel Approach Based on Hypergraph Convolutional Neural Networks for Cartilage Shape Description and Longitudinal Prediction of Knee Osteoarthritis Progression by John B. Theocharis, Christos G. Chadoulos, Andreas L. Symeonidis

“…The predictor includes spatial <i>HGCN</i> convolutions, attention-based temporal fusion of feature embeddings at multiple layers, and a transformer module that generates longitudinal predictions at follow-up times. We present comprehensive experiments on the Osteoarthritis Initiative (<i>OAI</i>) cohort to evaluate the performance of our methodology for various tasks, including node classification, longitudinal <i>KL</i> grading, and progression. …”
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Spatiotemporal optimization for communication-navigation-sensing collaborated emergency monitoring by Xicheng Tan, Bocai Liu, Chaopeng Li, Zeenat Khadim Hussain, Kaiqi Wang, Kai Wang, Mengyan Ye, Danyang Yang, Zhiyuan Mei

“…This work has three main components: (1) a neural network-based geospatial fitting model for ANET communication, (2) a ResNet based spatiotemporal feature and CNS node fusion encoding method for state space construction for reinforcement learning, and (3) a deep reinforcement learning algorithm called ResNet-DDPG for deploying ground ANET nodes dynamically. …”
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Artificial Intelligence and Radiomics in Cholangiocarcinoma: A Comprehensive Review by Marta Zerunian, Tiziano Polidori, Federica Palmeri, Stefano Nardacci, Antonella Del Gaudio, Benedetta Masci, Giuseppe Tremamunno, Michela Polici, Domenico De Santis, Francesco Pucciarelli, Andrea Laghi, Damiano Caruso

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The songbird connectome (OSCINE-NET.ORG): structure–function organization beyond the canonical vocal control network by Andrew Savoy, Katherine L. Anderson, Joseph V. Gogola

“…Thus, a more comprehensive understanding of brain-wide connectivity is essential to further assess the totality of circuitry underlying this complex learned behavior. Results We present the Oscine Structural Connectome for Investigating NEural NETwork ORGanization (OSCINE-NET.ORG), the first interactive mesoscale connectome for any vocal learner. …”
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Indian SUMO traffic scenario-based misbehaviour detection dataset for connected vehicles by Umesh Bodkhe, Sudeep Tanwar

“…Finally, we compare the AhmST dataset with recent datasets, assess the proposed dataset using various machine learning techniques and present an optimized model with improved accuracy.…”
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ReAHGN: Adaptive Heterogeneous Graph Neural Network With Relation-Aware Embedding by Xiaoyu Zhu, Xinzhe Yu, Enze Zha, Shiyang Lin

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A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines by Mustafa COBAN, Gokhan GELEN

“…The presented approach uses the decentralized node-based approach to reduce computational complexity. …”
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Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks by Guo Li, Hongyu Sheng

“…This study presents a machine learning-based approach to forecast Allocative Localization Error (ALE) in Wireless Sensor Networks (WSNs), addressing challenges such as dynamic network topologies and resource constraints. …”
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