Fog Service Placement Optimization: A Survey of State-of-the-Art Strategies and Techniques by Hemant Kumar Apat, Veena Goswami, Bibhudatta Sahoo, Rabindra K. Barik, Manob Jyoti Saikia

“…In such scenarios, finding the optimal computing node for processing and executing the service is a challenge. …”
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Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining by Yuxin You, Zhen Liu, Xiangchao Wen, Yongtao Zhang, Wei Ai

“…Graph mining is an important area in data mining and machine learning that involves extracting valuable information from graph-structured data. …”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…This framework is based on a two-sided game, enabling each layer to express its individual preferences for node allocation while allowing nodes to prioritize their preferred layers. …”
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Guided Decision Tree: A Tool to Interactively Create Decision Trees Through Visualization of Subsequent LDA Diagrams by Miguel A. Mohedano-Munoz, Laura Raya, Alberto Sanchez

“…Decision trees are a widely used machine learning technique due to their ease of interpretation and construction. …”
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QoS and Energy Aware Cooperative Routing Protocol for Wildfire Monitoring Wireless Sensor Networks by Mohamed Maalej, Sofiane Cherif, Hichem Besbes

“…In this paper, we use the technique of reinforcement learning by opponent modeling, optimizing a cooperative communication protocol based on RSSI and node energy consumption in a competitive context (RSSI/energy-CC), that is, an energy and quality-of-service aware-based cooperative communication routing protocol. …”
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Deployment Support for Sensor Networks in Indoor Climate Monitoring by Jaeseok Yun, Jaeho Kim

“…In this paper, we present a novel method of placing and minimizing sensor nodes for sensor networks in smart energy systems. …”
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GNN for LoRa Device Fingerprint Identification by Bojun Zhang

“…This paper presents a deep learning-based system for the classification and identification of LoRa signals. …”
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A Prediction Algorithm for Coexistence Problem in Multiple-WBAN Environment by Zilong Jin, Yoonjeong Han, Jinsung Cho, Ben Lee

“…Since a WBAN handles vital signs that affect human life, the detection or prediction of coexistence condition is needed to guarantee reliable communication for each sensor node of a WBAN. Therefore, this paper presents a learning-based algorithm to efficiently predict the coexistence condition in a multiple-WBAN environment. …”
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Enhanced Location Prediction for Wargaming with Graph Neural Networks and Transformers by Dingge Liang, Junliang Li, Junping Yin

“…By capturing complex inter-node relationships, our model effectively reduces the impact of data repetition and sparsity, achieving robust location predictions in dynamic and sparse wargaming environments. …”
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Enhanced Feature Selection via Hierarchical Concept Modeling by Jarunee Saelee, Patsita Wetchapram, Apirat Wanichsombat, Arthit Intarasit, Jirapond Muangprathub, Laor Boongasame, Boonyarit Choopradit

“…The presented methods are evaluated based on all learned attributes with 10 datasets from the UCI Machine Learning Repository by using three classification algorithms, namely decision trees, support vector machines (SVM), and artificial neural networks (ANN). …”
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SOFTWARE IMPLEMENTATION OF THE ARTIFICIAL NEURAL NETWORK FOR VIRTUAL OBJECTS СONTROL by Yu. B. Popova, S. V. Yatsynovich

“…The paper deals with the mathematical modeling of an artificial neural network by the method of back propagation of an error, the algorithms for calculating neurons and for teaching ANN are presented. The software implementation of the artificial neural network was performed in the JavaScript language using the Node. js library, which assumed the role of a server for managing the game process. …”
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Fog Computing Architecture for Load Balancing in Parallel Production with a Distributed MES by William Oñate, Ricardo Sanz

“…As basic and advanced technologies from the pillars of Industry 4.0 are gradually incorporated into their value chain, these factories can achieve adaptive technological transformation. This article presents a practical solution for companies seeking to evolve their production processes during the expansion phase of their manufacturing, starting from a base architecture with Industry 4.0 features which then integrate and implement specific tools that facilitate the duplication of installed capacity; this creates a situation that allows for the development of manufacturing execution systems (MESs) for each production line and a fog computing node, which is responsible for optimizing the load balance of order requests coming from the cloud and also acts as an intermediary between MESs and the cloud. …”
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Corporate governance network around social responsibility and activism against the Sustainable Development Goals by Julio E. Crespo, Cruz García Lirios, Sonia Sujell Vélez Báez, Isabel Cristina Rincón Rodríguez, Jorge E. Chaparro Medina, Víctor Hugo Meriño Córdoba, Arturo Sánchez Sánchez, Celia Yaneth Quiroz Campas, María del Rosario Molina González

“…The results reveal the financial category as the only discrepancy, with the present work considering it as an external factor to corporate governance, unlike the state-of-the-art literature that highlights it as a central node. …”
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Rumor detection using dual embeddings and text-based graph convolutional network by Barsha Pattanaik, Sourav Mandal, Rudra M. Tripathy, Arif Ahmed Sekh

“…These embeddings serve as node representations within the graph, enhancing rumor detection. …”
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StyleGraph: A Heterogeneous Graph Neural Framework for Stylistic and Semantic Rumor Detection on Social Media by Haider Jaffar, Ali Mohades, Mohammad Ebrahim Shiri

“…The growing prevalence of deceptive content presents a significant challenge that necessitates advanced detection techniques, beyond classical machine learning. …”
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GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data by Zeyu Fu, Chunlin Chen, Song Wang, Junping Wang, Shilei Chen

“…Current methods struggle to simultaneously preserve global structure, model cellular dynamics, and handle technical noise effectively. Results We present GNODEVAE, a novel architecture integrating Graph Attention Networks (GAT), Neural Ordinary Differential Equations (NODE), and Variational Autoencoders (VAE) for comprehensive single-cell analysis. …”
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Separating Repeating Fast Radio Bursts Using the Minimum Spanning Tree as an Unsupervised Methodology by C. R. García, Diego F. Torres, Jia-Ming Zhu-Ge, Bing Zhang

“…By constructing MSTs based on various combinations of variables, we identify those that lead to MSTs that exhibit a localized high density of repeaters at each side of the node with the largest betweenness centrality. Comparing the separation power of this methodology against known machine learning methods, and with the random expectation results, we assess the efficiency of the MST-based approach to unravel the physical implications behind the graph pattern. …”
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Condition monitoring of heterogeneous landslide deformation in spatio-temporal domain using advanced graph attention network by Huajin Li, Yu Zhu, Qiang Xu, Ran Tang, Chuanhao Pu, Yusen He

“…This research aims to develop an enhanced spatial-temporal monitoring system capable of capturing these complex deformation patterns. In this study, it presents a novel Graph Attention Network (GAT) framework that integrates multi-scale temporal embeddings, adaptive graph learning, and temporal self-attention mechanisms to simultaneously track localized stability variations and global deformation trends across monitoring points. …”
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Resting-state brain activation patterns and network topology distinguish human sign and goal trackers by Martino Schettino, Marika Mauti, Chiara Parrillo, Ilenia Ceccarelli, Federico Giove, Antonio Napolitano, Cristina Ottaviani, Marialuisa Martelli, Cristina Orsini

“…Abstract The “Sign-tracker/Goal-tracker” (ST/GT) is an animal model of individual differences in learning and motivational processes attributable to distinctive conditioned responses to environmental cues. …”
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Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data by Maoyue Zhang

“…With reference to image-based big data, this research integrates the application of artificial intelligence facial expression recognition technology with the research on educational theory and applies information technology to the actual teaching process, in order to promote the optimization of the teaching process and improve the learning effect. Method. A Hadoop cluster consisting of 3 nodes is built on the Linux system, and the environment required for Opencv execution is compiled for each node, which provides support for subsequent parallel optimization, feature extraction, feature fusion, and recognition of student facial images. …”
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