ECG-GraphNet: Advanced arrhythmia classification based on graph convolutional networks by Myeonghun Lee, BS, Jiwoo Lim, MS, JinKook Kim, MS

“…Objective: We propose Electrocardiogram Graph Convolutional Network (ECG-GraphNet), a graph convolutional network designed to classify arrhythmias into 3 types: normal (N), supraventricular ectopic (S), and ventricular ectopic (V) beats. …”
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Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

“…The experiment verifies that algorithm has been optimized by an average of 8.85%, 15.51%, and 17.03% in terms of transmission success rate, convergence delay ratio, and load balancing compared to the IGAGCT algorithm and RBDQN algorithm, and 10.41%, 16.5%, and 16.81%, respectively from three aspects: heterogeneous request success rate, algorithms convergence delay rate, and load error rate of computing first networks.…”
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A Secure and Green Cognitive Routing Protocol for Wireless Ad-Hoc Networks by Muhammad Saqib Javed, Rana Abu Bakar

“…We propose an efficient and intelligent Cognitive (COG) Protocol to address routing issues and ensure optimized and secure routing. Our proposed protocol is based on cognitive behavior and utilizes the extension header field of IPv6 for route selection in wireless ad hoc networks. …”
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Predicting Soft Soil Settlement with a FAGSO-BP Neural Network Model by Binhui Ma, Yarui Xiao, Tian Lan, Chao Zhang, Zengliang Wang, Zeshi Xiang, Yuqi Li, Zijing Zhao

“…Aiming at the problem that it is difficult to consider the prediction of foundation settlement in the case of multi-parameter coupling effect by theoretical formulas and numerical analysis, the fireworks algorithm with gravitational search operator (FAGSO) is introduced into the BP neural network model, and the FAGSO algorithm aims to enhance the neural network’s weight and threshold adjustment process; so, a new soft ground settlement prediction model was developed which uses a fireworks algorithm integrated with a gravitational search operator to optimize a BP neural network (referred to as FAGSO-BP). …”
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A Self-Supervised Adversarial Deblurring Face Recognition Network for Edge Devices by Hanwen Zhang, Myun Kim, Baitong Li, Yanping Lu

“…The model employs a generative adversarial network (GAN) as the core algorithm, optimizing its generation and recognition modules by decomposing the global loss function and incorporating a feature pyramid, thereby solving the balance challenge in GAN training. …”
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Efficient Integration of Reinforcement Learning in Graph Neural Networks-Based Recommender Systems by Abdurakhmon Sharifbaev, Mikhail Mozikov, Hakimjon Zaynidinov, Ilya Makarov

“…Although RL has been applied in recommendation systems, the integration of graph neural networks (GNNs) within this framework remains underexplored. …”
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Multi-scale cross-layer fusion and center position network for pedestrian detection by Qian Liu, Youwei Qi, Cunbao Wang

“…We add a center position branch into the localization regression sub-network in MCF-CP-NET to better detect occluded pedestrians, which predicts the centrality index of the localization box to obtain the center score, and further optimizes the score of non-maximum suppression. …”
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Prenatal Self-Evaluation Questionnaire in Peruvian Women: Analysis Through the Psychometric Network by Antonio Serpa-Barrientos, Juan Jose Gabriel Artica Martinez, Enrique Giovanni Pérez-Flores, Jacksaint Saintila

“…Results: The results obtained revealed the presence of a network structure consisting of five dimensions. These dimensions showed stability levels (0.70) and optimal average loads (0.15), supporting the idea that Lederman designed the prenatal self-evaluation questionnaire be composed of five different dimensions. …”
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Spatio-Temporal Graph Neural Networks for Streamflow Prediction in the Upper Colorado Basin by Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

“…This study presents a spatio-temporal graph neural network (STGNN) model for streamflow prediction in the Upper Colorado River Basin (UCRB), integrating graph convolutional networks (GCNs) to model spatial connectivity and long short-term memory (LSTM) networks to capture temporal dynamics. …”
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APPLICATION OF ARTIFICIAL NEURON NETWORK AND FUZZY INFERENCE IN THE HOUSEPLANT WATERING INTELLIGENT SYSTEM by Roman Korostenskyi, Igor Olenych

“…The proposed approach ensures an optimal soil moisture level of 50–60%, suitable for plant growth and development, while also reducing the average monthly water consumption by 25–27%. …”
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Integration of Convolutional Neural Network and Image Processing for Pulp Fibril Detection and Measurement by Tanachot Chirakitsakul, Pakaket Wattuya, Phichit Somboon, Panthira Jansakra, Chakrit Watcharopas

“…The fibrillation index is a critical metric in paper manufacturing, quantifying the degree of fibrillation achieved during the pulp refining process. Optimizing this metric enhances both paper quality and production efficiency. …”
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Evaluation of Network Design and Solutions of Fisheye Camera Calibration for 3D Reconstruction by Sina Rezaei, Hossein Arefi

“…The robust calibration solution is a two-step calibration process, including a pre-calibration stage and the consideration of the best possible network design. Fisheye undistortion was performed using OpenCV, and finally, calibration parameters were optimized with self-calibration through bundle adjustment to achieve both calibration parameters and 3D reconstruction using Agisoft Metashape software. …”
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Modified MCP-Based Modeling and Performance Analysis of 3-D Cellular Networks by Dorsaf Ghozlani, Aymen Omri, Seifeddine Bouallegue, Hela Chamkhia, Ridha Bouallegue

“…This innovative approach results in the development of a tractable analytical framework, which includes a detailed assessment of the non-interference probability, thereby optimizing resource allocation strategies across the network. …”
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Machine learning anomaly detection of lost and unaccounted for gas in natural gas networks by Omar Fayez Mohamed ElMahdy, Mohamed Ezz Hassan, Sayed M. Metwalli

“…Abstract Minimizing gas losses has become a crucial factor in optimizing the utilization of energy resources. Multiple factors contribute to the complexity of distinguishing between normal gas loss and anomalous behavior within the gas network. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…The YOLOv5 deep learning network structure is enhanced by improving convolutional blocks, incorporating attention mechanisms, and optimizing loss function processing, boosting the detector's overall performance in accurately capturing the motion of particles over short distances. …”
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Analysis of Factors Affecting the Spatial Association Network of Food Security Level in China by Chuansong Zhao, Chunxia Li, Jianxu Liu, Haixia Lian, Woraphon Yamaka

“…This paper investigates the spatial interrelationship of food security levels in China through a network analysis framework, examining its determinants and network dynamics. …”
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Optimization and Machine Learning in Modeling Approaches to Hybrid Energy Balance to Improve Ports’ Efficiency by Helena M. Ramos, João S. T. Coelho, Eyup Bekci, Toni X. Adrover, Oscar E. Coronado-Hernández, Modesto Perez-Sanchez, Kemal Koca, Aonghus McNabola, R. Espina-Valdés

“…AI-based ML analysis was applied to five scenarios (the ones with access to numerical results), accurately predicting energy balances and optimizing grid interactions. A neural network time series (NNTS) model trained on average year data achieved high accuracy (R²: 0.9253–0.9695). …”
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Dimensionality reduction for groundwater forecasting under drought and intensive irrigation with neural networks by Tarik Bouramtane, Ismail Mohsine, Nourelhouda Karmouda, Marc Leblanc, Yannick Estève, Ilias Kacimi, Mohamed Hilali, Salima Mdhaffar, Sarah Tweed, Mounia Tahiri, Nadia Kassou, Ali El Bilali, Omar Chafki

“…Study Region: This study focuses on the Berrechid aquifer system in northern Morocco.Study Focus: The research explores Principal Component Analysis (PCA) for optimizing input selection in groundwater level forecasting using neural networks. …”
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RIS partitioning and UAV selection for age-of-information optimization in RIS-assisted UAV communications by Juseoung Lee, Jaewoo So

“…Simulation results show that the proposed DRL-based joint UAV selection and partition-based RIS allocation scheme outperforms all the other schemes without joint optimization in terms of the average AoI.…”
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Optimization complexity and resource minimization of emitter-based photonic graph state generation protocols by Evangelia Takou, Edwin Barnes, Sophia E. Economou

“…These patterns allow us to process large graphs and still achieve a reduction of up to 66% in emitter CNOTs, without relying on subtle metrics such as edge density. We find the optimal emission orderings and circuits to prepare unencoded and encoded repeater graph states of any size, achieving global minimization of emitter and CNOT resources despite the average NP-hardness of both optimization problems. …”
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