CBGS-YOLO: A Lightweight Network for Detecting Small Targets in Remote Sensing Images Based on a Double Attention Mechanism by Zhenyuan Wu, Di Wu, Ning Li, Wanru Chen, Jie Yuan, Xiangyue Yu, Yongqiang Guo

“…Hence, in this paper, we propose a lightweight remote-sensing image target detection network model, CBGS-YOLO, created by introducing the Ghost module to decrease the model parameters, applying the SPD-Conv module to optimize downsampling, and integrating the convolutional block attention module to enhance detection accuracy. …”
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Impact of Land Use Change on Carbon Storage Dynamics in the Lijiang River Basin, China: A Complex Network Model Approach by Xinran Zhou, Jinye Wang, Liang Tang, Wen He, Hui Li

“…The paper finds that (1) land use transformation in the basin exhibits spatial heterogeneity and network complexity, as evidenced by a significant negative correlation between the node clustering coefficient and the average path length, revealing that land type transitions possess small-world network characteristics. (2) The forested land experienced a net decrease of 196.73 km² from 2001 to 2021, driving a 3.03% decline in carbon storage. …”
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Hybrid causal inference framework for long-chain drought propagation networks: Combining convergent cross-mapping and generalized random forest by Jiayou Wang, Zhi Li, Yaning Chen, Shiru Han, Lingxin Kong

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Incremental dynamic community discovery algorithm based on multi-core nodes by Jing CHEN, Zhijun LIU, Xinyu YANG, Mingxin LIU, Miaomiao LIU

“…A new incremental dynamic community discovery algorithm MCNIDCD based on multiple core nodes was proposed to address challenges in dynamic community discovery.It adapted to sudden events like the emergence or disappearance of communities during evolution.MCNIDCD categorized core nodes into diffusion and cohesion types, and devised four incremental updating strategies.It adjusted node community membership locally and optimized community structure using an incremental modularity method to facilitate community merging.Evaluation on artificial and real networks shows MCNIDCD’s high conformity to community evolution patterns.In real network experiments, MCNIDCD exhibits a 28% average improvement in modularity performance and significant stability advantages.Its superiority is important for studying dynamic community evolution.…”
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Investigating the InSAR Phase Bias in the SBAS Algorithm and Its Effect on Different Landcovers by Ebrahim Karami, Siavash Shami, Yasser Maghsoudi, Babak Ranjgar, Saeed Azadnejad

“…Additionally, various networks were processed to assess the amount of phase bias in the SBAS algorithm and to propose an optimal network for this algorithm. …”
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Investigation of Mechanical and Corrosion Behavior of ECAP Processed AA7075 Through ML, ANNW, RSM, and SA Methodologies by Majed Alinizzi, W. H. El‐Garaihy, A. I. Alateyah, Samar El‐Sanabary, Fahad Nasser Alsunaydih, Mansour Alturki, H. Abd El‐Hafez, Mohamed S. El‐Asfoury, Eman M. Zayed, Hanan Kouta

“…ABSTRACT This study employs a multi‐perspective modeling approach combining Response Surface Methodology (RSM), Machine Learning (ML), Artificial Neural Networks (ANNW), and Simulated Annealing (SA) to optimize Equal Channel Angular Pressing (ECAP) parameters for improving the mechanical and corrosion properties of AA7075 alloy. …”
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Rapid Prediction of High-Resolution 3D Ship Airwake in the Glide Path Based on CFD, BP Neural Network, and DWL by Qingsong Liu, Gan Ren, Dingfu Zhou, Bo Liu, Zida Li

“…Then, using the high spatial resolution ship airwake along the glide path obtained from steady RANS computations under different inflow conditions as a sample dataset, the BP neural network prediction models were trained and optimized. …”
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Enhancing the prediction of irrigation demand for open field vegetable crops in Germany through neural networks, transfer learning, and ensemble models by Samantha Rubo, Jana Zinkernagel

“…Precise irrigation management in vegetable production is key for optimizing water use and ensuring crop productivity. …”
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Hybrid machine learning techniques for knowledge extraction in communication networks and advanced decision based complex q-Rung orthopair fuzzy frameworks by Hushuang Zeng, Yonghua Zhang

“…Abstract Hybrid machine learning techniques for knowledge extraction in communication networks combine the strengths of multiple learning algorithms to analyze complex, high-dimensional, and dynamic network data effectively. …”
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Combined State-of-Charge Estimation Method for Lithium-Ion Batteries Using Long Short-Term Memory Network and Unscented Kalman Filter by Long Pu, Chun Wang

“…To address these challenges, this study introduces a combined UKF-LSTM algorithm that integrates a long short-term memory (LSTM) network with the UKF for the precise SOC estimation of LIBs. …”
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Efficient resource allocation in cloud environment using SHO-ANN-based hybrid approach by Sanjeev Sharma, Pradeep Singh Rawat

“…This manuscript proposes a hybrid Spotted Hyena optimizer and artificial neural network, named the SHO-ANN technique, to provide a solution to the virtual machine assignment problem. …”
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Designing metal halide-based road illumination systems in developing countries using regression and neural networksThe dataset is available through this link by Sourin Bhattacharya, Khondekar Lutful Hassan, Pallav Dutta

“…Through extensive photometric simulation and data analysis, this study provides useful insights for the commissioning of road lighting projects especially pertaining to the usefulness of ANN models for the planning and optimization of public road illumination systems in developing countries.…”
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Edge-driven resource allocation in vehicular networks: A joint framework of multi-agent reinforcement learning and demand-supply predictive modeling by Dhinesh Kumar R, Rammohan A

“…This decentralized and adaptive approach focuses on enhancing the packet transfer ratio for Vehicle-to-Vehicle (V2V) links while improving the sum capacity for Vehicle-to-Infrastructure (V2I) links. To further optimize resource allocation, a trained Long Short-Term Memory (LSTM) network is deployed at the edge to predict the next state of the vehicular network. …”
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Robust topology construction method with radio interface constraint for multi-radio multi-channel wireless mesh network using directional antennas by Xuecai Bao, Longzhe Han, Chengzhi Deng, Hai Zhang, Wenqun Tan

“…Multi-radio and multi-channel wireless mesh networks using directional antenna (MR-MC DWMN) greatly improve the spatial reuse of wireless channels and increase network capacity. …”
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A Temporal Attention-Based SARIMA-BiLSTM Residual Learning Model Tuned by Grey Wolf Optimizer for Parallel Urban Traffic Forecasting by Manas Kamal Das, Christopher Columbus Chinnappan, E. Elakiya

“…In this study, a novel hybrid residual learning framework is proposed that integrates Seasonal Autoregressive Integrated Moving Average (SARIMA) with a Bidirectional Long Short-Term Memory (BiLSTM) network enhanced by a temporal attention mechanism. …”
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A spatial clustering-based approach to design monitoring networks of infectious diseases: a case study of hand, foot, and mouth disease by Shuting Li, Yuanhua Liu, Ke Li, Zengliang Wang, Michael P. Ward, Wei Tu, Jiayao Xu, Rui Yuan, Lele Zhang, Na Wang, Jidan Zhang, Yu Zhao, Henry S. Lynn, Zhaorui Chang, Zhijie Zhang

“…Second, we applied the cost–benefit balance to determine the optimal sample size. Third, we performed simple random sampling within each stratum to establish an initial monitoring network. …”
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Energy, Traffic Load, and Link Quality Aware Ad Hoc Routing Protocol for Wireless Sensor Network Based Smart Metering Infrastructure by Hasan Farooq, Low Tang Jung

“…Smart meters, in addition to their primary billing functions, serve as distributed Wireless Sensor Network (WSN) nodes for enhancing grid reliability. …”
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Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…To mitigate those issues, we explored a gamut of architectural options of the Pix2Pix-based conditional generative adversarial network (cGAN) analyzing objective functions, optimizers, activation, and normalization layers. …”
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Integrated transmission expansion planning incorporating fault current limiting devices and thyristor-controlled series compensation using meta-heuristic optimization techniques by Abdulaziz Almalaq, Khalid Alqunun, Rabeh Abbassi, Ziad M. Ali, Mohamed M. Refaat, Shady H. E. Abdel Aleem

“…This paper presents a comprehensive study on the application of ten recent meta-heuristic algorithms for solving the TEP problem across three distinct power networks varying in scale. The ten meta-heuristic algorithms considered in this study include Sinh Cosh Optimizer, Walrus Optimizer, Snow Geese Algorithm, Triangulation Topology Aggregation Optimizer, Electric Eel Foraging Optimization, Kepler Optimization Algorithm (KOA), Dung Beetle Optimizer, Sea-Horse Optimizer, Special Relativity Search, and White Shark Optimizer (WSO). …”
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Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state by Aydin Larestani, Sara Sahebalzamani, Abdolhossein Hemmati-Sarapardeh, Ali Naseri

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