Predicting Olympic Medal Performance for 2028: Machine Learning Models and the Impact of Host and Coaching Effects by Zhenkai Zhang, Tengfei Ma, Yunpeng Yao, Ningjia Xu, Yujie Gao, Wanwan Xia

“…An ARIMA model predicts the factor coefficients for 2028 as 0.9539, 0.7999, and 0.2937, respectively. Four models (random forest, BP Neural Network, XGBoost, and SVM) are employed to predict medal outcomes, using historical data split into training and testing sets to compare their predictive performance. …”
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Optimization and Numerical Verification of Microseismic Monitoring Sensor Network in Underground Mining: A Case Study by Chenglu Hou, Xibing Li, Yang Chen, Wei Li, Kaiqu Liu, Longjun Dong, Daoyuan Sun

“…To evaluate and validate the monitoring effectiveness of the sensor networks, three layers of seismic sources were randomly generated within the network. …”
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Integrating Digital Twins and Artificial Intelligence Multi-Modal Transformers into Water Resource Management: Overview and Advanced Predictive Framework by Toqeer Ali Syed, Muhammad Yasar Khan, Salman Jan, Sami Albouq, Saad Said Alqahtany, Muhammad Tayyab Naqash

“…We critically analyze the existing literature on artificial neural networks (ANNs), deep learning (DL), long short-term memory (LSTM) networks, machine learning (ML) models such as supervised learning (SL) and unsupervised learning (UL), and random forest (RF). In response, we propose a novel framework that synergizes these techniques into a unified, multi-layered model and incorporates a digital twin and a multi-modal transformer approach. …”
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Intelligent Identification and Prediction of Roof Deterioration Areas Based on Measurements While Drilling by Jing Wu, Zhi-Qiang Zhao, Xiao-He Wang, Yi-Qing Wang, Xiao-Xiang Wei, Zhi-Qiang You

“…During roadway excavation, the presence of roof deterioration zones, such as layered spaces and weak interlayers, significantly affects the stability of the surrounding rock. …”
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Hybrid Deep Learning Approach for Automated Sleep Cycle Analysis by Sebastián Urbina Fredes, Ali Dehghan Firoozabadi, Pablo Adasme, David Zabala-Blanco, Pablo Palacios Játiva, Cesar A. Azurdia-Meza

“…This study presents a hybrid neural network architecture composed of convolutional neural network (CNN) layers, bidirectional long short-term memory (BiLSTM) layers, and attention mechanism layers in order to process large volumes of EEG data in PSG files. …”
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Comparative analysis of deep learning and traditional methods for IoT botnet detection using a multi-model framework across diverse datasets by Saeed Ullah, Junsheng Wu, Zhijun Lin, Mian Muhammad Kamal, Hala Mostafa, Muhammad Sheraz, Teong Chee Chuah

“…This study focuses on traditional machine learning and deep learning approaches, proposes a novel ensemble framework to address these issues, integrating Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM), Random Forest (RF), and Logistic Regression (LR) via a weighted soft-voting mechanism. …”
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A novel method based on improved SFLA for IP information extraction from TEM signals by Ruiyou Li, Ruiheng Li, Guang Li, Yong Zhang, Xiaohui Ding, Long Zhang

“…Then, an adaptive mobile factor is designed to replace the random operator, balancing local and global searches. …”
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Estimating Iranian Professional Football Players' Prices A Neural Networks Approach by Mehdi Salimi, Mohsen Tayebi, Amir Hossein Labbaf

“…In the quantitative section, the statistical population had all the football players in the Iranian Football Professional League during 2016-2020, and random sampling was done. So, 863 players were selected to use their data for analysis. …”
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Securing air defense visual information with hyperchaotic Folded Towel Map-Based encryption by Shamsa Kanwal, Saba Inam, Fahima Hajjej, Ala Saleh Alluhaidan

“…The proposed image encryption is a multi-layered procedure intended to secure image transmission. …”
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Error-correcting codes and genetics by Gérard Battail

“…., that several codes are combined into a layered structure which results in an unequal protection: the older and more fundamental parts of the genomic information are better protected than more recent ones. …”
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Lidar Simultaneous Localization and Mapping Algorithm for Dynamic Scenes by Peng Ji, Qingsong Xu, Yifan Zhao

“…To preserve more static feature points without altering the original point cloud, the Random Sample Consensus (RANSAC) ground fitting algorithm is employed to fit and segment the ground point cloud within the dynamic regions, followed by the removal of dynamic obstacles. …”
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Laor Initialization: A New Weight Initialization Method for the Backpropagation of Deep Learning by Laor Boongasame, Jirapond Muangprathub, Karanrat Thammarak

“…The results indicate that the Laor Initialization achieved the lowest K-fold cross-validation RMSE (0.00686), surpassing Xavier, He, and Random. Laor demonstrated a high convergence success (final RMSE = 0.00822) and the narrowest interquartile range (IQR), indicating superior stability. …”
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Diagnosis and classification of neuromuscular disorders using Bi-LSTM optimized with grey Wolf optimizer for EMG signals by Ruth Keziah Mani, Balakrishnan Nagaraj

“…Existing approaches range from deep learning techniques such as Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM) to conventional machine learning methods like Support Vector Machines (SVM) and Random Forest. Deep learning automates the process, reducing the dependency on manual feature extraction. …”
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Federated Deep Learning Model for False Data Injection Attack Detection in Cyber Physical Power Systems by Firdous Kausar, Sambrdhi Deo, Sajid Hussain, Zia Ul Haque

“…The results demonstrate that Bidirectional GRU and LSTM models with attention layers in a federated learning setup achieve superior performance, with accuracy approaching 99.8%. …”
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Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception–ResNet Model by Md. Ahasan Kabir, Ivan Lee, Sang-Heon Lee

“…The Lightweight 3D Inception–ResNet model, with 381 layers, offers a computationally efficient alternative suitable for real-time industrial applications. …”
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Fidelity to territory and mate and the causes and consequences of breeding dispersal in American goshawk (Astur atricapillus). by Richard T Reynolds, Shannon L Kay, Jeffrey S Lambert, Martha Ellis

“…Despite equivocal evidence of dispersal to territories more frequently occupied by egg-layers, there was otherwise little evidence that hawks on average dispersed to better territories. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…The architecture is composed of multiple convolutional and pooling layers, ensuring both depth and performance efficiency. …”
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Vitamin D Deficiency Prevalence in Pakistan: Common, Important, and Neglected: A Comprehensive Meta-Analysis by Benazir Mahar, Tazeen Shah, Noma Sadiq, Rozina Mangi, Jamshed Warsi, Qamar Abbas

“…They were combined with the random-effect method. Out of 429 articles, 37 studies, with a total sample size of 19,338, were selected for the final analysis. …”
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Evaluation of the C-reactive protein serum levels in periodontitis patients with or without atherosclerosis – A clinical study by Pooja Khatri, Kaustubh S Thakare, Minal Narendra Ganvir, Mitesh Khatri

“…Atherosclerosis is a progressive arterial disease that is characterized by the thickening of subintimal layers in muscular and elastic arteries of intermediate-to-large size due to the accumulation of athermanous plaque. …”
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A Hierarchical Cache Architecture-Oriented Cache Management Scheme for Information-Centric Networking by Yichao Chao, Rui Han

“…Information-Centric Networking (ICN) typically utilizes DRAM (Dynamic Random Access Memory) to build in-network cache components due to its high data transfer rate and low latency. …”
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