Non – Invasive, smartphone image-based screening for sickle cell disease at the point-of-need by Eudorah F. Vital, Meredith Haak LiCalzi, Robert G. Mannino, Patrick T. McGann, Wilbur A. Lam

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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

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Commodity Price Recognition and Simulation of Image Recognition Technology Based on the Nonlinear Dimensionality Reduction Method by Yongbin Liu, Jingjie Wang, Wei Bai

“…Although some traditional algorithms have achieved some results in the process of dimensionality reduction, they also expose their respective defects. …”
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Estimation and Reduction of CO₂ Emissions From Fossil Fuel Power Plants in Bangladesh by Deepak Kumar Chowdhury, Nur Mohammad, Tanjim Mahmud, Md. Khaliluzzaman, Karl Andersson, Mohammad Shahadat Hossain

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Advanced Deep Learning Algorithms for Energy Optimization of Smart Cities by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Adrianna Piszcz

“…These algorithms analyze real-time data from sensors and IoT devices to predict energy demand, enabling dynamic load balancing and reducing waste. …”
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Modeling Analysis of the Relationship between Adolescent Aerobic Exercise and Obesity Reduction Based on Deep Learning by Peng Mu

“…In order to explore the modeling analysis of the relationship between adolescent aerobic exercise and obesity reduction, the relationship modeling method of deep learning algorithm is proposed. …”
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Enhancing Residential Electricity Consumption Forecasting with Meta-Heuristic Algorithms by Milad Mohebbi, Behnam Sobhani

“…This study explores optimizing Artificial Neural Network (ANN) parameters using meta-heuristic algorithms instead of traditional gradient-based methods to predict residential electricity consumption across different seasons. …”
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Supercontinuum Generation in Suspended Core Fibers Based on Intelligent Algorithms by Meiqian Jing, Tigang Ning

“…A high-nonlinearity SCF structure (γ ≈ 6–7 W⁻¹·m⁻¹) was first designed, and a neural network model was developed to accurately predict effective modal refractive indices and mode-field areas (RMSE < 1%). …”
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Financial engineering and the digital economy: The implementations of machine learning algorithms by Pingping Fu, Honghao Yang, Wenhao Qian, ELsiddig Idriss Mohamed, Wafa Ali J. Almohri, Huda M. Alshanbari

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Finding Random Integer Ideal Flow Network Signature Algorithms by Kardi Teknomo, Erna Budhiarti Nababan, Indriati Njoto Bisono, Resmana Lim

“… We propose a Random Integer Ideal Flow Network (IFN) Signature Algorithm that generates integral flow assignments in strongly connected directed graphs under uncertainty. …”
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Application of the metaheuristic algorithms to quantify the GSI based on the RMR classification by Pouya Koureh Davoodi, Farnusch Hajizadeh, Mohammad Rezaei

“…This study addresses this challenge by analyzing data from fourteen different rock types and employing three metaheuristic optimization algorithms, namely Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Grey Wolf Optimization (GWO), to develop predictive models for quantifying GSI based on the RMR. …”
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Microservice Deployment Based on Multiple Controllers for User Response Time Reduction in Edge-Native Computing by Zhaoyang Wang, Jinqi Zhu, Jia Guo, Yang Liu

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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…A low-carbon, economic dispatch method for IES using an enhanced wind power scenario reduction algorithm is introduced in this paper. It employs an improved iterative self-organizing data analysis technique algorithm (ISODATA) for clustering historical wind power scenarios, addressing the limitations of traditional clustering algorithms in determining cluster centers and analyzing inherent data features. …”
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Optimizing circular antenna arrays with artificial rabbits optimization for beam control and side lobe reduction by Sunil Kumar, Harbinder Singh, Avtar Singh

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Merging Multiple System Perspectives: The Key to Effective Inland Shipping Emission-Reduction Policy Design by Solange van der Werff, Fedor Baart, Mark van Koningsveld

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Prediction Analysis of Pre-Camber for Continuous Girder Bridge Cantilever Casting Construction Based on DBO-CNN-BiLSTM-Attention Neural Network by Jinyang Zhang, Haiqing Liu, Xiangen Gong, Ming Lei, Zimu Chen

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Provident garbage collection algorithm for SSD storage system by Xuezhen TU, Zhenjiang Huang, Zhengguang CHEN

“…A predictive based proactive garbage collection algorithm was proposed.Firstly,the data was separated according to different heat factors,then the upper and lower predictions were performed on the number of different types of page allocation requests (PAR) that would be reached in the future.While satisfying the page allocation request lower prediction,the PAR upper prediction requirement was maximally satisfied,the WA problem was optimized,and invalid effective data migration was reduced,thereby maximizing the garbage collection utility.A mathematical model was defined for this problem,and an algorithm for obtaining the approximate optimal solution was given.The applicable scenario of the model was analyzed.The practical results show that the algorithm can obtain the maximum benefit and can significantly improve the performance of SSD and reduce the cost.…”
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Algorithm for optimization of cold‑rolled pipe rolling routes by S. V. Pilipenko

“…Among the latter, the maximum possible reduction in the cross‑sectional area, the required reduction in the cross‑sectional area in the last pass, the requirement for the nature of the distribution of the reduction value in the cross‑sectional area, in the wall thickness and in the pipe diameter from pass to pass and other parameters are highlighted. …”
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FM‐YOLOv8:Lightweight gesture recognition algorithm by Fanghai Li, Xitai Na, Jinshuo Shi, Qingbin Sun

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An efficient parallel DCNN algorithm in big data environment by Yimin Mao, Yaser Ahangari Nanehkaran, Neelakandan Chandrasekaran, Ying Huo, Zhan Qing Wen, ke Gong, Miao Decheng

“…Big data plays a vital role in developing remote sensing, landslide prediction, and enabling applications, the integration of deep convolutional neural networks (DCNN) has significantly improved its prediction accuracy. …”
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