ParaU-Net: An improved UNet parallel coding network for lung nodule segmentation by Yingqi Lu, Xiangsuo Fan, Jinfeng Wang, Shaojun Chen, Jie Meng

“…ParaU-Net enhances the segmentation accuracy and model performance by optimizing the encoding process, improving feature extraction, preserving down-sampling information, and expanding the receptive field. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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Utility-driven virtual machine allocation in edge cloud environments using a partheno-genetic algorithm by Jie Cao, Cuicui Zhang, Ping Qi, Kekun Hu

“…Simulation results demonstrate that the proposed virtual machine allocation algorithm improves service utility by more than 20% compared to other virtual machine allocation algorithms, significantly enhancing service utility in edge cloud environments while maintaining robust QoS guarantees.…”
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Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…Experimental results demonstrate that compared with classical UNet, the optimized network achieves 2.05% and 2.58% improvements in F1-Score and IoU, respectively, while reducing the parameter count to 57.25% of the original model. …”
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High-efficiency MPPT Using ZVS quasi-resonant converter and PSO algorithm: Simulation and PIL validation by Souhail Barakat, Abdelouahed Mesbahi, Badr N’hili, Ayoub Nouaiti, Mohcine Abouyaakoub

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Analytical and Geometric Foundations and Modern Applications of Kinetic Equations and Optimal Transport by Cécile Barbachoux, Joseph Kouneiher

“…By bridging entropy dissipation, optimal transport, and geometric analysis, our work offers a new perspective on stability, convergence, and structure in high-dimensional kinetic models and applications.…”
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Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…Mathematical models of Barnacle Mating Optimization (BMO) are based on observations of real-world barnacle mating behaviors such as sperm casting and self-fertilization. …”
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Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Second, a two-stage hybrid algorithm is proposed for the problem model. In the first stage, the deep neural network and the grid search improved support vector machine algorithm (DNN-GSM-SVM) are used to screen and classify customer priority features, and in the second stage, adaptive large-scale neighborhood search improved genetic algorithms (ALNS-GA) are used to solve the problem of vehicle-drone joint distribution path planning problem. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. The core of the research lies in enhancing the feature extraction capability of the model, optimizing the feature expression of the model by introducing the CBAM attention mechanism, and improving the original structure of the neck component. …”
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A Crowd Density Detection Algorithm for Tourist Attractions Based on Monitoring Video Dynamic Information Analysis by Lina Li

“…Also, the algorithm uses jump connections between the top convolution and the bottom void convolution layers to reduce the risk of network gradient disappearance and gradient explosion and optimizes the network parameters using an intermediate supervision strategy. …”
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Integrative machine learning approach for forecasting lung cancer chemosensitivity: From algorithm to cell line validation by Jinghong Chen, Yonglin Yi, Chunqian Yang, Haoxuan Ying, Jian Zhang, Anqi Lin, Ting Wei, Peng Luo

“…Therefore, predicting individual responses is critical for optimizing treatment outcomes and improving patient prognosis. …”
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Reliability Analysis of Complex Structures Under Multi-Failure Mode Utilizing an Adaptive AdaBoost Algorithm by Feng Zhang, Zijie Qiao, Yuxiang Tian, Mingying Wu, Xiayu Xu

“…A reliability analysis can become intricate when addressing issues related to nonlinear implicit models of complex structures. To improve the accuracy and efficiency of such reliability analyses, this paper presents a surrogate model based on an adaptive AdaBoost algorithm. …”
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Predicting Irrigation Water Quality Indices Based on Data-Driven Algorithms: Case Study in Semiarid Environment by Dimple Dimple, Jitendra Rajput, Nadhir Al-Ansari, Ahmed Elbeltagi

“…The KR and SAR values were predicted accurately by the SVM model in comparison to the observed values. As a result, machine learning algorithms can improve irrigation water quality characteristics, which is critical for farmers and crop management in various irrigation procedures. …”
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A device free high-precision indoor positioning and tracking method based on GMM-WKNN algorithm by Mumen Jiang, Jiangnan Yuan

“…Abstract To address the high deployment complexity and algorithmic intricacies associated with current indoor target localization and tracking methods, this paper presents a Wi-Fi CSI indoor localization and tracking algorithm that integrates a Gaussian Mixture Model (GMM) with Weighted K-Nearest Neighbors (WKNN) and Kalman filtering. …”
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A two phase differential evolution algorithm with perturbation and covariance matrix for PEMFC parameter estimation challenges by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe

“…These numerical results emphasize PCM-DE’s ability to outperform existing algorithms in accuracy, convergence speed, and consistency, showcasing its potential for advancing PEMFC modeling and optimization. …”
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Multi-service differentiated traffic management optimization strategy in cloud data center by Yaomin WANG, Xia WANG, Yi DONG, Lian GAO, Songhai ZHANG, Xinling SHI

“…In order to cope with the traffic management for multi-service differentiated in cloud data centers,improving network performance and service experience,the multi-service differentiated (MSD) traffic management model was designed that can suit operational requirements in cloud data center.Fibonacci tree optimization (FTO) algorithm was improved according to the MSD model.MSD-FTO traffic management strategy was proposed in SDN cloud data center.Simulation results show that the strategy takes advantage of FTO global optimization ability and multi-modal adaptive performance.Through the global local alternating optimization of the algorithm,differentiation traffic management schemes are obtained as needed,the problem of multi-services differentiated traffic management is solved in operator cloud data center that improve network performance and service experience in cloud data center effectively.…”
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Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

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Research of Speech Recognition Algorithm Based on Time Delay Neural Network and Its Application in Rail Transit by LIU Yue, LIN Jun, LUO Xiao, CHU Wei, LIU Ren

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Prediction of effective moment of inertia for hybrid FRP-steel reinforced concrete beams using the genetic algorithm by A. Kheyroddin, F. Maleki

“…In this paper, we proposed a new equation for estimating the effective moment of inertia of hybrid FRP-steel reinforced concrete (RC) beams on the basis of the genetic algorithm and experimental results.The genetic algorithm is used to optimize the percent error between experimental and analytical responses. …”
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Comparative Analysis of Gradient Descent Learning Algorithms in Artificial Neural Networks for Forecasting Indonesian Rice Prices by Rica Ramadana, Agus Perdana Windarto, Dedi Suhendro

“…To address these issues, appropriate parameters are needed in the Backpropagation training process, such as an optimal learning function. The aim of this study is to evaluate and compare various learning functions within the Backpropagation algorithm to determine the best one for prediction cases. …”
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