Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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An artificial neural network approach to comparative aspects: A predictive analysis of magnetic dipole on the heat transfer of maxwell hybrid nano coolants flow in an inclined cyli... by J. Aruna, H. Niranjan

“…This predictive analysis optimizes engine cooling and lubrication under varying thermal and flow conditions. …”
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Prediction of risk for acute kidney injury and its progression to mortality in obese patients admitted to ICU postoperatively by LI Qiang, LI Qiang, MU Guo, MU Guo, WANG Wenzhang

“…Conclusion‍　‍Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed, and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients. …”
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Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…The impact analysis on the factors such as input length, neuron number, artificial neural network (ANN) optimizer, and output scope, are taken. To highlight the trimaran high-frequency load fluctuation and improve the prediction accuracy, the LSTM neural network combines with different signal decomposition algorithms, such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and Variational Mode Decomposition (VMD). …”
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Underwater Target 3D Reconstruction via Integrated Laser Triangulation and Multispectral Photometric Stereo by Yang Yang, Yimei Liu, Eric Rigall, Yifan Yin, Shu Zhang, Junyu Dong

“…At the same time, we propose to optimize the laser place calibration and laser line separation processes, further improving the reconstruction performance of underwater laser triangulation and multispectral photometric stereo. …”
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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…The findings demonstrate that the proposed IoT-enabled model efficiently balances classification tasks, reduces congestion during algorithm execution, and minimizes energy waste. …”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
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sEMG-based gesture recognition using multi-stream adaptive CNNs with integrated residual modules by Yutong Xia, Dawei Qiu, Cheng Zhang, Jing Liu

“…In the future, in order to deal with differences in sEMG signals caused by variations among individuals, a universal multi-gesture recognition algorithm should be developed. Meanwhile, the model should focus on optimizing and streamlining the network to reduce computational load.…”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…In response to the limitations of current infrared and visible light image fusion algorithms-namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters-this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. …”
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ACCURACY ANALYSIS OF GALILEO CODE POSITIONING FOR UAV by Klaudia CYBULSKA-GAC, Kamil KRASUSKI, Adam CIEĆKO

“…The Galileo SPP code method algorithm was used to determine the UAV coordinates. …”
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Pig behavior recognition and disease warning based on compressed sensing and long-short term memory network by Ren Wang, Mingdong Zhao

“…In order to solve the problems of low precision and poor stability in pig behavior recognition process due to the deficiency of environment and hardware conditions such as complex lighting conditions, close color of target and background, poor camera Angle and parameters, a compressed sensing recognition algorithm via long and short term memory network for optimized feature extraction is proposed in this paper. …”
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Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…These additions help achieve an initial reduction in model size while preserving detection accuracy. Furthermore, we optimize the model by removing redundant parameters using the DepGraph pruning algorithm, which facilitates its application on edge devices. …”
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Enhanced identification of Morganella spp. using MALDI-TOF mass spectrometry by Mathilde Duque, Cécile Emeraud, Rémy A. Bonnin, Quentin Giai-Gianetto, Laurent Dortet, Alexandre Godmer

“…Methods: We applied Machine Learning (ML) algorithms to a collection of 235 clinicial Morganella spp. strains to develop an optimized identification model. …”
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A 3D reconstruction platform for complex plants using OB-NeRF by Sixiao Wu, Changhao Hu, Boyuan Tian, Yuan Huang, Shuo Yang, Shanjun Li, Shengyong Xu

“…Furthermore, the precision of the reconstruction was enhanced by optimizing camera poses. An exposure adjustment phase was integrated to improve the algorithm's robustness in uneven lighting conditions. …”
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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…This decision model overcomes the accuracy-robustness trade-off by matching algorithmic strengths to beam-specific dynamics, ensuring optimal performance during abrupt SNR transitions and high Doppler rates. …”
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A New Efficient Classifier for Bird Classification Based on Transfer Learning by Lesia Mochurad, Stanislav Svystovych

“…An optimal model architecture was built using the transfer learning approach. …”
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Accelerated Benders’ Decomposition for Integrated Forward/Reverse Logistics Network Design under Uncertainty by Vahab Vahdat, Mohammad Ali Vahdatzad

“…Numerical results confirmed that the proposed solution algorithm improved the convergence of BD lower bound and the upper bound, enabling to reach an acceptable optimality gap in a convenient time.…”
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Intelligent deep learning-based dual-task approach for robust power quality event classification by Lipsa Ray, Pampa Sinha, Siddhanta Pani, Anshuman Nayak, Kaushik Paul, Chitralekha Jena, Md. Minarul Islam, Taha Selim Ustun

“…These findings underscore the model’s efficacy in real-time PQ monitoring, contributing to improved reliability and stability in evolving power systems.…”
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多楔带轮增厚成形有限元模拟及试验 by 殷沙

“…The forming process of the multi-wedge belt pulley is proposed according to the structure.A 3D rigid-plastic FEA model of spinning thickening forming was established by the software,DEFORM.Based on the experimental data obtained through numerical simulation and orthogonal method,the influential of the processing parameters on the forming load including influential trend and the order of significance is determined in the process of thickening forming.Then,the optimization technology involving neural networks and genetic algorithms is utilized to optimize the processing parameters,and the optimum combination of processing parameters are acquired.Through CAE simulation and experimental verification,it is proved that the forming quality of thickening blank is improved and the forming load significantly decreases,thus protecting the spinning roller and spinning equipment.…”
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Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

“…Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. …”
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