Objectively measured environmental factors in relation to school travel mode among adolescents: a decision tree analysis by Lena Malnes, Tommy Haugen, Emma Charlott Andersson Nordbø, Andreas Ivarsson, Elin Kolle, Geir Kåre Resaland, Runar Barstad Solberg, Andreas Åvitsland, Sveinung Berntsen

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Energy-Efficient Distributed Compressed Sensing Data Aggregation for Cluster-Based Underwater Acoustic Sensor Networks by Deqing Wang, Ru Xu, Xiaoyi Hu, Wei Su

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Fusion Classification Method Based on Audiovisual Information Processing by Peiju Chen, Xuan Zhang, Huijun Zhao, Huiliang Cao, Xuemei Chen, Xiaochen Liu

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Design and optimization of planetary gear train pendulum type sugarcane seeding mechanism based on spatial offset trajectory by Jiaodi Liu, Chaoyuan Luo, Qingli Chen, Jianhao Chen, Jianlong Chen, Yihao Xing

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Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making by Zihan Sun, Jian Chen, Yang Chen, Wen Zhang, Tingting Zhang, Yicheng Zhang, Guangsheng Pan

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基于多重分形谱的转子系统故障诊断与参数优选 by 刘岩, 王金东, 郭建华, 胡清明

“…Because of the robustness of one dimensional time series reconstruction G-P algorithm to extract the fault omen is poor,especially influenced by a sensitive noise in the measured signal.A noise reduction method is proposed based on detrended fluctuat ion analysis（FDA） and kernel principal component analysis（KPCA）,the eigenvalue extraction algorithm based on Mult ifractal spectrum is presented.Through pseudo-phase portrait to determine the weighting factor threshold,optimize and choose parameter and compare with the defects of single G_P algorithm,and combine with the 3 kinds of rotor system common faults,the stability and accuracy of eigenvalue extraction of this method is analyzed,the results prove that,the diagnosis result is good.…”
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基于正态反高斯模型的自适应小波消噪方法 by 吴国洋

“…A locally adaptive wavelet de-noising method based on normal inverse Gaussian modal is proposed.Firstly,the db5 wavelet is used to decompose the signal.For those wavelet coefficients which contain a lot of noise,the normal inverse Gaussian modal with good approximation property is constructed as the prior distribution model of those coefficients,on the basis of the model,Bayesian maximum a posteriori estimator is used to estimate the noisy wavelet coefficients and got the realistic wavelet coefficients.Then in the process of posteriori estimation,in order to get the best posteriori approximation model,the particle swarm optimization algorithm is used to select the key coefficient of the model.Finally,new wavelet coefficients are used for the reconstruction of the de-noised signal,and the de-noised signal is gotten.The algorithm is analyzed by simulation and bearing fault signal respectively.Analysis results show that this algorithm has good noise reduction effect,and can efficiently reduce the noise.…”
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A multi-task genetic programming approach for online multi-objective container placement in heterogeneous cluster by Ruochen Liu, Haoyuan Lv, Ping Yang, Rongfang Wang

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Pyo-septic complications of severe necrotizing forms of acute pancreatitis by N. N. Veligotsky, S. E. Arutyunov, M. V. Klymenko, K. A. Aleksanyan

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Efficient Markerless Motion Classification Using Radar by Changhyeon Eom, Sooji Han, Sabin Chun, Soyoung Joo, Jisu Yoon, Min Kim, Jongchul Park, Sanghong Park

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Deep-Learning-Based Approach in Imaging Radiometry by Aperture Synthesis: Application to Real SMOS Data by Ali Khazaal, Richard Faucheron, Nemesio J. Rodriguez-Fernandez, Eric Anterrieu

“…A novel image reconstruction algorithm for aperture synthesis measurements using deep learning techniques was introduced recently. …”
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Analyzing Digital Political Campaigning Through Machine Learning: An Exploratory Study for the Italian Campaign for European Union Parliament Election in 2024 by Paolo Sernani, Angela Cossiri, Giovanni Di Cosimo, Emanuele Frontoni

“…Our findings highlight the significance of micro-targeting practices, the role of algorithmic biases, and the risks associated with disinformation in shaping public opinion. …”
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Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence by Ya Zhou, Yun Shi

“…The first experiment is to test the accuracy of various machine learning algorithms for clothing size measurement. The results obtained are as follows: the predicted value of the DBN neural network is the closest to the actual value, the average prediction accuracy of DBN for the cuff size is 90%, and the average prediction accuracy for the neck circumference is 91.5%. …”
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Ensemble machine learning model for forecasting wind farm generation by A. G. Rusina, Osgonbaatar Tuvshin, P. V. Matrenin, N. N. Sergeev

“…This study is carried out by ensemble algorithms, such as Random Forest, AdaBoost and XGBoost, which are one of the machine learning approaches. …”
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Design of the Urban Lighting Control System Based on Optical Multisensor Technology and the GM Model by Weili Wu, Xiang Tang

“…The results of the evaluations show that the fresh method is successful in dimming, prediction, and control. This conclusively demonstrates the efficacy of the paper’s proposed design solution, which integrates optical multisensor technology with sophisticated control algorithms and data analysis to improve the quality of life in urban areas by boosting the efficiency and sustainability of the urban lighting system.…”
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Application of Particle Filter to On-Board Life Estimation of LED Lights by Fazludeen Ruknudeen, Sundararajan Asokan

“…Life prediction methods based on reliability analysis and filtering algorithms proposed in the past were predominantly based on accelerated life tests and cannot be readily implemented for on-board diagnosis. …”
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Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches by Burcu Ramazanli, Oyku Yagmur, Efe Cesur Sarioglu, Huseyin Enes Salman

“…Accurate BCs can enhance ML predictions, increasing the clinical applicability. …”
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Advanced Supply Chain Management Using Adaptive Serial Cascaded Autoencoder with LSTM and Multi-Layered Perceptron Framework by Aniruddha Deka, Parag Jyoti Das, Manob Jyoti Saikia

“…The SGSO-ASCALSMLP model is highly efficient in predicting financial risks, outperforming conventional prediction techniques and heuristic algorithms, making it a promising approach for enhancing financial risk management in supply chain networks.…”
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Rediscovering histology – the application of artificial intelligence in inflammatory bowel disease histologic assessment by Giovanni Santacroce, Irene Zammarchi, Olga Maria Nardone, Ivan Capobianco, Miguel Puga-Tejada, Snehali Majumder, Subrata Ghosh, Marietta Iacucci

“…Additionally, AI shows promise in predicting adverse outcomes and therapeutic responses, making it a promising tool for clinical practice and clinical trials. …”
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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…Multiple machine learning algorithms were used to generate the LUSC classification. …”
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