Assessment of the impact of a new sequential approach to antimicrobial use in young febrile children in the emergency department (DIAFEVERCHILD): a French prospective multicentric... by Elsa Tavernier, Elise Launay, Christèle Gras Le Guen, Gaelle Hubert, Cécile Feildel Fournial, Anne Chauvire-Drouard, Fleur Lorton

“…The aims of this study are to demonstrate that using a procalcitonin (PCT) rapid test-based prediction rule (1) would not be inferior to usual practice in terms of morbidity and mortality (non-inferiority objective) and (2) would result in a significant reduction in antibiotic use (superiority objective).Methods and analysis This prospective multicentric cluster-randomised study aims to include 7245 febrile children aged 6 days to 3 years with a diagnosis of fever without source in 26 participating EDs in France and Switzerland during a 24-month period. …”
Get full text

Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data by B. Li, B. Li, B. Li, B. Li, H. Xie, H. Xie, S. Liu, Z. Ye, Z. Hong, Q. Weng, Q. Weng, Q. Weng, Y. Sun, Q. Xu, X. Tong

“…The results from the validation comparison show that the elevation accuracy of IC2-GDEM is evidently superior to that of the ASTER GDEM product: (1) the RMSE reduction ratio of the corrected GDEM elevation is between 16 % and 82 %, and the average reduction ratio is about 47 %; and (2) from the analysis of the different topographies and land covers, this error reduction is effective even in areas with high topographic relief (<span class="inline-formula">&gt;15<i>°</i></span>) and high vegetation cover (<span class="inline-formula">&gt;60 %</span>). …”
Get full text

Enhancing Efficiency and Reducing the Carbon Footprint of Cloud-Based Healthcare Applications through Optimal Data Preprocessing by El Aziz Btissam, Eddabbah Mohammed, Laaziz Yassin

“…Our results demonstrate that the impact of preprocessing on both accuracy and processing speed varies depending on the algorithm and the type of preprocessing applied. Notable improvements in precision and processing time reductions of up to 35% were observed, highlighting the potential of preprocessing to enhance the performance and sustainability of ML algorithms.…”
Get full text

Dose-Weighted Network Pharmacology: Evaluating Traditional Chinese Medicine Formulations for Lumbar Disc Herniation by Zhou C, Xiang T, Yu Y, Ma H, Liu C, Yang F, Yang L

“…These predictions were confirmed in animal studies, where YJD demonstrated the greatest reduction in thermal hyperalgesia and the most significant decrease in inflammatory markers, surpassing both TSD and PQT. …”
Get full text

Simultaneous determination of the amylose and amylopectin content of foxtail millet flour by hyperspectral imaging by Guoliang Wang, Min Liu, Hongtao Xue, Erhu Guo, Aiying Zhang

“…Results demonstrated that the key band extraction combined algorithm effectively reduced data dimension without compromising the accuracy of the prediction model. …”
Get full text

Modelling and Optimisation of Hysteresis and Sensitivity of Multicomponent Flexible Sensing Materials by Kai Chen, Qiang Gao, Yijin Ouyang, Jianyong Lei, Shuge Li, Songxiying He, Guotian He

“…Finally, the optimal solution of the prediction model is obtained using the multi-objective RIME (MORIME) algorithm. …”
Get full text

Lightweight Tea Shoot Picking Point Recognition Model Based on Improved DeepLabV3+ by HU Chengxi, TAN Lixin, WANG Wenyin, SONG Min

“…This led to a notable reduction in the model's parameter count and expedited the model training process. …”
Get full text

Faster R-CNN model for target recognition and diagnosis of scapular fractures by Qiong Fang, Anhong Jiang, Meimei Liu, Sen Zhao

“…The accuracy of the CNN algorithm model combined with orthopedist interpretation was 97.78 %, significantly higher than orthopedist-independent interpretation (82.95 %) and CNN algorithm-independent prediction (92.05 %) (P < 0.05). …”
Get full text

Revisiting Southern Gallo-Romance from a complexity theory standpoint: Occitan by Jean Léo Léonard

“…In this paper, the inner structure of the Occitan dialect network is revisited in the light of a range of cumulative (Ward’s method) vs. reductive (Complete linkage, Groupe Average, Weighted Average) hierarchical algorithms provided by Gabmap, an Online dialectometric application for calculating distance/similarities by edit distance (Levenshtein algorithm). …”
Get full text

Monitoring of Thoracopulmonary Compliance During High-Frequency Jet Ventilation: Theoretical and Practical Aspects by M. B. Kontorovich, B. D Zislin, A. V. Chistyakov, A. V. Markov

“…The clinical tests of the developed algorithms permitted a new assessment of the physiological essence of thoracopulmonary compliance during HFJV. …”
Get full text

Hyperspectral Inversion of Soil Cu Content in Agricultural Land Based on Continuous Wavelet Transform and Stacking Ensemble Learning by Kai Yang, Fan Wu, Hongxu Guo, Dongbin Chen, Yirong Deng, Zaoquan Huang, Cunliang Han, Zhiliang Chen, Rongbo Xiao, Pengcheng Chen

“…Therefore, the rapid and accurate prediction of heavy metal content in agricultural soil is crucial for environmental protection and soil remediation. …”
Get full text

Research on short-term power load forecasting based on deep reinforcement learning with multiple intelligences by Tianyun Luo, Dunlin Zhu, Jinming Liu, Sheng Yang, Jinglong He, Yuan Fu

“…Therefore, to realize accurate and efficient prediction of short-term power loads, a short-term power load prediction method based on multi-intelligence deep reinforcement learning is proposed to address the complex nonlinear characteristics of load data. …”
Get full text

Fractional Order Accumulation NGM (1, 1, k) Model with Optimized Background Value and Its Application by Jun Zhang, Yanping Qin, Xinyu Zhang, Bing Wang, Dongxue Su, Huaqiong Duo

“…The simulation and prediction results show the practicality and efficiency of the FBNGM (1, 1, k) model proposed in this study, which further broadens the application scope of the grey prediction model.…”
Get full text

A Novel Fault Diagnosis of Induction Motor by Using Various Soft Computation Techniques: BESO-RDFA by Kapu V. Sri Ram Prasad, K. Dhananjay Rao, Guruvulu Naidu Ponnada, Umit Cali, Taha Selim Ustun

“…The established hybrid forecast scheme signifies the combined execution of Bald-Eagle- Search-Optimization (BESO) and Random-Decision-Forest-Algorithm (RDFA), called as BESO-RDFA prediction scheme. …”
Get full text

Identification model of mine water inrush source based on XGBoost and SHAP by Bencong Kou, Tingxin Wen

“…Verified by 160 sample sets in Xinzhuangzi Mine, the average prediction precision of the CLSSA-XGBoost is 97.78%, the average prediction recall rate is 97.59% and the F1 is 97.61%, which are better than other comparison models. …”
Get full text

Harnessing Unsupervised Ensemble Learning for Biomedical Applications: A Review of Methods and Advances by Mehmet Eren Ahsen

“…Ensemble learning, particularly unsupervised ensemble approaches, emerges as a compelling solution by integrating predictions from multiple algorithms to leverage their strengths and mitigate weaknesses. …”
Get full text

Energy-efficient strategy for data migration and merging in Storm by Yonglin PU, Jiong YU, Liang LU, Ziyang LI, Chen BIAN, Bin LIAO

“…Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.…”
Get full text

Energy-efficient strategy for data migration and merging in Storm by Yonglin PU, Jiong YU, Liang LU, Ziyang LI, Chen BIAN, Bin LIAO

“…Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.…”
Get full text

A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

“…The results demonstrated the effectiveness of these algorithms. NSGA-II achieved the best performance, with reductions of 32.84% in energy losses and 42.41% in operating costs (with standard deviations of 0.21% and 0.39%, respectively) for the urban system; and reductions of 21.87% in energy losses and 43.36% in operating costs (with standard deviations of 0.07% and 0.24%, respectively) for the rural system. …”
Get full text

Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Additionally, multi-factor logistic regression analysis identified clinical predictors associated with PD-RBD, and these clinical features were integrated with the radiomics signatures to develop predictive models using various machine learning algorithms. …”
Get full text