A two-layer low-carbon economic planning method for park-level integrated energy systems with carbon-energy synergistic hub by Yunfei Mu, Haochen Guo, Zhijun Wu, Hongjie Jia, Xiaolong Jin, Yan Qi

“…From a dual “carbon-energy” perspective, it enhances investment effectiveness and carbon reduction sensitivity by deeply exploring the energy conservation and carbon reduction potential of PIES.…”
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Compute Nano topology by used the programing language python by Nawfal N. Abed, Ali A. Shihab

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Construction and analysis of a prognostic risk scoring model for gastric cancer anoikis-related genes based on LASSO regression by Ai CHEN, Xiaowei CHEN, Yanan WANG, Xiaobing SHEN

“…Gene expression levels in gastric cancer clinical samples and cells were detected by real-time quantitative PCR (RT-qPCR); Kaplan-Meier (KM) survival curves, univariate and multivariate Cox regression analyses were used to verify the predictive efficiency of the prognostic risk scoring model for the prognosis of gastric cancer patients; CIBERSORT and ESTIMATE algorithms were used to analyze the immune cell infiltration levels in patients with different risk groups; the correlation between risk scores and immune checkpoint expression levels in gastric cancer patients was analyzed using the R package "ggplot2" and "ggExtra", and the correlation between tumor mutation burden (TMB) and risk scores was assessed; chemotherapy drug sensitivity analysis was used to evaluate the value of the constructed prognostic risk scoring model in gastric cancer chemotherapy. …”
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Exploring the impact of deubiquitination on melanoma prognosis through single-cell RNA sequencing by Su Peng, Jiaheng Xie, Xiaohu He

“…Cell types were annotated based on known marker genes, and the AUCell algorithm assessed the enrichment of deubiquitination-related genes. …”
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Objective monitoring of motor symptom severity and their progression in Parkinson’s disease using a digital gait device by Tamara Raschka, Jackrite To, Tom Hähnel, Stefano Sapienza, Alzhraa Ibrahim, Enrico Glaab, Heiko Gaßner, Ralph Steidl, Jürgen Winkler, Jean-Christophe Corvol, Jochen Klucken, Holger Fröhlich

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Machine Learning-Based Methods for the Seismic Damage Classification of RC Buildings by Sung Hei Luk

“…In this study, the XGBoost method generally outperforms the other algorithms, with the highest accuracy and generalizability. …”
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A Method for Aileron Actuator Fault Diagnosis Based on PCA and PGC-SVM by Wei-Li Qin, Wen-Jin Zhang, Chen Lu

“…Second, the data feature extraction is performed with dimension reduction using PCA. Finally, the GS and CV algorithms are employed to train a one-versus-one SVM for fault classification, thus obtaining the optimal model parameters and assuring the generalization of the trained SVM, respectively. …”
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Signal-piloted processing and machine learning based efficient power quality disturbances recognition. by Saeed Mian Qaisar

“…Therefore, a remarkable reduction can be secured in the data storage, processing and transmission requirement towards the post classifier. …”
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Research and application of natural air-cooled traction transformer for EMU by JIN Jun

“…Verification results show that, compared with traditional forced air-cooled traction transformers for EMUs, this new natural air-cooled traction transformer achieves a 2% improvement in efficiency, a 50% reduction in losses, a decrease in noise levels by 15 dB(A), a reduction of approximately 90% in the maintenance workload for the cooling system, and a decrease in total lifecycle costs of about 40%. …”
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Analog Circuits Fault Diagnosis Using ISM Technique and a GA-SVM Classifier Approach by Sabah Kouachi, Nacerdine Bourouba, Kamel Mebarkia, Imad Laidani

“…This is built with GA and SVM algorithms combination targeting both data reduction and fault classification accuracy respectively. …”
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Dynamic strategy for adaptive block size optimization in blockchain technology by Shafique Ahmed Awan, Muazzam Ali Khan Khattak, Anwar Ali Sathio, Haleem Farman, Sumaira Memon, Moustafa M. Nasralla, Ahmed Sedik

“…This study proposes a dynamic block size optimization framework for private blockchain networks using hybrid heuristic algorithms—Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO)—integrated with Merkle trees and Directed Acyclic Graphs (DAGs). …”
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Assessing the effectiveness of transfer learning strategies in BLSTM networks for speech denoising by Marvin Coto-Jiménez, Astryd González-Salazar, Michelle Gutiérrez-Muñoz

“…Results show the convenience of transferring information from a single case of denoising network to the rest, with a significant reduction in training time and denoising capabilities of the BLSTM networks. …”
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Influence of Aerobic Exercise Load Intensity on Children’s Mental Health by Sihong Zhao

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Open system of text processing for scientometric and bibliometric purposes by L. S. Lomakina, A. S. Surkova, D. V. Zhevnerchuk, O. S. Rassadin

“…The key features of the proposed solution are the ability to implement basic algorithms for text data analyzing and processing in the form of RESTful services, executing of these processes in a distributed processing environment, creating combined algorithms based on them, and also the ability to build an applied programming interface for creating client-server systems with mobile and fixed client subsystems in the field of science and education.…”
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Hybrid Hunger Games Search optimization using a neural networks approach applied to UAVs by Nadia Samantha Zuñiga-Peña, Salatiel Garcia-Nava, Norberto Hernandez-Romero, Juan Carlos Seck-Touh-Mora

“…Optimization methods like population-based algorithms are valuable when applied to multidimensional and nonlinear problems. …”
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Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. …”
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An end-to-end real-time pollutants spilling recognition in wastewater based on the IoT-ready SENSIPLUS platform by Luca Gerevini, Gianni Cerro, Alessandro Bria, Claudio Marrocco, Luigi Ferrigno, Michele Vitelli, Andrea Ria, Mario Molinara

“…The data processing is based on a commercial Micro Control Unit (MCU), including an anomaly detection module, a classification module, and a false positive reduction module, all based on machine learning algorithms that have a computational complexity suitable for low-cost hardware implementation.An extensive experimental campaign on different contaminants has been carried out to train machine-learning algorithms suitable for low-cost and low-power MCU. …”
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A data-driven approach to solve the RT scheduling problem by Mruga Gurjar, Jesper Lindberg, Thomas Björk-Eriksson, Caroline Olsson

“…The comparison between manual and algorithm allocations showed that the number of delayed patients reduced by 10 % in the algorithm suggestion with an average delay reduction of 2 weeks. …”
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Unbiased High-Precision Cloud Detection for Advanced Himawari Imager Using Automatic Machine Learning by Bochun Liu, Jinming Ge, Qingyu Mu, Chi Zhang, Xiaoyu Hu, Jiajing Du, Yanyan Wu, Bo Wang, Xiang Li, Jianping Huang, Qiang Fu

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Pediatric anaphylaxis in the emergency department: Performances of dynamic tryptase measurement by Constance Gonzalez, MD, Meng Sun, MSc, Aurélie Morand, MD, PhD, Philippe Minodier, MD, Marc Leone, MD, PhD, Jean-Christophe Dubus, MD, PhD, Joana Vitte, MD, PhD, Moïse Michel, PharmD, PhD

“…A cutoff for sAT/sBT ratio of >1.74 yielded 66.7% sensitivity, 90.0% specificity, 96.8% positive predictive value, and 24.3% negative predictive value. …”
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