An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis by Haien Wang, Xingxing Jiang, Wenjun Guo, Juanjuan Shi, Zhongkui Zhu

“…Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. …”
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The influence of mind mapping on computational thinking skills and self-efficacy in students’ learning of graphical programming by Rong Guo, Yan Zheng, Haifei Miao

“…Computational thinking is regarded as an essential skill for students in the 21st century, and programming is one of the means to cultivate it. This study introduces mind mapping into graphical programming to visualize the cognitive process of computational thinking, aiming to enhance students’ computational thinking skills. …”
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A Social Media Sentiment Analysis Using Machine Learning Approaches by Noor Salah Irzooqi Al-Agele, Didem KIVANÇ TÜRELİ

“… Social media platforms like Twitter provide major means for individuals to express their opinions on various topics; therefore, a need for complex tools to distinguish between negative and positive attitudes in textual content. …”
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Advancements and Optimisation Strategies in Building Integrated Photovoltaic Thermal (BIPVT) Systems by Mon Prakash Upadhyay, Arjun Deo, Ajitanshu Vedratnam

“…The paper covers the current algorithms for various optimisation algorithms such as Genetic Algorithms and Particle Swarm Optimisation that provide enhanced utilization improvements. …”
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ARCHITECTURE AND FUNCTIONALITY OF INTEGRATED INFORMATION SYSTEM FOR ANALYSIS OF POTENTIAL OF RENEWABLE ENERGY SOURCES by B. A. Tonkonogov, S. P. Kundas, A. E. Moroz

“…This required the solution of the following problems: adaptation of existing and development of new methods for analyzing the potential of RES at various territorial levels using modern technologies of geographic information systems and computer technologies were accomplished; models for the assessment and calculation of the potential of renewable energy resources were developed; techniques for assessing of the economic effectiveness of decisions made for using of RES were adapted; architecture of the information system was developed and the choice of technologies and means for its implementation was made; algorithms of software modules and their interaction as a parts of the information system were developed. …”
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Comparison of the new formulation of the Radiation Network Method with the Radiosity Method in the analysis of radiative heat transfer by Rafał Buczyński

“…In addition, the paper estimates the accuracy of RNM and RM algorithms by validating the generated temperatures and heat fluxes against the data calculated by means of the Discrete Ordinates Method (DOM) and Surface-to-surface (S2S) model.This thorough examination aims to verify the performance and applicability of RNM and RM across distinct problems of radiative heat transfer. …”
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New non-primitive codes formed from primitive BCH and Hamming codes and their norm evaluation by V. K. Konopelko, V. A. Lipnitski

“…It is shown that it is impossible to implement plus-decoding by known classical methods and algorithms, but only by the available and developing means of the theory of norms syndromes. …”
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Simulation Analysis of Control Strategy for Doubly-fed Induction Generators by 李大虎, 石新春

“…The simulation results prove the validity of control algorithms and good control performance.…”
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Urban tourism management based on artificial neural networks analysis and data mining by Xin Cui

“…Tourists are categorized using K-means clustering algorithms according to their preferences and actions. …”
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Carbonate Seismic Facies Analysis in Reservoir Characterization: A Machine Learning Approach with Integration of Reservoir Mineralogy and Porosity by Papa Owusu, Abdelmoneam Raef, Essam Sharaf

“…To this end, this study utilizes an unsupervised comparative hierarchical and K-means ML classification of the whole 3D seismic data spectrum and a suite of spectral bands to overcome the cluster “facies” number uncertainty in ML data partition algorithms. …”
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On Neutrosophy logic for Multiple Correlation Analysis in Fuzzy Uncertain Database by Samar Wazir, M.M. Sufyan Beg, Tanvir Ahmad, Shahab Saquib Sohail

“…The work is further expanded by proposing two additional methods for mining frequent and interesting items, utilizing fuzzy means and the OWA operator along with multiple correlation analysis for more than two items in uncertain transactional databases. …”
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Unified Mathematical Framework for Slicing and Symmetry Reduction over Event Structures by Xinyan Gao, Yingcai Ding, Wenbo Liu, Kaidi Zheng, Siyu Huang, Ning Zhou, Dakui Li

“…Nonclassical slicing and symmetry reduction can act as efficient structural abstract methods for pruning state space when dealing with verification problems. In this paper, we mainly address theoretical and algorithmic aspects for nonclassical slicing and symmetry reduction over prime event structures. …”
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Current status and outlook of UWB radar personnel localization for mine rescue by ZHENG Xuezhao, MA Jiawen, HUANG Yuan, LI Qiang, REN Jing, LIU Yu

“…Future research directions of UWB radar personnel localization technology for mine rescue operations are proposed: ① optimizing the UWB radar localization system by constructing cross-modal information fusion models and developing highly adaptive signal processing methods to enhance the system's adaptability to post-mining disaster environments; ② improving the applicability of combined static and dynamic target localization by developing hybrid localization algorithms that integrate Bayesian networks or deep belief networks to fuse static and dynamic target features and establishing state-switching-based comprehensive models; ③ improving UWB radar echo processing algorithms, combining adaptive beamforming technology, Multiple Input Multiple Output (MIMO) technology, and optimized K-means++ or entropy-based hierarchical analysis algorithms, effectively distinguishing multi-target position information, and validating their adaptability and reliability in complex environments through extensive simulation experiments.…”
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Discovering and modeling hidden periodicities in science data by Antonio Napolitano, William A. Gardner

“…The popularity stems from the fact that detecting and characterizing periodicities can provide a means for extracting information from science data—information that might not otherwise be accessible. …”
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Applications of Machine Learning in Human Factors and Ergonomics: A Comprehensive Review of Research From the Past Decade by Erman Cakit, Waldemar Karwowski

“…ML techniques examined include Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), Random Forest (RF), Decision Trees (DTs), K-Nearest Neighbors (KNN), Naive Bayes (NB), boosting algorithms, and k-means clustering. Among the reviewed articles, Artificial Neural Networks (ANNs) and Deep Learning (DL) methods were the most prevalent, at 36%, followed by Support Vector Machines (SVMs) at 22% and Random Forests (RF) at 19%. …”
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Learning-Based Image Restorations of Sparse-View CT Data: Is It Reliable? by Philip Maurice Trapp, Elias Eulig, Joscha Maier, Frederic Ballach, Raoul Christoph, Ralf Christoph, Marc Kachelrieß

“…In addition, this work examines the influence of these methods on metrological specification measurements of CTs and the conclusions that can be drawn with regard to the objective specification of such algorithms.  …”
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PPLIO: Plane-to-Plane LiDAR-Inertial Odometry With Multi-View Constraint in Real-Time by Hanyeol Lee, Jae Hyung Jung, Won Young Chung, Suyong Lee, Chan Gook Park

“…Recent feature-based LiDAR-inertial odometry (LIO) algorithms mainly adopt a point-to-plane model, which requires complex association between numerous feature points and planes. …”
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Screening of endoplasmic reticulum stress characteristic genes and immune infiltration manifestations in chronic obstructive pulmonary disease by ZHANG Shuang, LUO Chenyang, HE Zhiyi

“…GO and KEGG analysis showed that ERs-DEGs were mainly enriched in ERS response, protein folding and multiple inflammatory signaling pathways, and DO analysis was mainly enriched in pulmonary vascular occlusive diseases and COPD and so on. …”
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Budget impact analysis of using procalcitonin to optimize antimicrobial treatment for patients with suspected sepsis in the intensive care unit and hospitalized lower respiratory t... by Osvaldo Ulises Garay, Gonzalo Guiñazú, Wanda Cornistein, Javier Farina, Ricardo Valentini, Gabriel Levy Hara

“…Procalcitonin-guided algorithms may represent helpful tools to reduce antibiotic overuse but the financial burden is unclear. …”
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Admission Control Methods in IP Networks by Erik Chromy, Marcel Jadron, Tomas Behul

“…The core of the paper is simulation of AC methods and algorithms for topology model in MATLAB. Our simulations are mainly focused on required bandwidth and loss rates. …”
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