High-performance traffic volume prediction: An evaluation of RNN, GRU, and CNN for accuracy and computational trade-offs by Pranolo Andri, Saifullah Shoffan, Bella Utama Agung, Wibawa Aji Prasetya, Bastian Muhammad, Hardiyanti P Cicin

“…Predicting urban traffic volume presents significant challenges due to complex temporal dependencies and fluctuations driven by environmental and situational factors. …”
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Prediction of the anti-carbonation performance of concrete based on random forest – least squares support vector machine model by Sivaraja M., Swaminathen A. N., Kuttimarks M. S., Rajprasad J., Sakthivel M., Rex J.

“…Traditional methods for predicting the anti-carbonation performance (ACP) of concrete often lack precision and fail to account for complex interactions between influencing factors. …”
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Analysis of the Influence of Different Turbulence Models on the Prediction of Vehicle Aerodynamic Performance by Luwei Wang, Xingjun Hu, Peng Guo, Zirui Wang, Jingyu Wang, Yuqi Wang, Yan Ma, Ying Li, Jing Zhao, Xu Yang, Ruixing Ma, Yinan Zhu, Jianjiao Deng

“…Overall, the study clarifies the varying applicability of turbulence models in complex flows, and offers a basis for model selection and technical support for vehicle aerodynamic optimization. …”
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Rational well spacings for CO2 miscible flooding based on superposed relationships between connected sand bodies by JI Yingchun

“…A composite superposition coefficient of connected sand bodies was introduced to further address the impact of the complex superposition relationships between connected sand bodies in glutenite reservoirs. …”
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Machine Learning‐Based Identification of Children With Intermittent Exotropia Using Multiple Resting‐State Functional Magnetic Resonance Imaging Features by Mengdi Zhou, Huixin Li, Xiaoxia Qu, Lirong Zhang, Xueying He, Xiwen Wang, Jie Hong, Jing Fu, Zhaohui Liu

“…The linear regression (LR) classifier with analysis of variance (ANOVA) feature selection achieved the highest area under the receiver operator characteristic curve values (0.957, 0.804, and 0.818 for the training, validation, and test datasets, respectively) using five features, including the slow‐5 fALFF values of the right inferior parietal gyrus (IPG), right supplementary motor area (SMA), left primary somatosensory complex, right frontal opercula, and left dorsolateral prefrontal cortex (DLPFC), and the accuracy, sensitivity, and specificity values were 0.759, 0.759, and 0.760, respectively. …”
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Sample Size in Multilevel Structural Equation Modeling - the Monte Carlo Approach by Adam Sagan

“…In the process of sample selection, an important issue is the relationship between sample size and the type and complexity of the statistical model, which is the basis for testing research hypotheses. …”
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MICROCIRCULATORY DISORDERS IN PATIENTS WITH ACUTE CORONARY SYNDROME by Sergey S. Krutitsky, Georgiy P. Plotnikov, Irina N. Sizova, Damir M. Galimzyanov, Dmitriy L. Shukevich, Evgeniy V. Grigoriev

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Metode COPRAS untuk Menentukan Kain Terbaik dalam Pembuatan Pakaian pada Butik Batik Hatta Semarang by Saifur Rohman Cholil, Mohamad Adi Setyawan

“…The method used by researchers is the COPRAS (Complex Proportional Assessment) method, the results that will be obtained in the form of complex and accurate recommendations in determining the best fabric for making clothes at the Butik Batik Hatta. …”
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Draping test with polygonal sample-holding table for measuring the shape-changing ability of sheet-like, bendable by gravity materials by Marianna Halász, Zsolt Borka, Gabriella Oroszlány

“…Abstract Draping is a 3-dimensional, complex shape change caused by gravity. It characterizes the ability of the given sheet-like material, often textiles, with low bending stiffness to adapt to the shape of an object in a complex way, and therefore, knowing it is important, especially from the point of view of simulating the behaviour of this material. …”
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Massive MIMO channel estimation and feedback based on compressed sensing by Pan MAO, Xiaoguang HUANG, Wei WANG, Jian SONG

“…Focused on the issue that the problem of low precision of channel estimation and complex feedback scheme in massive MIMO system,a compression sampling matching pursuit (BCC-CoSAMP) algorithm based on coefficient correlation was proposed in the differential channel estimation and feedback scheme.In this algorithm,the inner product of the relationship between two vectors in the CoSAMP algorithm was replaced by the vector relation based on the correlation coefficient,so the atoms with strong correlation of the original signal were quickly selected to improve the accuracy of channel estimation.The simulation results show that the proposed BCC-CoSAMP algorithm has an improved channel estimation accuracy compared with the CoSAMP algorithm and an average increase of the total system rate of 1.25 bit/(s.Hz) at low signal to noise ratio (SNR).…”
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Massive MIMO channel estimation and feedback based on compressed sensing by Pan MAO, Xiaoguang HUANG, Wei WANG, Jian SONG

“…Focused on the issue that the problem of low precision of channel estimation and complex feedback scheme in massive MIMO system,a compression sampling matching pursuit (BCC-CoSAMP) algorithm based on coefficient correlation was proposed in the differential channel estimation and feedback scheme.In this algorithm,the inner product of the relationship between two vectors in the CoSAMP algorithm was replaced by the vector relation based on the correlation coefficient,so the atoms with strong correlation of the original signal were quickly selected to improve the accuracy of channel estimation.The simulation results show that the proposed BCC-CoSAMP algorithm has an improved channel estimation accuracy compared with the CoSAMP algorithm and an average increase of the total system rate of 1.25 bit/(s.Hz) at low signal to noise ratio (SNR).…”
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New winter common wheat variety ‘Saban’ for the middle Volga Region by I. D. Fadeeva, F. F. Kurmakaev, R. Kh. Idiatova

“…Lodging resistance was 8.7 points with a coefficient of variation of 6.66 %. The variety ‘Saban’ is of the intensive type, responsive to the application of complex fertilizers. …”
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Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding by Huan Liang, Xiao Liang, Man Zheng, Shoudong Wang

“…Conclusions This research elucidates the complex relationship between KLRD1 and AS, underscoring its potential as a novel biomarker for diagnosing and monitoring the disease.…”
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Network Security Situational Awareness Based on Improved Particle Swarm Algorithm and Bidirectional Long Short-Term Memory Modeling by Peng Zheng, Yun Cheng, Wei Zhu, Bo Liu, Shuhong Liu, Shijie Wang, Jinyin Bai

“…Currently, there are various types of network attacks and complex attacking techniques, and the large differences between them have led to the difficulty of collecting and recognizing the common characteristics of network attacks. …”
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Comprehensive evaluation and ranking of CMIP6 global climate models for simulating climate extreme indices across diverse hydrological and geographical regions of Nepal by Shiksha Bastola, Koshish Raj Maharjan, Innkyo Choo, Younghun Jung

“…The proposed framework is scalable and transferable to other regions with complex climatic and topographic variations, enhancing the robustness of climate model selection for impact studies.…”
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Synergizing TabNet and SHAP for PM10 Forecasting: Insights From Makkah, Saudi Arabia by Abdulrazak H. Almaliki, Afaq Khattak

“…This study utilizes the TabNet model to estimate PM10 concentrations, taking advantage of its ability to perform sparse feature selection and sequential decision-making to uncover complex relationships among different environmental variables. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…Sub-surface soil hydrological characterization is one of the challenging tasks for engineers and soil scientists, especially the complex hydrological processes that combine key variables such as soil moisture, matric suction, and soil temperature. …”
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Hypercubes to identify geomarkers of rapid cystic fibrosis lung disease progression by Yizi Cheng, Cole Brokamp, Erika Rasnick Manning, Elizabeth L. Kramer, Patrick H. Ryan, Rhonda D. Szczesniak, Emrah Gecili

“…Methods We adapted an existing statistical procedure, which arranges candidate variables in a k-dimensional hypercube, where the hypercube forms a set of variables for a multi-stage selection process involving complex longitudinal data. …”
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A Moroccan soil spectral library use framework for improving soil property prediction: Evaluating a geostatistical approach by Tadesse Gashaw Asrat, Timo Breure, Ruben Sakrabani, Ron Corstanje, Kirsty L. Hassall, Abdellah Hamma, Fassil Kebede, Stephan M. Haefele

“…Notably, the Lin’s Concordance Correlation Coefficient (CCC) values using the spatial calibration sample selection was improved for Olsen extractable phosphorus (OlsenP) by 41.3% and Mehlich III extractable phosphorus (P_M3) by 8.5% for the MIR spectra and for CEC by 25.6%, pH by 13.0% and total nitrogen (Tot_N) by 10.6% for the NIR spectra in reference to use of the entire MSSL. …”
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Solvent Extraction And Spectrophotomteric Determination Of Cu(Ii) With Dicyclohexyl - 18- Crown-6 by Baghdad Science Journal

“…The method obeys Beer`s law over range from (2.5-22.5) ppm with the correlation coefficient of 0.9989. The molar absorptivity the stoichiometry of extracted complex is found to be 1:2. the proposed method is very sensitive and selective.…”
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