Value mining and application of big data in enterprise power credit investigation by Baojiang XIN, Dewen LI, Lanlan WANG

“…Aiming at the shortcomings of traditional power credit investigation platform such as insufficient stability and low test accuracy, a big data power credit investigation platform was designed.The online analytical method was used to analyze power big data, which was divided into four categories: user behavior, expense rules, user value and personal credit.Based on the modular structure, the data acquisition module, data analysis module and user interaction module were optimized respectively.The KNN and cross validation method were used to classify and process the power consumption data, and the regional power consumption law was obtained, so as to design and adjust the distribution scheme.Finally, the platform was compared with the traditional power credit investigation platform.The experimental results show that the stability and accuracy of the platform are improved, and the accuracy is as high as 98.9% during the test.…”
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A Hybrid Regression–Kriging–Machine Learning Framework for Imputing Missing TROPOMI NO₂ Data over Taiwan by Alyssa Valerio, Yi-Chun Chen, Chian-Yi Liu, Yi-Ying Chen, Chuan-Yao Lin

“…As the first RK–ML application for TROPOMI data in Taiwan, this study establishes a regional benchmark and offers a transferable methodology for satellite data imputation. …”
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Simulation Comparison of Different Cooling Modes of Blade Server in Data Centers by Liu Shengchun, Liu Zhang, He Wei, Jia Ziang, Luo Yilin, Zhu Kai

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Prediction of ball-on-plate friction and wear by ANN with data-driven optimization by Alexander Kovalev, Yu Tian, Yonggang Meng

“…To predict sliding friction and wear at mixed lubrication conditions, in this study a specific ANN structure was so designed that deep learning algorithms and data-driven optimization models can be used. …”
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Automatic control of air temperature in the greenhouse considering the weather forecast data by A. G. Senkov

“…The article proposes a method based on the principle of disturbance compensation using weather forecast data. The plant dynamic model structure is described by the linear 1st order aperiodic link with delay both for the control circuit and for the disturbance circuit. …”
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Design and verification of HDLC data frame parallel search and decapsulation module by Qian Yong, Liu Wei

“…The article follows the HDLC standard data link layer specification, uses the hardware description language Verilog HDL to implement a parallel structure-based HDLC frame search and decapsulation circuit, and uses System Verilog technology to build a verification platform, and randomly generates HDLC data frames to verify the correctness of the design. …”
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Data-Driven Photovoltaic System Modeling Based on Nonlinear System Identification by Ayedh Alqahtani, Mohammad Alsaffar, Mohamed El-Sayed, Bader Alajmi

“…The data are divided into estimation and validation sets. …”
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High-performance federated continual learning algorithm for heterogeneous streaming data by Hui JIANG, Tianliu HE, Min LIU, Sheng SUN, Yuwei WANG

“…Aiming at the problems of poor model performance and low training efficiency in training streaming data of AI models that provide intelligent services, a high-performance federated continual learning algorithm for heterogeneous streaming data (FCL-HSD) was proposed in the distributed terminal system with privacy data.In order to solve the problem of the current model forgetting old data, a model with dynamically extensible structure was introduced in the local training stage, and an extension audit mechanism was designed to ensure the capability of the AI model to recognize old data at the cost of small storage overhead.Considering the heterogeneity of terminal data, a customized global model strategy based on data distribution similarity was designed at the central server side, and an aggregation-by-block manner was implemented for different modules of the model.The feasibility and effectiveness of the proposed algorithm were verified under various data increment scenarios with different data sets.Experimental results show that, compared with existing works, the proposed algorithm can effectively improve the model performance to classify old data on the premise of ensuring the capability to classify new data.…”
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Analysis of Organizational Factors Promoting Data Utilization in Large Japanese Corporations by Kazuo Yagura

“…Building upon research on Big Data Analytics Capabilities, as represented by Gupta and George (2016), we categorized corporate structure into three primary organizational segments: “Data Utilization Organization,” “Executive/Corporate Level,” and “Business Units.” …”
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Entropy techniques for robust management decision making in high-dimensional data by Jan Kalina

“…This suggests that managerial decision-making processes should reflect the inherent fractal structure present in the given multivariate data. The work emphasizes the importance of considering fractal characteristics in managerial decision-making, thereby advancing the applicability and effectiveness of entropy-based methods in management science.…”
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Human development, inequality, and their associations with brain structure across 29 countries by Vicente Medel, Luz M. Alliende, Richard Bethlehem, Jakob Seidlitz, Grace Ringlein, Celso Arango, Aurina Arnatkevičiūtė, Laila Asmal, Mark Bellgrove, Vivek Benegal, Miquel Bernardo, Pablo Billeke, Jorge Bosch-Bayard, Rodrigo Bressan, Geraldo Busatto, Mariana Castro, Tiffany Chaim-Avancini, Monise Costanzi, Leticia Czepielewski, Paola Dazzan, Camilo de la Fuente-Sandoval, Covadonga M. Diaz-Caneja, Marta Di Forti, Ana Maria Diaz-Zuluaga, Stefan Du Plessis, Fabio Duran, Sol Fittipaldi, Alex Fornito, Nelson Freimer, Ary Gadelha, Clarissa Gama, Ranjini Garani, Clemente Garcia-Rizo, Cecilia Gonzalez Campo, Alfonso Gonzalez-Valderrama, Salvador Guinjoan, Bharath Holla, Agustin Ibañez, Daniza Ivanovic, Andrea Jackowski, Pablo Leon-Ortiz, Christine Lochner, Carlos Lopez-Jaramillo, Hilmar Luckhoff, Raffael Massuda, Philip McGuire, Jun Miyata, Romina Mizrahi, Robin Murray, Aysegul Ozerdem, Pedro Pan, Mara Parellada, Lebogang Phahladira, Juan P. Ramirez-Mahaluf, Ramiro Reckziegel, Tiago Reis Marques, Francisco Reyes-Madrigal, Annerine Roos, Pedro Rosa, Giovanni Salum, Freda Scheffler, Gunter Schumann, Mauricio Serpa, Dan J. Stein, Angeles Tepper, Jeggan Tiego, Tsukasa Ueno, Juan Undurraga, Eduardo A Undurraga, Pedro Valdes-Sosa, Isabel Valli, Mirta Villarreal, Toby T Winton-Brown, Nefize Yalin, Francisco Zamorano, Marcus Zanetti, Anderson M Winkler, Sara Evans-Lacko, Nicolas A. Crossley

“…We aimed to determine the association between the level of development and inequality of a country and the brain structure of healthy adults. Methods We conducted a cross-sectional study pooling brain imaging (T1-based) data from 145 magnetic resonance imaging (MRI) studies in 7,962 healthy adults (4,110 women) in 29 different countries. …”
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Understanding AI adoption among secondary education teachers: A pls-sem approach by Marta López-Costa, Belén Donate-Beby, Natividad Cabrera-Lanzo, Marcelo Fabián Maina

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Advanced predictive modeling of shear strength in stainless-steel column web panels using explainable AI insights by Sina Sarfarazi, Rabee Shamass, Federico Guarracino, Ida Mascolo, Mariano Modano

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University students' self-assessment of data literacy: A validation study. by Jeonghyun Kim, Lingzi Hong, Ayoung Yoon

“…Understanding and evaluating the factors that shape an individual's data literacy is important for benchmarking proficiency and tailoring curricula, yet the underlying components and structure of data literacy for students in four-year institutions are unknown. …”
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High-performance federated continual learning algorithm for heterogeneous streaming data by Hui JIANG, Tianliu HE, Min LIU, Sheng SUN, Yuwei WANG

“…Aiming at the problems of poor model performance and low training efficiency in training streaming data of AI models that provide intelligent services, a high-performance federated continual learning algorithm for heterogeneous streaming data (FCL-HSD) was proposed in the distributed terminal system with privacy data.In order to solve the problem of the current model forgetting old data, a model with dynamically extensible structure was introduced in the local training stage, and an extension audit mechanism was designed to ensure the capability of the AI model to recognize old data at the cost of small storage overhead.Considering the heterogeneity of terminal data, a customized global model strategy based on data distribution similarity was designed at the central server side, and an aggregation-by-block manner was implemented for different modules of the model.The feasibility and effectiveness of the proposed algorithm were verified under various data increment scenarios with different data sets.Experimental results show that, compared with existing works, the proposed algorithm can effectively improve the model performance to classify old data on the premise of ensuring the capability to classify new data.…”
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Data‐driven Buck converter model identification method with missing outputs by Jie Hou, Xinhua Zhang, Huiming Wang, Shiwei Wang

“…Based on the recovered data, the subspace identification method provides accurate estimates of the structure and parameter of the Buck converter synchronously. …”
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Structures of Community Life in Portuguese Home-Villages: Two Case Studies by Ana Bordalo

“… This study aims to investigate the structures of community life in Portuguese Home-Villages and the consequences of an ageing demographic population; the need to implement home structures for the elderly and on how these can contribute to a revitalization of the depopulated territories. …”
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Analysis of Linkage Effects among Currency Networks Using REER Data by Haishu Qiao, Ying Li, Yue Xia

“…In particular, and as the source of empirical data, we chose the monthly REER data for a set of 61 major currencies during the period from 1994 to 2014. …”
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Analysis and Evaluation of Competence of Information Sources in Problems of Intellectual Data Processing by Krisilov V. A., Komleva N. O.

“…The issues of work related to solving problems of intellectual data processing is to increase the efficiency of qualimetry, classification, diagnostics, choice, decision making, forecasting, tax-onomy, etc., using data mining algorithms and a statistical approach. …”
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Optimum Resolution Bandwidth for Spectral Analysis of Stationary Random Vibration Data by Allan G. Piersol

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