An Optimized Data Obtaining Strategy for Large-Scale Sensor Monitoring Networks by Yan Wang, Junlu Wang, Fengtong Wang, Ling Wang, Wei Wei

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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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Physics-based and data-driven hybrid modeling in manufacturing: a review by Sathish Kasilingam, Ruoyu Yang, Shubhendu Kumar Singh, Mojtaba A. Farahani, Rahul Rai, Thorsten Wuest

“…Sensors, connectivity, and platforms provide unprecedented access to quantify the quality and diversity of manufacturing data. Progress in data-driven modeling is exponential across all industries. …”
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Low Power OFDM Receiver Exploiting Data Sparseness and DFT Symmetry by Nikos Petrellis

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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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Anomaly traffic detection method based on data augmentation and feature mining by AN Yishuai, FU Yu, YU Yihan, LIU Taotao

“…Secondly, a feature correlation matrix was calculated using the Pearson correlation coefficient, transforming traffic data into graph-structured representations to construct a graph dataset. …”
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Insights from the South Sector at Histria. New archaeological and anthropological data by Crețu, C., Dabîca, M., Soficaru, A.

Fatigue Life Evaluation of Wind Turbine Tower Based on Measured Data by Yan Zhao, Xiaolu Li, Xinwu Wang, Jianqun Jiang, Zhenyu Wang

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Regularization for Unconditional Image Diffusion Models via Shifted Data Augmentation by Kensuke Nakamura, Bong-Soo Sohn, Simon Korman, Byung-Woo Hong

“…Diffusion models are a powerful class of techniques in ML for generating realistic data, but they are highly prone to overfitting, especially with limited training data. …”
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A Multisource Retrospective Audit Method for Data Quality Optimization and Evaluation by Li Jiang, Hao Chen, Yueqi Ouyang, Canbing Li

“…The heterogeneous data integration model based on retrospective audit is divided into four modules including original heterogeneous data, data structure, data processing, and data retrospective audit. …”
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ADOPTION OF IOT AND BIG DATA IN SHAPING AND ENHANCING ORGANIZATIONAL CITIZENSHIP BEHAVIOR by Pooja Kanojia, Rupa Khanna Malhotra, Amit Kumar Uniyal, Tannupriya Chaudhary

“…This paper focuses on the effect of demographic dimensions of organizational citizenship behavior (OCB) on the faculty of the HEIs of North West India. A structured questionnaire was adopted by (Podsakoff. et. al. 2000) and was circulated online to gather data from 309 faculties of the HEIs of North West India. …”
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A comparison of the Slovenian public librarianship based on the data of the Libecon study by Matjaž Žaucer

“…Abstract Focusing on economic aspects, the article compares the current state of librarianship in Slovenia to the average situation in the 15 old EU members and to the average situation in the 10 new EU members. Our data derive from the Libecon study for the year of 2001, as well as from other sources. …”
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Detecting global financial crises with scarce data by multivariate nonlinear filtering by Cécile Bastidon, Antoine Parent, Patrice Abry, Pierre Borgnat, Pablo Jensen, Barbara Pascal

“…Finally it is robust to scarce, incomplete and noisy data.…”
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Deep Learning Joint Inversion of Electrical Data for Ahead-Prospecting in Tunneling by Peng Jiang, Benchao Liu, Chuanwu Wang, Lei Chen, Yuting Tang

“…Among various advanced forecasting techniques, the direct current method is more cost-effective and sensitive to water-bearing structures. It has been widely used in exploring water inrush disasters in practical engineering. …”
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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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Optimizing Data Filtering in Multi-Armed Bandit Algorithms for Reinforcement Learning by Zhang Shengshi

“…This study investigates the performance of data filtering algorithms in multi-armed bandit (MAB) problems for reinforcement learning applications. …”
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