Application of Collective Intelligence of Artificial Bee Colony Algorithm in Optimization of Estimation and Zoning of Wind Erosion Intensity Using Geomorphological data (Case Study: Birjand Plain’s Drainage Basin, South Khorasan Province) by Mehdi Saghafi, Moohamadali Moodaresi

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Assessing the Applicability of Random Forest, Stochastic Gradient Boosted Model, and Extreme Learning Machine Methods to the Quantitative Precipitation Estimation of the Radar Data: A Case Study to Gwangdeoksan Radar, South Korea, in 2018 by Ju-Young Shin, Yonghun Ro, Joo-Wan Cha, Kyu-Rang Kim, Jong-Chul Ha

“…Machine learning algorithms should be tested for use in quantitative precipitation estimation models of rain radar data in South Korea because such an application can provide a more accurate estimate of rainfall than the conventional ZR relationship-based model. …”
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MIMD Programs Execution Support on SIMD Machines: A Holistic Survey by Dheya Mustafa, Ruba Alkhasawneh, Fadi Obeidat, Ahmed S. Shatnawi

“…It provides performance throughput in computation-intensive and data-parallel applications. Despite the similarity of data-processing principles between these architectures, porting various programming models between the reviewed platforms is challenging. …”
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Critical and creative pedagogies for artificial intelligence and data literacy: an epistemic data justice approach for academic practice by Javiera Atenas, Leo Havemann, Chrissi Nerantzi

“…Our methodology employs a triangulation model: initially, we conduct interpretative analyses of literature to gauge best practices for curriculum development in HE; then, we examine frameworks in data justice and ethics to identify principles and skills applicable to undergraduate, postgraduate and academic development programs; finally, we explore proposals for critical, creative, ethical, open and innovative ideas for educators to integrate data and AI into their practice.…”
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Deep Web new data discovery strategy based on the graph model of data attribute value lists by Zhi-ming CUI, Peng-peng ZHAO, Xue-feng XIAN, Li-gang FANG, Yuan-feng YANG, Cai-dong GU

“…A novel deep Web data discovery strategy was proposed for new generated data record in resources.In the ap-proach,a new graph model of deep Web data attribute value lists was used to indicate the deep Web data source,an new data crawling task was transformed into a graph traversal process.This model was only related to the data,compared with the ex-isting query-related graph model had better adaptability and certainty,applicable to contain only a simple query interface of deep Web data sources.Based on this model,which could discovery incremental nodes and predict new data mutual infor-mation was used to compute the dependencies between nodes.When the query selects,as much as possible to reduce the negative impact brought by the query-dependent.This strategy improves the data crawling efficiency.Experimental results show that this strategy could maximize the synchronization between local and remote data under the same restriction.…”
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A Data-Driven Approach for Urban Heat Island Predictions: Rethinking the Evaluation Metrics and Data Preprocessing by Berk Kıvılcım, Patrick Erik Bradley

“…A 2D raster data representing building volumes of each grids are derived from 3D vector-format urban data for use in machine learning applications. …”
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A Signature-Based Data Security Technique for Energy-Efficient Data Aggregation in Wireless Sensor Networks by Min Yoon, Miyoung Jang, Hyeong-Il Kim, Jae-Woo Chang

“…They can conserve the significant amount of energy by reducing data packet transmission costs. However, many data aggregation applications require privacy and integrity protection of the real data while transmitting data from the sensing nodes to a sink node. …”
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Privacy-Preserving Modeling of Trajectory Data: Secure Sharing Solutions for Trajectory Data Based on Granular Computing by Yanjun Chen, Ge Zhang, Chengkun Liu, Chunjiang Lu

“…Meanwhile, this work demonstrates the practical applications of the solution for the secure sharing of trajectory data. …”
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Data-driven thermal analysis of indoor cooling for a thermoelectric radiant panel systemMendeley Data by Muhammad ‘Amir Roslan, Farah Liana Mohd Redzuan

“…This study contributes to the development of sustainable cooling solutions and supports further research in thermoelectric cooling applications.…”
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Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data by Mohammad Alemi, Alireza Bosaghzadeh, Fadi Dornaika

“…Thirdly, existing models often struggle with predicting labels for unseen test data, restricting their utility in practical applications. …”
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Population data of 23 Y chromosome STR loci for Kyrgyz population from KyrgyzstanMendeley Data by Zhainagul Isakova, Alizhan Bukayev, Moldobek Irsaliev, Zhaxylyk Sabitov, Maxat Zhabagin

“…This dataset enhances our understanding of Kyrgyz genetic diversity, contributes to forensic applications, and fills a critical gap in population genetic research on Central Asian lineages.…”
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Validating Data Interpolation Empirical Orthogonal Functions Interpolated Soil Moisture Data in the Contiguous United States by Haipeng Zhao, Haoteng Zhao, Chen Zhang

“…However, the current 1-km product contains substantial data gaps, which poses challenges for applications that require continuous daily data. …”
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Trans-Border Trusted Data Spaces: A General Framework Supporting Trustworthy International Data Circulation by Chi Zhang, Yan Liu, Mudi Xu, Xingxing Yang, Peng Li, Changshui Yang, Qiang Liu, Xinning Xiong, Pan Chen, Wenyong Wang

“…To address this, we have taken “traceable, accountable, and multiparty compliant data-sharing” as design principles and propose a Trans-border Trusted Data Spaces (TTDS) framework. …”
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A hybrid steganography framework using DCT and GAN for secure data communication in the big data era by Kaleem Razzaq Malik, Muhammad Sajid, Ahmad Almogren, Tauqeer Safdar Malik, Ali Haider Khan, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

“…By leveraging deep learning techniques in both spatial and frequency domains, the proposed hybrid architecture offers a robust solution for applications requiring high levels of data integrity and security. …”
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An on‐chain trading model of real world asset backed digital assets by Dongsheng Hou, Wenjing Ma, Wei Zhang, Yixuan Li, Yu Du, Yukun Hao

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Blocked algorithm of finding all-pairs shortest paths in graphs divided into weakly connected clusters by O. N. Karasik, A. A. Prihozhy

“…The problem of finding all shortest paths between vertices in a graph (APSP) has real-life applications in planning, communication, economics and many other areas. …”
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Image dataset: UAV images and ground data of one ‘Bingo’ mandarin and two ‘Valencia’ orange rootstock trials conducted in FloridaAg Data CommonsAg Data Commons by Randall P. Niedz, Kim D. Bowman

“…The combination of ground validated measures and aerial images make this data set useful for building AI-based aerial image data collection applications. …”
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Research on the mechanism and key technologies for big data collection in education by Huanyou CHAI, Sannyuya LIU, Lingyun KANG, Yaxian ZHANG, Qing LI, Zhi LIU

“…The mechanism and its related technologies of data collection are the foundation of realizing the valuable potential of applying big data in education,and therefore are vital for the construction and application of big data in education.The contents,methods,means,standards and specifications of data collection of big data in education were outlined.Combining with the practical problems in the construction and application of big data in education,guidance on research on big data in education was provided,from the perspectives about balancing data sharing and privacy protection,driving data governance and talent acquisition,and improving the mechanisms and related technologies respectively.…”
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Industrial big data technologies and architecture by Shuquan ZHENG, Haihuan QIN, Qian WANG

“…Industrial big data is an important asset of industrial enterprises.It is a crucial factor for an industrial enterprise to realize transformation and upgrading.The main sources and characteristics of industrial big data were analyzed,and reference architecture of industrial big data with three dimensions was proposed.Three aspects of the realization of business innovation and transformation of industrial enterprise based on industrial big data respectively were discussed,which included the typical application and business innovation of enterprise,cyber (physical) systems deployed at all levels of the enterprise,and the business architecture,information systems architecture and IT architecture that guide the implementation of application of industrial big data.Finally,the architecture and technology of a typical application of industrial big data were analyzed,which verified the validity of the proposed architecture.…”
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A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques by Azka Mir, Attique Ur Rehman, Tahir Muhammad Ali, Sabeen Javaid, Maram Fahaad Almufareh, Mamoona Humayun, Momina Shaheen

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