A parameter uniform hybrid approach for singularly perturbed two-parameter parabolic problem with discontinuous data by N. Roy, A. Jha

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Deep learning with data transformation improves cancer risk prediction in oral precancerous conditions by John Adeoye, Yuxiong Su

“…Overall, decision curve analysis showed that the optimal DL models with transformed data had a higher net benefit than random forest and binary dysplasia grading. …”
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Prioritization of potential drug targets for diabetic kidney disease using integrative omics data mining and causal inference by Junyu Zhang, Jie Peng, Chaolun Yu, Yu Ning, Wenhui Lin, Mingxing Ni, Qiang Xie, Chuan Yang, Huiying Liang, Miao Lin

“…Our prospective study confirmed that higher levels of three prioritized targets—insulin-like growth factor binding protein 4 (IGFBP4), family with sequence similarity 3 member C (FAM3C), and prostaglandin D2 synthase (PTGDS)—were associated with a 4.35, 3.51, and 3.57-fold increased likelihood of developing DKD, respectively. In addition, population-level protein-altering variants (PAVs) analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD, through the classic NLR family pyrin domain containing 3 (NLRP3)-caspase-1-gasdermin D (GSDMD) apoptotic axis. …”
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An overview of big data analytics application in supply chain management published in 2010-2019 by Iman Ghalehkhondabi, Ehsan Ahmadi, Reza Maihami

“…These publications have increasingly focused on big data applications in predictive analysis, rather than in the other three types of data analysis: descriptive analysis, diagnostic analysis, and prescriptive analysis. …”
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Methodology for Assessing the Transport Accessibility of Capital Objects in a Megacity Based on Geoinformation Data by S. V. Mkhitaryan, Zh. B. Musatova, T. V. Murtuzalieva, G. S. Timokhina, I. P. Shirochenskaya

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“Education 4.0” in the Era of Digital Transformation: Ways to Improve Its Efficiency by F. T. Aghayev, G. A. Mammadova, R. T. Malikova

“…The purpose of this article is to show the evolution and requirements of the educational system in the era of the fourth industrial revolution, to identify the main problems, to identify current areas for further research.The fourth industrial revolution bases its development on smart technologies, artificial intelligence, big data, robotics, etc. …”
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Improvement of table tennis technology based on data mining in the environment of wireless sensor networks by Hongjian Ma

“…Then establishing a data mining model to realize the data and dynamic analysis of table tennis matches. …”
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Optimized workflow for behavior-coupled fiber photometry experiment: improved data navigation and accessibility by Anna Athanassi, Amaury François, Emmanuel Bourinet, Marc Thevenet, Nathalie Mandairon

“…We developed here a workflow starting from the intracerebral implantation of optical fibers in mice, to the analysis of fiber photometry signals, aligned with recorded behavioral data. …”
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Sports Broadcasting: How Big Data Technology Impacts the Viewer Experience in Baseball Broadcasting by Pi-Yun An

“…Through systematic analysis and understanding of the data collection and utilization of big data in the USA and Taiwan, the results of this study provide the basis for the application and technical capabilities of big data analysis in Taiwanese baseball broadcasting in the future.…”
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Sustainable Urban Land Management Based on Earth Observation Data—State of the Art and Trends by Elzbieta Bielecka, Anna Markowska, Barbara Wiatkowska, Beata Calka

“…This paper aims to analyze and synthesize research on sustainable urban land management (SULM) based on earth observation (EO) data. Particular attention is given to the intellectual foundations and emerging trends in the field. …”
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The role of nature-conformity presentation of data in the creation of an information system for the management of science and education by Sergey A. Saltykov, Elena Yu. Rusyaeva

“…The following issues were developed in the research: a structural and semantic analysis of the concept of «open data» was carried out; examples of successful work with open data are presented to the discussion by various organizations - state, commercial, banking, etc.…”
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Benefits and risks of health data reuse for healthcare providers: stakeholder perspectives from a qualitative interview study by Susanne Stark, Susanne Gabriele Schorr, Merle-Marie Pittelkow, Daniel Strech

“…Current ethical discussions on developing health data platforms (e.g. the German Medical Informatics Initiative, MII) have primarily addressed patient-related benefits and risks of reusing this data. …”
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E-Commerce Enterprise Supply Chain Cost Control under the Background of Big Data by Haijun Mao, Long Chen

“…Since the twentieth century, it has been an era of rapid development of information technology; the scale of data is almost the growth rate of the blowout type; no matter what it is, a large number of enterprises or departments are increasing a large number of cost data. …”
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On Hierarchical Bayesian Spatial Small Area Model for Binary Data under Spatial Misalignment by Kindie Fentahun Muchie, Anthony Kibira Wanjoya, Samuel Musili Mwalili

“…Model-based Bayesian analysis is popular for its ability to combine information from several sources as well as taking account uncertainties in the analysis and spatial prediction of spatial data. …”
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Design of Enterprise Economic Information Management System Based on Big Data Integration Algorithm by Xiao Liu

“…Based on the analysis of the current status of enterprise big data application, this paper constructs an enterprise economic informational management system based on big data and also describes in detail the key technologies of enterprise economic informational data management from three aspects: NoSQL-based big data storage management, Hadoop-based economic informational big data informational and economic informational big data analysis, and mining algorithm. …”
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Leveraging data science to understand and address multimorbidity in sub-Saharan Africa: the MADIVA protocol by Kobus Herbst, Stephen Tollman, Kathleen Kahn, Francesc Xavier Gómez-Olivé, Jaya George, Catherine Kyobutungi, Karen Hofman, Gershim Asiki, Michèle Ramsay, Daniel Ohene-Kwofie, Chodziwadziwa W Kabudula, Helen Robertson, Isaac Kisiangani, Palwende Boua, Eric Maimela, Damazo T Kadengye, Michelle Kamp, Daniel Maina Nderitu, Phelelani Thokozani Mpangase, Kayode Adetunji, Samuel Iddi, Skyler Speakman, Scott Hazelhurst, Kerry Glover, Tabitha Osler, Tanya Akumu, Diana Awuor, Victoria Bronstein, Joan Byamugisha, Jacques D Du Toit, Barry Dwolatzky, Paul A Harris, Celeste Holden, Nhlamulo Khoza, Faith Kimongo, Dekuwin E Kogda, Michael Klipin, Stephen P Levitt, Dylan Maghini, Karabo Maila, Ndivhuwo Makondo, Molulaqhooa Linda Maoyi, Reineilwe Given Mashaba, Nkosinathi Gabriel Masilela, Theophilous Mathema, Daphine T Nyachowe, Evelyn Thsehla, Siphiwe A Thwala, Roy Zent, Patrick Opiyo Owili

“…The Multimorbidity in Africa: Digital Innovation, Visualisation and Application Research Hub (MADIVA) aims to address MM by developing data science solutions informed by stakeholder engagement.Methods and analysis MADIVA uses complex, individual-level datasets from research centres in rural Bushbuckridge, South Africa and urban Nairobi, Kenya. …”
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Risk of AI Algorithmic Discrimination Embedded in Government Data Governance and Its Prevention and Control by PENG Lihui, ZHANG Qiong, LI Tianyi

“…[Purpose/Significance] The purpose of this study is to provide an in-depth analysis of the widespread application of artificial intelligence (AI) technology in the field of government data governance and its far-reaching implications, with a particular focus on the core issue of algorithmic discrimination. …”
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A Monte Carlo Simulation Study to Assess Estimation Methods in CFA on Ordinal Data by Nina Fitriyati, Madona Yunita Wijaya

“…Two robust estimators, i.e., unweighted least square (ULS) and diagonally weighted least square (DWLS) have been developed to deal with ordinal data in confirmatory factor analysis (CFA). …”
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Applying Big Data Analytics to Monitor Tourist Flow for the Scenic Area Operation Management by Siyang Qin, Jie Man, Xuzhao Wang, Can Li, Honghui Dong, Xinquan Ge

“…The analysis shows that the big data analysis method based on the CDR data of mobile phones can provide real-time information about tourist behaviours in a timely and effective manner. …”
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Non-Monetary Incentives for Participatory Sensing Data Collection: A Sequential Explanatory Design by Syarulnaziah Anawar, Wan Adilah Wan Adnan

“…The purpose of this paper is to examine the influence of non-monetary incentives for data collection in participatory sensing. Sequential explanatory design is employed where the study integrates both quantitative and qualitative data analysis. …”
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