Study on Missing Data Filling Algorithm of Nuclear Power Plant Operation Parameters by Tianshu Wang, Ren Yu, Qiao Peng

“…In order to improve the data quality, two parts of researches are carried on. …”
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Feasibility of Output-Only Modal Identification Using Wireless Sensor Network: A Quantitative Field Experimental Study by Wen-ai Shen, Ying Lei, Liang Hu, Yang Wang

“…This paper first assesses the accuracy of time synchronization performed by the WSN through a centralized beacon signal and then studies wireless data quality using two quantitative performance indexes. …”
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A Review of Multi-Source Data Fusion and Analysis Algorithms in Smart City Construction: Facilitating Real Estate Management and Urban Optimization by Binglin Liu, Qian Li, Zhihua Zheng, Yanjia Huang, Shuguang Deng, Qiongxiu Huang, Weijiang Liu

“…We found that multi-source data, including sensors, social media, citizen feedback, and GIS data, face challenges such as data quality and privacy security when being fused. Data fusion algorithms are diverse and have their own advantages and disadvantages. …”
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Neonatal indicator data in Tanzania District Health Information System: evaluation of availability and quality of selected newborn indicators, 2015-2022 by Josephine Shabani, Nahya Salim, Christine Bohne, Louise Tina Day, Claud Kumalija, Ahmad Mohamed Makuwani, Felix Bundala, Habib Ismail, Joy E. Lawn, Eric O. Ohuma

“…Placing greater emphasis on using DHIS2 data to monitor progress will help identify gaps and drive improvements in data quality, ultimately supporting better maternal and newborn health outcomes.…”
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Prevalence of overweight/obesity and its association with fast food consumption among adolescents in Southern Ethiopia, 2022: a community-based cross-sectional study by Chernet Elias, Awoke Abraham, Chernet Asrat, Tagese Yakob, Daniel Girma

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Transforming precision medicine: The potential of the clinical artificial intelligent single‐cell framework by Christian Baumgartner, Dagmar Brislinger

“…Despite its potential, caiSC lacks comprehensive data coverage across cell types and diseases, presenting challenges in data quality and model robustness. The article explores development strategies such as data expansion, machine learning advancements, and interpretability improvements. …”
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Advances in Biomedical Missing Data Imputation: A Survey by Miriam Barrabes, Maria Perera, Victor Novelle Moriano, Xavier Giro-I-Nieto, Daniel Mas Montserrat, Alexander G. Ioannidis

“…Missing values compromise data quality and can make it difficult to perform data-based studies. …”
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Open Data Release and Privacy Concerns: Complexity in Mitigating Vulnerability with Controlled Perturbation by Shah Imran Alam, Ihtiram Raza Khan, Syed Imtiyaz Hassan, Farheen Siddiqui, M. Afshar Alam, Anil Kumar Mahto

“…We discussed the gap and reported the benefits and loss with various combinations of K and l values, taken in combination with released data quality from an analyst’s perspective. We first used dummy fictitious data to explain the general expectations and then concluded the contrast in the findings with the real data from the food technology domain. …”
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Komparasi Kinerja Algoritma Blocking Pada Proses Indexing Untuk Deteksi Duplikasi by M. Miftakul Amin, Yevi Dwitayanti

“…Abstract   The process of integrating data from heterogeneous data sources requires good data quality. One of the characteristics of good data quality is avoiding data duplication. …”
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Automated skin lesion detection and prevalence estimation in Tamanend's bottlenose dolphins by Colin J. Murphy, Melissa A. Collier, Ann-Marie Jacoby, Eric M. Patterson, Megan M. Wallen, Janet Mann, Shweta Bansal

“…On the other hand, we find that individual-level analyses from the model predictions may be more sensitive to data quality, and thus, some individual scale questions may not be feasible to address if data quality is inconsistent. …”
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Historical Databases, Big and Small by Peter Doorn

“…Not only the volume of data defines if data is 'Big', but three more Vs characterise the term: velocity (speed of data generation and processing), veracity (referring to data quality) and variety. Perhaps the most defining is methodological: data becomes really big when new methods are needed to process and analyse it. …”
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Les observatoires de la mer et du littoral : du suivi des interactions hommes-milieux à la coordination des acteurs by Jean-Michel Salles, Hélène Rey Valette, Rémi Mongruel

“…In addition, it also addresses the issue of data quality and the legitimacy of the standards against which monitoring is carried out. …”
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Quality of routine malaria data captured at primary health facilities in the Hohoe Municipality, Ghana by Christopher Ayisah, Thywill Worlase Kpenu, Edem Kojo Dzantor, Clement Tetteh Narh

“…Although, half of the facilities showed evidence of good data quality, there is still a need for improvement in the capturing of routine malaria data.…”
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Insights gained through real-time monitoring of porcine reproductive and respiratory syndrome virus and description of temporal trends based on laboratory data in Ontario, Canada by Tatiana Petukhova, Maria Spinato, Tanya Rossi, Michele T. Guerin, Cathy A. Bauman, Pauline Nelson-Smikle, Davor Ojkic, Zvonimir Poljak

“…Most farms contributed one submission per week or per month for PRRSV testing (median: 1 submission per week; IQR: 0; max: 13; median: 1 submission per month; IQR: 1, max: 31). Epidemiological data quality showed considerable improvements over the 9 years of investigation. …”
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The assessment of routine health information system performance towards improvement of quality of reproductive, maternal, newborn, child and adolescent health services in Ondo and... by Victoria Oladoyin, Sunday Adedini, Kayode Ijadunola, Hassan Ogunwemimo, Olubunmi Folorunso, Elizabeth Chukwu, Ugo Okoli, Anthony Adoghe, Samuel Oyeniyi, Oniyire Adetiloye, Adesegun Fatusi

“…Performance of routine HMIS for RMNCAEH+N QoC in terms of data collection, data quality, and data use were analysed using univariate and bivariate statistics.…”
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Epigenetic variation in light of population genetic practice by Sarah A. Mueller, Justin Merondun, Sonja Lečić, Jochen B. W. Wolf

“…Efforts to advance data quality, study design, and statistical treatment are encouraged to consolidate our understanding of the source of heritable epigenetic variation, quantify its autonomous potential for evolution, and enrich population genetic analyses with an additional layer of information.…”
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Development and application of a clinical core data set for deep brain stimulation in Parkinson’s disease, dystonia or tremor: from data collection to data exchange and data sharin... by Anna-Lena Hofmann, Jonas Widmann, Lilly Brandstetter, Udo Selig, Fabian Haug, Julian Haug, Rüdiger Pryss, Jasper Mecklenburg, Andrea Kreichgauer, Philipp Capetian, Christian J. Hartmann, Christian Niklas, Petra Ritter, Patricia Krause, Alfons Schnitzler, Jens Volkmann, Andrea A. Kühn, Peter Heuschmann, Kirsten Haas

“…The development followed standardized methodology comprising review of available evidence, a consensus process and performance of the first phase of the study. To ensure high data quality, measures for standardized training, monitoring as well as plausibility and data quality tests were implemented. …”
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Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future by Vasileios Leivaditis, Eleftherios Beltsios, Athanasios Papatriantafyllou, Konstantinos Grapatsas, Francesk Mulita, Nikolaos Kontodimopoulos, Nikolaos G. Baikoussis, Levan Tchabashvili, Konstantinos Tasios, Ioannis Maroulis, Manfred Dahm, Efstratios Koletsis

“…Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. …”
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Seamless Integration of RESTful Services into the Web of Data by Markus Lanthaler, Christian Gütl

“…By embracing the heterogeneity, which is unavoidable at such a scale, and accepting the fact that the data quality and meaning are fuzzy, more adaptable, flexible, and extensible systems can be built. …”
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PENERAPAN ARTIFICIAL INTELLIGENCE (AI) DALAM PERAMALAN AKUNTANSI TINJAUAN LITERATUR DAN AGENDA PENELITIAN MASA DEPAN by Gilang Surya Pratama, Agus Munandar

“…Major implementation challenges include data quality, infrastructure limitations, and data security. …”
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