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Journal articles on the topic 'Data incompleteness'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Acharya, Nanyan V., Lynda V. Wilton, and Saad A. Shakir. "Incompleteness of Lamotrigine Data." Drug Safety 24, no. 2 (2001): 155–56. http://dx.doi.org/10.2165/00002018-200124020-00005.

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Messenheimer, John A., Marcus E. Risner, and Luigi Giorgi. "Incompleteness of Lamotrigine Data." Drug Safety 24, no. 2 (2001): 155–56. http://dx.doi.org/10.2165/00002018-200124020-00006.

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3

Muris, Chris. "Efficient GMM Estimation with Incomplete Data." Review of Economics and Statistics 102, no. 3 (2020): 518–30. http://dx.doi.org/10.1162/rest_a_00836.

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In the standard missing data model, data are either complete or completely missing. However, applied researchers face situations with an arbitrary number of strata of incompleteness. Examples include unbalanced panels and instrumental variables settings where some observations are missing some instruments. I propose a model for settings where observations may be incomplete, with an arbitrary number of strata of incompleteness. I derive a set of moment conditions that generalizes those in Graham's ( 2011 ) standard missing data setup. I derive the associated efficiency bound and propose efficie

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Yi, Hui, Zehui Mao, Bin Jiang, Cuimei Bo, Yufang Liu, and Hui Luo. "Fault Diagnosis in Condition of Sample Type Incompleteness Using Support Vector Data Description." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/432651.

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Faulty samples are much harder to acquire than normal samples, especially in complicated systems. This leads to incompleteness for training sample types and furthermore a decrease of diagnostic accuracy. In this paper, the relationship between sample-type incompleteness and the classifier-based diagnostic accuracy is discussed first. Then, a support vector data description-based approach, which has taken the effects of sample-type incompleteness into consideration, is proposed to refine the construction of fault regions and increase the diagnostic accuracy for the condition of incomplete sampl

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Trovati, Marcello, and Olayinka Johnny. "Big data inconsistencies and incompleteness: a literature review." International Journal of Grid and Utility Computing 11, no. 5 (2020): 705. http://dx.doi.org/10.1504/ijguc.2020.10030948.

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Johnny, Olayinka, and Marcello Trovati. "Big data inconsistencies and incompleteness: a literature review." International Journal of Grid and Utility Computing 11, no. 5 (2020): 705. http://dx.doi.org/10.1504/ijguc.2020.110057.

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Flores, Jorge R. "Taxon incompleteness and discrete time bins affect character change rates in simulated data." Biology Letters 16, no. 11 (2020): 20200418. http://dx.doi.org/10.1098/rsbl.2020.0418.

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Estimating how fast or slow morphology evolves through time (phenotypic change rate, PR) has become common in macroevolutionary studies and has been important for clarifying key evolutionary events. However, the inclusion of incompletely scored taxa (e.g. fossils) and variable lengths of discrete arbitrary time bins could affect PR estimates and potentially mask real PR patterns. Here, the impact of taxon incompleteness (unscored data) on PR estimates is assessed in simulated data. Three different time bin series were likewise evaluated: bins evenly spanning the tree length (i), a shorter midd

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Sanz, Joaquin, Emanuele Cozzo, Javier Borge-Holthoefer, and Yamir Moreno. "Topological effects of data incompleteness of gene regulatory networks." BMC Systems Biology 6, no. 1 (2012): 110. http://dx.doi.org/10.1186/1752-0509-6-110.

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Marino-Buslje, Cristina, Alexander Miguel Monzon, Diego Javier Zea, María Silvina Fornasari, and Gustavo Parisi. "On the dynamical incompleteness of the Protein Data Bank." Briefings in Bioinformatics 20, no. 1 (2017): 356–59. http://dx.doi.org/10.1093/bib/bbx084.

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Qi, Qianya, Li Yan, and Lili Tian. "Testing equality of means in partially paired data with incompleteness in single response." Statistical Methods in Medical Research 28, no. 5 (2018): 1508–22. http://dx.doi.org/10.1177/0962280218765007.

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In testing differentially expressed genes between tumor and healthy tissues, data are usually collected in paired form. However, incomplete paired data often occur. While extensive statistical researches exist for paired data with incompleteness in both arms, hardly any recent work can be found on paired data with incompleteness in single arm. This paper aims to fill this gap by proposing some new methods, namely, P-value pooling methods and a nonparametric combination test. Simulation studies are conducted to investigate the performance of the proposed methods in terms of type I error and pow

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Dr., K. Sathesh Kumar* Dr. S. Ramkumar*. "A PERSONALIZED SCHEME FOR INCOMPLETE AND DUPLICATE INFORMATION HANDLING IN RELATIONAL DATABASES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 9 (2016): 360–69. https://doi.org/10.5281/zenodo.154206.

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Missing data replacement is a crucial process in most real world databases. Due to the tremendous improvement of data management, users of such database can effectively manage the incompleteness using their customized policies. This work proposes the renovated concept of partial information handling with complete prediction model, which handle incompleteness in relational databases. The incomplete data management brings a new challenge which is the data duplication. The Customized Information Prediction Policies with effective index method has been proposed in this work for handling missing da

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KHOTIMAH, SITI NUR, and SYIFAUL LAILIYAH. "Literature Review: Analysis Of Incompleteness of Filling in Medical Records Data in Hospitals." Hang Tuah Medical Journal 21, no. 2 (2024): 293–304. http://dx.doi.org/10.30649/htmj.v21i2.492.

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Background: Analysis of incomplete filling of medical record information is needed to identify incomplete filling of patient cards in hospitals. Health information can be considered complete if the physician has filled in complete patient information within 1 x 24 hours after providing inpatient or outpatient services. Purposes: This study aims to determine incompleteness in filling hospital medical records and determine the factors that influence incomplete patient information in hospitals. Methods: Literature review with a comprehensive strategy via the internet using PRISMA. Literature was

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Wang, Maogang, Prithviraj Banerjee, and Majid Sarrafzadeh. "Placement with Incomplete Data." VLSI Design 10, no. 1 (1999): 57–70. http://dx.doi.org/10.1155/1999/42648.

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Traditional placement problems are studied under a fully specified cell library and a complete netlist. However, in the first, e.g., 2 years of a 2 – 3 year microprocessor design cycle, the detailed netlist is unavailable. For area and performance estimation, layout must nevertheless be done with incomplete information. Another source of incompleteness comes from logic synthesis changes; some instances and their parameters will change as the project evolves. In the re-configurable computing area, sometimes we need to perform quick placement before all information is available. The problem of p

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Islam, Syrus, Ralph Adler, and Deryl Northcott. "Managerial attitudes towards the incompleteness of performance measurement systems." Qualitative Research in Accounting & Management 15, no. 1 (2018): 84–103. http://dx.doi.org/10.1108/qram-10-2017-0106.

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Purpose Performance measurement systems (PMSs) are at the heart of most organisations. The aim of this study is to examine the attitudes of top-level managers towards the incompleteness of PMSs. Design/methodology/approach This paper draws on an in-depth field study conducted in an energy and environmental services provider based in New Zealand. The data, which were obtained from 20 semi-structured interviews, were triangulated against on-site observations and company documents. Findings The findings suggest that whether the incompleteness of a PMS is considered problematic or non-problematic

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Nwagwu, Honour Chika. "Visualising Inconsistency and Incompleteness in RDF Gene Expression Data using FCA." International Journal of Conceptual Structures and Smart Applications 2, no. 1 (2014): 68–82. http://dx.doi.org/10.4018/ijcssa.2014010105.

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The integration of data from different data sources can result to the existence of inconsistent or incomplete data (IID). IID can undermine the validity of information retrieved from an integrated dataset. There is therefore a need to identify these anomalies. This work presents SPARQL queries that retrieve from an EMAGE dataset, information which are inconsistent or incomplete. Also, it will be shown how Formal Concept Analysis (FCA) tools notably FcaBedrock and Concept Explorer can be applied to identify and visualise IID existing in these retrieved information. Although, instances of IID ca

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Aljojo, Nahla. "Examining Heterogeneity Structured on a Large Data Volume with Minimal Incompleteness." ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY 9, no. 2 (2021): 30–37. http://dx.doi.org/10.14500/aro.10857.

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While Big Data analytics can provide a variety of benefits, processing heterogeneous data comes with its own set of limitations. A transaction pattern must be studied independently while working with Bitcoin data, this study examines twitter data related to Bitcoin and investigate communications pattern on bitcoin transactional tweet. Using the hashtags #Bitcoin or #BTC on Twitter, a vast amount of data was gathered, which was mined to uncover a pattern that everyone either (speculators, teaches, or the stakeholders) uses on Twitter to discuss Bitcoin transactions. This aim is to determine the

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Gregori, Enrico, Alessandro Improta, Luciano Lenzini, Lorenzo Rossi, and Luca Sani. "A Novel Methodology to Address the Internet AS-Level Data Incompleteness." IEEE/ACM Transactions on Networking 23, no. 4 (2015): 1314–27. http://dx.doi.org/10.1109/tnet.2014.2323128.

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Furukawa, Kyoji, Dale L. Preston, Munechika Misumi, and Harry M. Cullings. "Handling incomplete smoking history data in survival analysis." Statistical Methods in Medical Research 26, no. 2 (2014): 707–23. http://dx.doi.org/10.1177/0962280214556794.

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While data are unavoidably missing or incomplete in most observational studies, consequences of mishandling such incompleteness in analysis are often overlooked. When time-varying information is collected irregularly and infrequently over a long period, even precisely obtained data may implicitly involve substantial incompleteness. Motivated by an analysis to quantitatively evaluate the effects of smoking and radiation on lung cancer risks among Japanese atomic-bomb survivors, we provide a unique application of multiple imputation to incompletely observed smoking histories under the assumption

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Najib, Fatma M., Rasha M. Ismail, Nagwa L. Badr, and Tarek F. Gharib. "Incomplete high dimensional data streams clustering." Journal of Intelligent & Fuzzy Systems 39, no. 3 (2020): 4227–43. http://dx.doi.org/10.3233/jifs-200297.

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Many recent applications such as sensor networks generate continuous and time varying data streams that are often gathered from multiple data sources with some incompleteness and high dimensionality. Clustering such incomplete high dimensional streaming data faces four constraints which are 1) data incompleteness, 2) high dimensionality of data, 3) data distribution, 4) data streams’ continuous nature. Thus, in this paper, we propose the Subspace clustering for Incomplete High dimensional Data streams (SIHD) framework that overcomes the above clustering issues. The proposed SIHD provides conti

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Gurupur, Varadraj P., and Muhammed Shelleh. "Machine Learning Analysis for Data Incompleteness (MADI): Analyzing the Data Completeness of Patient Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records." IEEE Access 9 (2021): 95994–6001. http://dx.doi.org/10.1109/access.2021.3095240.

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21

Zaveri, Amrapali, Andrea Maurino, and Laure-Berti Equille. "Web Data Quality." International Journal on Semantic Web and Information Systems 10, no. 2 (2014): 1–6. http://dx.doi.org/10.4018/ijswis.2014040101.

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The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify

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22

Kostopoulou, Olga, Christopher Tracey, and Brendan C. Delaney. "Can decision support combat incompleteness and bias in routine primary care data?" Journal of the American Medical Informatics Association 28, no. 7 (2021): 1461–67. http://dx.doi.org/10.1093/jamia/ocab025.

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Abstract Objective Routine primary care data may be used for the derivation of clinical prediction rules and risk scores. We sought to measure the impact of a decision support system (DSS) on data completeness and freedom from bias. Materials and Methods We used the clinical documentation of 34 UK general practitioners who took part in a previous study evaluating the DSS. They consulted with 12 standardized patients. In addition to suggesting diagnoses, the DSS facilitates data coding. We compared the documentation from consultations with the electronic health record (EHR) (baseline consultati

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Grande, Giuseppe, and Luigi Ventura. "Labor income and risky assets under market incompleteness: Evidence from Italian data." Journal of Banking & Finance 26, no. 2-3 (2002): 597–620. http://dx.doi.org/10.1016/s0378-4266(01)00236-9.

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Jacobs, Kris, Stéphane Pallage, and Michel A. Robe. "Market incompleteness and the equity premium puzzle: Evidence from state-level data." Journal of Banking & Finance 37, no. 2 (2013): 378–88. http://dx.doi.org/10.1016/j.jbankfin.2012.09.005.

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Ashby, Michael, and Joanna Przedlacka. "Measuring incompleteness: Acoustic correlates of glottal articulations." Journal of the International Phonetic Association 44, no. 3 (2014): 283–96. http://dx.doi.org/10.1017/s002510031400019x.

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The autocorrelation function, a measure of regularity in the speech signal, is applied in demarcating the seemingly diffuse intervals of glottalization which accompany or replace voiceless oral stops in elicited recordings from 22 young speakers of Southern British English. It is shown that a local minimum in autocorrelation characterizes almost all instances heard as intervocalic glottal stops; an annotation procedure is developed and used to gather data on glottalization gestures, including duration, f0, energy and autocorrelation. The same measure is used to assess regularity of vocal fold

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Destandau, Marie, and Jean-Daniel Fekete. "The missing path: Analysing incompleteness in knowledge graphs." Information Visualization 20, no. 1 (2021): 66–82. http://dx.doi.org/10.1177/1473871621991539.

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Knowledge Graphs (KG) allow to merge and connect heterogeneous data despite their differences; they are incomplete by design. Yet, KG data producers need to ensure the best level of completeness, as far as possible. The difficulty is that they have no means to distinguish cases where incomplete entities could and should be fixed. We present a new visualization tool: The Missing Path, to support them in identifying coherent subsets of entities that can be repaired. It relies on a map, grouping entities according to their incomplete profile. The map is coordinated with histograms and stacked cha

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Bhavsar, Nidhi, Khushbu Yadav, and Nita Goswami. "Efficient Missing Data Recovery with Closet Fit: A Scalable Solution for Large-Scale Data Mining." SPU - Journal of Science, Technology and Management Research, Special Edition- -ICMAETM-24 (July 1, 2024): 34–38. https://doi.org/10.63766/spujstmr.24.000025.

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Data preparation is a crucial step in data analysis, serving as the foundation for successful data mining. To uncover novel insights from existing databases, it is essential to ensure data completeness, quality, and real-world relevance. However, missing values can hinder analysis and application to new data, necessitating the employment of statistical techniques during data preparation. By leveraging statistical methods, we can address data incompleteness and ambiguity. This paper presents two sequential approaches for imputing missing attribute values, focusing on numerical variables in time

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Pinon, M., A. de Mattia, P. McDonald, et al. "Mitigation of DESI fiber assignment incompleteness effect on two-point clustering with small angular scale truncated estimators." Journal of Cosmology and Astroparticle Physics 2025, no. 01 (2025): 131. https://doi.org/10.1088/1475-7516/2025/01/131.

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Abstract We present a method to mitigate the effects of fiber assignment incompleteness in two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys, by truncating small angular scales from estimators. We derive the corresponding modified correlation function and power spectrum windows to account for the small angular scale truncation in the theory prediction. We validate this approach on simulations reproducing the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show that we recover unbiased cosmolog

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Lippiello, Eugenio, Alessandra Cirillo, Cataldo Godano, Elefetheria Papadimitriou, and Vassilis Karakostas. "Post Seismic Catalog Incompleteness and Aftershock Forecasting." Geosciences 9, no. 8 (2019): 355. http://dx.doi.org/10.3390/geosciences9080355.

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A growing interest appears among public authorities and society in accurate and nearly real time aftershock forecasting to manage and mitigate post-seismic risk. Existing methods for aftershock forecasting are strongly affected by the incompleteness of the instrumental datasets available soon after the main shock occurrence. The deficit of observed events, in the first part of aftershock sequences, can be naturally attributed to various mechanisms such as the inefficiency of the seismic network and the overlap of earthquake signals in seismic records. In this review, we show that short-term af

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Pink, Sarah, Minna Ruckenstein, Robert Willim, and Melisa Duque. "Broken data: Conceptualising data in an emerging world." Big Data & Society 5, no. 1 (2018): 205395171775322. http://dx.doi.org/10.1177/2053951717753228.

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In this article, we introduce and demonstrate the concept-metaphor of broken data. In doing so, we advance critical discussions of digital data by accounting for how data might be in processes of decay, making, repair, re-making and growth, which are inextricable from the ongoing forms of creativity that stem from everyday contingencies and improvisatory human activity. We build and demonstrate our argument through three examples drawn from mundane everyday activity: the incompleteness, inaccuracy and dispersed nature of personal self-tracking data; the data cleaning and repair processes of Bi

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A’yun Faradinna, Riskylah, and Budhi Setianto. "Description of Incompleteness of Prescription Writing at Surabaya Islamic Hospital A. Yani." KESANS : International Journal of Health and Science 2, no. 5 (2023): 261–71. http://dx.doi.org/10.54543/kesans.v2i5.139.

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Introduction: Medication error is an event that harms patients due to incorrect use of drugs during the treatment of health workers. Medication error can lead to increased mortality or mortality, increased duration of hospitalization, and increased cost of treatment. Objective: This study aims to provide an overview of efforts to reduce the incompleteness of prescription writing at Surabaya Islamic Hospital A. Yani in each of its parts, namely inscription, invocation, precriptio, subcribtio, and pro. Method: The type of research used is qualitative case studies and secondary data analysis of p

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Andrade, Laerson, Eucilene Santana, Marcos Santos, and Marluce Siqueira. "Evaluation of Incompleteness and Inconsistency in the Suicide Mortality Information System: A Time Series Analysis in Espírito Santo, Brazil (2014-2019)." International Journal of Psychology and Neuroscience 9, no. 2 (2023): 70–84. http://dx.doi.org/10.56769/ijpn09207.

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Abstract Background: Analysis of Health Systems databases is an essential process for planning, developing and evaluating health policies. This process provides evidence on the health needs of the population for public managers. Objective: To evaluate and analyze the in-completeness and inconsistency of the Suicide Mortality Information System in Espírito Santo, between 2014-2019. Methods: This is a time series study. Secondary data from the Mortality Information System on deaths by suicide between 2014-2019 were used. For de-scriptive analysis, the proportions of incompleteness and inconsiste

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Gai, Yu Lian, and Ya Ping Wang. "Data Fusion and Bayes Estimation Algorithm Research." Applied Mechanics and Materials 347-350 (August 2013): 2620–24. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.2620.

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This paper starts from the prospective of data processing and use of information, analysis the meaning and realistic background of processing integrated data by using Data Fusion technology. On the basis of a clear basic idea and principle theory of Data Fusion, studies and discusses its hierarchical levels from three aspects. A relatively comprehensive description of Data Fusion process is given in the paper. Incorporate with the description of the basic principles and ideas of Bayes estimation algorithm, identifies the limitation of Bayes estimation algorithm. The practical significance of D

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Xia, Hanjue, Johannes Horn, Monika J. Piotrowska, et al. "Effects of incomplete inter-hospital network data on the assessment of transmission dynamics of hospital-acquired infections." PLOS Computational Biology 17, no. 5 (2021): e1008941. http://dx.doi.org/10.1371/journal.pcbi.1008941.

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In the year 2020, there were 105 different statutory insurance companies in Germany with heterogeneous regional coverage. Obtaining data from all insurance companies is challenging, so that it is likely that projects will have to rely on data not covering the whole population. Consequently, the study of epidemic spread in hospital referral networks using data-driven models may be biased. We studied this bias using data from three German regional insurance companies covering four federal states: AOK (historically “general local health insurance company”, but currently only the abbreviation is u

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Vorobyeva, Anna. "Application of random forest machine learning and big geospatial data management systems applied to reconstruct the vegetation index data series." InterCarto. InterGIS 30, no. 1 (2024): 295–305. https://doi.org/10.35595/2414-9179-2024-1-30-295-305.

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This article discusses the content and results of the work devoted to the development of a machine learning model that allows for data incompleteness recovery using cloud computing. The problem is considered using the example of a study devoted to data modeling to fill in missing values of vegetation indices based on open data catalogs of cloud computing platforms. The proposed methodology is based on the use of a multi-year periodic sampling of vegetation index values and model training on large amounts of data to improve the quality of series reconstruction. The approach indicated in the wor

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Kondratyeva, Liya, Irina Alekseenko, Igor Chernov, and Eugene Sverdlov. "Data Incompleteness May form a Hard-to-Overcome Barrier to Decoding Life’s Mechanism." Biology 11, no. 8 (2022): 1208. http://dx.doi.org/10.3390/biology11081208.

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In this brief review, we attempt to demonstrate that the incompleteness of data, as well as the intrinsic heterogeneity of biological systems, may form very strong and possibly insurmountable barriers for researchers trying to decipher the mechanisms of the functioning of live systems. We illustrate this challenge using the two most studied organisms: E. coli, with 34.6% genes lacking experimental evidence of function, and C. elegans, with identified proteins for approximately 50% of its genes. Another striking example is an artificial unicellular entity named JCVI-syn3.0, with a minimal set o

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Kumari, Kimmi, and Mrunalini M. "A Framework for Analysis of Incompleteness and Security Challenges in IoT Big Data." International Journal of Information Security and Privacy 16, no. 2 (2022): 1–13. http://dx.doi.org/10.4018/ijisp.308305.

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Data quality (DQ) is gaining traction as a new area to focus on for increasing organisational effectiveness. Despite the fact that the implications of poor data quality are often felt in the day-to-day operations of businesses, only a small percentage of companies use particular approaches for measuring and monitoring data quality. In this paper, the focus is on the efficiency and incompleteness of IOT big data and since security is the major concern in large clusters, map reduce technique is proposed in order to overcome the issues and challenges faced on regular basis while dealing with huge

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Hariaha, Lesia. "THE CONCEPT OF DATA COMPLEMENTARITY IN FINANCIAL MARKETS." Actual Problems of Economics 1, no. 282 (2024): 231–38. https://doi.org/10.32752/1993-6788-2024-1-282-231-238.

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The article is devoted to the study of methodological approaches to financial market analysis, considering the fragmentation and incompleteness of financial data sets. The necessity of integrating alternative data sources to enhance the accuracy of analytical assessments is substantiated. The primary methods for researching financial markets – quantitative, qualitative, and mixed – are summarized, with their advantages and limitations highlighted. The concept of financial data complementarity is introduced, advocating the use of complementary datasets to address informational gaps. A multi-ste

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Sim, Jaemun, Jonathan Sangyun Lee, and Ohbyung Kwon. "Missing Values and Optimal Selection of an Imputation Method and Classification Algorithm to Improve the Accuracy of Ubiquitous Computing Applications." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/538613.

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In a ubiquitous environment, high-accuracy data analysis is essential because it affects real-world decision-making. However, in the real world, user-related data from information systems are often missing due to users’ concerns about privacy or lack of obligation to provide complete data. This data incompleteness can impair the accuracy of data analysis using classification algorithms, which can degrade the value of the data. Many studies have attempted to overcome these data incompleteness issues and to improve the quality of data analysis using classification algorithms. The performance of

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Lestari, Dian Fadilah Ayu, and Indah Muflihatin. "Analisis Faktor Penyebab Ketidaklengkapan Rekam Medis Pasien Rawat Inap di Puskesmas Kotaanyar." J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan 2, no. 1 (2020): 134–42. http://dx.doi.org/10.25047/j-remi.v2i1.2217.

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Based on the results of a preliminary study conducted at the Kotaanyar Public Health Center, 30 medical records of inpatients in April and May 2019 are known, which were identified based on patient identification, important reports and their authentication, the average overall number of incompleteness was 720 (53.08%). The incompleteness of the medical record has an impact which results of administrative and clinical data are not accurate, This incompleteness also creates a loss in fulfilling the patient's right to the contents of their medical record, obstruction of reporting activities and s

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Tinkler, Penny, Resto Cruz, and Laura Fenton. "Recomposing persons: Scavenging and storytelling in a birth cohort archive." History of the Human Sciences 34, no. 3-4 (2021): 266–89. http://dx.doi.org/10.1177/0952695121995398.

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Birth cohort studies can be used not only to generate population-level quantitative data, but also to recompose persons. The crux is how we understand data and persons. Recomposition entails scavenging for various (including unrecognised) data. It foregrounds the perspective and subjectivity of survey participants, but without forgetting the partiality and incompleteness of the accounts that it may generate. Although interested in the singularity of individuals, it attends to the historical and relational embeddedness of personhood. It examines the multiple and complex temporalities that suffu

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Xia, Shaobo, Dong Chen, Jiju Peethambaran, Pu Wang, and Sheng Xu. "Point Cloud Inversion: A Novel Approach for the Localization of Trees in Forests from TLS Data." Remote Sensing 13, no. 3 (2021): 338. http://dx.doi.org/10.3390/rs13030338.

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Tree localization in point clouds of forest scenes is critical in the forest inventory. Most of the existing methods proposed for TLS forest data are based on model fitting or point-wise features which are time-consuming, sensitive to data incompleteness and complex tree structures. Furthermore, these methods often require lots of preprocessing such as ground filtering and noise removal. The fast and easy-to-use top-based methods that are widely applied in processing ALS point clouds are not applicable in localizing trees in TLS point clouds due to the data incompleteness and complex canopy st

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Hyun, Jung Soon, and Byung Kun Rhee. "On the Incompleteness of Korean Stock Index Options Market." Journal of Derivatives and Quantitative Studies 12, no. 2 (2004): 25–43. http://dx.doi.org/10.1108/jdqs-02-2004-b0002.

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When the Black-Scholes assumptions hold market is instantaneously complete and options are redundant securities. This paper tests whether options are needed for spanning of the pricing kernel in addition to the risk-free bond and underlying asset in Korean stock index options market. Using Hansen's GMM estimation method, we find that pricing kernel cannot be spanned with the risk-free bond and underlying asset. Options are needed for spanning to incorporate the additional risk factor. This result is consistent with previous results using American options market data.

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Shaikh, Riaz Ahmed, Kamel Adi, and Luigi Logrippo. "A Data Classification Method for Inconsistency and Incompleteness Detection in Access Control Policy Sets." International Journal of Information Security 16, no. 1 (2016): 91–113. http://dx.doi.org/10.1007/s10207-016-0317-1.

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Orlova, K. P., and V. E. Serkin. "Method for calculating the steady-state availability in case of the initial data incompleteness." Automation and informatization of the fuel and energy complex, no. 3 (2023): 61–64. http://dx.doi.org/10.33285/2782-604x-2023-3(596)-61-64.

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Vicente, José, and Daniela Kubudi. "Extracting inflation risk premium from nominal and real bonds using survey information." Journal of Economic Studies 45, no. 2 (2018): 307–25. http://dx.doi.org/10.1108/jes-03-2017-0066.

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Purpose The purpose of this paper is to forecast future inflation using a joint model of the nominal and real yield curves estimated with survey data. The model is arbitrage free and embodies incompleteness between the nominal and real bond markets. Design/methodology/approach The methodology is based on the affine class of term structure of interest rate. The model is estimated using the Kalman filter technique. Findings The authors show that the inclusion of survey data in the estimation procedure improves significantly the inflation forecasting. Moreover, the authors find that the monetary

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Sedova, N. V., and V. A. Eremkin. "Analysis of the Reliability and Comparability of Data on Rural areas in Russia Collected by Federal Executive Authorities." Machinery and Equipment for Rural Area, no. 10 (October 26, 2023): 43–48. http://dx.doi.org/10.33267/2072-9642-2023-10-43-48.

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The main point of the problem of duplication or incompleteness of data in various statistical informational systems formed at the federal level is revealed. The comprehensive list of duplications and “white spots” (absence of necessaryinformation) in the compared databases has been compiled, statistical discrepancies in data have been highlighted using a modal example, and measures have been proposed to improve the statistical record-keeping of data on rural areas.

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Lufianti, Siti Alifa, Rossalina Adi Wijayanti, Demiawan Rachmatta Putro Mudiono, and Indah Muflihatin. "Analisis Faktor Penyebab Ketidaklengkapan Resume Medis Rawat Inap di Puskesmas Cermee Bondowoso." Jurnal Rekam Medik & Manajemen Informasi Kesehatan 1, no. 2 (2022): 80–86. http://dx.doi.org/10.47134/rmik.v1i2.21.

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The patient's medical resume form is a summary of the entire period of patient care and treatment as has been attempted by health workers and related parties. Based on a preliminary study in March 2021, researchers obtained data information on incomplete medical resume forms, the highest incompleteness was found in the identification component, which was 86.7%, the next incompleteness was in the Authentication component, which was 80%, the next incompleteness was in the Authentication component. important reports that is equal to 56.7%. The purpose of this study was to analyze the factors caus

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Hua, Wei, Xiao Juan Li, Yong Guan, Zhi Ping Shi, Jie Zhang, and Ling Ling Dong. "Formal Verification for SpaceWire Data Flow Control Using Model Checking." Applied Mechanics and Materials 241-244 (December 2012): 2466–70. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.2466.

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SpaceWire is a high-speed, full-duplex serial bus standard which is applied in aerospace, so its functions require high accuracy. The traditional methods of verification, such as simulation and test, are not complete. In order to prove the design of the SpaceWire faithfully implemented the SpaceWire protocol’s specification, we presented our experience on the model checking of SpaceWire data flow control using the Cadence SMV tool. It overcomes the incompleteness of traditional verification. And by injecting the errors to ensure the accuracy of the artificial extraction properties and complete

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Chandra, Kanchan. "Design measures of ethnic identity: The problems of overlap and incompleteness." Qualitative & Multi-Method Research 7, no. 1 (2009): 36–41. https://doi.org/10.5281/zenodo.940730.

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A great deal of new work in the field of ethnic politics has focused on improving the quality of the data we put into our measures—and critiquing the quality of the data that went into measures such as the Index of Ethnolinguistic Fractionalization (the ELF index) (Chandra 2009, Chandra and Wilkinson 2008, Cederman and Girardin 2007, Posner 2004).

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