The DC-bias monitoring device of a transformer is easily affected by external noise interference, equipment aging, and communication failure, which makes it difficult to guarantee the validity of monitoring data and causes great problems for future d...
In addressing the potential anomalies in wind turbine monitoring data, it is essential to note that a single data source cannot independently ascertain the validity of data. This paper proposes a correlation coupling judgment algorithm designed to ev...
The validity of infant mortality data is essential in assessing health care quality and in the setting of preventive measures. This study explores different diagnostic procedures used to determine the cause of death across forensic settings and thus...
Cluster validity indices (CVIs) for evaluating the result of the optimal number of clusters are critical measures in clustering problems. Most CVIs are designed for typical data-type objects called certain data objects. Certain data objects only have...
Compared with traditional anomaly analysis, intelligent connected vehicle (ICV) data validity analysis is faced with a variety of data anomalies, including sensor anomalies, driving behavior anomalies, malicious tampering, and so on, which eventually...
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An Input validation can be a critical issue. Typically, a little attention is paid to it in a web development project, because overenthusiastic validation can tend to cause failures in the software, and can also break the security upon web applicatio...
In the Qinghai-Tibet Plateau region, operational deficiencies and limited maintenance capacities often impair automatic air quality monitoring stations. This results in frequent data omissions, compromising the reliability of environmental assessment...
Accurate geospatial data are essential for intelligent transportation systems and automated reporting applications, as location precision directly impacts safety analysis and decision-making. GPS devices are now routinely employed by law enforcement...
Data collection and review are the building blocks of academic research regardless of the discipline. The gathered and reviewed data, however, need to be validated in order to obtain accurate information. The Delphi consensus is known as a method for...
In the early stages of computer software information system development, requirements errors can lead to software system failure and performance degradation and even cause huge security incidents. Traditional requirements verification methods are ine...
This study validates a Spanish-language instrument designed to assess self-efficacy, digital competence, and anxiety in data-driven decision-making (DDDM) among pre-service teachers. Based on the 3D-MEA and the Beliefs about Basic ICT Competencies sc...
The validation of initial data is an important process to reduce the risk of errors in calculations. The large amount of heterogeneous data in the area of hydrocarbon reservoirs development leads to a significant increasing in complexity and calculat...
The implementation of valid freight transport simulation models requires an extensive and detailed validation phase for understanding the feasibility of the outputs and the capacity of the structure of the proposed models in representing the real-wor...
Machine learning is increasingly used to predict machining and process quality from experimental data, yet such data are typically small, generated by designed experiments, and hierarchically organized, with several measurements taken on the same spe...
This study provides a unique procedure for validating and reconstructing temperature and precipitation data. Although developed from data in Middle Italy, the validation method is intended to be universal, subject to appropriate calibration according...
Research on sensitive human narratives is increasingly constrained by ethical and privacy regulations that limit access to primary data, creating a structural small-data challenge that limits deep computational analysis. To address this limitation, t...
The merging of the Internet of Things (IoT) and Artificial Intelligence (AI) advances has intensified challenges related to data authenticity and security. These advancements necessitate a multi-layered security approach to ensure the security, relia...
Reference data collected to validate land-cover maps are generally considered free of errors. In practice, however, they contain errors despite best efforts to minimize them. These errors propagate during accuracy assessment and tweak the validation...
Urban Building Energy Modeling (UBEM) offers a scalable, physics-based method to simulate energy demand at the district level, enabling data-driven district energy demand planning and optimization. However, translating UBEM into a reliable, openly re...
Skills in reproducing monthly rainfall over Calabria (southern Italy) have been validated for the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) satellite data, the E-OBS dataset and 13 Global Climate Model-Regional Climate M...
The success of the analysis and design of a Water Network (WN) is strongly dependent on the veracity of the data and a priori knowledge used in the model calibration of the network. This fact motivates this paper in which an off-line approach to veri...
Validation is a crucial technique used to strengthen the application capabilities of earthobservation satellite data and solve the quality problems of remote-sensing products. Observing land-surface parameters in the field is one of the key steps of...
Background: Dental insurance claims data are vital for research in oral health, epidemiology, and policy. However, issues like data quality, coding standards, validity, interoperability, and analytical approaches hinder their use. This review outline...
Data validation in cancer registration is a critical operation but is resource-intensive and has traditionally depended on proprietary software. Ontology-based AI is a novel approach utilising machine reasoning based on axioms formally described in d...
Crowdsourced online food images, when combined with food image recognition technologies, have the potential to offer a cost-effective and scalable solution for the assessment of the restaurant nutrition environment. While previous research has explor...
As incidences of osteoporotic hip fractures (OHFs) have increased, identifying OHFs has become important to establishing the medical guidelines for their management. This study was conducted to develop an operational definition to identify patients w...
The validation of significant wave height (SWH) data measured by the Sentinel-3A/3B SAR Altimeter (SRAL) is essential for the application of the data in ocean wave monitoring, forecasting and wave climate studies. Sentinel-3A/3B SWH data are validate...
Earlier, hydrological simulation calibration and validation relied on flow observations at hydrological stations, but multisource observations changed the basin hydrological simulation from single-flow validation to multivariate validation, including...
Clustering is one of the main tasks of machine learning. Internal clustering validation indexes (CVIs) are used to measure the quality of several clustered partitions to determine the local optimal clustering results in an unsupervised manner, and ca...
Validation is an essential process to evaluate the quality of waterbody remote sensing products, and the reliability and effective application of the in situ data of waterbody parameters are an important part of validation. Based on the in situ data...
Cluster validation for categorical data remains a critical challenge in unsupervised learning, where traditional distance-based indices often fail to capture meaningful structures. This paper introduces SLEDgeHammer (SLEDgeH), an enhanced internal va...
Background: Readily available population-based data about cancer recurrence would improve surveillance and research for women of reproductive age. Methods: We randomly selected 200 women from the Alberta Cancer Registry who had received a cancer diag...
Background: Prospective bedside data collection in perioperative research is labour-intensive and error-prone. Methods: We describe a workflow for prospective data capture in a 10-bed cardiac surgical intensive care unit: four Google Forms modules wr...
Synthetic data generation has become a strategic capability in financial analytics, promising to reconcile the sector’s appetite for data-hungry machine learning with strict privacy, confidentiality, and regulatory constraints. This review prov...
This study validated wind speed (WS) and significant wave height (SWH) retrievals from the Sentinel-3A/3B and Jason-3 altimeters for the period of data beginning 31 October 2019 (to 18 September 2019 for Jason-3) using moored buoy data and satellite...
Ensuring the trustworthiness of data used in real-time analytics remains a critical challenge in smart city monitoring and decision-making. This is because the traditional data validation methods are insufficient for handling the dynamic and heteroge...
We conducted a systematic survey of COVID-19 endpoint prediction literature to: (a) identify publications that include data that adhere to FAIR (findability, accessibility, interoperability, and reusability) principles and (b) develop and reuse morta...
Purpose: This study addresses the small data challenge in additive manufacturing, where destructive tensile testing limits sample size (n = 81), by developing and validating a probabilistic synthetic data generation pipeline. Design, Method, and Appr...
Unmanned aerial vehicles have become essential tools in a wide range of applications. As drone operations grow more complex, the accurate prediction of battery runtime and aerodynamic flight safety risks, particularly those caused by wind, becomes in...
The problem of consistency of medical data in Hospital Data Management Systems is considered in the context of correctness of medical images stored in a PACS (Picture Archiving and Communication System) and legality of actions authorized users perfor...
This study evaluates the potential and limitations of open/model-derived hydroclimatic data for multi-horizon river discharge forecasting in Babahoyo, Ecuador. A quantitative, applied, retrospective longitudinal design used daily data for 2017–...
Climate data derived from long-term, multisource altimeter significant wave height (SWH) measurements are more valuable than those obtained from a single altimeter source. Such data facilitate exploration of long-term air–sea momentum transfer...
Accurate reference data to validate burned area (BA) products are crucial to obtaining reliable accuracy metrics for such products. However, the accuracy of reference data can be affected by numerous factors; hence, we can expect some degree of devia...
Large-scale microsimulations are increasingly resourceful tools for analysing in detail citywide effects and alternative scenarios of our policy decisions, approximating the ideal of ‘urban digital twins’. Yet, these models are costly and...
This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and...
The idea of symmetry, which is used to describe the shape of a probability distribution, is a key concept in the theory of probability. The use of symmetric and asymmetric distributions is common in statistical inference, decision-making, and probabi...
Cluster Validity Indices (CVIs) act as a pivotal tool in machine learning for assisting in the determination of the optimal number of clusters. Nevertheless, traditional CVIs often exhibit subpar performance when confronted with the complex character...
The future development of personalized medicine depends on a vast exchange of data from different sources, as well as harmonized integrative analysis of large-scale clinical health and sample data. Computational-modelling approaches play a key role i...
Global land-cover products play an important role in assisting the understanding of climate-related changes and the assessment of progress in the implementation of international initiatives for the mitigation of, and adaption to, climate change. Howe...
Background/Objectives: Hospital discharge data are increasingly reused for research and within health data spaces, but their value depends on accurate diagnostic coding. The validity of type 2 diabetes mellitus (T2DM) coding in the Spanish hospital d...
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