Search results for "data quality"
showing 10 items of 96 documents
Data repeatability and acquisition techniques for Time-Domain Spectral Induced Polarization
2013
The Time Domain Induced Polarization (TDIP) technique is widely used in applied geophysics, particularly for environmental issues, for instance for delineating landfills or detecting leachate percolation. Because the reliability of IP data remains an issue at the field scale, this paper deals with the factors controlling data quality and compares different arrays and acquisition parameters for optimal collection of data in the field. The first part focuses on repeatability experiments carried out in the former Horlokke landfill (Denmark), in order to infer the degree of which a signal can be reproduced over time. Results show a good repeatability, with on average less than 10% of difference…
A Combined Non-Destructive and Micro-Destructive Approach to Solving the Forensic Problems in the Field of Cultural Heritage: Two Case Studies
2021
The present paper discusses the importance of non-destructive and micro-destructive technology in forensic investigations in the field of cultural heritage. Recent technological developments and the wide availability of modern analytical instrumentation are creating new possibilities for performing scientific measurements and acquiring data directly on-site—thereby limiting, where possible, sampling activity—as well as learning about the technologies and materials that were employed in the past to create cultural assets. Information on periods, chemical composition, manufacturing techniques, etc., can be gathered more easily. Overall, the benefits of on-site forensic investigations are mult…
Influence of Quality Filtering Approaches in BEC SMOS L3 Soil Moisture Products
2019
2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2019), 28 July - 2 August 2019, Yokohama, Japan
Range-based versus automated markerless image-based techniques for rock art documentation
2014
Nowadays there is a huge proliferation of fully automatic image-based solutions producing either three-dimensional (3D) point clouds or 3D models. However, the reliability of the output is not usually reported and clarified. This paper presents a comparison of the 3D modelling results achieved on two rock art shelters at separate archaeological sites using a high-resolution digital camera. The 3D point clouds were produced using automatic image-based photogrammetric and computer vision software running either locally (FOTOGIFLE and VisualSFM) or through a webbased reconstruction service (Autodesk 123D Catch). The first two automatic approaches are compared with a manual bundle block adjustm…
Data quality of 5 years of central norovirus outbreak reporting in the European Network for food-borne viruses
2008
ABSTRACT Background The food-borne viruses in Europe (FBVE) network database was established in 1999 to monitor trends in outbreaks of gastroenteritisdue to noroviruses (NoVs), to identify major transmission routes of NoV infections within and between participating countries and to detectdiffuse international food-borne outbreaks.Methods We reviewed the total of 9430 NoVoutbreak reports from 13 countries with date of onset between 1 January 2002 and 1 January2007 for representativeness, completeness and timeliness against these objectives.Results Rates of reporting ranged from a yearly average of 1.8 in 2003 to 11.6 in 2006. Completeness of reporting of an agreed minimumdataset improved ove…
Identifying critical incidents in naturalistic driving data: experiences from a promoting real life observation for gaining understanding of road use…
2013
The methodology of naturalistic driving observation aspires to observe the driver and his environment while driving in natural driving settings. It is of great importance in research on road safety as this method of observing road users eliminates the disadvantages of traditional methods like simulator studies or interviews. However, it produces vast such amounts of data and challenges data reduction and data analysis. Therefore automatic methods for filtering critical incidents based on thresholds for numerical data are often applied to select the data to be analysed. This study reports a small-scale field trial in Valencia, Spain, which was conducted within the promoting real life observa…
Enhancing scientific information systems with semantic annotations
2013
International audience; Scientific Information Systems aim to produce or improve knowledge on a subject through activities of research and development. The management of scientific dat a requires some essential properties. We propose SemLab an architecture that sup ports interoperability, data quality and extensibility through a unique paradigm: semantic annotation. We present two app lications that validate our architecture.
Architecture Enabling Adaptation of Data Integration Processes for a Research Information System
2018
Abstract Today, many efforts have been made to implement information systems for supporting research evaluation activities. To produce a good framework for research evaluation, the selection of appropriate measures is important. Quality aspects of the systems’ implementation should also not be overlooked. Incomplete or faulty data should not be used and metric computation formulas should be discussed and valid. Correctly integrated data from different information sources provide a complete picture of the scientific activity of an institution. Knowledge from the data integration field can be adapted in research information management. In this paper, we propose a research information system f…
Artificial intelligence in the diagnosis of pediatric allergic diseases.
2020
Abstract: Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In pediatric allergy research, the recent developments in AI approach provided new perspectives for characterizing the heterogeneity of allergic diseases among patients. Moreover, the increasing use of electronic health records and personal healthcare records highlighted the relevance of AI in …
Epidemiology of childhood cancer
2010
The present contribution reports childhood cancer incidence and survival rates as well as time trends and geographical variation. The report is based on the databases of population-based cancer registries which joined forces in cooperative projects such as Automated Childhood Cancer Information System (ACCIS) and EUROCARE. According to these data, which refer to the International Classification of Childhood Cancer, leukemias, at 34%, brain tumors, at 23%, and lymphomas, at 12%, represent the largest diagnostic groups among the under 15-year-olds. The most frequent single diagnoses are: acute lymphoblastic leukemia, astrocytoma, neuroblastoma, non-Hodgkin lymphoma, and nephroblastoma. There …