scholarly journals Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4975
Author(s):  
Yi Mao ◽  
Yi Yang ◽  
Yuxin Hu
Keyword(s):  
Data Integration ◽  
Traffic Management ◽  
Surveillance System ◽  
Logical Structure ◽  
Surveillance Data ◽  
Weighting Method ◽  
Integration Algorithm ◽  
Target Track ◽  
Data Integration System ◽  
Measurement Variance

Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace and approaching airspace, this paper proposes a filter-based covariance matrix weighting method, measurement variance weighting method, and measurement-first weighted fusion method weighting integration algorithm to improve the efficiency of data integration calculation under fixed accuracy. Besides this, this paper focuses on the technology of the integration of a multi-radar surveillance system and automated related surveillance system in the ATM system and analyzes the constructional method of a multigeneration surveillance data integration system, as well as establishing the targeted model of sensors and the target track and designing the logical structure of multi-radar and ADS data integration.

scholarly journals Quality Assessment of an Antimicrobial Resistance Surveillance System in a Province of Nepal

2021 ◽  
Vol 6 (2) ◽  
pp. 60
Author(s):  
Jyoti Acharya ◽  
Maria Zolfo ◽  
Wendemagegn Enbiale ◽  
Khine Wut Yee Kyaw ◽  
Meika Bhattachan ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Surveillance System ◽  
Surveillance Data ◽  
World Health ◽  
Cross Sectional ◽  
Antimicrobial Resistance Surveillance ◽  
Data Collection Process ◽  
Data Compilation ◽  
Site Variation ◽  
Health Organization

Antimicrobial resistance (AMR) is a global problem, and Nepal is no exception. Countries are expected to report annually to the World Health Organization on their AMR surveillance progress through a Global Antimicrobial Resistance Surveillance System, in which Nepal enrolled in 2017. We assessed the quality of AMR surveillance data during 2019–2020 at nine surveillance sites in Province 3 of Nepal for completeness, consistency, and timeliness and examined barriers for non-reporting sites. Here, we present the results of this cross-sectional descriptive study of secondary AMR data from five reporting sites and barriers identified through a structured questionnaire completed by representatives at the five reporting and four non-reporting sites. Among the 1584 records from the reporting sites assessed for consistency and completeness, 77–92% were consistent and 88–100% were complete, with inter-site variation. Data from two sites were received by the 15th day of the following month, whereas receipt was delayed by a mean of 175 days at three other sites. All four non-reporting sites lacked dedicated data personnel, and two lacked computers. The AMR surveillance data collection process needs improvement in completeness, consistency, and timeliness. Non-reporting sites need support to meet the specific requirements for data compilation and sharing.

scholarly journals Graph-based sequence annotation using a data integration approach

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Robert Pesch ◽  
Artem Lysenko ◽  
Matthew Hindle ◽  
Keywan Hassani-Pak ◽  
Ralf Thiele ◽  
...  
Keyword(s):  
Data Integration ◽  
Gene Function ◽  
High Throughput Sequencing ◽  
Prediction Method ◽  
Function Prediction ◽  
Function Annotation ◽  
Automated Annotation ◽  
Data Integration System ◽  
Reference Databases ◽  
Function Assignment

SummaryThe automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara- Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation.The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.

scholarly journals Towards an integrated animal health surveillance system in Tanzania: making better use of existing and potential data sources for early warning surveillance

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Janeth George ◽  
Barbara Häsler ◽  
Erick Komba ◽  
Calvin Sindato ◽  
Mark Rweyemamu ◽  
...  
Keyword(s):  
Early Warning ◽  
Surveillance System ◽  
Animal Health ◽  
Health Surveillance ◽  
Surveillance Data ◽  
Data Sources ◽  
Surveillance Systems ◽  
Cross Sectional Survey ◽  
Traceability System ◽  
Spatial Coverage

Abstract Background Effective animal health surveillance systems require reliable, high-quality, and timely data for decision making. In Tanzania, the animal health surveillance system has been relying on a few data sources, which suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration of data from multiple sources can enhance early detection and response to animal diseases and facilitate the early control of outbreaks. This study aimed to identify and assess existing and potential data sources for the animal health surveillance system in Tanzania and how they can be better used for early warning surveillance. The study used a mixed-method design to identify and assess data sources. Data were collected through document reviews, internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The assessment was done using pre-defined criteria. Results A total of 13 data sources were identified and assessed. Most surveillance data came from livestock farmers, slaughter facilities, and livestock markets; while animal dip sites were the least used sources. Commercial farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and information systems such as the Tanzania National Livestock Identification and Traceability System (TANLITS) and Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health surveillance system. The common variables found across most sources were: the name of the place (12/13), animal type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there was significant variation in terms of data frequency, accuracy and cost. There were limited integration and coordination of data flow from the identified sources with minimum to non-existing automated data entry and transmission. Conclusion The study demonstrated how the available data sources have great potential for early warning surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a multi-source surveillance system would be best placed to harness these different strengths.

scholarly journals Evaluation of Measles Surveillance Systems in Ginnir District, Bale Zone, Southeast Ethiopia: A Concurrent Embedded Mixed Quantitative/Qualitative Study 

2020 ◽  
Author(s):  
Falaho Sani ◽  
Mohammed Hasen ◽  
Mohammed Seid ◽  
Nuriya Umer
Keyword(s):  
Public Health ◽  
Qualitative Study ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Health Facilities ◽  
Surveillance Data ◽  
Surveillance Systems ◽  
Southeast Ethiopia ◽  
Bale Zone

Abstract Background: Public health surveillance systems should be evaluated periodically to ensure that the problems of public health importance are being monitored efficiently and effectively. Despite the widespread measles outbreak in Ginnir district of Bale zone in 2019, evaluation of measles surveillance system has not been conducted. Therefore, we evaluated the performance of measles surveillance system and its key attributes in Ginnir district, Southeast Ethiopia.Methods: We conducted a concurrent embedded mixed quantitative/qualitative study in August 2019 among 15 health facilities/study units in Ginnir district. Health facilities are selected using lottery method. The qualitative study involved purposively selected 15 key informants. Data were collected using semi-structured questionnaire adapted from Centers for Disease Control and Prevention guidelines for evaluating public health surveillance systems through face-to-face interview and record review. The quantitative findings were analyzed using Microsoft Excel 2016 and summarized by frequency and proportion. The qualitative findings were narrated and summarized based on thematic areas to supplement the quantitative findings.Results: The structure of surveillance data flow was from the community to the respective upper level. Emergency preparedness and response plan was available only at the district level. Completeness of weekly report was 95%, while timeliness was 87%. No regular analysis and interpretations of surveillance data, and the supportive supervision and feedback system was weak. The participation and willingness of surveillance stakeholders in implementation of the system was good. The surveillance system was found to be useful, easy to implement, representative and can accommodate and adapt to changing conditions. Report documentation and quality of data was poor at lower level health facilities. Stability of the system has been challenged by shortage of budget and logistics, staff turnover and lack of update trainings.Conclusions: The surveillance system was acceptable, useful, simple, flexible and representative. Data quality, timeliness and stability of the system were attributes that require improvement. The overall performance of measles surveillance system in the district was poor. Hence, regular analysis of data, preparation and dissemination of epidemiological bulletin, capacity building and regular supervision and feedback are recommended to enhance performance of the system.

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