Aircraft anomaly detection using algorithmic model and data model trained on FOQA data

2015 ◽  
Author(s):  
Alvin Megatroika ◽  
Maulahikmah Galinium ◽  
Adhiguna Mahendra ◽  
Neno Ruseno
Keyword(s):  
Anomaly Detection ◽  
Data Model ◽  
Algorithmic Model

scholarly journals DATA MODELLING SOLUTION FOR REFLECTIVE ePORTFOLIO SYSTEM

2015 ◽  
Vol 2 ◽  
pp. 312
Author(s):  
Aleksandrs Gorbunovs ◽  
Dainis Gorbunovs ◽  
Atis Kapenieks
Keyword(s):  
Information System ◽  
Information Systems ◽  
Learning Outcomes ◽  
Data Model ◽  
Data Modelling ◽  
Technological Solution ◽  
Validation And Verification ◽  
Living Lab ◽  
Algorithmic Model

An importance of creating of efficacious information systems, which would enhance learning outcomes, leads to development of appropriate models.Modelling process with further validation and verification of developed information system or technological solution is essential. This paper displays the considerations and efforts made to work out such model in a form of reflection stimulating and learning outcomes enhancing ePortfolio information system. The authors introduce architecture of developed system from a view of used technologies, system’s algorithmic model and data model, as well its approbation results in Living Lab.

Incompatimic model of anomaly detection on different panoramas

2021 ◽  
Author(s):  
O.P. Arkhipov ◽  
M.V. Tsukanov
Keyword(s):  
Anomaly Detection ◽  
Singular Points ◽  
Single View ◽  
Noise Type ◽  
Automatic Methods ◽  
Algorithmic Model ◽  
Special Points ◽  
Selection Of

The development of automatic methods for comparing panoramas obtained at different times during the inspection flight of UAVs of the same area is currently an urgent and popular task. In this connection, a new algorithmic model for detecting anomalies on multi-time panoramas was proposed, based on the comparison of the found singular points and descriptors, establishing their mutual correspondence on panoramas, and highlighting the found differences in non-overlapping areas of anomalies. The strategy aimed at bringing the panoramas to a single view and their subsequent synchronization is proposed. The results of the algorithm are presented, using the example of multi-time panoramas of the selected inspected area. We managed to synchronize the panoramas at different times to minimize differences in the shooting angles and illumination. Perform a search for anomalies on multi-time panoramas, excluding the selection of anomalies of the "noise" type and minor deviations in the color and geometric coordinates of special points. Sort the found anomalies by importance groups.

AIS data analytics for adaptive rotating shift in vessel traffic service

2020 ◽  
Vol 120 (4) ◽  
pp. 749-767
Author(s):  
Gangyan Xu ◽  
Chun-Hsien Chen ◽  
Fan Li ◽  
Xuan Qiu
Keyword(s):  
Anomaly Detection ◽  
Data Model ◽  
Data Analytics ◽  
Detection Method ◽  
Traffic Information ◽  
Automatic Identification ◽  
Identification System ◽  
Content Type ◽  
Maritime Traffic ◽  
Free Data

PurposeConsidering the varied and dynamic workload of vessel traffic service (VTS) operators, design an adaptive rotating shift solution to prevent them from getting tired while ensuring continuous high-quality services and finally guarantee a benign maritime traffic environment.Design/methodology/approachThe problem of rotating shift in VTS and its influencing factors are analyzed first, then the framework of automatic identification system (AIS) data analytics is proposed, as well as the data model to extract spatial–temporal information. Besides, K-means-based anomaly detection method is adjusted to generate anomaly-free data, with which the traffic trend analysis and prediction are made. Based on this knowledge, strategies and methods for adaptive rotating shift design are worked out.FindingsIn VTS, vessel number and speed are identified as two most crucial factors influencing operators' workload. Based on the two factors, the proposed data model is verified to be effective on reducing data size and improving data processing efficiency. Besides, the K-means-based anomaly detection method could provide stable results, and the work shift pattern planning algorithm could efficiently generate acceptable solutions based on maritime traffic information.Originality/valueThis is a pioneer work on utilizing maritime traffic data to facilitate the operation management in VTS, which provides a new direction to improve their daily management. Besides, a systematic data-driven solution for adaptive rotating shift is proposed, including knowledge discovery method and decision-making algorithm for adaptive rotating shift design. The technical framework is flexible and can be extended for managing other activities in VTS or adapted in diverse fields.

Decision Making in Team Sports: Data, model and applied perspective

2008 ◽  
Author(s):  
Pedro J. M. Passos ◽  
Duarte Araujo ◽  
Keith Davids ◽  
Ana Diniz ◽  
Luis Gouveia ◽  
...  
Keyword(s):  
Decision Making ◽  
Data Model ◽  
Team Sports ◽  
Sports Data

Anomaly Detection in Sensor Data

2018 ◽  
Vol 18 (1) ◽  
pp. 20-32 ◽  
Author(s):  
Jong-Min Kim ◽  
Jaiwook Baik
Keyword(s):  
Anomaly Detection ◽  
Sensor Data

A Structured Method for the Recognition of Complex Historical Tables

1997 ◽  
Vol 9 (1-3) ◽  
pp. 58-77
Author(s):  
Vitaly Kliatskine ◽  
Eugene Shchepin ◽  
Gunnar Thorvaldsen ◽  
Konstantin Zingerman ◽  
Valery Lazarev
Keyword(s):  
Nineteenth Century ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Complex Structure ◽  
Source Material ◽  
Historical Sources ◽  
Tax Assessment ◽  
Optical Character ◽  
Algorithmic Model ◽  
Machine Readable

In principle, printed source material should be made machine-readable with systems for Optical Character Recognition, rather than being typed once more. Offthe-shelf commercial OCR programs tend, however, to be inadequate for lists with a complex layout. The tax assessment lists that assess most nineteenth century farms in Norway, constitute one example among a series of valuable sources which can only be interpreted successfully with specially designed OCR software. This paper considers the problems involved in the recognition of material with a complex table structure, outlining a new algorithmic model based on ‘linked hierarchies’. Within the scope of this model, a variety of tables and layouts can be described and recognized. The ‘linked hierarchies’ model has been implemented in the ‘CRIPT’ OCR software system, which successfully reads tables with a complex structure from several different historical sources.

A Qualified Assertion Database for the History of Places

2019 ◽  
Vol 13 (1-2) ◽  
pp. 95-115
Author(s):  
Brandon Plewe
Keyword(s):  
Data Model ◽  
Temporal Change ◽  
Religious Congregations ◽  
Historical Gis ◽  
The Past ◽  
Model Based ◽  
Complex Information ◽  
Invaluable Tool ◽  
History Of ◽  
The Rich

Historical place databases can be an invaluable tool for capturing the rich meaning of past places. However, this richness presents obstacles to success: the daunting need to simultaneously represent complex information such as temporal change, uncertainty, relationships, and thorough sourcing has been an obstacle to historical GIS in the past. The Qualified Assertion Model developed in this paper can represent a variety of historical complexities using a single, simple, flexible data model based on a) documenting assertions of the past world rather than claiming to know the exact truth, and b) qualifying the scope, provenance, quality, and syntactics of those assertions. This model was successfully implemented in a production-strength historical gazetteer of religious congregations, demonstrating its effectiveness and some challenges.

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