scholarly journals Predictive Fail-Safe Improving the Safety of Industrial Environments through Model-based Analytics on hidden Data Sources

2018 ◽  
Author(s):  
Amer Kajmakovic ◽  
Robert Zupanc ◽  
Simon Mayer ◽  
Nermin Kajtazovic ◽  
Martin Hoeffernig ◽  
...  
Keyword(s):  
Data Sources ◽  
Model Based ◽  
Industrial Environments ◽  
Hidden Data ◽  
Fail Safe

scholarly journals Bridging the gap between decision-making and emerging big data sources: An application of a model-based framework to disaster management in Brazil

2017 ◽  
Vol 97 ◽  
pp. 12-22 ◽  
Author(s):  
Flávio E.A. Horita ◽  
João Porto de Albuquerque ◽  
Victor Marchezini ◽  
Eduardo M. Mendiondo
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Disaster Management ◽  
Data Sources ◽  
Model Based

Research of Multi-Data Sources Report Model Based on Data Dictionary

2012 ◽  
Vol 532-533 ◽  
pp. 846-849
Author(s):  
Yu Jing Lu ◽  
Qing Hui Hu
Keyword(s):  
Data Sources ◽  
Software System ◽  
Data Dictionary ◽  
Application Program ◽  
Model Based ◽  
Report System ◽  
System Data ◽  
Data Source

This paper put forward an idea of multi-data sources report model based on data dictionary in order to separate the report from application program. When report changed, we can alter the system data dictionary, data source dictionary or modal file dictionary to adapt to new requests without any changes for application program. This brings to high independence between application program and report system. At the same time we can transplant the report system to different software system without any changes.

An enhanced personal credit identification coin-day destruction model based on blockchain technology fuzzy sets for region of China pearl river delta

2021 ◽  
pp. 1-7
Author(s):  
Jiansai Zhang ◽  
Lu Guo ◽  
Tingjie Lyu
Keyword(s):  
Fuzzy Sets ◽  
Pearl River Delta ◽  
River Delta ◽  
Data Sources ◽  
Pearl River ◽  
Personal Credit ◽  
Model Based ◽  
Blockchain Technology ◽  
Coastal Cities ◽  
Global Financial System

Nowadays, the Expansion and evolution of the global financial system oblige lenders to develop stricter requirements for assessing creditworthiness of borrowers. This paper analyses the problems prevalent in the existing credit models of coastal cities in China Pearl River Delta, including data centralization, difficulties in detecting forged data and delay in data transmission; we constructed a CDDC model based fuzzy sets that employs all the issues. The related results showed that the technology fuzzy sets decentralizes and expands data sources, acquires and processes data automatically and self-perfects its ability to rank borrowers into cohorts of creditworthiness. Moreover, the CDDC model out-performs the traditional model in assessing creditworthiness and reducing delinquencies and defaults. That means our fuzzy sets model employs decentralized data sources, destroys historical data regularly and facilitates training and improvement. It ranks creditworthy borrowers in a better fashion than the statistics-based traditional credit model.

scholarly journals A Model-Based Chatbot Generation Approach to Converse with Open Data Sources

2021 ◽  
pp. 440-455
Author(s):  
Hamza Ed-douibi ◽  
Javier Luis Cánovas Izquierdo ◽  
Gwendal Daniel ◽  
Jordi Cabot
Keyword(s):  
Open Data ◽  
Data Sources ◽  
Model Based

scholarly journals A Cognition Knowledge Representation Model Based on Multidimensional Heterogeneous Data

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Dong Zhong ◽  
Yi-An Zhu ◽  
Lanqing Wang ◽  
Junhua Duan ◽  
Jiaxuan He
Keyword(s):  
Knowledge Representation ◽  
Data Sources ◽  
Knowledge Graph ◽  
Information Representation ◽  
Reasoning Ability ◽  
Model Based ◽  
Representation Model ◽  
Industrial Internet ◽  
Cognitive Information ◽  
Cognitive Knowledge

The information in the working environment of industrial Internet is characterized by diversity, semantics, hierarchy, and relevance. However, the existing representation methods of environmental information mostly emphasize the concepts and relationships in the environment and have an insufficient understanding of the items and relationships at the instance level. There are also some problems such as low visualization of knowledge representation, poor human-machine interaction ability, insufficient knowledge reasoning ability, and slow knowledge search speed, which cannot meet the needs of intelligent and personalized service. Based on this, this paper designs a cognitive information representation model based on a knowledge graph, which combines the perceptual information of industrial robot ontology with semantic description information such as functional attributes obtained from the Internet to form a structured and logically reasoned cognitive knowledge graph including perception layer and cognition layer. Aiming at the problem that the data sources of the knowledge base for constructing the cognitive knowledge graph are wide and heterogeneous, and there are entity semantic differences and knowledge system differences among different data sources, a multimodal entity semantic fusion model based on vector features and a system fusion framework based on HowNet are designed, and the environment description information such as object semantics, attributes, relations, spatial location, and context acquired by industrial robots and their own state information are unified and standardized. The automatic representation of robot perceived information is realized, and the universality, systematicness, and intuition of robot cognitive information representation are enhanced, so that the cognition reasoning ability and knowledge retrieval efficiency of robots in the industrial Internet environment can be effectively improved.

Black-box model-based regression testing of fail-safe behavior in web applications

2019 ◽  
Vol 149 ◽  
pp. 318-339 ◽  
Author(s):  
Anneliese Andrews ◽  
Ahmed Alhaddad ◽  
Salah Boukhris
Keyword(s):  
Web Applications ◽  
Black Box ◽  
Regression Testing ◽  
Box Model ◽  
Model Based ◽  
Safe Behavior ◽  
Fail Safe

scholarly journals Research on Heterogeneous Digital Map Resource Query Algorithm Based on Web Services

2020 ◽  
Vol 194 ◽  
pp. 05001
Author(s):  
Liu Wen-bing ◽  
Wang Jun ◽  
Wu You-feng ◽  
Feng Xing-lai
Keyword(s):  
Web Services ◽  
Retrieval System ◽  
Current Situation ◽  
Data Sources ◽  
Retrieval Model ◽  
Fusion Algorithm ◽  
Digital Map ◽  
Model Based ◽  
Retrieval Result ◽  
Query Algorithm

Based on the current situation of digital map resource interconnection and mutual inspection, this paper studies three modes of unified retrieval of traditional guided data sources, and proposes a digital map resource retrieval model based on Web Services. This paper also designs digital map resources unified retrieval result fusion algorithm and metadata update algorithm based on Web Services in detail, which can be used for the development of digital map resource unified retrieval system.

scholarly journals Model-based integration of citizen-science data from disparate sources increases the precision of bird population trends

2020 ◽  
Author(s):  
Lionel R Hertzog ◽  
Claudia Frank ◽  
Sebastian Klimek ◽  
Norbert Röder ◽  
Hannah GS Böhner ◽  
...  
Keyword(s):  
Hierarchical Models ◽  
Bird Species ◽  
Population Trends ◽  
Data Sources ◽  
Bird Population ◽  
Benchmark Model ◽  
Model Based ◽  
Time Investment ◽  
Monitoring Programs ◽  
Online Databases

AbstractAimTimely and accurate information on population trends is a prerequisite for effective biodiversity conservation. Structured biodiversity monitoring programs have been shown to track population trends reliably, but require large financial and time investment. The data assembled in a large and growing number of online databases are less structured and suffer from bias, but the number of observations is much higher compared to structured monitoring programs. Model-based integration of data from these disparate sources could capitalize on their respective strengths.LocationGermany.MethodsAbundance data for 26 farmland bird species were gathered from the standardized Common Breeding Bird Survey (CBBS) and three online databases that varied with regard to their degree of survey standardization. Population trends were estimated with a benchmark model that included only CBBS data, and five Bayesian hierarchical models integrating all data sources in different combinations. Across models, we compared consistency and precision of the predicted population trends, and the accuracy of the models. Bird species body mass, prevalence in the dataset and abundance were tested as potential predictors of the explored quantities.ResultsConsistency in predicted annual abundance indices was generally high especially when comparing the benchmark models to the integrated models without unstructured data. The accuracy of the estimated population changes was higher in the hierarchical models compared to the benchmark model but this was not related to data-integration. Precision of the predicted population trends increased as more data sources were integrated.Main conclusionsModel-based integration of data from different sources can lead to improved precision of bird population trend estimates. This opens up new opportunities for conservation managers to identify declining populations earlier. Integrating data from online databases could substantially increase sample size and thus allowing to derive trends for currently not well-monitored species, especially at sub-national scales.

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