Artwork Identification in a Museum Environment: A Quantitative Evaluation of Factors Affecting Identification Accuracy

2021 ◽  
pp. 588-595
Author(s):  
A. Lanitis ◽  
Z. Theodosiou ◽  
H. Partaourides
Keyword(s):  
Quantitative Evaluation ◽  
Identification Accuracy ◽  
Factors Affecting ◽  
Museum Environment

scholarly journals Development of the Correction Algorithm to Limit the Deformation of Bacterial Colonies Diffraction Patterns Caused by Misalignment and Its Impact on the Bacteria Identification in the Proposed Optical Biosensor

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5797
Author(s):  
Igor Buzalewicz ◽  
Agnieszka Suchwałko ◽  
Magdalena Karwańska ◽  
Alina Wieliczko ◽  
Halina Podbielska
Keyword(s):  
Optical Biosensor ◽  
High Accuracy ◽  
Identification Accuracy ◽  
Optical Biosensors ◽  
Bacterial Colony ◽  
Factors Affecting ◽  
Bacteria Identification ◽  
Spatial Intensity Distribution ◽  
Diffraction Patterns ◽  
The Impact

Recently proposed methods of bacteria identification in optical biosensors based on the phenomenon of light diffraction on macro-colonies offer over 98% classification accuracy. However, such high accuracy relies on the comparable and repeatable spatial intensity distribution of diffraction patterns. Therefore, it is essential to eliminate all non-species/strain-dependent factors affecting the diffraction patterns. In this study, the impact of the bacterial colony and illuminating beam misalignment on the variation of classification features extracted from diffraction patterns was examined. It was demonstrated that misalignment introduced by the scanning module significantly affected diffraction patterns and extracted classification features used for bacteria identification. Therefore, it is a crucial system-dependent factor limiting the identification accuracy. The acceptable misalignment level, when the accuracy and quality of the classification features are not affected, was determined as no greater than 50 µm. Obtained results led to development of image-processing algorithms for determination of the direction of misalignment and concurrent alignment of the bacterial colonies’ diffraction patterns. The proposed algorithms enable the rigorous monitoring and controlling of the measurement’s conditions in order to preserve the high accuracy of bacteria identification.

scholarly journals Genetic stock identification of Atlantic salmon and its evaluation in a large population complex

2017 ◽  
Vol 74 (3) ◽  
pp. 327-338 ◽  
Author(s):  
Juha-Pekka Vähä ◽  
Jaakko Erkinaro ◽  
Morten Falkegård ◽  
Panu Orell ◽  
Eero Niemelä
Keyword(s):  
Atlantic Salmon ◽  
Large Population ◽  
Identification Accuracy ◽  
Lower Sensitivity ◽  
Stock Identification ◽  
Genetic Structuring ◽  
Genetic Stock ◽  
Factors Affecting ◽  
Genetic Stock Identification ◽  
Genetic Structure And Diversity

Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate among distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon (Salmo salar) population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed-stock fisheries.

scholarly journals Factors affecting the identification of individual mountain bongo antelope

PeerJ ◽  
2015 ◽  
Vol 3 ◽  
pp. e1303 ◽  
Author(s):  
Gwili E.M. Gibbon ◽  
Markus Bindemann ◽  
David L. Roberts
Keyword(s):  
Morphological Traits ◽  
Camera Trap ◽  
Model System ◽  
Error Rates ◽  
Identification Accuracy ◽  
Matching Task ◽  
Automated Identification ◽  
Factors Affecting ◽  
As Species ◽  
Monitoring Protocols

The recognition of individuals forms the basis of many endangered species monitoring protocols. This process typically relies on manual recognition techniques. This study aimed to calculate a measure of the error rates inherent within the manual technique and also sought to identify visual traits that aid identification, using the critically endangered mountain bongo,Tragelaphus eurycerus isaaci, as a model system. Identification accuracy was assessed with a matching task that required same/different decisions to side-by-side pairings of individual bongos. Error rates were lowest when only the flanks of bongos were shown, suggesting that the inclusion of other visual traits confounded accuracy. Accuracy was also higher for photographs of captive animals than camera-trap images, and in observers experienced in working with mountain bongos, than those unfamiliar with the sub-species. These results suggest that the removal of non-essential morphological traits from photographs of bongos, the use of high-quality images, and relevant expertise all help increase identification accuracy. Finally, given the rise in automated identification and the use of citizen science, something our results would suggest is applicable within the context of the mountain bongo, this study provides a framework for assessing their accuracy in individual as well as species identification.

Quantitative evaluation and application of Cryptosporidium parvum inactivation with ozone treatment

2007 ◽  
Vol 55 (1-2) ◽  
pp. 241-250 ◽  
Author(s):  
M. Cho ◽  
J. Yoon
Keyword(s):  
Quantitative Evaluation ◽  
Cryptosporidium Parvum ◽  
Contact Time ◽  
Treatment System ◽  
Ozone Treatment ◽  
Quantitative Methodology ◽  
Water Parameters ◽  
Factors Affecting ◽  
Unique Line ◽  
Ozone Disinfection

Despite a wealth of studies concerning the factors affecting the inactivation of Cryptosporidium parvum on ozone disinfection, practical approaches for predicting the inactivation level on ozone treatment system and determining the required ozone dose or contact time to achieve the required inactivation level remain unclear. When modified version of the “Delayed Chick–Watson model” was applied, the results show that Cryptosporidium parvum inactivation was well fitted with one unique line as “C̄Tlag” and “inactivation slope” for several water parameters and water types. Thus, this study suggests quantitative methodology for predicting the Cryptosporidium parvum inactivation level with observation for the contact time of ozone and Cryptosporidium parvum and ozone residual.

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