Combining Movement Model with Finger-Stroke Level Model Towards Designing a Security Enhancing Mobile Friendly CAPTCHA

2020 ◽  
Author(s):  
Ahmed Iqbal Pritom ◽  
Mehrab Zaman Chowdhury ◽  
Joy Protim ◽  
Shanto Roy ◽  
Md Rashedur Rahman ◽  
...  
Keyword(s):  
Movement Model ◽  
Level Model

Exciton dynamics in thick GaN MOVPE epilayers deposited on sapphire.

1997 ◽  
Vol 2 ◽  
Author(s):  
J. Allègre ◽  
P. Lefebvre ◽  
J. Camassel ◽  
B. Beaumont ◽  
Pierre Gibart
Keyword(s):  
Layer Thickness ◽  
Buffer Layers ◽  
Rate Equations ◽  
Time Resolved ◽  
Versus Layer ◽  
Level Model ◽  
Shallow Impurities ◽  
Aln Buffer ◽  
Time Resolved Photoluminescence

Time-resolved photoluminescence spectra have been recorded on three GaN epitaxial layers of thickness 2.5 μm, 7 μm and 16 μm, at various temperatures ranging from 8K to 300K. The layers were deposited by MOVPE on (0001) sapphire substrates with standard AlN buffer layers. To achieve good homogeneities, the growth was in-situ monitored by laser reflectometry. All GaN layers showed sharp excitonic peaks in cw PL and three excitonic contributions were seen by reflectivity. The recombination dynamics of excitons depends strongly upon the layer thickness. For the thinnest layer, exponential decays with τ ~ 35 ps have been measured for both XA and XB free excitons. For the thickest layer, the decay becomes biexponential with τ1 ~ 80 ps and τ2 ~ 250 ps. These values are preserved up to room temperature. By solving coupled rate equations in a four-level model, this evolution is interpreted in terms of the reduction of density of both shallow impurities and deep traps, versus layer thickness, roughly following a L−1 law.

Modeling and design of role engineering in development of access control for dynamic information systems

2013 ◽  
Vol 61 (3) ◽  
pp. 569-579 ◽  
Author(s):  
A. Poniszewska-Marańda
Keyword(s):  
Information Systems ◽  
Dynamic Information ◽  
Minimal Set ◽  
Distributed Information ◽  
Heterogeneous Information ◽  
System Protection ◽  
Level Model ◽  
Model Independent ◽  
Role Concept ◽  
High Level

Abstract Nowadays, the growth and complexity of functionalities of current information systems, especially dynamic, distributed and heterogeneous information systems, makes the design and creation of such systems a difficult task and at the same time, strategic for businesses. A very important stage of data protection in an information system is the creation of a high level model, independent of the software, satisfying the needs of system protection and security. The process of role engineering, i.e. the identification of roles and setting up in an organization is a complex task. The paper presents the modeling and design stages in the process of role engineering in the aspect of security schema development for information systems, in particular for dynamic, distributed information systems, based on the role concept and the usage concept. Such a schema is created first of all during the design phase of a system. Two actors should cooperate with each other in this creation process, the application developer and the security administrator, to determine the minimal set of user’s roles in agreement with the security constraints that guarantee the global security coherence of the system.

An Analysis on Factors of Parent Involvement in Middle School Using Multi-Level Model

2018 ◽  
Vol 18 (5) ◽  
pp. 521-540
Author(s):  
Eunyoung Kim ◽  
◽  
Soonbum Kwon ◽  
Meejung Chin ◽  
◽  
...  
Keyword(s):  
Middle School ◽  
Parent Involvement ◽  
Level Model ◽  
Multi Level

Conclusions

2017 ◽  
Author(s):  
Alan Baron ◽  
John Hassard ◽  
Fiona Cheetham ◽  
Sudi Sharifi
Keyword(s):  
Empirical Research ◽  
Critical Review ◽  
Organization Theory ◽  
Organization Culture ◽  
Workplace Attitudes ◽  
Level Model ◽  
Preceding Study

The final chapter brings together a series of conclusions based on the preceding study of workplace attitudes, behaviour, and experiences within an English hospice. Initially it examines the nature of relationships between the three concepts that form the analytical core of this study—culture, identity, and image. This includes a wide-ranging critical review of these concepts in relation to the relevant fields of literature in management and organization theory. Subsequently a number of limitations are considered with regard to the use of Schein’s well-known three-level model of culture as a framework for guiding empirical research. The chapter ends by discussing some metaphorical issues relevant to the study and specifically makes proposals for perceiving organization culture as something that is philosophically fluid, uncertain, and in flux.

scholarly journals Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shan Guleria ◽  
Tilak U. Shah ◽  
J. Vincent Pulido ◽  
Matthew Fasullo ◽  
Lubaina Ehsan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Diagnostic Accuracy ◽  
High Sensitivity ◽  
Confocal Laser Endomicroscopy ◽  
Confocal Laser ◽  
Learning Approaches ◽  
Learning Models ◽  
Whole Slide Image ◽  
Slide Image ◽  
Level Model

AbstractProbe-based confocal laser endomicroscopy (pCLE) allows for real-time diagnosis of dysplasia and cancer in Barrett’s esophagus (BE) but is limited by low sensitivity. Even the gold standard of histopathology is hindered by poor agreement between pathologists. We deployed deep-learning-based image and video analysis in order to improve diagnostic accuracy of pCLE videos and biopsy images. Blinded experts categorized biopsies and pCLE videos as squamous, non-dysplastic BE, or dysplasia/cancer, and deep learning models were trained to classify the data into these three categories. Biopsy classification was conducted using two distinct approaches—a patch-level model and a whole-slide-image-level model. Gradient-weighted class activation maps (Grad-CAMs) were extracted from pCLE and biopsy models in order to determine tissue structures deemed relevant by the models. 1970 pCLE videos, 897,931 biopsy patches, and 387 whole-slide images were used to train, test, and validate the models. In pCLE analysis, models achieved a high sensitivity for dysplasia (71%) and an overall accuracy of 90% for all classes. For biopsies at the patch level, the model achieved a sensitivity of 72% for dysplasia and an overall accuracy of 90%. The whole-slide-image-level model achieved a sensitivity of 90% for dysplasia and 94% overall accuracy. Grad-CAMs for all models showed activation in medically relevant tissue regions. Our deep learning models achieved high diagnostic accuracy for both pCLE-based and histopathologic diagnosis of esophageal dysplasia and its precursors, similar to human accuracy in prior studies. These machine learning approaches may improve accuracy and efficiency of current screening protocols.

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