Supporting Privacy Control and Personalized Data Usage Explanations in a Context-Based Adaptive Collaboration Environment

Author(s):  
Mandy Goram ◽  
Dirk Veiel
Author(s):  
Seyed Kourosh Mahjour ◽  
Antonio Alberto Souza Santos ◽  
Manuel Gomes Correia ◽  
Denis José Schiozer

AbstractThe simulation process under uncertainty needs numerous reservoir models that can be very time-consuming. Hence, selecting representative models (RMs) that show the uncertainty space of the full ensemble is required. In this work, we compare two scenario reduction techniques: (1) Distance-based Clustering with Simple Matching Coefficient (DCSMC) applied before the simulation process using reservoir static data, and (2) metaheuristic algorithm (RMFinder technique) applied after the simulation process using reservoir dynamic data. We use these two methods as samples to investigate the effect of static and dynamic data usage on the accuracy and rate of the scenario reduction process focusing field development purposes. In this work, a synthetic benchmark case named UNISIM-II-D considering the flow unit modelling is used. The results showed both scenario reduction methods are reliable in selecting the RMs from a specific production strategy. However, the obtained RMs from a defined strategy using the DCSMC method can be applied to other strategies preserving the representativeness of the models, while the role of the strategy types to select the RMs using the metaheuristic method is substantial so that each strategy has its own set of RMs. Due to the field development workflow in which the metaheuristic algorithm is used, the number of required flow simulation models and the computational time are greater than the workflow in which the DCSMC method is applied. Hence, it can be concluded that static reservoir data usage on the scenario reduction process can be more reliable during the field development phase.


2021 ◽  
pp. 1-8
Author(s):  
Janessa Mladucky ◽  
Bonnie Baty ◽  
Jeffrey Botkin ◽  
Rebecca Anderson

Introduction: Customer data from direct-to-consumer genetic testing (DTC GT) are often used for secondary purposes beyond providing the customer with test results. Objective: The goals of this study were to determine customer knowledge of secondary uses of data, to understand their perception of risks associated with these uses, and to determine the extent of customer concerns about privacy. Methods: Twenty DTC GT customers were interviewed about their experiences. The semi-structured interviews were transcribed, coded, and analyzed for common themes. Results: Most participants were aware of some secondary uses of data. All participants felt that data usage for research was acceptable, but acceptability for non-research purposes varied across participants. The majority of participants were aware of the existence of a privacy policy, but few read the majority of the privacy statement. When previously unconsidered uses of data were discussed, some participants expressed concern over privacy protections for their data. Conclusion: When exposed to new information on secondary uses of data, customers express concerns and a desire to improve consent with transparency, more opt-out options, improved readability, and more information on future uses and potential risks from direct-to-consumer companies. Effective ways to improve readership about the secondary use, risk of use, and protection of customer data should be investigated and the findings implemented by DTC companies to protect public trust in these practices.


2021 ◽  
Vol 10 (1) ◽  
pp. 30
Author(s):  
Alfonso Quarati ◽  
Monica De Martino ◽  
Sergio Rosim

The Open Government Data portals (OGD), thanks to the presence of thousands of geo-referenced datasets, containing spatial information are of extreme interest for any analysis or process relating to the territory. For this to happen, users must be enabled to access these datasets and reuse them. An element often considered as hindering the full dissemination of OGD data is the quality of their metadata. Starting from an experimental investigation conducted on over 160,000 geospatial datasets belonging to six national and international OGD portals, this work has as its first objective to provide an overview of the usage of these portals measured in terms of datasets views and downloads. Furthermore, to assess the possible influence of the quality of the metadata on the use of geospatial datasets, an assessment of the metadata for each dataset was carried out, and the correlation between these two variables was measured. The results obtained showed a significant underutilization of geospatial datasets and a generally poor quality of their metadata. In addition, a weak correlation was found between the use and quality of the metadata, not such as to assert with certainty that the latter is a determining factor of the former.


Author(s):  
Sébastien Canard ◽  
Nicolas Desmoulins ◽  
Sébastien Hallay ◽  
Adel Hamdi ◽  
Dominique Le Hello

2014 ◽  
Author(s):  
Baojun Ma ◽  
Hailiang Chen
Keyword(s):  

2015 ◽  
Vol 1117 ◽  
pp. 283-286
Author(s):  
Inga Dāboliņa ◽  
Ausma Viļumsone ◽  
Jānis Dāboliņš ◽  
Dana Beļakova

Computer aided designing software not only the possibility to speed up the process of putting a new model into production and improve the quality of the products, but also reduces material costs and labour intensity, ensuring an elastic change of the assortment. The designing of clothes includes a row of processes and one of the most time and labour consuming is constructing. A construction displays the layout (pattern) of the surface of the body (garment). As it depends on correct anthropometric data, it is very important to get ones right. The use of 3D surface scanning technologies to produce digitized representations of the human anatomy has the potential to help change the way a wide range of products are designed and produced. Every scanning device is equipped with optic (light) appliances to ensure non-contact measuring. Measurements acquired by 3D scanning device should be checked out for compliance with CAD systems for automatized pattern making procedure. The paper introduces the experiment with scanned data usage in CAD pattern making. The project aims to implement scanned data values in the CAD/CAM individual measurement list for acquiring individualized pattern blocks.


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