The Experts below are selected from a list of 522792 Experts worldwide ranked by ideXlab platform
Aaron Roth - One of the best experts on this subject based on the ideXlab platform.
-
differential privacy an Economic Method for choosing epsilon
IEEE Computer Security Foundations Symposium, 2014Co-Authors: Justin Hsu, Marco Gaboardi, Andreas Haeberlen, Sanjeev Khanna, Arjun Narayan, Benjamin C Pierce, Aaron RothAbstract:Differential privacy is becoming a gold standard notion of privacy, it offers a guaranteed bound on loss of privacy due to release of query results, even under worst-case assumptions. The theory of differential privacy is an active research area, and there are now differentially private algorithms for a wide range of problems. However, the question of when differential privacy works in practice has received relatively little attention. In particular, there is still no rigorous Method for choosing the key parameter a#x03B5;, which controls the crucial trade off between the strength of the privacy guarantee and the accuracy of the published results. In this paper, we examine the role of these parameters in concrete applications, identifying the key considerations that must be addressed when choosing specific values. This choice requires balancing the interests of two parties with conflicting objectives: the data analyst, who wishes to learn something about the data, and the prospective participant, who must decide whether to allow their data to be included in the analysis. We propose a simple model that expresses this balance as formulas over a handful of parameters, and we use our model to choose a#x03B5; on a series of simple statistical studies. We also explore a surprising insight: in some circumstances, a differentially private study can be more accurate than a non-private study for the same cost, under our model. Finally, we discuss the simplifying assumptions in our model and outline a research agenda for possible refinements.
-
CSF - Differential Privacy: An Economic Method for Choosing Epsilon
2014 IEEE 27th Computer Security Foundations Symposium, 2014Co-Authors: Justin Hsu, Marco Gaboardi, Andreas Haeberlen, Sanjeev Khanna, Arjun Narayan, Benjamin C Pierce, Aaron RothAbstract:Differential privacy is becoming a gold standard notion of privacy, it offers a guaranteed bound on loss of privacy due to release of query results, even under worst-case assumptions. The theory of differential privacy is an active research area, and there are now differentially private algorithms for a wide range of problems. However, the question of when differential privacy works in practice has received relatively little attention. In particular, there is still no rigorous Method for choosing the key parameter a#x03B5;, which controls the crucial trade off between the strength of the privacy guarantee and the accuracy of the published results. In this paper, we examine the role of these parameters in concrete applications, identifying the key considerations that must be addressed when choosing specific values. This choice requires balancing the interests of two parties with conflicting objectives: the data analyst, who wishes to learn something about the data, and the prospective participant, who must decide whether to allow their data to be included in the analysis. We propose a simple model that expresses this balance as formulas over a handful of parameters, and we use our model to choose a#x03B5; on a series of simple statistical studies. We also explore a surprising insight: in some circumstances, a differentially private study can be more accurate than a non-private study for the same cost, under our model. Finally, we discuss the simplifying assumptions in our model and outline a research agenda for possible refinements.
Elmira Fallahi - One of the best experts on this subject based on the ideXlab platform.
-
optimizing the insulation thickness of external wall by a novel 3e energy environmental Economic Method
Construction and Building Materials, 2019Co-Authors: Ehsan Amiri Rad, Elmira FallahiAbstract:Abstract One of the main challenges in the building industry is determining the thickness and material of insulations that are used in the external wall. The selection of the above-mentioned parameters depends upon various aspects, including energy, environment, and economy. In many cases, the analysis which is carried out based on each of these aspects leads to different results. In the present study, a comprehensive analysis was carried out based on energy, environment, and economy criteria where the energy, environment, and Economic costs of producing insulations are also taken into account. Accordingly, material and optimum thickness of insulation for the external wall of an office building were determined. The results showed that Polyurethane with the thickness of 8 cm, EPS with the thickness of 20 cm, and Rockwool with the thickness of 7 cm were optimum states with regard to the aspects of energy, environment, and economy respectively. Finally, a novel function, which considered all three parameters simultaneously, was defined. Consequently, 3E (energy, environmental, and Economic) analysis was carried out and led to the presentation of the Mineral wool insulation with the thickness of 11 cm as the optimum state of investigated cases according to the 3E criterion.
Justin Hsu - One of the best experts on this subject based on the ideXlab platform.
-
differential privacy an Economic Method for choosing epsilon
IEEE Computer Security Foundations Symposium, 2014Co-Authors: Justin Hsu, Marco Gaboardi, Andreas Haeberlen, Sanjeev Khanna, Arjun Narayan, Benjamin C Pierce, Aaron RothAbstract:Differential privacy is becoming a gold standard notion of privacy, it offers a guaranteed bound on loss of privacy due to release of query results, even under worst-case assumptions. The theory of differential privacy is an active research area, and there are now differentially private algorithms for a wide range of problems. However, the question of when differential privacy works in practice has received relatively little attention. In particular, there is still no rigorous Method for choosing the key parameter a#x03B5;, which controls the crucial trade off between the strength of the privacy guarantee and the accuracy of the published results. In this paper, we examine the role of these parameters in concrete applications, identifying the key considerations that must be addressed when choosing specific values. This choice requires balancing the interests of two parties with conflicting objectives: the data analyst, who wishes to learn something about the data, and the prospective participant, who must decide whether to allow their data to be included in the analysis. We propose a simple model that expresses this balance as formulas over a handful of parameters, and we use our model to choose a#x03B5; on a series of simple statistical studies. We also explore a surprising insight: in some circumstances, a differentially private study can be more accurate than a non-private study for the same cost, under our model. Finally, we discuss the simplifying assumptions in our model and outline a research agenda for possible refinements.
-
CSF - Differential Privacy: An Economic Method for Choosing Epsilon
2014 IEEE 27th Computer Security Foundations Symposium, 2014Co-Authors: Justin Hsu, Marco Gaboardi, Andreas Haeberlen, Sanjeev Khanna, Arjun Narayan, Benjamin C Pierce, Aaron RothAbstract:Differential privacy is becoming a gold standard notion of privacy, it offers a guaranteed bound on loss of privacy due to release of query results, even under worst-case assumptions. The theory of differential privacy is an active research area, and there are now differentially private algorithms for a wide range of problems. However, the question of when differential privacy works in practice has received relatively little attention. In particular, there is still no rigorous Method for choosing the key parameter a#x03B5;, which controls the crucial trade off between the strength of the privacy guarantee and the accuracy of the published results. In this paper, we examine the role of these parameters in concrete applications, identifying the key considerations that must be addressed when choosing specific values. This choice requires balancing the interests of two parties with conflicting objectives: the data analyst, who wishes to learn something about the data, and the prospective participant, who must decide whether to allow their data to be included in the analysis. We propose a simple model that expresses this balance as formulas over a handful of parameters, and we use our model to choose a#x03B5; on a series of simple statistical studies. We also explore a surprising insight: in some circumstances, a differentially private study can be more accurate than a non-private study for the same cost, under our model. Finally, we discuss the simplifying assumptions in our model and outline a research agenda for possible refinements.
Galen D Stucky - One of the best experts on this subject based on the ideXlab platform.
-
nonaqueous production of nanostructured anatase with high energy facets
Journal of the American Chemical Society, 2008Co-Authors: Binghui Wu, Nanfeng Zheng, Galen D StuckyAbstract:Although solution-based synthesis is the most powerful and Economic Method to create nanostructured anatase TiO2, under those synthesis conditions the {101} facets are the most thermodynamically stable, making it difficult to create anatase nanomaterials with a large percentage of high-energy {001} or {010} facets exposed. Here, we report a facile nonaqueous synthetic route to prepare anatase nanosheets with exposed {001} facets and high-quality rhombic-shaped anatase nanocrystals with a large percentage of exposed {010} facets. Including adscititious water in the nonaqueous synthesis and eliminating the use of carboxylic acid type capping agents are the two keys to integrating the structural diversity from aqueous systems into large-quantity synthesis in nonaqueous systems. The nanostructured TiO2 that we prepared exhibits conspicuous activity in the photocatalytic degradation of organic contaminants.
Imran Ali - One of the best experts on this subject based on the ideXlab platform.
-
novel and Economic Method of carbon nanotubes synthesis on a nickel magnesium oxide catalyst using microwave radiation
Journal of Molecular Liquids, 2018Co-Authors: Elena Burakova, T P Dyachkova, A V Rukhov, E N Tugolukov, Evgeny Galunin, A G Tkachev, Al Arsh Basheer, Imran AliAbstract:Abstract Carbon nanotubes (CNTs) are gaining increased importance in many fields of science and technology due to their unique properties of greater surface area, mechanical strength, electrical and thermal conductivity. A novel Method of carbon nanotubes synthesis on a nickel magnesium oxide catalyst using microwave radiation was developed and presented. In the present paper, the possibility of modifying a Ni-MgO catalyst, for carbon nanotube synthesis with microwave radiation (0.8 kW and 2.45 GHz) at the production stage, is studied. The effect of this radiation on the catalyst characteristics (specific surface area, catalytic activity, etc.) is experimentally considered. It is shown that the use of short term exposure to the microwave radiation in preparing the catalyst made it possible to increase its specific surface area from 5.2 to 9.1 m2/g. The implementation of chemical vapor deposition of the catalyst, modified with the microwave radiation for 30 s, contributed to an increase in the yield of a nanostructured material by 40–45%; making carbon nanotubes inexpensive in production. The synthesized carbon nanostructured material predominantly represented multilayered nanotubes with a diameter of 10–40 nm. The developed Method was capable to produce 40–45% yield with almost two time's greater surface area. The synthesized carbon nanotubes may be used for various purposes including water treatment due to the economy in production and large surface area.
