A Computationally Efficient MCMC Approach to Estimating Structural Models of Aggregate Demand

2012 ◽  
Author(s):  
Yutec Sun ◽  
Masakazu Ishihara
Keyword(s):  
Aggregate Demand ◽  
Structural Models ◽  
Computationally Efficient ◽  
Mcmc Approach

Computationally-Efficient Structural Models for Analysis of Woven Composites

2020 ◽  
Author(s):  
Ibrahim Kaleel ◽  
Alberto Garcia de Miguel ◽  
Marco Petrolo ◽  
Alfonso Pagani ◽  
Erasmo Carrera ◽  
...  
Keyword(s):  
Structural Models ◽  
Woven Composites ◽  
Computationally Efficient

Validation of the Short Dark Triad in a German Sample

2020 ◽  
pp. 1-12
Author(s):  
Caroline Wehner ◽  
Ulrike Maaß ◽  
Marius Leckelt ◽  
Mitja D. Back ◽  
Matthias Ziegler
Keyword(s):  
Sensation Seeking ◽  
Factor Model ◽  
Structural Models ◽  
Self Esteem ◽  
Dark Triad ◽  
Fit Indices ◽  
Nomological Network ◽  
Competitive Test ◽  
Three Factor ◽  
Behavioral Criteria

Abstract. The structure, correlates, and assessment of the Dark Triad are widely discussed in several fields of psychology. Based on the German version of the Short Dark Triad (SDT), we add to this by (a) providing a competitive test of existing structural models, (b) testing the nomological network, and (c) proposing an ultrashort 9-item version of the SDT (uSDT). A sample of N = 969 participants provided data on the SDT and a range of further measures. Our competitive test of five structural models revealed that fit indices and nomological network assumptions were best met in a three-factor model, with separate factors for psychopathy, Machiavellianism, and narcissism. The results provided an extensive overview of the raw, unique, and shared associations of Dark Triad dimensions with narcissism facets, sadism, impulsivity, self-esteem, sensation seeking, the Big Five, maladaptive personality traits, sociosexual orientation, and behavioral criteria. Finally, the uSDT exhibited satisfactory psychometric properties. The highest overlap in expected relations between SDT and uSDT, and convergent and discriminant measures was also found for the three-factor model. Our study underlines the utility of a three-factor model of the Dark Triad, extends findings on its nomological network, and provides an ultrashort instrument.

A meta-analysis of age-cognition relations in adulthood: Structural models

1997 ◽  
Author(s):  
Paul Verhaeghen ◽  
Timothy A. Salthouse
Keyword(s):  
Meta Analysis ◽  
Structural Models

Computationally efficient model of the implanted knee for time-sensitive applications

2020 ◽  
Author(s):  
E Bori ◽  
A Navacchia ◽  
L Wang ◽  
L Duxbury ◽  
S McGuan ◽  
...  
Keyword(s):  
Computationally Efficient

Economic effects of monetary policy in Russia: What do large datasets tell us?

2020 ◽  
pp. 31-53 ◽  
Author(s):  
Anna A. Pestova ◽  
Natalia A. Rostova
Keyword(s):  
Monetary Policy ◽  
Interest Rate ◽  
Interest Rates ◽  
Economic Activity ◽  
Global Financial Crisis ◽  
Exchange Rate Regime ◽  
Aggregate Demand ◽  
Economic Effects ◽  
Theoretical Concepts ◽  
Empirical Estimates

Is the Bank of Russia able to control inflation and, at the same time, manage aggregate demand using its interest rate instruments? In other words, are empirical estimates of the effects of monetary policy in Russia consistent with the theoretical concepts and experience of advanced economies? This paper is aimed at addressing these issues. Unlike previous research, we employ “big data” — a large dataset of macroeconomic and financial data — to estimate the effects of monetary policy in Russia. We focus exclusively on the period after the 2008—2009 global financial crisis when the Bank of Russia announced the abandoning of its fixed ruble exchange rate regime and started to gradually transit to an interest rate management. Our estimation results do not confirm standard responses of key economic activity and price variables to tightening of monetary policy. Specifically, our estimates do not reveal a statistically significant restraining effect of the Bank of Russia’s policy of high interest rates on inflation in recent years. At the same time, we find a significant deteriorating effect of the monetary tightening on economic activity indicators: according to our conservative estimates, each of the key rate increases occurred in March and December 2014 had led to a decrease in the industrial production index by about 0.2 percentage points within a year.

Cloud-Based Multimedia Content Protection System

2020 ◽  
pp. 164-169
Author(s):  
B. Aparna ◽  
S. Madhavi ◽  
G. Mounika ◽  
P. Avinash ◽  
S. Chakravarthi
Keyword(s):  
Large Scale ◽  
Protection System ◽  
Multimedia Content ◽  
Computationally Efficient ◽  
Content Protection ◽  
Protection Systems ◽  
Multimedia Content Protection ◽  
High Scalability ◽  
Cloud Infrastructures ◽  
Rapid Deployment

We propose a new design for large-scale multimedia content protection systems. Our design leverages cloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads. The proposed system can be used to protect different multimedia content types, including videos, images, audio clips, songs, and music clips. The system can be deployed on private and/or public clouds. Our system has two novel components: (i) method to create signatures of videos, and (ii) distributed matching engine for multimedia objects. The signature method creates robust and representative signatures of videos that capture the depth signals in these videos and it is computationally efficient to compute and compare as well as it requires small storage. The distributed matching engine achieves high scalability and it is designed to support different multimedia objects. We implemented the proposed system and deployed it on two clouds: Amazon cloud and our private cloud. Our experiments with more than 11,000 videos and 1 million images show the high accuracy and scalability of the proposed system. In addition, we compared our system to the protection system used by YouTube and our results show that the YouTube protection system fails to detect most copies of videos, while our system detects more than 98% of them.

Structural models of water

2006 ◽  
Vol 176 (8) ◽  
pp. 833 ◽  
Author(s):  
Gari N. Sarkisov
Keyword(s):  
Structural Models
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