Pandora: Description of a Painting Database for Art Movement Recognition with Baselines and Perspectives

To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.To facilitate computer analysis of visual art, in the form of paintings, we introduce Pandora (Paintings Dataset for Recognizing the Art movement) database, a collection of digitized paintings labelled with respect to the artistic movement. Noting that the set of databases available as benchmarks for evaluation is highly reduced and most existing ones are limited in variability and number of images, we propose a novel large scale dataset of digital paintings. The database consists of more than 7700 images from 12 art movements. Each genre is illustrated by a number of images varying from 250 to nearly 1000. We investigate how local and global features and classification systems are able to recognize the art movement. Our experimental results suggest that accurate recognition is achievable by a combination of various categories.Comment: 11 pages, 1 figure, 6 table

A General Purpose Technology at Work: The Corliss Steam Engine in the late 19th Century US

The steam engine is widely regarded as the icon of the Industrial Revolution and a prime example of a 'General Purpose Technology,' and yet its contribution to growth is far from transparent. This paper examines the role that a particular innovative design in steam power, the Corliss engine, played in the intertwined processes of industrialization and urbanization that characterized the growth of the US economy in the late 19th century. Waterpower offered abundant and cheap energy, but restricted the location of manufacturing just to areas with propitious topography and climate. Steam engines offered the possibility of relaxing this severe constraint, allowing industry to locate where key considerations such as access to markets for inputs and outputs directed. The enhanced performance of the Corliss engine as well as its fuel efficiency helped tip the balance in favor of steam in the fierce contest with waterpower. With the aid of detailed data on the location of Corliss engines and waterwheels and a two-stage estimation strategy, we show that the deployment of Corliss engines indeed served as a catalyst for the massive relocation of industry away from rural areas and into large urban centers, thus fueling agglomeration economies, and attracting further population growth. This illustrates what we believe is an important aspect of the dynamics of GPTs, whether it is electricity in the early 20th century or Information Technologies in the present era: the fact that GPTs induce the widespread and more efficient relocation of economic activity, which in turn fosters long-term growth.

From Growth Spurts to Sustained Growth

This paper presents new evidence on the existence of pre-industrial growth spurts and the nature of economic growth during the transition from Malthus to Solow. In this research, growth spurts are an intrinsic feature of the economy, but throughout history their effect on standards of living is mostly temporary. Sustained rises in living standards only become sustained when there are complementarities between the triple engines of growth of technological development, human capital and the organization of the workplace. In Malthusian economies, most technologies were basic and only required straightforward knowledge or human capital, and thus the skill-technology complementarity did not play a role in their development. As a consequence, most technological developments in Malthusian economies generated growth spurts that did not become sustained, although there was a temporary increase in standards of living. However, the increasing complexity of the epistemic knowledge base reported by the historical literature meant that investments in applied technology were progressively more significant, enhancing the role of human capital. After a certain threshold of the knowledge base was surpassed, more and more complex applied technologies were developed, and growth spurts became permanent features of the economy.Growth spurts, unified growth theory, sustained economic growth

Properties of materials in high pressure hydrogen at cryogenic, room, and elevated temperatures Annual report

Mechanical property tests of nickel, titanium, and iron alloys in 5000 psig gaseous helium and hydrogen at various temperature

Design and Analysis of an Estimation of Distribution Approximation Algorithm for Single Machine Scheduling in Uncertain Environments

In the current work we introduce a novel estimation of distribution algorithm to tackle a hard combinatorial optimization problem, namely the single-machine scheduling problem, with uncertain delivery times. The majority of the existing research coping with optimization problems in uncertain environment aims at finding a single sufficiently robust solution so that random noise and unpredictable circumstances would have the least possible detrimental effect on the quality of the solution. The measures of robustness are usually based on various kinds of empirically designed averaging techniques. In contrast to the previous work, our algorithm aims at finding a collection of robust schedules that allow for a more informative decision making. The notion of robustness is measured quantitatively in terms of the classical mathematical notion of a norm on a vector space. We provide a theoretical insight into the relationship between the properties of the probability distribution over the uncertain delivery times and the robustness quality of the schedules produced by the algorithm after a polynomial runtime in terms of approximation ratios