Search results for "machine"
showing 10 items of 2592 documents
Promotion of service industries by means of entry restriction: the case of operators in the slot machine industry
2009
This article examines the effects of government policy on entry restriction for firms within a specific market of the Spanish gambling industry. Spain is an ideal economic region for studying this topic, as it allows for the analysis of quasi-identical populations exposed to different regulatory regimes. In Spain, gaming legislation is determined at the autonomous community level (state level), where differences across states within a single country are of particular interest. This paper analyses the performance of slot machine operators in three autonomous communities, each with different policies with regard to entry restriction. Fifty-eight firms were analysed using multiple regression, …
Technical efficiency and the vertical boundaries of the firm: theory and evidence
2013
This article provides a theoretical and empirical analysis of the relationship between firms’ technical efficiency and the vertical organization of production. Technical inefficiency is explicitly introduced as the source of firms’ heterogeneity in a Bertrand–Nash model of industry competition: the main prediction of the model is that the most efficient firms choose vertical integrated structures and the less-efficient ones choose disintegrated structures. The empirical part of the article rests on a stochastic frontier analysis (SFA) in a sample of about 400 Italian machine tool (MT) builders, and the result supports the prediction of the theoretical model.
The iGEM Competition
2014
The international Genetically Engineered Machine (iGEM) competition is a well-known example of synthetic biology and a workbench for the development of heterodox, multidisciplinary and frontier work made by undergraduate students. We review the origin, organization and structure of the competition; we describe how an iGEM team can be set in place, and briefly summarize some of the main milestones and challenges of a competition that is only one decade old. We discuss the links of the competition with the Registry of Standard Biological Parts and the flagship role of iGEM as a very trench of the synthetic biology revolution.
Incremental Generalized Discriminative Common Vectors for Image Classification.
2015
Subspace-based methods have become popular due to their ability to appropriately represent complex data in such a way that both dimensionality is reduced and discriminativeness is enhanced. Several recent works have concentrated on the discriminative common vector (DCV) method and other closely related algorithms also based on the concept of null space. In this paper, we present a generalized incremental formulation of the DCV methods, which allows the update of a given model by considering the addition of new examples even from unseen classes. Having efficient incremental formulations of well-behaved batch algorithms allows us to conveniently adapt previously trained classifiers without th…
On the Online Classification of Data Streams Using Weak Estimators
2016
In this paper, we propose a novel online classifier for complex data streams which are generated from non-stationary stochastic properties. Instead of using a single training model and counters to keep important data statistics, the introduced online classifier scheme provides a real-time self-adjusting learning model. The learning model utilizes the multiplication-based update algorithm of the Stochastic Learning Weak Estimator (SLWE) at each time instant as a new labeled instance arrives. In this way, the data statistics are updated every time a new element is inserted, without requiring that we have to rebuild its model when changes occur in the data distributions. Finally, and most impo…
Codification schemes and finite automata
2000
This paper is a note on how Information Theory and Codification Theory are helpful in the computational design both of communication protocols and strategy sets in the framework of finitely repeated games played by boundedly rational agents. More precisely, we show the usefulness of both theories to improve the existing automata bounds of Neyman¿s (1998) work on finitely repeated games played by finite automata.
Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles
2016
Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…
Towards more Valid Assessment of Learning from Animations
2020
Animated explanations have become an ubiquitous feature of modern educational practice. They provide a distinctive, non-verbal means of presenting information that is particularly appropriate for dynamic subject matter. However, the prevailing approaches used to assess learning from educational animations are almost exclusively verbal. There is thus a clear disconnect between the form of representation students encounter during their learning activity and the very different form of representation used to assess the resulting learning outcomes. This fundamental inconsistency undermines the validity of current assessment approaches and signals the need for a fresh look at how learning from an…
Local operators to detect regions of interest
1997
The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.
Approximation of functions over manifolds : A Moving Least-Squares approach
2021
We present an algorithm for approximating a function defined over a $d$-dimensional manifold utilizing only noisy function values at locations sampled from the manifold with noise. To produce the approximation we do not require any knowledge regarding the manifold other than its dimension $d$. We use the Manifold Moving Least-Squares approach of (Sober and Levin 2016) to reconstruct the atlas of charts and the approximation is built on-top of those charts. The resulting approximant is shown to be a function defined over a neighborhood of a manifold, approximating the originally sampled manifold. In other words, given a new point, located near the manifold, the approximation can be evaluated…