A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Solving Large Location-Allocation problems by Clustering and Simulated Annealing

Globalization involves several facility location problems that need to be handled at large scale. Location Allocation (LA) is a combinatorial problem in which the distance among points in the data space matter. Precisely, taking advantage of the distance property of the domain we exploit the capability of clustering techniques to partition the data space in order to convert an initial large LA problem into several simpler LA problems. Particularly, our motivation problem involves a huge geographical area that can be partitioned under overall conditions. We present different types of clustering techniques and then we perform a cluster analysis over our dataset in order to partition it. After that, we solve the LA problem applying simulated annealing algorithm to the clustered and non-clustered data in order to work out how profitable is the clustering and which of the presented methods is the most suitable

Financial constraints and the failure of innovation projects

Theoretical and empirical approaches have stressed the existence of financial constraints in innovative activities of firms. This paper analyses the role of financial obstacles on the likelihood of abandoning an innovation project. Although a large number of innovation projects are abandoned before their completion, the empirical evidence has focused on the determinants of innovation while failed projects have received little attention. Our analysis differentiates between internal and external barriers on the probability of abandoning a project and we examine whether the effects are different depending on the stage of the innovation process. In the empirical analysis carried out for a panel data of potential innovative Spanish firms for the period 2004-2010, we use a bivariate probit model to take into account the simultaneity of financial constraints and the decision to abandon an innovation project. Our results show that financial constraints most affect the probability of abandoning an innovation project during the concept stage and that low-technological manufacturing and non-KIS service sectors are more sensitive to financial constraints.

List-based decision problems

When encountering a set of alternatives displayed in the form of a list, the decision maker usually determines a particular alternative, after which she stops checking the remaining ones, and chooses an alternative from those observed so far. We present a framework in which both decision problems are explicitly modeled, and axiomatically characterize a stop-and-choose rule which unifies position-biased successive choice and satisficing choice.

Financial constraints and the failure of innovation projects

Theoretical and empirical approaches have stressed the existence of financial constraints in innovative activities of firms. This paper analyses the role of financial obstacles on the likelihood of abandoning an innovation project. Although a large number of innovation projects are abandoned before their completion, the empirical evidence has focused on the determinants of innovation while failed projects have received little attention. Our analysis differentiates between internal and external barriers on the probability of abandoning a project and we examine whether the effects are different depending on the stage of the innovation process. In the empirical analysis carried out for a panel data of potential innovative Spanish firms for the period 2004-2010, we use a bivariate probit model to take into account the simultaneity of financial constraints and the decision to abandon an innovation project. Our results show that financial constraints most affect the probability of abandoning an innovation project during the concept stage and that low-technological manufacturing and non-KIS service sectors are more sensitive to financial constraints. Keywords: barriers to innovation, failure of innovation projects, financial constraints JEL Classifications: O31, D21

The Geographical Scope of Industrial Location Determinants: An Alternative Approach

This paper considers the estimation of the geographical scope of industrial location determinants. While previous studies impose strong assumptions on the weighting scheme of the spatial neighbour matrix, we propose a exible parametrisation that allows for di fferent (distance-based) de finitions of neighbourhood and di fferent weights to the neighbours. In particular, we estimate how far can reach indirect marginal e ffects and discuss how to report them. We also show that the use of smooth transition functions provides tools for policy analysis that are not available in the traditional threshold modelling. Keywords: count data models, industrial location, smooth transition functions, threshold models. JEL-Codes: C25, C52, R11, R30.

Leveraging explicitly disclosed location information to understand tourist dynamics: a case study

In recent years, the large deployment of mobile devices has led to a massiveincrease in the volume of records of where people have been and when they were there.The analysis of these spatio-temporal data can supply high-level human behaviorinformation valuable to urban planners, local authorities, and designer of location-basedservices. In this paper, we describe our approach to collect and analyze the history ofphysical presence of tourists from the digital footprints they publicly disclose on the web.Our work takes place in the Province of Florence in Italy, where the insights on thevisitors’ flows and on the nationalities of the tourists who do not sleep in town has beenlimited to information from survey-based hotel and museums frequentation. In fact, mostlocal authorities in the world must face this dearth of data on tourist dynamics. In thiscase study, we used a corpus of geographically referenced photos taken in the provinceby 4280 photographers over a period of 2 years. Based on the disclosure of the locationof the photos, we design geovisualizations to reveal the tourist concentration and spatiotemporalflows. Our initial results provide insights on the density of tourists, the points ofinterests they visit as well as the most common trajectories they follow.

Neuronal adaptation effects in decision making

Recently, there has been an increased interest on the neural mechanisms underlying perceptual decision making. However, the effect of neuronal adaptation in this context has not yet been studied. We begin our study by investigating how adaptation can bias perceptual decisions. We considered behavioral data from an experiment on high-level adaptation-related aftereffects in a perceptual decision task with ambiguous stimuli on humans. To understand the driving force behind the perceptual decision process, a biologically inspired cortical network model was used. Two theoretical scenarios arose for explaining the perceptual switch from the category of the adaptor stimulus to the opposite, nonadapted one. One is noise-driven transition due to the probabilistic spike times of neurons and the other is adaptation-driven transition due to afterhyperpolarization currents. With increasing levels of neural adaptation, the system shifts from a noise-driven to an adaptation-driven modus. The behavioral results show that the underlying model is not just a bistable model, as usual in the decision-making modeling literature, but that neuronal adaptation is high and therefore the working point of the model is in the oscillatory regime. Using the same model parameters, we studied the effect of neural adaptation in a perceptual decision-making task where the same ambiguous stimulus was presented with and without a preceding adaptor stimulus. We find that for different levels of sensory evidence favoring one of the two interpretations of the ambiguous stimulus, higher levels of neural adaptation lead to quicker decisions contributing to a speed–accuracy trade off.

La immigració i els efectes en el comportament empresarial: una anàlisi a nivell municipal de Catalunya

En aquest context de canvi econòmic i dels ritmes d’arribada dels fluxos migratoris, aquest treball aborda els efectes de la població immigrant sobre les empreses manufactureres localitzades en ciutats catalanes amb més de 1.000 habitants durant el període 2000-2008. El desenvolupament empíric posa especial èmfasi en la localització d’empreses i la població immigrada així com l’impacte que exerceix sobre el comportament de les empreses. Per tal de recollir les dades hem treballat amb tres bases de dades diferents: dades ofertes per Idescat, INE i Sistema de Anàlisis de Balances Ibéricos. En especial aquesta darrera base ha ofert informació a nivell individual de les empreses el qual ha requerit un procés de depuració complex i exhaustiu a través de programació estadística. En la literatura sobre els impactes econòmics dels immigrants predominen els treballs que han abordat un impacte sobre el mercat de treball, posant especial èmfasis en els diferencials salarials i la reducció de la bretxa salarial en funció del temps de residència dels immigrants. En canvi, en poques ocasions s’ha analitzat l’efecte de la immigració sobre el comportament de l’empresa. L’objectiu d’aquest treball és analitzar l’impacte dels entorns amb població immigrant a les ciutats catalanes i de forma més específica amb el creixement de les empreses locals i l’evolució dels seus nivells d’eficiència. Els objectius concrets que volem analitzar són els següents: i) mostrar les principals conclusions de la literatura ii) observar les pautes de localització d’immigrantsiii) mostrar les pautes de localització de les empreses iv) analitzar si les ciutats catalanes amb una major població immigrant presenten un impacte positiu o negatiu sobre el creixement de les empreses locals i l’evolució dels seus nivells d’eficiència a través d’eines economètriques.

New Trends in Public Facility Location Modeling

The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.

Incorporating waiting time in competitive location models: formulations and heuristics

In this paper we propose a metaheuristic to solve a new version of the Maximum Capture Problem. In the original MCP, market capture is obtained by lower traveling distances or lower traveling time, in this new version not only the traveling time but also the waiting time will affect the market share. This problem is hard to solve using standard optimization techniques. Metaheuristics are shown to offer accurate results within acceptable computing times.

Estimating Bayesian decision problems with heterogeneous priors

In many areas of economics there is a growing interest in how expertise andpreferences drive individual and group decision making under uncertainty. Increasingly, we wish to estimate such models to quantify which of these drive decisionmaking. In this paper we propose a new channel through which we can empirically identify expertise and preference parameters by using variation in decisionsover heterogeneous priors. Relative to existing estimation approaches, our \Prior-Based Identification" extends the possible environments which can be estimated,and also substantially improves the accuracy and precision of estimates in thoseenvironments which can be estimated using existing methods.