See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights

IDENTIFICATION OF TECHNOLOGICAL DISTRICTS: THE CASE OF SPAIN

In recent years, several contributions have been focused on a new sort of productive systems that share some characteristics with Marshallian industrial districts. These contributions have analysed the competitiveness of these new areas and how have been promoted by policy makers. In this line, the Marshallian concept of industrial district has been increasingly related to high technology and innovation in order to analysis technological districts or clusters. The aim of this research is to show how these new areas have characteristics are not similar to those shown by traditional industrial districts. Therefore, framework and techniques for analysis that have been traditionally used for industrial districts must be adapted for identifying technological districts. Specifically, some reflections about the framework analysis of sector and spatial units are introduced in the first part of this research as well as those techniques that can be useful to identify and analyse technological districts. Next, the analysis is focused on the identification of technological districts in Spain. A multivariate analysis will be applied to calculate a synthetic index that will be used to identify those areas with a high degree of specialization in high and medium technology activities. This synthetic index will collect data about those technological activities that are involved not only in manufacturing but also in activities of innovation and R&D. Until now, there have been not many attempts to identify technological clusters through the application of quantitative methodologies; therefore, the purpose of this research is to contribute to the enhancement of knowledge about these areas in Spain. Keywords: technological districts, clusters, location, spatial agglomerations.

The new economy in Spain: a regional analysis

There is no enough evidence about the effects of the new information and communication technologies (ICT) in Spain and how these ICT cause differences between regions. So, the aim of this work is to analyze the regional disparities relative to the new economy in Spain. In the first part of this work, we will review the literature about the concept and measure of the new economy and the problems derived from the high number of definitions about it that difficult an homogeneous analysis. Despite of the several definitions, new economy refers, basically, to an economic development based in Internet and the technologic knowledge as the main inputs. Secondly, we review the empirical evidence about the location factors associated with the new economy. As we highlight in this section, the main conclusion is the complexity of the location dynamic related with the new economy because the results of the empirical studies range from the spatial concentration to the spatial dispersion. In the third section, we analyze the methodology and the empirical results. We collect regional indicators of the new economy in Spain trying to establish if the growth of the new economy in Spain has generated a high spatial concentration. But measuring the new economy at the regional level is even more difficult than it is at the national level because many of the most useful data tend to be nationally oriented. Therefore, it will be used a statistical database with the 28 regional indicators. The 28 indicators in this database are divided into 4 categories about the new economy: ICT industry, ICT services, the knowledge society and the information society. Firstly, we analyse the spatial concentration of the new economy variables in the Spanish territory with the aim of comparing the spatial concentration of the new economy with the spatial concentration of the economic activity. Next, we will construct a composite indicator that will give us the information about the relative position of a region in the new economy in order to find a variable that reflects the regional development of the new economy. Also, to compare the new economy indicator with the conventional economy it will be used the GDP per capita. As a preliminary result we find that the regional disparities in economic growth are more reduced than the regional disparities in the development of the new economy. So, the spatial concentration of the new economy is higher than the spatial concentration of the conventional economic activity. Also, a second preliminary conclusion is the relationship between a high economic development and a high level of the new economy. Finally, we conclude with an exposition of the main conclusions highlighting that the Internet and the ICT are an important progress instruments but can generate a growing of the regional disparities. Therefore, the role of the public sector promoting the introduction and development of the information and knowledge society, specially, in the regions with a low position in the new economy characteristics is essential.

THE INDUSTRY LOCATION IN SPAIN - NEW METHODS FOR MEASURING INDUSTRIAL AGGLOMERATION

A range of quantitative techniques have been employed by researchers in economic geography and other social science disciplines to measure and, spatially, define agglomerations of industrial activity. However, the application of these techniques in the literature results in a low consistency level. Because of this, new quantitative techniques have introduced solutions to solve the problems founded in the location’s analysis. One of these problems is the discrimination between geographic concentration arising from individual plants locating near to each other and that due to the concentration in an industrial structure. A relevant limitation of traditional location indexes is the absence of data about the differences in the size distribution of firms between geographic units. Recent papers by Ellison and Glaeser (1997) and Maurel and Sédillot (1999) have proposed indexes designed to measure agglomerations or geographic concentrations in excess of that which would be expected given industrial concentrations. These measures are all based on the distribution of activity over discrete geographic units. Another problem is the use of arbitrary cut-off values for determining what level of industrial specialization defines an agglomeration. O’Donoghue and Gleave (2004) have proposed a new measure, the ‘standardized location quotient (SLQ)’, which recognizes agglomerations as being comprised of locations with statistically significant location quotient values for the industry/activity under analysis. Other questions that appear when constructing these measures are the specification of the regional division’s level and the suitable use of administrative territorial units. New quantitative techniques of spatial econometrics solve this question. The use of a spatial autocorrelation indexes will allow us to know if the location of a concrete economic activity in a municipality is influenced by the location of the same activity in other neighbouring municipalities. We use global spatial autocorrelation statistics as I Moran Index (Moran, 1948) and Local Measures of Spatial Autocorrelation (LISA). The cluster map (LISA map) shows the significant locations by type of association. With LISA map, we measure geographic concentration of employment in industry clusters by detecting spatial association patterns in administrative areas (in this case, municipalities). In the empirical analysis the municipality, the micro level of administrative regions (NUTS5) in Spain, will be used as territorial unit. The data will be provided by the Industrial Register (Ministry of Industry, 2000) that contains information about the population of production plants in Spain at two and/or three-digit industry level. This includes the location of the plant (given by municipality), the plant’s three-digit industrial classification and the number of employees. So, the objective of this work will be to identify spatial agglomerations within the Spanish industrial sectors using all these new contributions to the spatial analysis and, as a secondary objective, to compare the difference of the results obtained with each quantitative technique. The results will offer a wide view of the geographic concentration and agglomeration of industrial activity in Spain.

Identification of the local productive systems in Spain: a new approach

In the last two decades there have been significant spatial changes influenced by the industrial re-organization processes. And the studies made about these changes have defined new forms of territorial distribution. One of these new forms appears because of territorial diffusion of the economic activity due to a flexible decentralization process and, simultaneously, the endogenous development in a geographical area. This industrial organization model has promoted the development of local geographic areas composed by a high number of small enterprises of the same industrial sector. These areas receive the denomination of local productive systems (LPS). However, these local areas can’t be identified with the administrative areas in which is divided a province or a region. In fact, a LPS can be defined as a certain number of towns, near geographically, with a high concentration of the same industrial activity, but not necessary located in the same municipality. The aim of this work is to identify and locate the LPS in the Spanish territory. So, the first phase will be to identify the industrial sectors which are highly concentrated in certain areas using the municipality which is the basic administrative unit in Spain. For that purpose it will be used indicators of the geographical concentration of the economic activity as the Gini index and the location coefficient. Also, the use of a spatial autocorrelation index will allow us to know if the location of a concrete economic activity in a municipality is influenced by the location of the same activity in other neighbouring municipalities. With this index it will be possible to identify the industrial sectors which are highly concentrated in one territorial area that could be different from the administrative division of the territory, being an agglomeration of municipalities with a high specialization in one industrial sector. In a second phase, the objective will be to establish the geographic areas with a high concentration level in one industrial sector. Next, we will try to delimitate the territorial boundaries in order to identify the LPS using the methodology developed by Frederic Lainé for the French case. In this methodology the characterization of the municipalities is based in four basic requirements for a concrete sector: number of establishments, employment, industrial density and specialization degree. The results, that is, the number of municipalities that fulfil these requirements, will be aggregated in order to search for the municipalities which are specialized in one industrial sector and are geographically nearby from other municipalities with the same industrial specialization. Finally, we will obtain a new spatial unit different from the administrative units traditionally used. These new units will represent a local production systems composed of several nearby municipalities specialized in the same industrial sector. In our opinion, this new spatial unit would represent better the idea of economic unit, more accurate than the administrative-political division. Industrial specialization.

The location of the Spanish technological centers

The Technological Centers have been created with the aim of being a supplier of different R&D's activities and services for those entreprises with a lack of material and financial resources to develop by themselves an innovation process. In most cases, these enterprises are SME's (Small and Medium Enterprises) placed in the area of influence of each Technological Center. Usually, these Technological Centers are located in strategic areas with specific characteristics like to be closed to the SME's (one of the valued highly characteristics by them), a good access to qualified staff and the existence of a good innovation environment. So, this situation has promoted that many decisions about the creation of the Technological Centers have depended on the distance between these and the SME's-clients. The purpose of this work will be the study about where are stablished the Spanish Technological Centers and it will be analysed if the metropolitan areas have been a key factor in their creation. First, we will analyse the spacial distribution of the possible SME'sclients of the Technological Centers (the Spanish industry). We also study how the Technological Centers are integrated in the national and regional goverment Technological Policy.

Identification and Analysis of the Industrial Districts in Spain: A Quantitative Approach

The identification and analysis of the industrial districts in Spain using a quantitative approach is the aim of this research. In the first part, the industrial districts are identified applying the methodology developed by the Italian Statistics Institute (ISTAT). This identification is possible due to the availability of information about the local labour markets; these have been estimated with labour mobility data between municipalities and the industrial data used to analyse the location of the Spanish industry comes from the Industrial Register published by the Ministry of Industry, Tourism and Commerce. This statistical source classifies the different industrial activities in 23 sectors. In the second part, the characteristics of the, previously identified, industrial districts are quantitatively analysed and the results are compared with those obtained in other similar researches developed in Spain and Italy. Some of the characteristics that will be analysed are the relevance of the industrial districts for the Spanish industry (in a national, sectorial and regional level), the industrialization degree, the sectorial specialization level or the predominance of small and medium enterprises in the whole industry or by sectors. Finally, with the quantitative results, a typology of the industrial districts in Spain will be constructed, that could be used in a further analysis based in qualitative techniques.

A pan-tilt camera Fuzzy vision controller on an unmanned aerial vehicle

is paper presents an implementation of two Fuzzy Logic controllers working in parallel for a pan-tilt camera platform on an UAV. This implementation uses a basic Lucas-Kanade tracker algorithm, which sends information about the error between the center of the object to track and the center of the image, to the Fuzzy controller. This information is enough for the controller, to follow the object moving a two axis servo-platform, besides the UAV vibrations and movements. The two Fuzzy controllers of each axis, work with a rules-base of 49 rules, two inputs and one output with a more significant sector defined to improve the behavior of those

Feasibility and Numerical Analysis of Hybrid Photovoltaic (PV) Panels with Thermoelectric Cooling (TEC) Systems

Photovoltaic-thermoelectric hybrid (PV-TE) systems combine photovoltaic (PV) cells and thermoelectric cooling (TEC) modules to improve the system performance. PV panels efficiency is undesirably influenced by temperature rise, reducing power outlet from PV cells. As a countermeasure, cooling methods have been widely suggested. In this chapter, we provide an overview of both technologies, as well as an analysis of thermoelectric cooling as a possible solution to temperature rise in PV panels. Energy and exergy balances of hybrid system are conducted to determine if the thermoelectric cooling is viable for a self-sustaining system. Our results show that copper indium gallium selenide (CIGS), crystalline silicon (c-Si), amorphous silicon (a-Si), and cadmium tellurium (CdTe) PV panels are unsuitable candidates using the TE cooling. Even though exergy losses diminish with temperature decrease in CIGS, c-Si, and a-Si, the power consumption of the TEC has shown to overcome power generation from PV panels