Low-noise high-voltage DC power supply for nanopositioning applications

Nanopositioning techniques currently applied to characterize physical properties of materials interesting for applications at the microscopic scale rely on high-voltage electronic control circuits that should have the lowest possible noise level. Here we introduce a simple, flexible, and custom-built power supply circuit that can provide +375\,V with a noise level below 10\,ppm. The flexibility of the circuit comes from its topology based on discrete MOSFET components that can be suitable replaced in order to change the polarity as well as the output voltage and current.Comment: 3 pages, 2 figure

La resiliencia internacional de los distritos industriales/clusters (ID/C) italianos entre la relocalización del conocimiento y la deslocalización (en proximidad) de la manufactura

La literatura sobre ID/C se basa en los escritos seminales de Marshall, seguida del redescubrimiento de Giacomo Becattini el concepto de un «distrito industrial». Pero el concepto de un «cluster» fue también promovido durante la década de 1980 por Porter, y destacó la importancia de las empresas e instituciones geográficamente agrupados e interconectados, especializados en un campo particular. A pesar de que el modelo de ID/C ha sido a menudo descrito como localmente auto-contenido, varias investigaciones empíricas y nuestro análisis han señalado su creciente participación en el proceso de internacionalización. La reciente entrada y salida de empresas multinacionales (MNEs) y el fenómeno de la deslocalización no cuestionaron el modelo de ID/C per se, pero contribuyeron a mostrar hasta qué punto está interrelacionada la evolución de las economías locales y las empresas multinacionales.The literature regarding ID/C is based on seminal writings of Marshall, followed by Giacomo Becattini’s rediscovering of the concept of an «industrial district». But the concept of a «cluster» was also promoted during the 1980s by Porter, and highlighted the importance of geographically clustered and interconnected firms and institutions specialised in a particular field. Despite the model of ID/C has been often described as locally self-contained, various empirical researches and our analysis have pointed out its increasing involvement in the process of internationalization. The recent entry and exit of MNEs, and the phenomena of off-shoring did not question the model of ID/C per se, but it contributed to showing how interwoven the evolution of local economies and MNEs is

A Spatio-Temporal Framework for Managing Archeological Data

Space and time are two important characteristics of data in many domains. This is particularly true in the archaeological context where informa- tion concerning the discovery location of objects allows one to derive important relations between findings of a specific survey or even of different surveys, and time aspects extend from the excavation time, to the dating of archaeological objects. In recent years, several attempts have been performed to develop a spatio-temporal information system tailored for archaeological data. The first aim of this paper is to propose a model, called Star, for repre- senting spatio-temporal data in archaeology. In particular, since in this domain dates are often subjective, estimated and imprecise, Star has to incorporate such vague representation by using fuzzy dates and fuzzy relationships among them. Moreover, besides to the topological relations, another kind of spatial relations is particularly useful in archeology: the stratigraphic ones. There- fore, this paper defines a set of rules for deriving temporal knowledge from the topological and stratigraphic relations existing between two findings. Finally, considering the process through which objects are usually manually dated by archeologists, some existing automatic reasoning techniques may be success- fully applied to guide such process. For this purpose, the last contribution regards the translation of archaeological temporal data into a Fuzzy Temporal Constraint Network for checking the overall data consistency and reducing the vagueness of some dates based on their relationships with other ones

A framework for integrating multi-accuracy spatial data in geographical applications

In recent years the integration of spatial data coming from different sources has become a crucial issue for many geographical applications, especially in the process of building and maintaining a Spatial Data Infrastructure (SDI). In such context new methodologies are necessary in order to acquire and update spatial datasets by collecting new measurements from different sources. The traditionalapproach implemented in GIS systems for updating spatial data does not usually consider the accuracy of these data, but just replaces the old geometries with the new ones. The application of such approach in the case of an SDI, where continuous and incremental updates occur, will lead very soon to an inconsistent spatial dataset withrespect to spatial relations and relative distances among objects. This paper addresses such problem and proposes a framework for representing multi-accuracy spatial databases, based on a statistical representation of the objects geometry, together with a method for the incremental and consistent update of the objects, that applies acustomized version of the Kalman filter.Moreover, the framework considers also the spatial relations among objects, since they represent a particular kind of observation that could be derived from geometries or be observed independently in the real world. Spatial relations among objects need also to be compared in spatial dataintegration and we show that they are necessary in order to obtain a correct result in merging objects geometries

A Balanced Solution for the Partition-based Spatial Merge join in MapReduce

Several MapReduce frameworks have been developed in recent years in order to cope with the need to process an increasing amount of data. Moreover, some extensions of them have been proposed to deal with particular kind of information, like the spatial one. In this paper we will refer to SpatialHadoop, a spatial extension of Apache Hadoop which provides a rich set of spatial data types and operations. In the geo-spatial domain, spatial join is considered a fundamental operation for performing data analysis. However, the join operation is generally classified as a critical task to be performed in MapReduce, since it requires to process two datasets at time. Several different solutions have been proposed in literature for efficiently performing a spatial join which may or may not require the presence of a spatial index computed on both datasets or only one of them. As already discussed in literature, the efficiency of such operation depends on the ability to both prune unnecessary data as soon as possible and to provide a balanced amount of work to be done by each parallelly executed task. In this paper,we take a step forward in this direction by proposing an evolution of the Partition-based Spatial Merge Join algorithm which tries to completely exploit the benefit of the parallelism induced by the MapReduce framework. In particular, we concentrate on the partition phase which has to produce filtered balanced and meaningful subdivisions of the original datasets

An Interoperable Spatio-Temporal Model for Archaeological Data Based on ISO Standard 19100

Archaeological data are characterized by both spatial and temporal dimensions that are often related to each other and are of particular interest during the interpretation process. For this reason, several attempts have been performed in recent years in order to develop a GIS tailored for archaeological data. However, despite the increasing use of information technologies in the archaeological domain, the actual situation is that any agency or research group independently develops its own local database and management application which is isolated from the others. Conversely, the sharing of information and the cooperation between different archaeological agencies or research groups can be particularly useful in order to support the interpretation process by using data discovered in similar situations w.r.t. spatio-temporal or thematic aspects. In the geographical domain, the INSPIRE initiative of European Union tries to support the development of a Spatial Data Infrastructure (SDI) through which several organizations, like public bodies or private companies, with overlapping goals can share data, resources, tools and competencies in an effective way. The aim of this paper is to lay the basis for the development of an Archaeological SDI starting from the experience acquired during the collaboration among several Italian organizations. In particular, the paper proposes a spatio-temporal conceptual model for archaeological data based on the ISO Standards of the 19100 family and promotes the use of the GeoUML methodology in order to put into practice such interoperability. The GeoUML methodology and tools have been enhanced in order to suite the archaeological domain and to automatically produce several useful documents, configuration files and codebase starting from the conceptual specification. The applicability of the spatio-temporal conceptual model and the usefulness of the produced tools have been tested in three different Italian contexts: Rome, Verona and Isola della Scala

Idmb: a tool for navigating the Inspire data model and generating an Inspire SQL database and WFS Configuration

The Inspire Data Model Browser (IDMB) is a free tool that performs the following functions: (i) it presents the Inspire UML Data Model as a tree-based structure, which is complementary to the UML diagrams; (ii) it generates a Postgis SQL Script for creating an INSPIRE compliant SQL database (Inspire Database) and a configuration file for the Deegree tool that enables the access to the Inspire Database through a Web Feature Service (WFS) producing GML according to the Inspire XML Schemas

A framework for evaluating 3D topological relations based on a vector data model

3D topological relations are commonly used for testing or imposing the existence of desired properties between objects of a dataset, such as a city model. Currently available GIS systems usually provide a limited 3D support which usually includes a set of 3D spatial data types together with few operations and predicates, while limited or no support is generally provided for 3D topological relations. Therefore, an important problem to face is how such relations can be actually implemented by using the constructs already provided by the available systems. In this paper, we introduce a generic 3D vector model which includes an abstract and formal description of the 3D spatial data types and of the related basic operations and predicates that are commonly provided by GIS systems. Based on this model, we formally demonstrate how these limited sets of operations and predicates can be combined with 2D topological relations for implementing 3D topological relations

Skewness-Based Partitioning in SpatialHadoop

In recent years, several extensions of the Hadoop system have been proposed for dealing with spatial data. SpatialHadoop belongs to this group of projects and includes some MapReduce implementations of spatial operators, like range queries and spatial join. the MapReduce paradigm is based on the fundamental principle that a task can be parallelized by partitioning data into chunks and performing the same operation on them, (map phase), eventually combining the partial results at the end (reduce phase). Thus, the applied partitioning technique can tremendously affect the performance of a parallel execution, since it is the key point for obtaining balanced map tasks and exploiting the parallelism as much as possible. When uniformly distributed datasets are considered, this goal can be easily obtained by using a regular grid covering the whole reference space for partitioning the geometries of the input dataset; conversely, with skewed distributed datasets, this might not be the right choice and other techniques have to be applied. for instance, SpatialHadoop can produce a global index also by means of a Quadtree-based grid or an Rtree-based grid, which in turn are more expensive index structures to build. This paper proposes a technique based on both a box counting function and a heuristic, rooted on theoretical properties and experimental observations, for detecting the degree of skewness of an input spatial dataset and then deciding which partitioning technique to apply in order to improve as much as possible the performance of subsequent operations. Experiments on both synthetic and real datasets are presented to confirm the effectiveness of the proposed approach

Tracking Data Provenance of Archaeological Temporal Information in Presence of Uncertainty

The interpretation process is one of the main tasks performed by archaeologists who, starting from ground data about evidences and findings, incrementally derive knowledge about ancient objects or events. Very often more than one archaeologist contributes in different time instants to discover details about the same finding and thus, it is important to keep track of history and provenance of the overall knowledge discovery process. To this aim, we propose a model and a set of derivation rules for tracking and refining data provenance during the archaeological interpretation process. In particular, among all the possible interpretation activities, we concentrate on the one concerning the dating that archaeologists perform to assign one or more time intervals to a finding to define its lifespan on the temporal axis. In this context, we propose a framework to represent and derive updated provenance data about temporal information after the mentioned derivation process. Archaeological data, and in particular their temporal dimension, are typically vague, since many different interpretations can coexist, thus, we will use Fuzzy Logic to assign a degree of confidence to values and Fuzzy Temporal Constraint Networks to model relationships between dating of different findings represented as a graph-based dataset. The derivation rules used to infer more precise temporal intervals are enriched to manage also provenance information and their following updates after a derivation step. A MapReduce version of the path consistency algorithm is also proposed to improve the efficiency of the refining process on big graph-based datasets