959 resultados para ArcGIS API for JavaScript


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En esta presentación se introduce el lenguaje JavaScript, su uso en la web y la gestión de eventos.

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Presentación "JavaScript desnudo" realizada en la Escuela Politécnica Nacional (Quito, Ecuador) el 11 de julio de 2016.

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Mode of access: Internet.

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Mode of access: Internet.

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Beginning with 1971 ed. published under title: Multicylinder test sequencs for evaluating automotive engine oils.

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Mode of access: Internet.

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Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.

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* The research has been partially supported by INFRAWEBS - IST FP62003/IST/2.3.2.3 Research Project No. 511723 and “Technologies of the Information Society for Knowledge Processing and Management” - IIT-BAS Research Project No. 010061.

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Shield UI’s advanced framework for creating rich charts and graphs is the first of a line of data visualization components, giving web developers the power for embedding rich graphics in their web projects with minimum effort. Built with HTML, CSS3 and packaged as a jQuery plugin, the library has full support for legacy and modern desktop web browsers, as well as the latest mobile devices.

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This paper is about the development and the application of an ESRI ArcGIS tool which implements multi-layer, feed-forward artificial neural network (ANN) to study the climate envelope of species. The supervised learning is achieved by backpropagation algorithm. Based on the distribution and the grids of the climate (and edaphic data) of the reference and future periods the tool predicts the future potential distribution of the studied species. The trained network can be saved and loaded. A modeling result based on the distribution of European larch (Larix decidua Mill.) is presented as a case study.

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A comprehensive forensic investigation of sensitive ecosystems in the Everglades Area is presented. Assessing the background levels of contamination in these ecosystems represents a vital resource to build up forensic evidence required to enforce future environmental crimes within the studied areas. This investigation presents the development and validation of a fractionation and isolation method for two families of herbicides commonly applied in the vicinity of the study area, including phenoxy acids like 2,4-D, MCPA, and silvex; as well as the most common triazine-based herbicides like atrazine, prometyne, simazine and related metabolites like DIA and DEA. Accelerated solvent extraction (ASE) and solid phase extraction (SPE) were used to isolate the analytes from abiotic matrices containing large amounts of organic material. Atmospheric-pressure ionization (API) with electrospray ionization in negative mode (ESP-), and Chemical Ionization in the positive mode (APCI+) were used to perform the characterization of the herbicides of interest.

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Inventory of some important datasets related to the physical characteristics of the seafloor surrounding the Azores Archipelago. The objective is to ensure that our compilation is readily available for any researchers interested in this type information but also to support institutions responsible for the management and conservation of local resources.

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Sono dette “challenged networks” quelle reti in cui lunghi ritardi, frequenti partizionamenti e interruzioni, elevati tassi di errore e di perdita non consentono l’impiego dei classici protocolli di comunicazione di Internet, in particolare il TCP/IP. Il Delay-/Disruption-Tolerant Networking (DTN) è una soluzione per il trasferimento di dati attraverso queste reti. L’architettura DTN prevede l’introduzione, sopra il livello di trasporto, del cosiddetto “bundle layer”, che si occupa di veicolare messaggi, o bundle, secondo l’approccio store-and-forward: ogni nodo DTN conserva persistentemente un bundle finché non si presenta l’opportunità di inoltrarlo al nodo successivo verso la destinazione. Il protocollo impiegato nel bundle layer è il Bundle Protocol, le cui principali implementazioni sono tre: DTN2, l’implementazione di riferimento; ION, sviluppata da NASA-JPL e più orientata alle comunicazioni spaziali; IBR-DTN, rivolta soprattutto a dispositivi embedded. Ciascuna di esse offre API che consentono la scrittura di applicazioni in grado di inviare e ricevere bundle. DTNperf è uno strumento progettato per la valutazione delle prestazioni in ambito DTN. La più recente iterazione, DTNperf_3, è compatibile sia con DTN2 che con ION nella stessa versione del programma, grazie all’introduzione di un “Abstraction Layer” che fornisce un’unica interfaccia per l’interazione con le diverse implementazioni del Bundle Protocol e che solo internamente si occupa di invocare le API specifiche dell’implementazione attiva. Obiettivo della tesi è estendere l’Abstraction Layer affinché supporti anche IBR-DTN, cosicché DTNperf_3 possa essere impiegato indifferentemente su DTN2, ION e IBR DTN. Il lavoro sarà ripartito su tre fasi: nella prima esploreremo IBR DTN e le sue API; nella seconda procederemo all’effettiva estensione dell’Abstraction Layer; nella terza verificheremo il funzionamento di DTNperf a seguito delle modifiche, sia in ambiente esclusivamente IBR-DTN, sia ibrido.