Abstract
The integration of Information and Communication Technologies (ICT) in the tourism industry is an essential element for the success of any tourism enterprise. ICTs provide access to information of tourism products from anywhere and at any time. Tour companies may also reach out to target customers around the world through a series of emerging technologies. This paper aims to make a review of the main key factors of ICT in Tourism. Aspects such as the quality of the website, Digital Marketing, Social Networking, Multimedia, Mobile Technologies and Intelligent Environments are discussed.

Abstract
Within the supply chain, the customer does not simply buy parts or services from suppliers, but also buys supplier capabilities, which results in quality products and services. Having a tool that handles the Inspection as well as the Nonconformance, Complaint, Corrective Action and Concession processes is key to successfully track the supplier performance. Taking as a case study a Supplier Quality Management (SQM) currently in operation in an Original Equipment Manufacturer (OEM) for automotive industry, this paper presents a platform to support a Supplier Quality Management System (SQMS), that fits the technical specification ISO/TS 16949 requirements. This prototype is composed by a web platform and a mobile App, having flexibility and mobility as key main characteristics. Copyright © 2016 International Business Information Management Association

Abstract
The integration of Information and Communication Technologies (ICT) in the tourism industry is an essential element for the success of any tourism enterprise. ICTs provide access to information of tourism products from anywhere and at any time. Tour companies may also reach out to target customers around the world through a series of emerging technologies. This paper aims to make a review of the main key factors of ICT in Tourism. Aspects such as the quality of the website, Digital Marketing, Social Networking, Multimedia, Mobile Technologies and Intelligent Environments are discussed. Copyright © 2016 International Business Information Management Association

Abstract
The R package micompr implements a procedure for assessing if two or more multivariate samples are drawn from the same distribution. The procedure uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar high-dimension multivariate observations.

Abstract

Abstract
PhenoSat is a software tool that extracts phenological information from satellite based vegetation index time-series. This chapter presents PhenoSat and tests its main characteristics and functionalities using a multi-year experiment and different vegetation types – vineyard and semi-natural meadows. Three important features were analyzed: (1) the extraction of phenological information for the main growing season, (2) detection and estimation of double growth season parameters, and (3) the advantages of selecting a sub-temporal region of interest. Temporal NDVI satellite data from SPOT VEGETATION and NOAA AVHRR were used. Six fitting methods were applied to filter the satellite noise data: cubic splines, piecewise-logistic, Gaussian models, Fourier series, polynomial curve-fitting and Savitzky-Golay. PhenoSat showed to be capable to extract phenological information consistent with reference measurements, presenting in some cases correlations above 70% (n=10; p=0.012). The start of in-season regrowth in semi-natural meadows was detected with a precision lower than 10-days. The selection of a temporal region of interest, improve the fitting process (R-square increased from 0.596 to 0.997). This improvement detected more accurately the maximum vegetation development and provided more reliable results. PhenoSat showed to be capable to adapt to different vegetation types, and different satellite data sources, proving to be a useful tool to extract metrics related with vegetation dynamics. © Springer International Publishing AG 2016.