Abstract
A generalization of the use of websites in tourism and in other areas has not always been synonymous of quality, thus justifying the search for evaluation of this type of software product, which is required systematically and effectively. Although, it is difficult to make a systematic and complete evaluation on websites, they are quality due to their diversity of functionalities, which make them complex to analyses. Many studies have proposed new website evaluation frameworks and criteria. The main objective of this paper is to analyse Portugal and Spain tourism websites, using one model for evaluate tourism websites and a qualitative method approach in order to assess the quality of the respective websites and to identify possible improvements.

Abstract
Todays' market is ruled by several mobile devices applications for all types of proposes. Still, for many destinations, it lacks applications that work in an integrated way, combining cooperative mechanisms that allow the effective support the wide range of tourists need when they visit a destination. Many applications, currently available, to the tourism industry are limited in content and cultural offerings, and commercial applications only communicate with their partners and have no cultural content. This paper presents a framework of a mobile application implementation to support the tourist information needs when tourists are visiting the Portuguese city of Mirandela in which interest points are combined with commercial content. The presented model allows the tourist to have only one application that integrates the contents that he wishes/subscribes, both cultural and commercial, creating a parametrizable universal profile that can be accessed by any of the entities in the system. This approach will benefit both tourists and entities involved. This will also allow increasing the dissemination of regional products and/or services and thereby increase their market potential and consequently their sales.

Abstract
A high-resolution advanced laser induced breakdown spectroscopy prototype was used to quantify lithium (Li) in lithiniferous rocks. Samples were collected from Barroso's mine (Portugal), claimed as Western Europe's largest spodumene Li discovery. 51 samples from a reverse circulation drill were collected, one for each meter interval, dried, milled, pressed into pellets and further analyzed by laser induced breakdown spectroscopy. Quantification was attempted using either linear models based on the intensity of selected Li spectral lines or advanced chemometrics methods. The latter was very successful, with correlation coefficients of 0.97 against certified laboratory results.

Abstract
A low-computational intensive laser control approach is proposed for implementing an embedded control system, using pattern recognition by relevant principal component analysis for laser induced breakdown spectroscopy applications. The laser energy is directly related to the resulting spectral pattern and is determined by iterations in the feature space. Results show that single shot iterations until optimum energy can be significantly reduced by pattern recognition. A performance benchmark with minerals, alloys and pellets from material collected from a drill demonstrated an average of 50% improvement, significantly reducing sample deterioration and improving measurement safety.

Abstract
Spectral information is characterized by multi-scaled interference, convolution and variability. Spectral lines are fragmented and diffused along the spectra. In many cases, matrix and physical effects do not allow to determine specific bands. Despite this limitation, the observed spectra contains significant amounts of information about the sample composition and characteristics, which once understood, can make spectroscopy an ideal technology for analyzing complex samples, such as bodyfluids and tissues. Breaking down and deciphering the structure of spectral information is paramount for the development of reagent-free point-of-care devices. A self-learning artificial intelligence was developed to take advantage of spectral complex information structure. It determines the relationships between composition and/or spectral features in high-dimensional space, where different sub-spaces correlate to specific constituents or characteristics. It also establishes a knowledgebase, by feature space transformations and optimizing co-variance search direction under the correct 'matrix effect' context. An example of hemogram analysis with erythrocyte and leucocyte counts is presented to demonstrate the advantages of the developed methodology.

Abstract
Soil moisture (SM) at three depths (15, 25, and 30 cm), derived from the optical trapezoidal model (OPTRAM), was used for multiyear, multisite monitoring of agricultural droughts over two agricultural crops (Maize and Soybean) in southern Mozambique. The OPTRAM was implemented using satellite data from Sentinel-2 and was validated against field SM assessed by gravimetric methods and by Watermark Sensors in sandy-soils with very low water holding capacity (0.13 cm(3)/cm(3)). The OPTRAM model estimated the SM at 15 and 25 cm yielding a R-2 >= 0.79 and RMSE <= 0.030 cm(3)/cm(3). The OPTRAM-derived SM was successfully used as input to compute and map the soil water deficit index, an indicator of agricultural drought. The results indicate that OPTRAM can provide useful information to improve water productivity in cropland under the specific conditions of Mozambique agricultural systems and for early warning systems development. (C) 2019 Society of Photo-Optical Instrumentation Engineers (SPIE)