59 research outputs found
Segmenting tourists by expenditure patterns: An instrument for enhancing tourism economic benefits on a Portuguese World Heritage site
Tourism is an activity with high potential for stimulating the development of local economies,
with different types of visitors having distinct environmental, social and economic effects on
destinations (Lundie, Dwyer, & Forsyth, 2007; Nickerson, Jorgenson, & Boley, 2016). Notwithstanding,
there is a research gap on strategies aimed at maximizing the economic relevance of tourism for local
tourism destinations using market segmentation, based on visitors’ daily expenditure level at the destination,
as a starting point (Lima, Eusébio, & Kastenholz, 2012). This gap becomes more evident when
we refer to World Heritage Sites (WHS) destinations (Amir, Osman, Bachok, & Ibrahim, 2016). This
study presents the results of the tourist market segmentation of a Portuguese municipality - Évora, a
UNESCO’s WHS, located in Alentejo. The study aims to identify the homogenous groups of visitors
that prevail in a WHS destination based on expenditure patterns and furthermore at contributing to the development of marketing strategies to enhance the economic development of this cultural destination.This research is funded with a grant from the FCT – National Funding Agency for
Science, Research and Technology, COMPETE, FEDER, Portugal 2020 under the project UID/HIS/00057/
2013 (POCI-01-0145-FEDER-007702) – CIDEHUS
Estratégia de sensibilização dos alunos universitários para o tema do turismo acessível: O caso da licenciatura em Turismo da Universidade de Évora
Vive-se atualmente um contexto de reflexão internacional por parte de diversos investigadores
que reconhecem a necessidade de reinventar os planos de estudos e as suas dinâmicas de formação,
de modo a que os alunos fiquem mais aptos a enfrentar os desafios do mercado de trabalho (e.g. Ayikoru,
Tribe & Airey, 2009; Fidgeon, 2010; Hoidn & Kärkkäinen, 2014; OECD, 2016; Stergiou, Airey & Riley,
2008). São valorizadas iniciativas que envolvam dinâmicas educativas inovadoras e que sejam capazes
de incutir nos alunos as qualidades humanas necessárias para desenvolver um sentido mais crítico sobre
os problemas sociais que realmente afetam a nossa sociedade e, em consequência, possam ter efeitos
positivos no nível de competitividade das empresas.
Neste contexto, o presente trabalho tem como objetivo apresentar o contexto no qual a licenciatura
em Turismo da Universidade de Évora promoveu uma iniciativa, de carácter voluntário e inovador, para
comemorar o Dia Mundial de Turismo, em 27 de setembro de 2016, subordinado ao tema “Tourism For
All – Promoting Universal Accessibility”. Em anos anteriores, o Dia Mundial de Turismo foi comemorado
com a dinamização de iniciativas que visavam sensibilizar a população local para a existência deste acontecimento. No entanto, este ano optou-se por uma estratégia educativa que pudesse reforçar as
competências dos alunos sobre este tema de relevante atualidade e importância.Este trabalho é financiado por fundos nacionais através da Fundação para a Ciência
e a Tecnologia e pelo Fundo Europeu de Desenvolvimento Regional (FEDER) através do COMPETE
2020 – Programa Operacional Competitividade e Internacionalização (POCI) e PT2020, no âmbito do
projeto UID/HIS/00057 – POCI-01-0145-FEDER-00770
MARTA: A high-energy cosmic-ray detector concept with high-accuracy muon measurement
A new concept for the direct measurement of muons in air showers is
presented. The concept is based on resistive plate chambers (RPCs), which can
directly measure muons with very good space and time resolution. The muon
detector is shielded by placing it under another detector able to absorb and
measure the electromagnetic component of the showers such as a water-Cherenkov
detector, commonly used in air shower arrays. The combination of the two
detectors in a single, compact detector unit provides a unique measurement that
opens rich possibilities in the study of air showers.Comment: 11 page
Semantically Aware Text Categorisation for Metadata Annotation
In this paper we illustrate a system aimed at solving a longstanding and challenging problem: acquiring a classifier to automatically annotate bibliographic records by starting from a huge set of unbalanced and unlabelled data. We illustrate the main features of the dataset, the learning algorithm adopted, and how it was used to discriminate philosophical documents from documents of other disciplines. One strength of our approach lies in the novel combination of a standard learning approach with a semantic one: the results of the acquired classifier are improved by accessing a semantic network containing conceptual information. We illustrate the experimentation by describing the construction rationale of training and test set, we report and discuss the obtained results and conclude by drawing future work.</p
Gastronomy and Wine in the Alentejo Portuguese Region: Motivation and Satisfaction of Turists from Évora
Food and winemaking are a recognized tangible and intangible culturalheritage
of Portugal. From the relationshipbetween these twocomponents, astrategic
product emerged with a considerable potential for tourism industry, which is
notignored bymany of tourism organizations. This chapter intends to analyze food
and winemaking from atourism demand perspective. Particularly, this study
describes visitors’ profi le, including, their motivations, their knowledgeabout theenological
and gastronomicresourcesand the degreeof satisfaction. A total of 308
questionnaires were collected between February and May of 2012, from the visitors
that visited the historic center of Évora (Alentejo-Portugal). Results reveal a visitor
profi le associated with regional cuisine and wine products from Portugal. Moreover,
visitors’ evidenced a high level of knowledge regarding the Portuguese cuisine and
regional wines; although this not matches with their primary motivation for visit the
city of Évora
Machine Learning based tool for CMS RPC currents quality monitoring
The muon system of the CERN Compact Muon Solenoid (CMS) experiment includes
more than a thousand Resistive Plate Chambers (RPC). They are gaseous detectors
operated in the hostile environment of the CMS underground cavern on the Large
Hadron Collider where pp luminosities of up to
are routinely achieved. The CMS RPC system
performance is constantly monitored and the detector is regularly maintained to
ensure stable operation. The main monitorable characteristics are dark current,
efficiency for muon detection, noise rate etc. Herein we describe an automated
tool for CMS RPC current monitoring which uses Machine Learning techniques. We
further elaborate on the dedicated generalized linear model proposed already
and add autoencoder models for self-consistent predictions as well as hybrid
models to allow for RPC current predictions in a distant future
Effects of the electronic threshold on the performance of the RPC system of the CMS experiment
Resistive Plate Chambers have a very important role for muon triggering both in the barrel and in the endcap regions of the CMS experiment at the Large Hadron Collider (LHC). In order to optimize their performance, it is of primary importance to tune the electronic threshold of the front-end boards reading the signals from these detectors. In this paper we present the results of a study aimed to evaluate the effects on the RPC efficiency, cluster size and detector intrinsic noise rate, of variations of the electronics threshold voltage
Programas de exercício na prevenção de lesões em jogadores de futebol: uma revisão sistemática
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