Search results for " Network"
showing 10 items of 6428 documents
Familiarity and visit characteristics as determinants of tourists' experience at a cruise destination
2019
Abstract The main aim of this study was to examine the differences in the interrelationships between destination image-satisfaction-behavioural intention across cruise tourists with varying visit characteristics (length of stay and type of visit arrangement) and familiarity. The data for the study was obtained through interviews with cruise passengers visiting a major Spanish port of call. The results revealed that both familiarity (informational and behavioural) and type of visit arrangement (excursion versus independent visit) moderated the hypothesized structural relationships. The moderating role of length of stay onshore was only demonstrated on the impact of satisfaction on behavioura…
The moderating effect of personal and situational characteristics in behavioural factors affecting ports of call
2017
This research aims to study the moderating effects of cruise passengers’ gender, age, education, and prior experiences on a Mediterranean port of call destination image formation and the influence ...
Tourist destination network analysis: The ego network role
2017
This paper aims to analyse the different roles that enterprises have within a tourist destination by identifying the presence and possible role of leaders within the system. The Social Network Analysis (SNA) is a tool that offers a greater degree of understanding of the operation of the destination. The map of commercial relations between the leading players of tourist supply can provide greater insight into the main relations existing between enterprises and the principles that ensure and regulate operation. In keeping with this objective and building on the results of a previous paper (Iannolino and Ruggieri, 2012), the authors have focused their attention on the role of some enterprises …
Cruise passengers' behavior at the destination: Investigation using GPS technology
2016
This paper aims at segmenting cruise passengers in order to identify passengers' profiles according to their behavior at destination. Through an integrated use of traditional survey instruments and of GPS technologies, a set of indicators for the analysis of passengers' mobility at destination is proposed. Data collected in the port of Palermo are used in order to investigate space-time activities of cruise passengers at the destination. Monothetic Analysis is used in order to segment passengers according to their behavior at destination, and groups are then compared in terms of socio-demographic characteristics and other variables collected through questionnaire-based survey. Results ident…
Energy efficiency and CO2 emissions of port container terminal equipment: Evidence from the Port of Valencia
2019
Abstract Energy efficiency has emerged as a key point in port industry because of different factors such as the adoption of stronger environmental regulations and the increasing pressure of the local community on the surrounding ports. As gathering operational data from port terminals can be difficult due to privacy, studies on emissions and energy efficiency of these terminals are scarce. The following research provides key information about the real energy consumption and CO2 emissions of one of the most relevant container terminals in the Mediterranean area, located in Valencia, Spain. The results show that yard terminal tractors and rubber tyred gantry cranes (RTGs) are the main emissio…
Computer-Aided Diagnosis System with Backpropagation Artificial Neural Network—Improving Human Readers Performance
2016
This article presents the results of a study into possibility of artificial neural networks (ANNs) to classify cancer changes in mammographic images. Today’s Computer-Aided Detection (CAD) systems cannot detect 100 % of pathological changes. One of the properties of an ANN is generalized information —it can identify not only learned data but also data that is similar to training set. The combination of CAD and ANN could give better result and help radiologists to take the right decision.
Multilayer neural networks: an experimental evaluation of on-line training methods
2004
Artificial neural networks (ANN) are inspired by the structure of biological neural networks and their ability to integrate knowledge and learning. In ANN training, the objective is to minimize the error over the training set. The most popular method for training these networks is back propagation, a gradient descent technique. Other non-linear optimization methods such as conjugate directions set or conjugate gradient have also been used for this purpose. Recently, metaheuristics such as simulated annealing, genetic algorithms or tabu search have been also adapted to this context.There are situations in which the necessary training data are being generated in real time and, an extensive tr…
Towards to deep neural network application with limited training data: synthesis of melanoma's diffuse reflectance spectral images
2019
The goal of our study is to train artificial neural networks (ANN) using multispectral images of melanoma. Since the number of multispectral images of melanomas is limited, we offer to synthesize them from multispectral images of benign skin lesions. We used the previously created melanoma diagnostic criterion p'. This criterion is calculated from multispectral images of skin lesions captured under 526nm, 663nm, and 964nm LED illumination. We synthesize these three images from multispectral images of nevus so that the p' map matches the melanoma criteria (the values in the lesion area is >1, respectively). Demonstrated results show that by transforming multispectral images of benign nevus i…
Inter-organizational networks and innovation in small, knowledge-intensive firms: A literature review
2013
Published version of article from the journal: International Journal of Innovation Management In this study, we address the effect of innovation strategy and an innovative working climate on financial performance in the Norwegian wood industry. Innovation strategy embodies four dimensions: the degrees to which innovation in the form of products, processes, and business systems are embedded in the management values and priorities as well as the degree of expenditure in R&D. An innovative working climate is exemplified by team cohesion, supervisory encouragement, resources, autonomy, challenge, and openness to innovation. Previous studies have indicated a lack of research in traditional manuf…
Resting state FMRI: A tool to investigate functional connectivity modulation induced by transcranial direct current stimulation of the motor network
2016
Introduction: Resting-state functional connectivity (fcMRI) represents a novel fMRI approach that allows detection of temporal correlations in spontaneous BOLD signal oscillations while subjects rest quietly in the scanner. Under resting conditions the brain is engaged in spontaneous activity that causes a low frequencies (<0.1 Hz) BOLD signal fluctuations. Functional connectivity (FC) can be defined as the synchrony of neural activity among spatially distant regions. Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that is known to modulate cortical activity and FC among brain regions, as measured by functional magnetic resonance imaging. This st…