Tourism Destination Management: A Collaborative Approach

Part 6: Engineering and Implementation of Collaborative Networks

The Sensing Enterprise: Towards the Next Generation Dynamic Virtual Organisations

Part 6: Engineering and Implementation of Collaborative Networks

An Innovation Model for Collaborative Networks of SOA-Based Software Providers

Part 5: Service Orientation in Collaborative Networks

Enterprise Collaboration Framework for Managing, Advancing and Unifying the Functionality of Multiple Cloud-Based Services with the Help of a Graph API

Part 5: Service Orientation in Collaborative Networks

Virtual Enterprise Process Management: An Application to Industrial Maintenance

Part 2: Behaviour and Coordination

The specific shapes of gender imbalance in scientific authorships : a network approach

Gender differences in collaborative research have received little at- tention when compared with the growing importance that women hold in academia and research. Unsurprisingly, most of bibliomet- ric databases have a strong lack of directly available information by gender. Although empirical-based network approaches are often used in the study of research collaboration, the studies about the influence of gender dissimilarities on the resulting topological outcomes are still scarce. Here, networks of scientific subjects are used to characterize patterns that might be associated to five categories of authorships which were built based on gender. We find enough evidence that gen- der imbalance in scientific authorships brings a peculiar trait to the networks induced from papers published in Web of Science (WoS) in- dexed journals of Economics over the period 2010-2015 and having at least one author affiliated to a Portuguese institution. Our re- sults show the emergence of a specific pattern when the network of co-occurring subjects is induced from a set of papers exclusively au- thored by men. Such a male-exclusive authorship condition is found to be the solely responsible for the emergence that particular shape in the network structure. This peculiar trait might facilitate future network analyses of research collaboration and interdisciplinarity.

A Collaborative Mobile Crowdsensing System for Smart Cities

Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.

The Academic-enterprise experiences framework as a guide for design education

The establishment of support platforms for the development of a new culture in design education, in order to achieve both research exploitation and its results, as an approach to the industrial community, challenges higher education institutions to rethink their functioning, divided between investigation on their own initiative or on demand, and its usefulness / practical application. At the same time, through design education, how can they be the engine that aggregates all these frequently antagonistic interests? Polytechnic institutes are predisposed to collaboration and interdisciplinarity. In our course of Technology and Design of Furniture, the availability of a production unit, testing laboratories, and expertise in engineering, design and marketing, encourage the development of a holistic project. In order to develop such knowledge, we adapt three important ways of thinking in designing interactions influenced by the traditional approach, namely, 1) identifying and understanding a design problem, i.e. a market need, 2) defining the design process and knowing what can be used for design education, i.e. opportunities for design education, and 3) sustainability of this framework and design projects' alignment with education in the same field. We explain our approach by arguing from the academicenterprise experiences perspective. This concept is proposed as a way to achieve those three ways of thinking in design education. Then, a set of interaction attributes is defined to explain how engineering and product design education can enhance meaningful relations with manufacturers, stakeholders and society in general. A final discussion is presented with the implications and benefits of this approach. The results suggest that through academic-enterprise partnerships in design, several goals such as students' motivation, product design innovation and potential for knowledge transfer to industries can be achieved.

The Evolution of Norms in Trade and Financial Networks in the First Global Age: the case of Simon Ruiz's network

In the 16th century, merchants and bankers gained a social influence and political relevance, due to their capacity of ‘faire travailler l’argent des autres’ (Benassar 1972:50). For the success of their activity, they built evolving networks with cooperative partners. These networks were much more than the sum of all partners. In the case study of the Castilian merchant Simon Ruiz, the network functioned in an unique way and independent from any formal institutional control. Its functioning varied in how different partners were associated and the particular characteristics and contents of these social ties. Being a self-organized network, since the formal institutions of trade regulation and the Crown control didn’t influence the network functioning, the Simon Ruiz network was deeply embedded in the economic and financial performance of the Hispanic Empires, in two different ways. The first, purely commercial. The monopolistic regime which was applied by the two crowns in the trade of certain colonial goods was insufficient to the costs of imperial maintenance. In such manner, particulars tried to rent a contract of exploration of trade, paying an annual sum to the crown, as in the Portuguese trade. Some of these agents also moved along Simon Ruiz’s network. But others were involved in relations with the imperial crowns on a second way, the finance. Maintaining Empires implied a lot of human, technical but also financial means, and most of the times Kings were forced to recur to these merchants, as we will demonstrate. What were the implications of these collaborative relations in both parts? The main goal of this paper is to comprehend the evolution of informal norms within Simon Ruiz’s network and how they influenced cooperative behavior of the agents, particularly analyzing mechanisms of sanctioning, control, punishment and reward, as well as their consequences in different dimensions: future interactions, social repercussions and in agent’s economic health and activity. The research is based in the bills of exchange and commercial correspondence of the private archive of Simon Ruiz, located in the Provincial Archive of Valladollid, Spain.

INTERNATIONAL EDUCATION & RESEARCH FOR OH. Experiences of international networks for collaborative education and research using the One Health approach.

The Authors describe first-hand experiences carried out within the framework of selected International projects aimed at developing collaborative research and education using the One Health (OH) approach. Special emphasis is given to SAPUVETNET, a series of projects co-financed under the EU-ALFA program, and aimed to support an International network on Veterinary Public Health (VPH) formed by Veterinary Faculties from Latin-America (LA) and Europe (EU). SAPUVETNET has envisaged a series of objectives/activities aimed at promoting and enhancing VPH research/training and intersectoral collaboration across LA and EU using the OH approach, as well as participating in research and/or education projects/networks under the OH umbrella, namely EURNEGVEC-European Network for Neglected Vectors & Vector-Borne Infections, CYSTINET-European Network on Taeniosis/Cysticercosis, and NEOH-Network for Evaluation of One Health; the latter includes expertise in multiple disciplines (e.g. ecology, economics, human and animal health, epidemiology, social and environmental sciences, etc.) and has the primary purpose of enabling quantitative evaluation of OH initiatives by developing a standardized evaluation protocol. The Authors give also an account of the ongoing creation of OHIN-OH International Network, founded as a spin-off result of SAPUVETNET. Finally, some examples of cooperation development projects characterised by an OH approach are also briefly mentioned.

Comparison between 5G private network and Wifi6 in industrial environment

Industry 4.0 refers to the 4th industrial revolution and at its bases, we can see the digitalization and the automation of the assembly line. The whole production process has improved and evolved thanks to the advances made in networking, and AI studies, which include of course machine learning, cloud computing, IoT, and other technologies that are finally being implemented into the industrial scenario. All these technologies have in common a need for faster, more secure, robust, and reliable communication. One of the many solutions for these demands is the use of mobile communication technologies in the industrial environment, but which technology is better suited for these demands? Of course, the answer isn’t as simple as it seems. The 4th industrial revolution has a never seen incomparable potential with respect to the previous ones, every factory, enterprise, or company have different network demands, and even in each of these infrastructures, the demands may diversify by sector, or by application. For example, in the health care industry, there may be e a need for increased bandwidth for the analysis of high-definition videos or, faster speeds in order to have analytics occur in real-time, and again another application might be higher security and reliability to protect patients’ data. As seen above, choosing the right technology for the right environment and application, considers many things, and the ones just stated are but a speck of dust with respect to the overall picture. In this thesis, we will investigate a comparison between the use of two of the available technologies in use for the industrial environment: Wi-Fi 6 and 5G Private Networks in the specific case of a steel factory.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer׳s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.

Can We Predict The Clinical Outcomes Of Genitourinary Trauma Patients And Offer Them An Evidence-based Support? The Case For Telemedicine Network.

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