The world wide success of large scale social information systems with diverse purposes, such as e-commerce platforms, facilities sharing communities and social networks, make them a very promising paradigm for large scale information sharing and management. However the anonymity, distributed and open nature of these frameworks, that, on the one hand, foster the communication capabilities of their users, may contribute, on the other hand, to the propagation of low quality information, attacks and manipulations from users with malicious intentions. All of these risks could end up decreasing users’ confidence in these systems and in a reduction of their utilisation. With these issues in mind, the objective of this contribution is to create DeciTrustNET, a trust and reputation based framework for social networks that takes into consideration the users relationships, the historic evolution of their reputations and their profile similarity to develop a tamper resilient network that guarantees trustworthy communications and transactions. An extensive experimental analysis of the developed framework has been carried out confirming that the proposed approach supports robust trust and reputation establishment among the users, even in social network under the presence of malicious users.
The development of innovative solutions that allow the aging population to remain 1 healthier and independent longer is essential to alleviate the burden that this increasing segment of the 2 population supposes for the long term sustainability of the public health systems. It has been claimed 3 that promoting physical activity could prevent functional decline. However, given the vulnerability of 4 this population, the activity prescription requires to be tailored to the individual's physical condition. 5 We propose m-SFT (mobile Senior Fitness Test), a novel m-health system, that allows the health 6 practitioner to determine the elderly physical condition by implementing a smartphone-based version 7 of the senior fitness test (SFT). The technical reliability of m-SFT has been tested by carrying out a 8 comparative study in 7 volunteers (53-61 years) between the original SFT and the proposed m-health 9 system obtaining high agreement (Intra-class correlation coefficient (ICC) between 0.93 and 0.99). The 10 system usability has been evaluated by 34 independent health experts (Mean=36.64 years; Standard 11 Deviation=6.26 years) by means of the System Usability Scale (SUS) obtaining an average SUS score 12 of 84.4 out of 100. Both results point out that m-SFT is a reliable and easy to use m-health system for 13 the evaluation of the elderly physical condition, also useful in intervention programs to follow-up 14 the patient's evolution. 15
In group decision making scenarios, where multiple anonymous agents interact, as is the case of social networks, the uncertainty in the provided information as well as the diversity in the experts’ opinions make of them a real challenge from the point of view of information aggregation and consensus achievement. This contribution addresses these two main issues in the following way: On the one hand, in order to deal with highly uncertainty group decision making scenarios, whose main particularity is that some of their experts may not be able to provide any single judgment about an alternative, the proposed approach estimates these missing information using the preferences coming from other trusted similar experts who present high degrees of confidence and consistency. On the other hand, with the objective of increasing the consensus among the agents involved in the decision making process, a feedback based influence network has been proposed. In this network, the influence between the agents is calculated by means of a dynamic combination of the inter agents trust, their self confidence, and their similarity. Thanks to this influence network our approach is able to recognize and isolate malicious users adjusting their influence according to the trust degree between them.
Nowadays, in the social network–based decision‐making processes, like the ones involved in e‐commerce and e‐democracy, multiple users with different backgrounds may take part and diverse alternatives might be involved. This diversity enriches the process, but at the same time, increases the uncertainty of opinions. This uncertainty can be considered from two different perspectives: (i) the uncertainty in the meaning of the words given as preferences, that is, motivated by the heterogeneity of the decision makers; and (ii) the uncertainty inherent to any decision‐making process that may lead to an expert not being able to provide all their judgments. The main objective of this study is to address these two types of uncertainty. To do so, the following approaches are proposed: First, to capture, process, and keep the uncertainty in the meaning of the linguistic assumption, the Interval Type‐2 Fuzzy Sets are introduced as a way to model the experts' linguistic judgments. Second, a measure of the coherence of the information provided by each decision maker is proposed. Finally, a consistency‐based completion approach is introduced to deal with the uncertainty presented in the expert judgments. The proposed approach is tested in an e‐democracy decision‐making scenario.
On-line platforms foster the communication capabilities of the Internet to develop large-scale influence networks in which the quality of the interactions can be evaluated based on trust and reputation. So far, this technology is well known for building trust and harnessing cooperation in on-line marketplaces, such as Amazon (www.amazon.com) and eBay (www.ebay.es). However, these mechanisms are poised to have a broader impact on a wide range of scenarios, from large scale decision making procedures, such as the ones implied in e-democracy, to trust based recommendations on e-health context or influence and performance assessment in e-marketing and e-learning systems. This contribution surveys the progress in understanding the new possibilities and challenges that trust and reputation systems pose. To do so, it discusses trust, reputation and influence which are important measures in networked based communication mechanisms to support the worthiness of information, products, services opinions and recommendations. The existent mechanisms to estimate and propagate trust and reputation, in distributed networked scenarios, and how these measures can be integrated in decision making to reach consensus among the agents are analysed. Furthermore, it also provides an overview of the relevant work in opinion dynamics and influence assessment, as part of social networks. Finally, it identifies challenges and research opportunities on how the so called trust based network can be leveraged as an influence measure to foster decision making processes and recommendation mechanisms in complex social networks scenarios with uncertain knowledge, like the mentioned in e-health and e-marketing frameworks.
The early and accurate detection of brain tumors is key to improve the quality of life and the survival of cancer patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. Consequently, automatic and reliable segmentation methods are required. However, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this contribution, we present a new model of segmentation of brain magnetic resonance images. In order to obtain the region of interest, we propose a hybrid approach that carries out both fuzzy c-mean algorithm and multiobjective optimization taking into account both compactness and separation in the clusters with the purpose of improving the cluster center detection and speed up the convergence time. This new segmentation approach is a key component of the proposed magnetic resonance image-based classification system for brain tumors. Experimental results are presented to demonstrate the effectiveness and efficiency of the proposed approach using the DICOM MRI database.
Nowadays we are living the apogee of the Internet based technologies and consequently web 2.0 communities, where a large number of users interact in real time and share opinions and knowledge, is a generalized phenomenon. This type of social networks communities constitute a challenge scenario from the point of view of Group Decision Making approaches, because it involves a large number of agents coming from different backgrounds and/or with different level of knowledge and influence. In these type of scenarios there exists two main key issues that requires attention. Firstly, the large number of agents and their diverse background may lead to uncertainty and or inconsistency and so, it makes difficult to assess the quality of the information provided as well as to merge this information. Secondly, it is desirable, or even indispensable depending on the situation, to obtain a solution accepted by the majority of the members or at least to asses the existing level of agreement. In this contribution we address these two main issues by bringing together both decision Making approaches and opinion dynamics to develop a similarity-confidence-consistency based Social network that enables the agents to provide their opinions with the possibility of allocating uncertainty by means of the Intuitionistic fuzzy preference relations and at the same time interact with like-minded agents in order to achieve an agreement.
The age of the population in the developed countries is increasing as well as the life expectancy for this population. This suppose a challenge for the health care system that requires of new tools to be able to face the increasing expenses that this ageing in the population suppose. With this regard, it has been demonstrated that promoting physical activity in the elderly, could prevent functional decline, frailty, falls, and fractures and reduce the risk of premature mortality. However, in order to obtain the maximum benefits of this physical activity, the activity prescription and health coaching support requires to be tailored to the functional and personal characteristics of each individual . Therefore, it is of vital relevance to have tools to asses the elderly physical condition in an easy way using low cost and simple tools. In this contribution we present a preliminary version of a mobile health application, m-health app, specially aimed for the elderly population. The proposed approach offers to the health practitioners a reliable, real-time, affordable and easy to use tool to evaluate senior patients physical condition. This m-Health System could be a promising approach not only for physical assessment but as well as a tool in intervention programs to asses the patient evolution.