Cloud-based online social network

International audienceOnline social media network has become part of human life by transforming the way users create new social relations or relate with family and friends. Online social network (OSN) has drastically increased the rate at which people interact with each other by simplifying the means of communication. However, privacy is raising a serious concern. All user generated data within the OSN system need to be protected against unauthorized friends or hackers or even against the provider of OSN. Many research works are going on to encounter the privacy issues in OSN. This paper analyses the limitations of the recent work being done in this field and proposes an efficient abstract solution to them

Transnational lifelong education course in robotic systems

Robotics constitutes a multidisciplinary area, congregating knowledge from different scientific domains. The learning of robotic systems requires the acquisition of multidisciplinary scientific bases, and high integration and synthesis abilities, which is not an easy task. This paper describes the implementation of a lifelong course that aims to provide a global insight on robotics field, introducing the concepts and technologies for different domain applications, namely industrial robotics, autonomous mobile robotics and robotics applied in medicine. This is accomplished in an international framework where individual knowledge and experiences will be confronted in a multidisciplinary level and intercultural environment.The work described in this paper was financially supported by the Lifelong Learning Programme Erasmus, under the projects n. 2012-1-PT1-ERA10-12529 and 2013-1-PT1- ERA10-16656.info:eu-repo/semantics/publishedVersio

Edge Detection Method Driven by Knowledge-Based Neighborhood Rules

Edge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the rules is based on the observed continuity properties and the neighborhood characteristics of the edge pixels, which are expressed as simple arithmetical operations to improve computational complexity. The results show that the method has an advantage over the gradient-based methods in terms of performance and computational load. It is appropriately four times faster than Canny method and shows superior performance compared to the gradient-based methods in general. Furthermore, the proposed method provides robustness to effectively identify edges at the corners. Due to its light computational requirement and inherent parallelization properties, the method would be also suitable for hardware implementation on field-programmable gate arrays (FPGA)

Evalutation of performance of KNN, MLP and RBF classifiers in emotion detection problem

IEEE 15th Signal Processing and Communications Applications Conference -- JUN 11-13, 2007 -- Eskisehir, TURKEYWOS: 000252924600115Emotion Detection has gained increasing attention and become an active research area. The problem is solved with improved feature set with different number of feature groups, by employing different classifiers in order to achieve satisfactory recognition rate. In this study, speech related features are employed to evaluate the performance of different classifiers in emotion detection problem.IEE

Comparison of simulation algorithms for the Hopfield neural network: an application of economic dispatch

This paper is mainly concerned with an investigation of the suitability of Hopfield neural network structures in solving the power economic dispatch problem. For Hopfield neural network applications to this problem three important questions have been answered: what the size of the power system is; how efficient the computational method; and how to handle constraints. A new mapping process is formulated and a computational method for obtaining the weights and biases is described. A few simulation algorithms used to solve the dynamic equation of the Hopfield neural network are discussed. The results are compared with those of a classical technique, Hopfield neural network approaches and an improved Hopfield neural network approach [1]. 1

On the comparison of classifiers' performance in emotion classification: Critiques and Suggestions

IEEE 16th Signal Processing and Communications Applications Conference -- APR 20-22, 2008 -- Aydin, TURKEYWOS: 000261359200056In literature there is a huge body of references available which compare various classifiers in a particular application. However, the reliability of such a comparison is only valid if the model parameters, performance criteria and training environment are chosen in a fair framework, as successful application of a classifier is dependent on the those parameters. In this study we attempt to answer the questions below in a emotion detection framework, using classifiers such as KNN, SVM, RBF and MLP: Is the success of a classifier enough to make the claim that a classifier is "the best one" in a particular classification task? How is it possible to carry out a fair comparison between classifiers?IEE