3 research outputs found
Capturing the influence of geopolitical ties from Wikipedia with reduced Google matrix
Interactions between countries originate from diverse aspects such as geographic proximity, trade, socio-cultural habits, language, religions, etc. Geopolitics studies the influence of a country’s geographic space on its political power and its relationships with other countries. This work reveals the potential of Wikipedia mining for geopolitical study. Actually, Wikipedia offers solid knowledge and strong correlations among countries by linking web pages together for different types of information (e.g. economical, historical, political, and many others). The major finding of this paper is to show that meaningful results on the influence of country ties can be extracted from the hyperlinked structure of Wikipedia. We leverage a novel stochastic matrix representation of Markov chains of complex directed networks called the reduced Google matrix theory. For a selected small size set of nodes, the reduced Google matrix concentrates direct and indirect links of the million-node sized Wikipedia network into a small Perron-Frobenius matrix keeping the PageRank probabilities of the global Wikipedia network. We perform a novel sensitivity analysis that leverages this reduced Google matrix to characterize the influence of relationships between countries from the global network. We apply this analysis to two chosen sets of countries (i.e. the set of 27 European Union countries and a set of 40 top worldwide countries). We show that with our sensitivity analysis we can exhibit easily very meaningful information on geopolitics from five different Wikipedia editions (English, Arabic, Russian, French and German)
A multiobjective Tabu framework for the optimization and evaluation of wireless systems
This chapter will focus on the multiobjective formulation of an optimization
problem and highlight the assets of a multiobjective Tabu implementation for
such problems. An illustration of a specific Multiobjective Tabu heuristic
(referred to as MO Tabu in the following) will be given for 2 particular
problems arising in wireless systems. The first problem addresses the planning
of access points for a WLAN network with some Quality of Service requirements
and the second one provides an evaluation mean to assess the performance
evaluation of a wireless sensor network. The chapter will begin with an
overview of multiobjective (MO) optimization featuring the definitions and
concepts of the domain (e.g. Dominance, Pareto front,...) and the main MO
search heuristics available so far. We will then emphasize on the definition of
a problem as a multiobjective optimization problem and illustrate it by the two
examples from the field of wireless networking. The next part will focus on MO
Tabu, a Tabu-inspired multiobjective heuristic and describe its assets compared
to other MO heuristics. The last part of the chapter will show the results
obtained with this MO Tabu strategy on the 2 wireless networks related
problems. Conclusion on the use of Tabu as a multiobjective heuristic will be
drawn based on the results presented so far
AN AUTONOMOUS MOBILE ROBOT FOR REFINERY INSPECTION
Industrial safety is one of the main aspects of industry specially refining industry. To avoid any types of unwanted phenomena all refining industry follows some basic precaution and phenomena. Communication is the main key factor for any industry today to monitor different parameters and take necessary actions accordingly to avoid any types of hazards.To implement a robotic system to autonomously navigate in an oil and gas refinery and it must be able to communicate with the control room and also localize it and alert workers in hazardous leakages and other accidents. Oil and gas refineries can be a dangerous environment for numerous reasons, including heat, gasses and humidity at the refinary. In order to augment how human operators interact with this environment, a mobile robotic platform is developed. This paper focuses on the use of WiFi for communicating with and localizing the robot. All the algorithms implemented are tested in real world scenarios with the robot developed and results are promising