Abstract

Information technologies have changed our lives, this includes new ways to generate, collect, and process large volumes of information. Big data are in the hands of large companies that delegate the management of data to algorithms and artificial intelligence programs that play a part in deciding who is the most suitable candidate for a job or who should receive mortgage credit. All this generates new ethical dilemmas; therefore, the existence of digital humanists becomes increasingly necessary. Philosophers, historians, and thinkers with knowledge and a critical vision of technology become the ones who alert and help us understand the limits and consequences of the use of big data.

Abstract

The aim of this article is to analyze the web positioning factors that can influence the order, by relevance, in Google Scholar and the subsequent evaluation of the importance of received citations in this ordering process. The methodology of reverse engineering was applied, in which a comparison was made between the Google Scholar ranking and another ranking consisting of only the number of citations received by documents. This investigation was conducted employing four types of searches without the use of keywords: by publication, year, author, and “cited by”. The results were matched in the four samples with correlation coefficients between the two highest rankings, which exceeded 0.9. The present study demonstrates more clearly than in previous research how citations are the most relevant off-page feature in the ranking of search results on Google Scholar. The other features have minimal influence. This information provides a solid basis for the academic search engine optimization (ASEO) discipline. We also developed a new analysis procedure for isolating off-page features that might be of practical use in forthcoming investigations.

Abstract

Algorithms in the strategies of political parties are becoming increasingly significant, particularly with the use of big data and the inclusion of the automation in the production and circulation of online content obtained from personal data. This paper studies the scope of algorithmic political communication, its strengths, weaknesses and implications in democracy in order to measure the real scenario of robotized information in parties. A qualitative analysis is designed based on in-depth interviews with political advisors and consultants. The results highlight the widespread implementation of algorithmic political communication in the main Spanish parties, although their level of development is irregular. It’s detected that automated information systems are being used primarily in the pre-production and circulation phase of the message and are beginning to be implemented in the production phases. Robots advance in their path as infomediaries between politicians and citizens.

Abstract

The aim of this article is to analyze the web positioning factors that can influence the order, by relevance, in Google Scholar and the subsequent evaluation of the importance of received citations in this ordering process. The methodology of reverse engineering was applied, in which a comparison was made between the Google Scholar ranking and another ranking consisting of only the number of citations received by documents. This investigation was conducted employing four types of searches without the use of keywords: by publication, year, author, and “cited by”. The results were matched in the four samples with correlation coefficients between the two highest rankings, which exceeded 0.9. The present study demonstrates more clearly than in previous research how citations are the most relevant off-page feature in the ranking of search results on Google Scholar. The other features have minimal influence. This information provides a solid basis for the academic search engine optimization (ASEO) discipline. We also developed a new analysis procedure for isolating off-page features that might be of practical use in forthcoming investigations.

Abstract

YouTube is a company representative of its original context, Web 2.0, that originally positioned itself as an open and collaborative platform to broadcast videos created by all kinds of users; their slogan was, and remains, Broadcast yourself. The acquisition of YouTube by Google introduced it in the search for profit in the framework of OTT (over the top) communication. The YouTube homepage reveals the successive business policies followed by the platform. In this work we analyze the evolution of the unlogged homepage of YouTube Spain between 2009 and 2018. We observe the gradual disappearance of the videos produced by private users and its replacement by those made by professional users (youtubers) and cultural industries. There is a remarkable parallelism between the implementation of business models and the greater or lesser recommendation of video from one kind of user or another.

Abstract

 

The computer simulation of forced vibrations induced on a water pool is presented in this paper. The complexity of the seismic fluid-structure interaction problem is accentuated by the large free surface motion. To overcome this difficulty, the arbitrary Lagrangian Eulerian (ALE) finite element formulation is employed. Moreover, the nonlinear behavior of the free surface motion is also taken into account. The results of the numerical simulation are compared with published experimental data and the effectiveness of the ALE algorithm is demonstrated

Abstract

This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering. 5th IFIP International Conference on Network Control & Engineering for QoS, Security and Mobility Red de Universidades con Carreras en Informática (RedUNCI) Document type: Part of book or chapter of book

Abstract

n eco-driving prototype, named EcoNav, is developed with the aim of optimizing a vessel speed in order to reduce fuel consumption for a given itinerary. EcoNav is organized in several modules : - a 2D hydraulic model simulating the flow conditions (current speed and water depth) along the itinerary; - a ship resistance model calculating the thrust necessary to counteract the hydrodynamic forces ; - a fuel consumption model calculating the fuel consumption corresponding to the thrust input; - a non linear optimization algorithm calculating the optimal speed profile. In order to evaluate the fuel consumption of an inland vessel, a ship resistance numerical model is developed in the first part of this PhD. This 3D numerical model simulates the flow around an inland self-propelled vessel and evaluates the hydrodynamic forces acting on the hull. A RANS solver is coupled with a quasi-Newton approach to find the equilibrium position and calculate ship sinkage. This method is validated by comparing the results of numerical simulations to towing tank tests. The numerical results with and without sinkage are also compared to study the influence of sinkage on ship resistance and on the accuracy of the method. Additionally, some empirical models are investigated and compared with the accuracy of the numerical method. Finally, the numerical model is used to determine if channel with and water depth restriction contribute to the same amount of ship resistance increase for the same level of restriction. The results of that investigation give insight to whether channel restriction can be characterized by a unique parameter (for instance the blockage ratio) or two parameters to distinguish water depth and channel with effects. In the second part of this PhD, the numerical methods used in the speed optimization model are described and validated. The speed optimization model is then used to simulate a real case: the itinerary of the self-propelled ship Oural on river Seine, between Chatou and Poses (153 km). The optimized fuel consumption is compared with the non-optimized fuel consumption, based on AIS speed profile retrieved on this itinerary. The effects of the ship trajectory and travel duration on fuel consumption are also investigated. The results of those investigations showed that optimizing the ship speed lead to an average fuel saving of 8 % and that using an optimal track and including real time information such as lock availability and river traffic can lead to additional fuel savings.; Les travaux de cette thèse ont pour but de développer un prototype d’éco-pilote, nommé EcoNav, permettant d’optimiser la vitesse d’un bateau afin de réduire sa consommation de carburant. EcoNav est composé de plusieurs modules dont : un modèle hydraulique 2D simulant l’écoulement hydrodynamique (vitesse du courant et hauteur d’eau) le long du trajet du bateau; - un modèle de résistance à l’avancement servant à alimenter un modèle de prédiction de la consommation de carburant; - un algorithme d’optimisation permettant de trouver le profil optimal de vitesse. Afin de pouvoir estimer la consommation de carburant, un modèle numérique de la résistance à l’avancement en milieu confiné a été développé durant la première partie de cette thèse. Ce modèle numérique 3D simule l’écoulement du fluide autour du bateau et permet de calculer les forces agissant sur sa coque. La résolution des équations RANS est couplée avec un algorithme de quasi-Newton afin de trouver la position d’équilibre du bateau et calculer son enfoncement. Cette méthode est validée en comparant les résultats numériques avec des résultats expérimentaux issus d’essais en bassin de traction. L’influence de l’enfoncement sur la résistance à l’avancement et la précision de la méthode est étudiée en comparant les résultats numériques obtenus avec et sans enfoncement. La précision des modèles empiriques de prédiction de la résistance à l’avancement est également comparée à celle du modèle numérique. Enfin, le modèle numérique est utilisé afin de déterminer si le confinement en largeur ou en profondeur ont une influence identique sur l’augmentation de résistance à l’avancement. Les résultats de cette étude permettent d’établir si le confinement de la voie d’eau peut être caractérisé à l’aide d’un paramètre unique (coefficient de blocage par exemple) ou bien deux paramètres permettant de distinguer le confinement latéral et vertical. Dans la seconde partie de cette thèse, les méthodes numériques utilisées pour le modèle d’éco-pilote sont décrites et comparées afin de sélectionner celles qui sont le plus adaptées à chaque module. EcoNav est ensuite utilisé afin de modéliser un cas réel : celui du bateau automoteur Oural navigant sur la Seine entre Chatou et Poses (153 km). La consommation optimisée est comparée à la consommation non optimisée, calculée à partir des vitesses AIS observées sur le tronçon étudié. L’influence de la trajectoire du bateau et de son temps de parcours sur sa consommation sont également étudiés. Les résultats de ces investigations ont montré qu’optimiser la vitesse du bateau permet d’obtenir une réduction de la consommation de carburant de l’ordre de 8 % et qu’optimiser la trajectoire du bateau ainsi que prendre en compte des informations en temps réel (disponibilité des écluses, trafic sur le fleuve) peuvent permettre de réaliser des économies de carburant supplémentaires.