165 research outputs found
PIO I-II tendencies case study. Part 1. Mathematical modeling
No full textIn the paper, a study is performed from the perspective of giving a method to reduce the conservatism of the well known PIO (Pilot-Induced Oscillation) criteria in predicting the susceptibility of an aircraft to this very harmful phenomenon. There are three interacting components of a PIO – the pilot, the vehicle, and the trigger (in fact, the hazard). The study, conceived in two parts, aims to underline the importance of human pilot model involved in analysis. In this first part, it is shown, following classical sources, how the LQG theory of control and estimation is used to obtain a complex model of human pilot. The approach is based on the argument, experimentally proved, that the human behaves “optimally” in some sense, subject to his inherent psychophysical limitations. The validation of such model is accomplished based on the experimental model of a VTOL-type aircraft. Then, the procedure of inserting typical saturation nonlinearities in the open loop transfer function is presented. A second part of the paper will illustrate PIO tendencies evaluation by means of a grapho-analytic method
The persuasive use of pronouns in action games of election campaigns
No full textAbstract
Action games of election campaigns are one of the best venues for politicians to team up with specialists in communication studies in order to build, review, construct or deconstruct their own or their opponent’s image with the purpose of persuading the electorate to vote for a certain political group. Various action games of Donald Trump’s presidential campaign are analysed with regard to different dialogic means used by the speaker in order to persuade the audience to vote for him. For instance, he evokes nationalistic views in his speeches and skilfully uses pronouns in order to establish his role as dominant, strong, and credible nominee for presidency. Since we focus on a particular practice in dialogic language use, we will show that the Mixed Game Model (MGM) is more appropriate to study the argumentative power of words than integrationism.</jats:p
Control of uncertain systems by feedback linearization with neural networks augmentation. Part II. Controller validation by numerical simulation
No full textThe paper was conceived in two parts. Part I, previously published in this journal, highlighted the main steps of adaptive output feedback control for non-affine uncertain systems, having a known relative degree. The main paradigm of this approach was the feedback linearization (dynamic inversion) with neural network augmentation. Meanwhile, based on new contributions of the authors, a new paradigm, that of robust servomechanism problem solution, has been added to the controller architecture. The current Part II of the paper presents the validation of the controller hereby obtained by using the longitudinal channel of a hovering VTOL-type aircraft as mathematical model
Major Players in the Credit Market in Romania in the European Context
No full textAbstractThe present article illustrates the context in which European credit rating agencies emerged, their roles and modus operandi. To exemplify, we proceeded to a comparative, quantitative analysis of two such companies, respectively the Credit Bureau JSC of Romania and Schufa Holding AG in Germany between 2009 and 2013. We present the establishment and the evolution of the two agencies, also touching on aspects related to some relevant macroeconomic indicators concerning the retail credit market in both countries such as the income per capita, total population, gross domestic product, the declared unemployment rate as a percentage of the total labor force, the number of domestic loans and the percentage of the adult population coverage by the rating agencies
Variations in Heavy Metal Contents in Milk and Incorporation of Global Positioning System (GPS) for Food Safety, Soil Chemicals and Agricultural Product Traceability (Legislation Proposal)
No full textOn the synthesis of the pilot optimal control model
No full textThe study continues some work of the authors, this time performing a synthesis of optimal control model of the human pilot in systems with input delay, by removing the Padé or Hess approximations characterizing the pilot structural central nervous block and their introduction as a pure delay block. On the one hand, the method ensures a better accuracy of synthesis and on the other hand is advantageous with respect to general results to date for time delay systems since: a) the optimal control law is given explicitly and b) the Riccati equations for the gain matrices do not contain any time advanced or delayed arguments. The approach is stimulated by recent works of M. Basin and his collaborators
Mesures des risques et arbitrages réglementaires dans l'odyssée bâloise
No full textInternational audienceAu cours de l'histoire, la construction de la réglementation et de la supervision coordonnée des établissements bancaires internationaux est souvent apparue comme une réponse aux nombreux chocs financiers et économiques qui ont suivi les épisodes de libéralisation financière. Tandis que la définition des fonds propres est restée plutôt inchangée depuis l'accord initial de Bâle I, la mesure des risques a quant à elle subi des mutations importantes. En particulier, la sensibilité aux risques, notion clé au cœur même de la réglementation de la solvabilité bancaire, a été refondue en profondeur dans le cadre dit de Bâle II. Avec la liberté accrue conférée aux établissements bancaires, celle de pouvoir évaluer eux-mêmes le risque perçu, le régulateur a involontairement introduit des incitations adverses et laissé place à l'arbitrage réglementaire, ce qui a dès lors nuit à l'efficacité des normes de solvabilité. L'arbitrage réglementaire joue ainsi un rôle central dans la conception de la régulation prudentielle et constitue la force motrice de la dialectique réglementaire
Depth Light Field Training (DeLFT): NeRF as a rendering primitive
No full textNeural radiance fields (NeRF) based solutions for novel view synthesis can achieve state of the art results. Recent work proposes models that take less time to render, need less training data or take up less space. However, few papers explore the use of NeRFs in classic rendering scenarios such as rasterization, which could contribute to wider adoption. Our paper tackles the issue of shadow generation and proposes a deep residual MLP network with fast evaluation times, that generates view-dependent shadow maps. The network distills the knowledge of an existing NeRF model and achieves the speedup through the use of neural light fields, by only doing one network forward per ray.CSE3000 Research ProjectComputer Science and Engineerin
Machine-Learning for Optimal Fitness Function Selection in Automated Testing
No full textThe perpetual desire for more qualitative software has been an excellent incentive for software engineers to create automated tools to ease and improve the process of software testing. EvoSuite is an example of a state-of-the-art tool that synthesises test cases automatically. It uses a genetic algorithm to produce test cases based on given search targets. Previous studies have analysed the performance of single or combinations of targets but have not yet explored the differences between various combinations. In this research, we compare the Weak Mutation + Branch setting to Branch and the Default (combination of eight separate targets) of EvoSuite. We aim to provide insightful information about their differences in branch coverage and mutation scores. Moreover, we discuss machine-learning models that can predict which combination has the highest score (i.e., branch coverage, mutation score) based on characteristics of the tested classes, such as the number of lines of code. Our results highlight that the Weak Mutation + Branch combination outperforms Branch for the mutation score metric and Default for the branch coverage metric. They also show that Weak Mutation + Branch is outperformed by the branch criterion for Branch Coverage and by the Default combination for mutation score. Our findings also cover the performance of the models, having concluded that the Random Forest and Decision Tree classifiers produce the best results and are feasible options for predicting the best combinations from the ones analysed. Finally, static code metrics such as 'wmc', 'loc', and 'mathOperationsOty' often appear as relevant features for our models. We visualise how they influence the most suitable combination of criteria through our Decision Trees.CSE3000 Research ProjectComputer Science and Engineerin
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