University of Rwanda Digital Repository
Not a member yet
17358 research outputs found
Sort by
SUMP PLUS Governance tools : questionnaire and users' guide
No full textDeveloped throughout the SUMP PLUS Project (2019-2022). Contribution to the CityConsult AngencyThese tools provide an opportunity for cities to self-examine existing structures and resources and what is lacking to achieve transformative change and deliver on their sustainable mobility goals. As a result, cities will be better equipped to develop strategies to overcome such barriers and know where to focus their efforts
Place-based approach to Health and Transport decarbonisation: WP3 Workshop summary report (Greater Manchester), June13-14, 2022
No full textA longer version including quotes
LocURa4IoT - Localisation and Ultra-Wide Band Ranging for the IoT - Rapport d’activité scientifique 2016-2021
No full textLA SIBÉRIE SOUS LA DOMINATION RUSSE
No full textCet article s'appuie principalement sur l'étude de A.V. Remnev sur le statut de la Sibérie sous l'Empire russe et sur les ouvrages de O.E. Çarkov sur l'histoire de la Yakoutie (peuple Sakha), qui contiennent d'abondants éléments factuels de réflexion
Synthèse des débats de l’atelier de la Chaire maritime sur la caractérisation des activités humaines en mer - Atelier du 28 et 29 septembre 2021
No full textSynthèse des débats de l'atelier de la Chaire maritime sur la caractérisation des activités humaines en mer - Atelier du 27 et 28 septembre 2021
No full text
Nonlinear Dynamics in Complexity Quantification
No full textChaotic systems which are due to nonlinearity have attracted a great concern in the current world and chaotic models. Systems for a wide range of operation conditions have their application in almost all branches of engineering and science. In the history of chaotic studies and nonlinearity, many different but co-existent phases can be distinguished [1]. In the initial phase, chaos was considered as a deterministic regime which, most probably, was responsible for the variations that was regarded as noise and thus was being modeled as a stochastic process. In the second phase, it was of great significance to establish criteria for detecting chaotic dynamics and thus establishing dynamical invariants which were necessary in quantifying chaos. The third step which was to develop machine learning models which could learn the dynamics and chaos from the data of the strange attractor [2]. With respect to this aspect, various model structures were developed and investigated on their ability to detect chaos from a given set of data [3]. These model structures included radial basis functions, and local linear mapping among others. The third phase is currently being investigated together with other issues surrounding nonlinear dynamics and chaos, for instance in noise reduction and control, among other issues
Repository Guidelines
No full textThis document, prepared by the Data Strand of the PARSEC project funded by the Belmont Forum, provides guidelines for researchers about the importance and benefits of data repositories, the risks if you choose the wrong repository for your data, suggestions for selection of the right, TRUSTed repository and where to find them