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We prove that the class LOGSPACE (L, for short) is different from the class NP.

We study parametric inference on a rich class of hazard regression models in the presence of right-censoring. Previous literature has reported some inferential challenges, such as multimodal or flat likelihood surfaces, in this class of models for some particular data sets. We formalize the study of these inferential problems by linking them to the concepts of near-redundancy and practical non-identifiability of parameters. We show that the maximum likelihood estimators of the parameters in this class of models are consistent and asymptotically normal. Thus, the inferential problems in this class of models are related to the finite-sample scenario, where it is difficult to distinguish between the fitted model and a nested non-identifiable (i.e., parameter-redundant) model. We propose a method for detecting near-redundancy, based on distances between probability distributions. We also employ methods used in other areas for detecting practical non-identifiability and near-redundancy, including the inspection of the profile likelihood function and the Hessian method. For cases where inferential problems are detected, we discuss alternatives such as using model selection tools to identify simpler models that do not exhibit these inferential problems, increasing the sample size, or extending the follow-up time. We illustrate the performance of the proposed methods through a simulation study. Our simulation study reveals a link between the presence of near-redundancy and practical non-identifiability. Two illustrative applications using real data, with and without inferential problems, are presented., Comment: To appear in Biometrical Journal

We prove that NL is strictly contained in P. We get this separation as a corollary of the following result: the set of context-free languages is not contained in NL. The reader should recall that CFL is contained in DTIME(n^3), Comment: There is a gap that cannot be fixed

In many countries around the world, most of the waste use to be disposed of to landfills, this generate public concern about the health effects of emissions. Landfill gases are produced by the natural bacterial decomposition of waste and it is about half of methane, with the remainder mostly carbon dioxide and minor amounts of other gases. Real-time measurement and modelling of emissions gases in landfills is important. In this work a low cost wireless measurement system is developed using MOS gas sensors (MQ4-1,MQ4-2, MQ5 and MQ9), microcontroller and XBee/HC-12 wireless communications modules. The system can be mounted on an unmanned aircraft (UAV, drone) or deployed as a wireless sensor network. Experiments have been carried out near a closed landfill, which show high gas concentration, Comment: Poster presentation at 22nd IEEE NPSS Real Time Conference, Oct 12-23, 2020

Satellite communications have recently entered a period of renewed interest motivated by technological advances and nurtured through private investment and ventures. The present survey aims at capturing the state of the art in SatComs, while highlighting the most promising open research topics. Firstly, the main innovation drivers are motivated, such as new constellation types, on-board processing capabilities, nonterrestrial networks and space-based data collection/processing. Secondly, the most promising applications are described i.e. 5G integration, space communications, Earth observation, aeronautical and maritime tracking and communication. Subsequently, an in-depth literature review is provided across five axes: i) system aspects, ii) air interface, iii) medium access, iv) networking, v) testbeds & prototyping. Finally, a number of future challenges and the respective open research topics are described., Comment: Submitted for possible publication in IEEE Communications Surveys & Tutorials

Planar automata seems to be representative of the synchronizing behavior of deterministic finite state automata. We conjecture that \v{C}erny's conjecture holds true, if and only if, it holds true for planar automata. In this paper we have gathered some evidence concerning this conjecture. This evidence amounts to show that the class of planar automata is representative of the algorithmic hardness of synchronization, Comment: 17 pages, 2 figures

We prove that the almost-entropic region of order four is not semialgebraic, we get as a corollary the well-known Theorem of Matus, which asserts that this region is not polyhedral, Comment: 9 pages The paper has been withdrawn by the authors due to a flaw in the proof of the main result

We propose two classes of nonparametric point estimators of $\theta=P(X