An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to take tuning decisions on the number of samples improving the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36% and 81%) with respect to a static approach while considering different traffic situations, paths and error requirements. Given the negligible runtime overhead of the proposed approach, it results in an execution-time speedup between 1.5x and 5.1x. This speedup is reflected at infrastructure-level in terms of a reduction of around 36% of the computing resources needed to support the whole navigation pipeline

IN VITRO AND IN VIVO REMOVAL OF ORAL ANTIDIABETIC AGENTS (METFORMIN) USING ACTIVATED CARBONS

Diabetes is the most worldwide common chronic disease, according the International Diabetes Federation [1], more than 32 million citizens living in the European Union have diabetes, representing nearly 10% of the population, to which we should add equal number of people suffering from impaired glucose tolerance. Diabetes prevalence is growing at alarming rate worldwide, being of particular relevance the type 2 diabetes. Nowadays 285 million people worldwide live with diabetes and it is expected that this numbers will increase by 20% until 2030 due to obesity and the ageing of the population [1]. This growth leads to an increasing consumption of drugs such as oral antidiabetics. Metformin is one of the active principles most commonly used for this purpose being among the pharmaceuticals with the highest production numbers worldwide to treat type 2 diabetes because is cheap, has high level of tolerance and when used in the prescribed dosage is very secure with minimal side effects. However, in case of overdose of metformin upon a ingestion of more than 10 times the prescribed dosage, accidentally or on propose, lactic acidosis and low blood pressure can occur. Overdoses with metformin are relatively uncommon, but may have serious consequences, if medical attention is not given on time, it may lead to coma and ultimately death Because of its spread use another problem must be taken into consideration, which needs to be addressed, the occurrence of metformin residues in sewage and surface waters due to improper discharge of the non-used tablets to regular garbage [2]. This situation is becoming a serious problem of environmental pollution and public health. This paper reports the use of activated carbon produced from biomass for the removal of metformin in 2 different settings. On one hand, from aqueous solutions and, in another hand, from simulated biological fluids (gastric and intestinal) conjugated with in vivo testing

Analysis and Real-time Data of Meteorologic Impact on Home Solar Energy Harvesting

Solar energy production increased in the world from 0 TWh in 1965 to 724.09 TWh in 2019. Solar energy is adopted as a source for residential renewable energy sources because, besides Biomass sources, it’s the only one that can be installed and maintained at home. Operating efficiency is an important consideration when evaluating the application of photovoltaic panels (PV) technology. A real-time system monitoring is required to analyse the current production and understand the impact of the weather conditions on PV production. This paper extends the literature on the residence solar energy harvesting subject, by providing a scalable architecture that can be used as starting point on data analysis on PV panels efficiency and how weather conditions impact energy production. A dataset was collected related to PV panel energy production, the residence energy consumption and that’s reading weather conditions. Wind intensity and direction, temperature, precipitation, humidity, atmospheric pressure and radiation were weather conditions analysed. Moreover, this data was analysed and interpreted in order to evaluate the pros and cons of the architecture as well as how the weather impacted the energy production

A texture segmentation prototype for industrial inspection applications based on fuzzy grammar

Purpose – The purpose of this paper is to propose a set of techniques, in the domain of texture analysis, dedicated to the classification of industrial textures. One of the main purposes was to deal with a high diversity of textures, including structural and highly random patterns. Design/methodology/approach – The global system includes a texture segmentation phase and a classification phase. The approach for image texture segmentation is based on features extracted from wavelets transform, fuzzy spectrum and interaction maps. The classification architecture uses a fuzzy grammar inference system. Findings – The classifier uses the aggregation of features from the several segmentation techniques, resulting in high flexibility concerning the diversity of industrial textures. The resulted system allows on-line learning of new textures. This approach avoids the need for a global re-learning of the all textures each time a new texture is presented to the system. Practical implications – These achievements demonstrate the practical value of the system, as it can be applied to different industrial sectors for quality control operations. Originality/value – The global approach was integrated in a cork vision system, leading to an industrial prototype that has already been tested. Similarly, it was tested in a textile machine, for a specific fabric inspection, and gave results that corroborate the diversity of possible applications. The segmentation procedure reveals good performance that is indicated by high classification rates, revealing good perspectives for full industrialization

An existence and uniqueness result about algebras of Schwartz distributions

We prove that there exists essentially one {\it minimal} differential algebra of distributions \A, satisfying all the properties stated in the Schwartz impossibility result [L. Schwartz, Sur l'impossibilit\'e de la multiplication des distributions, 1954], and such that \C_p^{\infty} \subseteq \A \subseteq \DO' (where \C_p^{\infty} is the set of piecewise smooth functions and \DO' is the set of Schwartz distributions over \RE). This algebra is endowed with a multiplicative product of distributions, which is a generalization of the product defined in [N.C.Dias, J.N.Prata, A multiplicative product of distributions and a class of ordinary differential equations with distributional coefficients, 2009]. If the algebra is not minimal, but satisfies the previous conditions, is closed under anti-differentiation and the dual product by smooth functions, and the distributional product is continuous at zero then it is necessarily an extension of \A.Comment: 17 pages, to appear in Monatshefte f\"ur Mathemati