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Relationship between physical and acoustical parameters for road surface characterizationAn acoustic system for automated road surface conditions detection from acoustic signals of surface interaction is introduced. The aim of this work is to obtain different characteristics of the roadway surface by which the vehicle is circulating, to analyze its texture, friction and other characteristics related to the road surface with anticipation so that this information could be used in future automotive safety applications. The advantages of using an acoustic device compared with other current technologies is the low cost of the equipment and its portability. The robustness of our approach is evaluated on audio that span an extensive range of vehicle speeds, noises from the environment, road surface types, and pavement conditions including international friction index (IFI) values from 0 km/hr to 100 km/hr. The training and evaluation of the model were performed on different roads to minimize the impact of environment and other external factors on the accuracy of the classification. The results showed that there is a correlation between what we measured with the mechanical systems and what we obtained as a reply from the acoustic system. The hypothesis is that with the application of an acoustic device that characterizes the pavement in real time, future automotive applications such as adjusting the ABS system automatically in an optimal range of braking, showing a warning indicator light on the dashboard, or improving the driving decision making of autonomous cars will be possible by having prior information of the slippery surface conditions in which the vehicle transits.
Métodos heurísticos para el problema de asignación de trabajadores y balanceo de líneas de ensamblajeSome types of distribution in assembly lines of manufacturing process begin as an assembly balancing problem of a certain type. In this work we propose two different algorithms based on two different methods to find a solution to the ALWABP (Assembly Line and Worker Assignment Balancing Problem) which is a generalization of the simple assembly line problem where workers assignment is introduced as a new problem for the balancing problem. Task times in this problem depends on each worker and in some cases one worker will not be capable of perform some task. The first method developed in this work is based on a GRASP metaheuristic combined with a VND metaheuristic as part of the first one. The second method is based on a Matheuristic combining a metaheuristic with an exact method. The experimental results shown in this paper are promising for the second model, due to the improvement obtained in the objective function value, in many of the instances evaluated of the different families. Therefore, the proposed model is competitive and efficient in comparison to previous methods found in the literature and exact approaches for this problem.
The influence of pH in the kinetic characterization of thermophilic β-fructosidase from T. maritimaGiven their advantageous features such as high reaction rates, increased specificity and negligible by-products generations, enzyme-catalyzed reactions are keep gaining ground over conventional chemical process. However, only a small fraction of currently known enzymes, is used in commercial processes at a large scale. Catalytic efficiency and stability reduction at drastic process conditions are some of the factors that restrain large scale biocatalysis boom. This can be exemplified in the industrial hydrolysis of sucrose where, at process conditions, S. cerevisiae β-fructosidase (BfrA) is subjected to thermal denaturation and substrate inhibition. In this regard, kinetic characterization of a thermophilic BfrA could help to overcome these inconveniences. Therefore, the main objective of this study is the kinetic characterization of T. maritima BfrA through a mathematical model that accounts for the simultaneous effects of pH and substrate inhibition over catalytic activity and kinetic parameters. Fitting of proposed model to experimental data yielded a surface of response which confirmed substrate uncompetitive inhibition at 146 mM of sucrose and optimum pH interval between 4.5 and 5.5. Estimation of kinetic parameters showed that Km and Ki are slightly pH dependent while vmax demonstrated to be sensitive to pH shifts. Likewise, estimated ionization constants of 3.0 and 6.60 suggested side-chain carboxylic groups of nucleophilic Asp and general acid/base Glu, which agreed with previous structural and mechanistic studies of T. maritima BfrA. These results suggest that the proposed model provide good estimations with respect of expected enzymatic activity of T. maritima BfrA at different conditions of pH and sucrose concentrations. Hence, can be useful for further kinetic characterization studies with potential application in biocatalysis process design.
GPGPU workload characterization using memory bottleneck detection and hierarchical clustering analysisThe use of Graphic Processing Units (GPU) for General Computing (GPGPU) has become increasingly common in recent years. In this type of processor, memory bottlenecks are a critical issue and the way data are commissioned to the partitions can cause several requests to get stalled behind each other, waiting for resources. In this thesis, a methodology to characterize GPGPU kernels based on their likeability to create bottlenecks in the GPGPU memory hierarchy is presented. A GPGPU simulator is used to obtain unique fingerprints from more than 100 workloads and classify them using a Hierarchical Clustering Analysis. The thesis also shows that that optimizations made to the kernels impact its run time memory bottleneck generation and that this behavior is successfully detected by the methodology. Two major groups of kernels were defined, naïve and optimized ones, and to characterize a set of exploration kernels within those groups with an effectiveness rate of over 75% for the two groups. A discussion is also held about how different levels of optimizations can be identified by our clustering engine and how those results could be use by subsequent approaches to predict bottleneck related issues in new kernels added to the cluster. Overall, a simple and transparent methodology to study bottleneck generation on GPGPU kernels is proposed which proves useful for future applications like static chararacterizer and statics predictor.
Wind Farm Integration Through VSC-HVDCHigh Voltage Direct Current (HVDC) systems has been an alternative method of transmitting electric power from one location to another with some inherent advantages over AC transmission systems. The efficiency and rated power carrying capacity of direct current transmission lines highly depends on the converter used in transforming the current from one form to another (AC to DC and vice versa). A well-configured converter reduces harmonics, increases power transfer capabilities, and reliability in that it offers high tolerance to fault along the line. Different HVDC converter topologies have been proposed, built and utilized all over the world. The two dominant types are the line-commutated converter (LCC) and the voltage-source converter (VSC). This thesis is focused on explaining the basic concepts of HVDC Systems and their usefulness for the integration of renewable energy. With the improvement in VSC technology and the advantages which it offers over LCC, VSC is bound to grow, and gain more recognition and market share, especially with the large-scale renewable energy integration into traditional AC power grids going on worldwide. Wind energy also has matured to a level of development at which it is ready to become a generally accepted power generation technology. This thesis provides a state of the art in the area of electrical machines and power-electronic systems for high-power wind energy generation applications. Wind power is considered as the most promising renewable energy and has been under extensive development globally.