Typescript (photocopy). / Digitized by Kansas Correctional Industries

In the current market, there is a large number of SMEs that have a large margin of economic losses due to lack of stocks, due to the supply process. In other words, the lost sales and the costs of the services generated by not having their products available in their warehouses is a critical scenario in the distribution companies, whose added value lies in maximizing their level of customer service. To solve this problem, we propose a system that integrates the development of the attention and the model of the inventories of the periodic review, the bases based on the framework of the work. The results, after analyzing the demand, their patterns and choosing the best method to use, are antecedents to develop the management of inventories and their policies. Likewise, knowledge management will act as an integrated support. Through the simulation carried out for a distribution of lubricants, results were obtained that indicate a reduction of 93% in losses due to stock-outs and an increase in the service level that goes from 77% to 91%. This is an integrated system of interest to be applied as a solution for SMEs that have high stock-outs and lack this type of tools..

abstract: ABSTRACT Developing new non-traditional device models is gaining popularity as the silicon-based electrical device approaches its limitation when it scales down. Membrane systems, also called P systems, are a new class of biological computation model inspired by the way cells process chemical signals. Spiking Neural P systems (SNP systems), a certain kind of membrane systems, is inspired by the way the neurons in brain interact using electrical spikes. Compared to the traditional Boolean logic, SNP systems not only perform similar functions but also provide a more promising solution for reliable computation. Two basic neuron types, Low Pass (LP) neurons and High Pass (HP) neurons, are introduced. These two basic types of neurons are capable to build an arbitrary SNP neuron. This leads to the conclusion that these two basic neuron types are Turing complete since SNP systems has been proved Turing complete. These two basic types of neurons are further used as the elements to construct general-purpose arithmetic circuits, such as adder, subtractor and comparator. In this thesis, erroneous behaviors of neurons are discussed. Transmission error (spike loss) is proved to be equivalent to threshold error, which makes threshold error discussion more universal. To improve the reliability, a new structure called motif is proposed. Compared to Triple Modular Redundancy improvement, motif design presents its efficiency and effectiveness in both single neuron and arithmetic circuit analysis. DRAM-based CMOS circuits are used to implement the two basic types of neurons. Functionality of basic type neurons is proved using the SPICE simulations. The motif improved adder and the comparator, as compared to conventional Boolean logic design, are much more reliable with lower leakage, and smaller silicon area. This leads to the conclusion that SNP system could provide a more promising solution for reliable computation than the conventional Boolean logic. / Dissertation/Thesis / M.S. Electrical Engineering 2013

Yes / Computational theory and practice generally focus on single-paradigm systems, but relatively little is known about how best to combine components based on radically different approaches (e.g. silicon chips and wetware) into a single coherent system. In particular, while testing strategies for single-technology artefacts are generally well developed, it is unclear at present how to perform integration testing on heterotic systems: can we develop a test-set generation strategy for checking whether specified behaviours emerge (and unwanted behaviours do not) when components based on radically different technologies are combined within a single system? In this paper, we describe an approach to modelling multi-technology heterotic systems using a general-purpose formal specification strategy based on Eilenberg's X-machine model of computation. We show how this approach can be used to represent disparate technologies within a single framework, and propose a strategy for using these formal models for automatic heterotic test-set generation. We illustrate our approach by showing how to derive a test set for a heterotic system combining an X-machine-based device with a cell-based P system (membrane system).

no / Presents comprehensive descriptions of the most significant membrane computing tools developed for various models Describes the most relevant applications, facilitating a better understanding of how the tools are used in building, experimenting with and analysing membrane computing models of complex problems arising in robotics, automatic design of P systems, image processing, ecosystem modelling, systems and synthetic biology, and bioinformatics Discusses efficient software and hardware solutions, together with the algorithms and platforms used