Time complexity analysis of the stochastic diffusion search

The Stochastic Diffusion Search algorithm -an integral part of Stochastic Search Networks is investigated. Stochastic Diffusion Search is an alternative solution for invariant pattern recognition and focus of attention. It has been shown that the algorithm can be modelled as an ergodic, finite state Markov Chain under some non-restrictive assumptions. Sub-linear time complexity for some settings of parameters has been formulated and proved. Some properties of the algorithm are then characterised and numerical examples illustrating some features of the algorithm are presented.

Fault Coverage-Driven Incremental Test Generation

In this paper, we consider a classical problem of complete test generation for deterministic finite-state machines (FSMs) in a more general setting. The first generalization is that the number of states in implementation FSMs can even be smaller than that of the specification FSM. Previous work deals only with the case when the implementation FSMs are allowed to have the same number of states as the specification FSM. This generalization provides more options to the test designer: when traditional methods trigger a test explosion for large specification machines, tests with a lower, but yet guaranteed, fault coverage can still be generated. The second generalization is that tests can be generated starting with a user-defined test suite, by incrementally extending it until the desired fault coverage is achieved. Solving the generalized test derivation problem, we formulate sufficient conditions for test suite completeness weaker than the existing ones and use them to elaborate an algorithm that can be used both for extending user-defined test suites to achieve the desired fault coverage and for test generation. We present the experimental results that indicate that the proposed algorithm allows obtaining a trade-off between the length and fault coverage of test suites.

Mapas cognitivos SODA ampliados: prescrição de um método para articular atitudes, comportamentos e seqüências cognitivas a mapas SODA

Este trabalho de tese tem por objetivo ampliar o alcance e aplicação de mapas SODA, preservando a metodologia originalmente desenvolvida. Inicialmente é realizada uma revisão do método, abordando de forma conjunta os artigos seminais, a teoria psicológica de Kelly e a teoria dos grafos; e ao final propomos uma identidade entre construtos de mapas SODA com os conhecimentos tácitos e explícitos, da gestão do conhecimento (KM). Essa sequencia introdutória é completada com uma visão de como os mapas SODA tem sido aplicado. No estágio seguinte o trabalho passa a analisar de forma crítica alguns pontos do método que dão margens a interpretações equivocadas. Sobre elas passamos a propor a aplicação de teorias, de diversos campos, tais como a teoria de means-end (Marketing), a teoria da atribuição e os conceitos de atitude (Psicologia), permitindo inferências que conduzem à proposição da primeira tese: mapas SODA são descritores de atitudes. O próximo estágio prossegue analisando criticamente o método, e foca no paradigma estabelecido por Eden, que não permite conferir ao método o status de descritor de comportamento. Propomos aqui uma mudança de paradigma, adotando a teoria da ação comunicativa, de Habermas, e sobre ela prescrevemos a teoria da ação e da escada da inferência (Action Science) e uma teoria da emoção (neuro ciência), o que permite novas inferências, que conduzem à proposição da segunda tese: mapas SODA podem descrever comportamentos. Essas teses servem de base para o alargamento de escopos do método SODA. É proposta aqui a utilização da teoria de máquinas de estado finito determinístico, designadas por autômato. Demonstramos um mapeamento entre autômato com mapas SODA, obtendo assim o autômato SODA, e sobre ele realizamos a última contribuição, uma proposta de mapas SODA hierárquicos, o que vem a possibilitar a descrição de sequencias de raciocínio, ordenando de forma determinística atitudes e comportamentos, de forma estruturada. A visão de como ela pode ser aplicada é realizada por meio de estudo de caso.

Estimação paramétrica e não-paramétrica em modelos de markov ocultos

In this work we study the Hidden Markov Models with finite as well as general state space. In the finite case, the forward and backward algorithms are considered and the probability of a given observed sequence is computed. Next, we use the EM algorithm to estimate the model parameters. In the general case, the kernel estimators are used and to built a sequence of estimators that converge in L1-norm to the density function of the observable process

Ergodicidade em cadeias de Markov não-homogêneas e cadeias de Markov com transições raras

The central objective of a study Non-Homogeneous Markov Chains is the concept of weak and strong ergodicity. A chain is weak ergodic if the dependence on the initial distribution vanishes with time, and it is strong ergodic if it is weak ergodic and converges in distribution. Most theoretical results on strong ergodicity assume some knowledge of the limit behavior of the stationary distributions. In this work, we collect some general results on weak and strong ergodicity for chains with space enumerable states, and also study the asymptotic behavior of the stationary distributions of a particular type of Markov Chains with finite state space, called Markov Chains with Rare Transitions

A REACHABILITY TREE FOR STATECHARTS AND ANALYSIS OF SOME PROPERTIES

Statecharts are an extension to finite state machines with capability for expressing hierarchical decomposition and parallelism. They also have a mechanism called history, to remember the last visit to a superstate. An algorithm to create a reachability tree for statecharts is presented. Also shown is how to use this tree to analyse dynamic properties of statecharts; reachability from any state configuration, usage of transitions, reinitiability, deadlocks, and valid sequence of events. Owing to its powerful notation, building a reachability tree for statecharts presents some difficulties, and we show how these problems were solved in the tree we propose.

Stochastic Stability for Markovian Jump Linear Systems Subject to a Crucial Failure Event

This paper is concerned with the stability of discrete-time linear systems subject to random jumps in the parameters, described by an underlying finite-state Markov chain. In the model studied, a stopping time τ Δ is associated with the occurrence of a crucial failure after which the system is brought to a halt for maintenance. The usual stochastic stability concepts and associated results are not indicated, since they are tailored to pure infinite horizon problems. Using the concept named stochastic τ-stability, equivalent conditions to ensure the stochastic stability of the system until the occurrence of τ Δ is obtained. In addition, an intermediary and mixed case for which τ represents the minimum between the occurrence of a fix number N of failures and the occurrence of a crucial failure τ Δ is also considered. Necessary and sufficient conditions to ensure the stochastic τ-stability are provided in this setting that are auxiliary to the main result.

Ambiente computacional para projetos de sistemas com tecnologia mista

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ferramentas para a integração de redes de Petri e VHDL na síntese de sistemas digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

On reducing test length for FSMs with extra states

A long-standing problem when testing from a deterministic finite state machine is to guarantee full fault coverage even if the faults introduce extra states in the implementations. It is well known that such tests should include the sequences in a traversal set which contains all input sequences of length defined by the number of extra states. This paper suggests the SPY method, which helps reduce the length of tests by distributing sequences of the traversal set and reducing test branching. It is also demonstrated that an additional assumption about the implementation under test relaxes the requirement of the complete traversal set. The results of the experimental comparison of the proposed method with an existing method indicate that the resulting reduction can reach 40%. Experimental results suggest that the additional assumption about the implementation can help in further reducing the test suite length. Copyright (C) 2011 John Wiley & Sons, Ltd.

MODEL PARTITIONS AND COMPACT TEST CASE SUITES

We present a generalized test case generation method, called the G method. Although inspired by the W method, the G method, in contrast, allows for test case suite generation even in the absence of characterization sets for the specification models. Instead, the G method relies on knowledge about the index of certain equivalences induced at the implementation models. We show that the W method can be derived from the G method as a particular case. Moreover, we discuss some naturally occurring infinite classes of FSM models over which the G method generates test suites that are exponentially more compact than those produced by the W method.

ParTec and KarnUMa-Digital tools as a help for freshman learning

[EN]Freshman students always present lower success rates than other levels of students. Digital systems is a course usually taught at first year studentsand its success rate is not very high. In this work we introduce three digital tools to improve freshman learning designed for easy use and one of them is a tool for mobile terminals that can be used as a game. The first tool is ParTec and is used to implement and test the partition technique. This technique is used to eliminate redundant states in finite state machines. This is a repetitive task that students do not like to perform. The second tool is called KarnUMa and is used for simplifying logic functions through Karnaugh Maps. Simplifying logical functions is a core task for this course and although students usually perform this task better than other tasks, it can still be improved. The third tool is a version of KarnUMa, designed for mobile devices. All the tools are available online for download and have been a helpful tool for students.

Modeling and simulation of a synthetic genetic circuit that implements a multicelled behavior in a growing microcolony of E. coli

Synthetic Biology is a relatively new discipline, born at the beginning of the New Millennium, that brings the typical engineering approach (abstraction, modularity and standardization) to biotechnology. These principles aim to tame the extreme complexity of the various components and aid the construction of artificial biological systems with specific functions, usually by means of synthetic genetic circuits implemented in bacteria or simple eukaryotes like yeast. The cell becomes a programmable machine and its low-level programming language is made of strings of DNA. This work was performed in collaboration with researchers of the Department of Electrical Engineering of the University of Washington in Seattle and also with a student of the Corso di Laurea Magistrale in Ingegneria Biomedica at the University of Bologna: Marilisa Cortesi. During the collaboration I contributed to a Synthetic Biology project already started in the Klavins Laboratory. In particular, I modeled and subsequently simulated a synthetic genetic circuit that was ideated for the implementation of a multicelled behavior in a growing bacterial microcolony. In the first chapter the foundations of molecular biology are introduced: structure of the nucleic acids, transcription, translation and methods to regulate gene expression. An introduction to Synthetic Biology completes the section. In the second chapter is described the synthetic genetic circuit that was conceived to make spontaneously emerge, from an isogenic microcolony of bacteria, two different groups of cells, termed leaders and followers. The circuit exploits the intrinsic stochasticity of gene expression and intercellular communication via small molecules to break the symmetry in the phenotype of the microcolony. The four modules of the circuit (coin flipper, sender, receiver and follower) and their interactions are then illustrated. In the third chapter is derived the mathematical representation of the various components of the circuit and the several simplifying assumptions are made explicit. Transcription and translation are modeled as a single step and gene expression is function of the intracellular concentration of the various transcription factors that act on the different promoters of the circuit. A list of the various parameters and a justification for their value closes the chapter. In the fourth chapter are described the main characteristics of the gro simulation environment, developed by the Self Organizing Systems Laboratory of the University of Washington. Then, a sensitivity analysis performed to pinpoint the desirable characteristics of the various genetic components is detailed. The sensitivity analysis makes use of a cost function that is based on the fraction of cells in each one of the different possible states at the end of the simulation and the wanted outcome. Thanks to a particular kind of scatter plot, the parameters are ranked. Starting from an initial condition in which all the parameters assume their nominal value, the ranking suggest which parameter to tune in order to reach the goal. Obtaining a microcolony in which almost all the cells are in the follower state and only a few in the leader state seems to be the most difficult task. A small number of leader cells struggle to produce enough signal to turn the rest of the microcolony in the follower state. It is possible to obtain a microcolony in which the majority of cells are followers by increasing as much as possible the production of signal. Reaching the goal of a microcolony that is split in half between leaders and followers is comparatively easy. The best strategy seems to be increasing slightly the production of the enzyme. To end up with a majority of leaders, instead, it is advisable to increase the basal expression of the coin flipper module. At the end of the chapter, a possible future application of the leader election circuit, the spontaneous formation of spatial patterns in a microcolony, is modeled with the finite state machine formalism. The gro simulations provide insights into the genetic components that are needed to implement the behavior. In particular, since both the examples of pattern formation rely on a local version of Leader Election, a short-range communication system is essential. Moreover, new synthetic components that allow to reliably downregulate the growth rate in specific cells without side effects need to be developed. In the appendix are listed the gro code utilized to simulate the model of the circuit, a script in the Python programming language that was used to split the simulations on a Linux cluster and the Matlab code developed to analyze the data.

Stationary states in random walks on networks

In this thesis we dealt with the problem of describing a transportation network in which the objects in movement were subject to both finite transportation capacity and finite accomodation capacity. The movements across such a system are realistically of a simultaneous nature which poses some challenges when formulating a mathematical description. We tried to derive such a general modellization from one posed on a simplified problem based on asyncronicity in particle transitions. We did so considering one-step processes based on the assumption that the system could be describable through discrete time Markov processes with finite state space. After describing the pre-established dynamics in terms of master equations we determined stationary states for the considered processes. Numerical simulations then led to the conclusion that a general system naturally evolves toward a congestion state when its particle transition simultaneously and we consider one single constraint in the form of network node capacity. Moreover the congested nodes of a system tend to be located in adjacent spots in the network, thus forming local clusters of congested nodes.