967 resultados para Multilevel Systems Model


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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

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We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

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Social, technological, and economic time series are divided by events which are usually assumed to be random, albeit with some hierarchical structure. It is well known that the interevent statistics observed in these contexts differs from the Poissonian profile by being long-tailed distributed with resting and active periods interwoven. Understanding mechanisms generating consistent statistics has therefore become a central issue. The approach we present is taken from the continuous-time random-walk formalism and represents an analytical alternative to models of nontrivial priority that have been recently proposed. Our analysis also goes one step further by looking at the multifractal structure of the interevent times of human decisions. We here analyze the intertransaction time intervals of several financial markets. We observe that empirical data describe a subtle multifractal behavior. Our model explains this structure by taking the pausing-time density in the form of a superstatistics where the integral kernel quantifies the heterogeneous nature of the executed tasks. A stretched exponential kernel provides a multifractal profile valid for a certain limited range. A suggested heuristic analytical profile is capable of covering a broader region.

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The study develops an approach that tries to validate software functionality to work systems needs in SMEs. The formulated approach is constructed by using a SAAS based software i.e., work collaboration service (WCS), and SMEs as the elements of study. Where the WCS’s functionality is qualified to the collaboration needs that exist in operational and project work within SMEs. For this research constructivist approach and case study method is selected because the nature of the current study requires an in depth study of the work collaboration service as well as a detailed study of the work systems within different enterprises. Four different companies are selected in which fourteen interviews are conducted to gather data pertaining. The work systems method and framework are used as a central part of the approach to collect, analyze and interpret the enterprises work systems model and the underlying collaboration needs on operational and project work. On the other hand, the functional model of the WCS and its functionality is determined from functional model analysis, software testing, documentation and meetings with the service vendor. The enterprise work system model and the WCS model are compared to reveal how work progression differs between the two and make visible unaddressed stages of work progression. The WCS functionality is compared to work systems collaboration needs to ascertain if the service will suffice the needs of the project and operational work under study. The unaddressed needs provide opportunities to improve the functionality of the service for better conformity to the needs of enterprise and work. The results revealed that the functional models actually differed in how operational and project work progressed within the stages. WCS shared similar stages of work progression apart from the stages of identification and acceptance, and progress and completion stages were only partially addressed. Conclusion is that the identified unaddressed needs such as, single point of reference, SLA and OLA inclusion etc., should be implemented or improved within the WCS at appropriate stages of work to gain better compliance of the service to the needs of the enterprise an work itself. The developed approach can hence be used to carry out similar analysis for the conformance of pre-built software functionality to work system needs with SMEs.

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Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

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We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

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The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

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During the last 30 years, significant debate has taken place regarding multilevel research. However, the extent to which multilevel research is overtly practiced remains to be examined. This article analyzes 10 years of organizational research within a multilevel framework (from 2001 to 2011). The goals of this article are (a) to understand what has been done, during this decade, in the field of organizational multilevel research and (b) to suggest new arenas of research for the next decade. A total of 132 articles were selected for analysis through ISI Web of Knowledge. Through a broad-based literature review, results suggest that there is equilibrium between the amount of empirical and conceptual papers regarding multilevel research, with most studies addressing the cross-level dynamics between teams and individuals. In addition, this study also found that the time still has little presence in organizational multilevel research. Implications, limitations, and future directions are addressed in the end. Organizations are made of interacting layers. That is, between layers (such as divisions, departments, teams, and individuals) there is often some degree of interdependence that leads to bottom-up and top-down influence mechanisms. Teams and organizations are contexts for the development of individual cognitions, attitudes, and behaviors (top-down effects; Kozlowski & Klein, 2000). Conversely, individual cognitions, attitudes, and behaviors can also influence the functioning and outcomes of teams and organizations (bottom-up effects; Arrow, McGrath, & Berdahl, 2000). One example is when the rewards system of one organization may influence employees’ intention to quit and the existence or absence of extra role behaviors. At the same time, many studies have showed the importance of bottom-up emergent processes that yield higher level phenomena (Bashshur, Hernández, & González-Romá, 2011; Katz-Navon & Erez, 2005; Marques-Quinteiro, Curral, Passos, & Lewis, in press). For example, the affectivity of individual employees may influence their team’s interactions and outcomes (Costa, Passos, & Bakker, 2012). Several authors agree that organizations must be understood as multilevel systems, meaning that adopting a multilevel perspective is fundamental to understand real-world phenomena (Kozlowski & Klein, 2000). However, whether this agreement is reflected in practicing multilevel research seems to be less clear. In fact, how much is known about the quantity and quality of multilevel research done in the last decade? The aim of this study is to compare what has been proposed theoretically, concerning the importance of multilevel research, with what has really been empirically studied and published. First, this article outlines a review of the multilevel theory, followed by what has been theoretically “put forward” by researchers. Second, this article presents what has really been “practiced” based on the results of a review of multilevel studies published from 2001 to 2011 in business and management journals. Finally, some barriers and challenges to true multilevel research are suggested. This study contributes to multilevel research as it describes the last 10 years of research. It quantitatively depicts the type of articles being written, and where we can find the majority of the publications on empirical and conceptual work related to multilevel thinking.

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The purpose of this article is to present a new method to predict the response variable of an observation in a new cluster for a multilevel logistic regression. The central idea is based on the empirical best estimator for the random effect. Two estimation methods for multilevel model are compared: penalized quasi-likelihood and Gauss-Hermite quadrature. The performance measures for the prediction of the probability for a new cluster observation of the multilevel logistic model in comparison with the usual logistic model are examined through simulations and an application.

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The design and implementation of an ERP system involves capturing the information necessary for implementing the system's structure and behavior that support enterprise management. This process should start on the enterprise modeling level and finish at the coding level, going down through different abstraction layers. For the case of Free/Open Source ERP, the lack of proper modeling methods and tools jeopardizes the advantages of source code availability. Moreover, the distributed, decentralized decision-making, and source-code driven development culture of open source communities, generally doesn't rely on methods for modeling the higher abstraction levels necessary for an ERP solution. The aim of this paper is to present a model driven development process for the open source ERP ERP5. The proposed process covers the different abstraction levels involved, taking into account well established standards and common practices, as well as new approaches, by supplying Enterprise, Requirements, Analysis, Design, and Implementation workflows. Copyright 2008 ACM.

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The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

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This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

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High-quality software, delivered on time and budget, constitutes a critical part of most products and services in modern society. Our government has invested billions of dollars to develop software assets, often to redevelop the same capability many times. Recognizing the waste involved in redeveloping these assets, in 1992 the Department of Defense issued the Software Reuse Initiative. The vision of the Software Reuse Initiative was "To drive the DoD software community from its current "re-invent the software" cycle to a process-driven, domain-specific, architecture-centric, library-based way of constructing software.'' Twenty years after issuing this initiative, there is evidence of this vision beginning to be realized in nonembedded systems. However, virtually every large embedded system undertaken has incurred large cost and schedule overruns. Investigations into the root cause of these overruns implicates reuse. Why are we seeing improvements in the outcomes of these large scale nonembedded systems and worse outcomes in embedded systems? This question is the foundation for this research. The experiences of the Aerospace industry have led to a number of questions about reuse and how the industry is employing reuse in embedded systems. For example, does reuse in embedded systems yield the same outcomes as in nonembedded systems? Are the outcomes positive? If the outcomes are different, it may indicate that embedded systems should not use data from nonembedded systems for estimation. Are embedded systems using the same development approaches as nonembedded systems? Does the development approach make a difference? If embedded systems develop software differently from nonembedded systems, it may mean that the same processes do not apply to both types of systems. What about the reuse of different artifacts? Perhaps there are certain artifacts that, when reused, contribute more or are more difficult to use in embedded systems. Finally, what are the success factors and obstacles to reuse? Are they the same in embedded systems as in nonembedded systems? The research in this dissertation is comprised of a series of empirical studies using professionals in the aerospace and defense industry as its subjects. The main focus has been to investigate the reuse practices of embedded systems professionals and nonembedded systems professionals and compare the methods and artifacts used against the outcomes. The research has followed a combined qualitative and quantitative design approach. The qualitative data were collected by surveying software and systems engineers, interviewing senior developers, and reading numerous documents and other studies. Quantitative data were derived from converting survey and interview respondents' answers into coding that could be counted and measured. From the search of existing empirical literature, we learned that reuse in embedded systems are in fact significantly different from nonembedded systems, particularly in effort in model based development approach and quality where the development approach was not specified. The questionnaire showed differences in the development approach used in embedded projects from nonembedded projects, in particular, embedded systems were significantly more likely to use a heritage/legacy development approach. There was also a difference in the artifacts used, with embedded systems more likely to reuse hardware, test products, and test clusters. Nearly all the projects reported using code, but the questionnaire showed that the reuse of code brought mixed results. One of the differences expressed by the respondents to the questionnaire was the difficulty in reuse of code for embedded systems when the platform changed. The semistructured interviews were performed to tell us why the phenomena in the review of literature and the questionnaire were observed. We asked respected industry professionals, such as senior fellows, fellows and distinguished members of technical staff, about their experiences with reuse. We learned that many embedded systems used heritage/legacy development approaches because their systems had been around for many years, before models and modeling tools became available. We learned that reuse of code is beneficial primarily when the code does not require modification, but, especially in embedded systems, once it has to be changed, reuse of code yields few benefits. Finally, while platform independence is a goal for many in nonembedded systems, it is certainly not a goal for the embedded systems professionals and in many cases it is a detriment. However, both embedded and nonembedded systems professionals endorsed the idea of platform standardization. Finally, we conclude that while reuse in embedded systems and nonembedded systems is different today, they are converging. As heritage embedded systems are phased out, models become more robust and platforms are standardized, reuse in embedded systems will become more like nonembedded systems.

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In American society, the incidence of divorce continues to rise. In 1974, the estimate was that 40% of all new marriages would end in divorce. When children are involved, the mother usually regains custody. Although the number of children of divorce living with their fathers is increasing, it is still a small percent. In addition, the rate of remarriages is lower when children are involved (Hetherington.et al.,1977). Consequently, a large number of children are being raised in father-absent homes, and indications are that the numbers are increasing. A recent Denver Post article predicted that 50% of all children now being born will spend some of their childhood in a single-parent home. In terms of frequency, the father-absent family is becoming quite common, even "normal," yet it often continues to be considered a "broken" home and, when compared to the two-parent family, an inadequate structure in which to raise healthy children. Since father-absent families are so common these days, this opinion is in need of review.This paper will present a review of the father absence research in three areas: sex role development, cognitive development and personality development. The role of moderator variables will be discussed. And, finally,an open systems model will be proposed as a vehicle to better understand the effects of father absence and as a guide for future research.

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