A Functional Verification Methodology Based on Parameter Domains for Efficient Input Stimuli Generation and Coverage Modeling

Modern Integrated Circuit (IC) design is characterized by a strong trend of Intellectual Property (IP) core integration into complex system-on-chip (SOC) architectures. These cores require thorough verification of their functionality to avoid erroneous behavior in the final device. Formal verification methods are capable of detecting any design bug. However, due to state explosion, their use remains limited to small circuits. Alternatively, simulation-based verification can explore hardware descriptions of any size, although the corresponding stimulus generation, as well as functional coverage definition, must be carefully planned to guarantee its efficacy. In general, static input space optimization methodologies have shown better efficiency and results than, for instance, Coverage Directed Verification (CDV) techniques, although they act on different facets of the monitored system and are not exclusive. This work presents a constrained-random simulation-based functional verification methodology where, on the basis of the Parameter Domains (PD) formalism, irrelevant and invalid test case scenarios are removed from the input space. To this purpose, a tool to automatically generate PD-based stimuli sources was developed. Additionally, we have developed a second tool to generate functional coverage models that fit exactly to the PD-based input space. Both the input stimuli and coverage model enhancements, resulted in a notable testbench efficiency increase, if compared to testbenches with traditional stimulation and coverage scenarios: 22% simulation time reduction when generating stimuli with our PD-based stimuli sources (still with a conventional coverage model), and 56% simulation time reduction when combining our stimuli sources with their corresponding, automatically generated, coverage models.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

MODELING THE UNVOICED COMPONENT IN THE CANONICAL REPRESENTATION OF SPEECH

The canonical representation of speech constitutes a perfect reconstruction (PR) analysis-synthesis system. Its parameters are the autoregressive (AR) model coefficients, the pitch period and the voiced and unvoiced components of the excitation represented as transform coefficients. Each set of parameters may be operated on independently. A time-frequency unvoiced excitation (TFUNEX) model is proposed that has high time resolution and selective frequency resolution. Improved time-frequency fit is obtained by using for antialiasing cancellation the clustering of pitch-synchronous transform tracks defined in the modulation transform domain. The TFUNEX model delivers high-quality speech while compressing the unvoiced excitation representation about 13 times over its raw transform coefficient representation for wideband speech.

Modeling and Filtering Double-Frequency Jitter in One-Way Master-Slave Chain Networks

One-way master-slave (OWMS) chain networks are widely used in clock distribution systems due to their reliability and low cost. As the network nodes are phase-locked loops (PLLs), double-frequency jitter (DFJ) caused by their phase detectors appears as an impairment to the performance of the clock recovering process found in communication systems and instrumentation applications. A nonlinear model for OWMS chain networks with P + 1 order PLLs as slave nodes is presented, considering the DFJ. Since higher order filters are more effective in filtering DFJ, the synchronous state stability conditions for an OWMS chain network with third-order nodes are derived, relating the loop gain and the filter coefficients. By using these conditions, design examples are discussed.

Evaluation of Characterization and Performance Modeling of Cementitiously Stabilized Layers in the Mechanistic-Empirical Pavement Design Guide

Cementitious stabilization of aggregates and soils is an effective technique to increase the stiffness of base and subbase layers. Furthermore, cementitious bases can improve the fatigue behavior of asphalt surface layers and subgrade rutting over the short and long term. However, it can lead to additional distresses such as shrinkage and fatigue in the stabilized layers. Extensive research has tested these materials experimentally and characterized them; however, very little of this research attempts to correlate the mechanical properties of the stabilized layers with their performance. The Mechanistic Empirical Pavement Design Guide (MEPDG) provides a promising theoretical framework for the modeling of pavements containing cementitiously stabilized materials (CSMs). However, significant improvements are needed to bring the modeling of semirigid pavements in MEPDG to the same level as that of flexible and rigid pavements. Furthermore, the MEPDG does not model CSMs in a manner similar to those for hot-mix asphalt or portland cement concrete materials. As a result, performance gains from stabilized layers are difficult to assess using the MEPDG. The current characterization of CSMs was evaluated and issues with CSM modeling and characterization in the MEPDG were discussed. Addressing these issues will help designers quantify the benefits of stabilization for pavement service life.

Model for facilities or vendors location in a global scale considering several echelons in the Chain

The facilities location problem for companies with global operations is very complex and not well explored in the literature. This work proposes a MILP model that solves the problem through minimization of the total logistic cost. Main contributions of the model are the pioneer carrying cost calculation, the treatment given to the take-or-pay costs and to the international tax benefits such as drawback and added value taxes in Brazil. The model was successfully applied to a real case of a chemical industry with industrial plants and sales all over the world. The model application recommended a totally new sourcing model for the company.

Modeling technique for honeycomb FRP deck bridges via finite elements

Honeycomb structures have been used in different engineering fields. In civil engineering, honeycomb fiber-reinforced polymer (FRP) structures have been used as bridge decks to rehabilitate highway bridges in the United States. In this work, a simplified finite-element modeling technique for honeycomb FRP bridge decks is presented. The motivation is the combination of the complex geometry of honeycomb FRP decks and computational limits, which may prevent modeling of these decks in detail. The results from static and modal analyses indicate that the proposed modeling technique provides a viable tool for modeling the complex geometry of honeycomb FRP bridge decks. The modeling of other bridge components (e.g., steel girders, steel guardrails, deck-to-girder connections, and pier supports) is also presented in this work.

Modeling and measuring double-frequency jitter in one-way master-slave networks

The double-frequency jitter is one of the main problems in clock distribution networks. In previous works, sonic analytical and numerical aspects of this phenomenon were studied and results were obtained for one-way master-slave (OWMS) architectures. Here, an experimental apparatus is implemented, allowing to measure the power of the double-frequency signal and to confirm the theoretical conjectures. (C) 2008 Elsevier B.V. All rights reserved.

Emerging Threats and Opportunities for Large-Scale Ecological Restoration in the Atlantic Forest of Brazil

Over the past 150 years, Brazil has played a pioneering role in developing environmental policies and pursuing forest conservation and ecological restoration of degraded ecosystems. In particular, the Brazilian Forest Act, first drafted in 1934, has been fundamental in reducing deforestation and engaging private land owners in forest restoration initiatives. At the time of writing (December 2010), however, a proposal for major revision of the Brazilian Forest Act is under intense debate in the National Assembly, and we are deeply concerned about the outcome. On the basis of the analysis of detailed vegetation and hydrographic maps, we estimate that the proposed changes may reduce the total amount of potential areas for restoration in the Atlantic Forest by approximately 6 million hectares. As a radically different policy model, we present the Atlantic Forest Restoration Pact (AFRP), which is a group of more than 160 members that represents one of the most important and ambitious ecological restoration programs in the world. The AFRP aims to restore 15 million hectares of degraded lands in the Brazilian Atlantic Forest biome by 2050 and increase the current forest cover of the biome from 17% to at least 30%. We argue that not only should Brazilian lawmakers refrain from revising the existing Forest Law, but also greatly step up investments in the science, business, and practice of ecological restoration throughout the country, including the Atlantic Forest. The AFRP provides a template that could be adapted to other forest biomes in Brazil and to other megadiversity countries around the world.

The generalized inverse Weibull distribution

The inverse Weibull distribution has the ability to model failure rates which are quite common in reliability and biological studies. A three-parameter generalized inverse Weibull distribution with decreasing and unimodal failure rate is introduced and studied. We provide a comprehensive treatment of the mathematical properties of the new distribution including expressions for the moment generating function and the rth generalized moment. The mixture model of two generalized inverse Weibull distributions is investigated. The identifiability property of the mixture model is demonstrated. For the first time, we propose a location-scale regression model based on the log-generalized inverse Weibull distribution for modeling lifetime data. In addition, we develop some diagnostic tools for sensitivity analysis. Two applications of real data are given to illustrate the potentiality of the proposed regression model.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

Watershed scale temporal stability of soil water content

The recognition of temporally stable locations with respect to soil water content is of importance for soil water management decisions, especially in sloping land of watersheds. Neutron probe soil water content (0 to 0.8 m), evaluated at 20 dates during a year in the Loess Plateau of China, in a 20 ha watershed dominated by Ust-Sandiic Entisols and Aeolian sandy soils, were used to define their temporal stability through two indices: the standard deviation of relative difference (SDRD) and the mean absolute bias error (MABE). Specific concerns were (a) the relationship of temporal stability with soil depth, (b) the effects of soil texture and land use on temporal stability, and (c) the spatial pattern of the temporal stability. Results showed that temporal stability of soil water content at 0.2 m was significantly weaker than those at the soil depths of 0.6 and 0.8 m. Soil texture can significantly (P<0.05) affect the stability of soil water content except for the existence of an insignificant difference between sandy loam and silt loam textures, while temporal stability of areas covered by bunge needlegrass land was not significantly different from those covered by korshinsk peashrub. Geostatistical analysis showed that the temporal stability was spatially variable in an organized way as inferred by the degree of spatial dependence index. With increasing soil depth, the range of both temporal stability indices showed an increasing trend, being 65.8-120.5 m for SDRD and 148.8-214.1 m for MABE, respectively. This study provides a valuable support for soil water content measurements for soil water management and hydrological applications on sloping land areas. (C) 2010 Elsevier B.V. All rights reserved.

Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

A generalized modified Weibull distribution for lifetime modeling

A four parameter generalization of the Weibull distribution capable of modeling a bathtub-shaped hazard rate function is defined and studied. The beauty and importance of this distribution lies in its ability to model monotone as well as non-monotone failure rates, which are quite common in lifetime problems and reliability. The new distribution has a number of well-known lifetime special sub-models, such as the Weibull, extreme value, exponentiated Weibull, generalized Rayleigh and modified Weibull distributions, among others. We derive two infinite sum representations for its moments. The density of the order statistics is obtained. The method of maximum likelihood is used for estimating the model parameters. Also, the observed information matrix is obtained. Two applications are presented to illustrate the proposed distribution. (C) 2008 Elsevier B.V. All rights reserved.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.