Ergonomic factors and production target evaluation in eucalyptus timber harvesting operations in mountainous terrains

There are several forest operations involved in Eucalyptus timber harvesting. This study was carried out during brush-cutting; tree felling, bucking, delimbing, piling and manual extraction operations, with the following objectives: a) analyzing, ergonomically, two systems of brush-cutting: one manual and the other semi-mechanized, using two different machines; b) ergonomically evaluating three different brands of pruner machines used in delimbing felled trees. c) determining the feasible target of productivity as a function of ergonomic factors relevant to establish the time of resting pauses for workers in manual and semi-mechanized timber harvesting systems in mountainous terrain. Brush-cutting, either manual or semimechanized, is an activity carried out prior to timber harvesting. It is usually a hard work, with low productivity when compared with mechanized systems. Pruner machines have been used by forest companies, due to the great possibilities to improve productivity, quality and the health of workers. Ergonomics is a discipline that promotes the adequacy of work to the physical and mental characteristics of human beings, seeking to design production systems and products considering relevant aspects, including social, organizational and environmental factors. Companies should consider the ergonomic factor in the determination of daily worker production targets.     

Designing the safety of healthcare. Participation of ergonomics to the design of cooperative systems in radiotherapy

This communication deals with the involvement of ergonomists in a research-action design process of a software platform in radiotherapy. The goal of the design project is to enhance patient safety by designing a workflow software that supports cooperation between professionals producing treatment in radiotherapy. The general framework of our approach is the ergonomics management of a design process, which is based in activity analysis and grounded in participatory design. Two fields are concerned by the present action: a design environment which is a participatory design process that involves software designers, caregivers as future users and ergonomists; and a reference real work setting in radiotherapy. Observations, semi-structured interviews and participatory workshops allow the characterization of activity in radiotherapy dealing with uses of cooperative tools, sources of variability and non-ruled strategies to manage the variability of the situations. This production of knowledge about work searches to enhance the articulation between technocentric and anthropocentric approaches, and helps in clarifying design requirements. An issue of this research-action is to develop a framework to define the parameters of the workflow tool, and the conditions of its deployment.     

Odd-Burr generalized family of distributions with some applications

We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.     

A Bayesian model for multiple change point to extremes,with application to environmental and financial data

Abrupt changes often occur for environmental and financial time series. Most often, these changes are due to human intervention. Change point analysis is a statistical tool used to analyze sudden changes in observations along the time series. In this paper, we propose a Bayesian model for extreme values for environmental and economic datasets that present a typical change point behavior. The model proposed in this paper addresses the situation in which more than one change point can occur in a time series. By analyzing maxima, the distribution of each regime is a generalized extreme value distribution. In this model, the change points are unknown and considered parameters to be estimated. Simulations of extremes with two change points showed that the proposed algorithm can recover the true values of the parameters, in addition to detecting the true change points in different configurations. Also, the number of change points was a problem to be considered, and the Bayesian estimation can correctly identify the correct number of change points for each application. Environmental and financial data were analyzed and results showed the importance of considering the change point in the data and revealed that this change of regime brought about an increase in the return levels, increasing the number of floods in cities around the rivers. Stock market levels showed the necessity of a model with three different regimes.     

Study of activities of postmen motorcyclists: a look at motorcycle accidents

This article presents the steps of transforming the material and organizational aspects in the work environment, beyond the social order for the proper development of activities in the Household Distribution Center, the Postmen Motorcyclists. The demand was made by managers from the accident records, establishing the need to identify the working conditions of postmen motorcyclists, regarding motorcycle accidents occurring on public roads. Method: Based on the characteristics of the steps required by the methodology, was necessary to realize internal and external observations, with the aim of identifying the dynamics of the accident and the collective dimensions of activity which requires a strategy for monitoring the work on the street.     

Influential observation in complex normal data for problems in allometry

Abstract

The aim of this paper is to investigate how some results related to the complex normal distribution are relevant in size and shape analysis. Our main focus is on the derivation of influential measures. In particular, Cook and Kullback–Leibler distances are combined with their respective asymptotic results as well as to an alternative process of defining cut-off points. Some numerical examples illustrate how these measures are used in practice. We perform an application to simulated and actual data. Results provide evidence that the methodology based on Kullback–Leibler distance outperforms one in terms of the Cook classic distance.     

Hayter and Tsui's test with double sampling for the vector mean of multivariate normal population

Abstract

In this paper, we introduce a version of Hayter and Tsui's statistical test with double sampling for the vector mean of a population under multivariate normal assumption. A study showed that this new test was more or as efficient than the well-known Hotelling's T² with double sampling. Some nice features of Hayter and Tsui's test are its simplicity of implementation and its capability of identifying the errant variables when the null hypothesis is rejected. Taking that into consideration, a new control chart called HTDS is also introduced as a tool to monitor multivariate process vector mean when using double sampling.     

Research on termites in urban areas: approaches and gaps

Urban Ecosystems - Termites comprise a large group of organisms in urban areas, and this leads us to believe that there is a comprehensive literature on the subject, sufficient for conducting a...     

Using a genetic algorithm-based RAROC model for the performance and persistence of the funds

Assisting fund investors in making better investment decisions when faced with market climate change is an important subject. For this purpose, we adopt a genetic algorithm (GA) to search for an optimal decay factor for an exponential weighted moving average model, which is used to calculate the value at risk combined with risk-adjusted return on capital (RAROC). We then propose a GA-based RAROC model. Next, using the model we find the optimal decay factor and investigate the performance and persistence of 31 Taiwanese open-end equity mutual funds over the period from November 2006 to October 2009, divided into three periods: November 2006–October 2007, November 2007–October 2008, and November 2008–October 2009, which includes the global financial crisis. We find that for three periods, the optimal decay factors are 0.999, 0.951, and 0.990, respectively. The rankings of funds between bull and bear markets are quite different. Moreover, the proposed model improves performance persistence. That is, a fund's past performance will continue into the future.     

A semiparametric Bayesian approach to extreme value estimation

This paper is concerned with extreme value density estimation. The generalized Pareto distribution (GPD) beyond a given threshold is combined with a nonparametric estimation approach below the threshold. This semiparametric setup is shown to generalize a few existing approaches and enables density estimation over the complete sample space. Estimation is performed via the Bayesian paradigm, which helps identify model components. Estimation of all model parameters, including the threshold and higher quantiles, and prediction for future observations is provided. Simulation studies suggest a few useful guidelines to evaluate the relevance of the proposed procedures. They also provide empirical evidence about the improvement of the proposed methodology over existing approaches. Models are then applied to environmental data sets. The paper is concluded with a few directions for future work.