Abstract

Abstract
Decision making is an important role performed by managers. This chapter will analyze the importance of information systems (IS) on the decision-making process at rural organizations in Portugal's Algarve region. Managers' perceptions were analyzed and compared with the decision-making process model proposed in this chapter, which was based on the models of Simon (1977) and Mintzberg, Raisinghani, and Theorêt (1976). This chapter will discuss the capacity of rural tourism organizations to solve problems, as well as review the time needed to solve problems through the use of IS. This chapter will conclude that IS in the organizational decision-making process is positively related to the identification of the decision-making problem and time needed to solve the problems. This investigation will allow other sectors the opportunity to discuss decision process models based on technology, information capability, and organizational competitiveness.

Abstract
CFD simulations are a fundamental engineering application, implying huge workloads, often with dynamic behaviour due to runtime mesh refinement. Parallel processing over heterogeneous distributed memory clusters is often used to process such workloads. The execution of dynamic workloads over a set of heterogeneous resources leads to load imbalances that severely impacts execution time, when static uniform load distribution is used. This paper proposes applying dynamic, heterogeneity aware, load balancing techniques within CFD simulations. nSharma, a software package that fully integrates with OpenFOAM, is presented and assessed. Performance gains are demonstrated, achieved by reducing busy times standard deviation among resources, i.e., heterogeneous computing resources are kept busy with useful work due to an effective workload distribution. To best of authors’ knowledge, nSharma is the first implementation and integration of heterogeneity aware load balancing in OpenFOAM and will be made publicly available in order to foster its adoption by the large community of OpenFOAM users.

Abstract

Abstract
Autoregressive Moving Average (ARMA) time series model fitting is a procedure often based on aggregate data, where parameter estimation plays a key role. Therefore, we analyze the effect of temporal aggregation on the accuracy of parameter estimation of mixed ARMA and MA models. We derive the expressions required to compute the parameter values of the aggregate models as functions of the basic model parameters in order to compare their estimation accuracy. To this end, a simulation experiment shows that aggregation causes a severe accuracy loss that increases with the order of aggregation, leading to poor accuracy.

Abstract
Experimenting is one of the basic tools for design and improvement of products and manufacturing processes. Experiments conducted in industrial conditions should marginally interfere with course of a studied process. These expectations are fulfilled in the best way by so-called passive experiments, in which data is gathered using records obtained from processes conducted in their natural environment and real conditions, without any alteration of set-up parameters. However, it is difficult to control interference originating from variability of studied factors during course of such experiments. That is why use of passive experiments in practice is limited. It is probably caused by distrust regarding credibility of obtained results. Aim of the paper is to compare results obtained from passive and active experiments, conducted in comparable conditions during a process of manufacturing of a selected product and presentation of guidelines for application of passive experiments, developed on the basis of the obtained results.