Abstract
In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the MatSrn models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Abstract
A virtual enterprise (VE) is a temporary organisation that pools the core competencies of its member enterprises in order to exploit fast-changing market opportunities. Making successful collaborative partnerships is, in this context, a major challenge in today's competitive business environments. The success of such a 'virtual' organisation is strongly dependent on its composition, and the selection of partners becomes therefore a crucial issue. This problem is particularly difficult because of the uncertainties related to information, market dynamics, customer expectations and technology speed-up, with a strongly stochastic decision-making context. In this paper, a chance-constrained approach to rank alternative VE configurations in business environments with uncertainty, and vague and random information, is proposed. This approach is based on a two-stage model: a chance-constraint multi-objective directional Tabu Search metaheuristic, complemented by a 2-tuple fuzzy linguistic representation model. Preliminary computational results clearly demonstrate the potential of the approach for practical application.

Abstract

Abstract
The ability to select the most appropriate materials for a given application is the fundamental challenge faced by a design engineer. The objective of any material selection procedure is to identify appropriate selection criteria and to obtain the most appropriate combination of criteria in conjunction with requirements. Hence, selection of material is a multicriteria decision making problem. This study investigates and evaluates critical material selection criteria in a priority framework using the fuzzy Delphi-analytical hierarchy process method to overcome all shortcomings from AHP and Delphi methods that are common in material selection problem. 75 of the most important criteria for material selection have been collected from the literature. These criteria have been questioned in automobile interior design firms in Iran for car dashboard design. This ranking method would help product designers to decide on appropriate materials in a consistent method. Results indicate that "general" criteria such as availability, quality, risk, and technology are the most important criteria from the viewpoint of Iranian car manufacturers. Other criteria such as financial, technical, social and environmental, and sensorial criteria are relatively important in subsequent ranks.

Abstract

Abstract
Purpose– The purpose of this paper is to characterize the knowledge flow between companies and universities based on national and sectoral systems of innovation perspective. It is argued here that high-tech sectors can describe a knowledge flow mainly based on scientific research, while sectors with lower technological impact may establish relations based on technical needs.Design/methodology/approach– A case study research was conducted in the horticulture and aerospace sectors in Brazil. Thirteen interviews were performed with chief executive officer’s and academic researchers from both fields.Findings– Results demonstrated differences in technology development and knowledge infrastructure when comparing both sectors, reflecting the impacts of national and sectoral systems of innovation. The horticulture sector presented technological limitations due to restricted eating habits, logistics, knowledge development at universities and difficulties on the establishment of partnerships between local companies and Embrapa, the main public research centre. Such restrictions limit academic activities while companies look for research partnerships abroad. Space industry also has limited technological development due to international embargoes and lack of research alignment between companies and universities. Companies end up developing research activities internally, usually funded by governmental tenders.Research limitations/implications– The horticulture sector has limitations, as it is not the main agriculture area in science and technology applications. Future studies may analyse areas like soy beans, sugar cane and coffee, which may present differences specially regarding sectoral systems of innovation.Originality/value– The finding of this paper may influence the review of sectoral innovation policies, improving the development of local research activities which may be a source of valuable knowledge to companies. It also demonstrates the importance of the knowledge flow to improve sector’s technology level.