Magnetic quadrupole doublet focusing system for high energy ions

A high energy focused ion beam microprobe using a doublet arrangement of short magnetic quadrupole lenses was used to focus 1-3 MeV protons to spot sizes of 1x1 microm2 and 1-4.5 MeV carbon and silicon ion beams to spot sizes of 1.5x1.5 microm2. The results presented clearly demonstrate that this simple doublet configuration can provide high energy microbeams for microanalysis and microfabrication applications.     

Experience report on the application of genetic algorithms to reduce costs of the software validation process in the automotive sector during an engine control unit project

Software Quality Journal - The number of electronic control units (ECU) installed in vehicles is increasingly high. Manufacturers must improve the software quality and reduce cost by proposing...     

Coupled temperature and moisture effects on the tensile behavior of strain hardening cementitious composites (SHCC) reinforced with PVA fibers

This paper reports the experimental findings on the tensile behavior of strain-hardening cement-based composites (SHCC). The composites were subjected to the combined effects of elevated temperatures and internal moisture condition. Uniaxial tensile tests on dumbbell-shaped SHCC specimens with in situ temperature control were performed at 22, 60 and 100 °C. In addition, the effect of the internal humidity of SHCC (95, 50, 20 and 0%) coupled to the elevated temperatures was investigated. It was shown that the tensile strength decreases and the strain capacity increases with an increase in temperature. The influence of the internal moisture conditions was more significant in high temperatures. The strain capacity reduced significantly with a decrease in the humidity level. The crack pattern of the SHCC specimens was determined. Furthermore, single fiber pullout tests were performed under the considered high temperatures condition. Finally, the results are discussed based on the thermogravimetry analysis of the PVA fiber, alterations on its microstructure and surface coating.     

A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams

This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings.     

Implementing enterprise resource planning systems: organizational performance and the duration of the implementation

This paper examines the impact of the duration of ERP implementation on firm performance both during and after implementation. Organizations choose either an accelerated implementation approach or a traditional (longer) implementation approach. The former approach gives the organization the advantage of speed, but the disadvantage of fitting its processes to that of a packaged (thus, undifferentiated from competitors) ERP. The latter approach allows the organization to redesign strategy and processes, and thus, search for ways to be unique from its competition. The study uses a regression model to capture the changes in various performance measures during and after implementation between firms that implemented the ERP, using the performance measure of a matched group of firms that did not implement an ERP as a benchmark/control sample, on the basis of the duration of the implementation. Financial data from Compustat, and data on start date and end date of ERP implementation between 1990 and 2005 for firms in the Oil and Gas industry was collected from an ERP vendor. Results show that measures such as return on sales improved after implementation. However, measures such as inventory turnover, which reflect operational benefits, improve during implementation. We find that accelerated implementation confers both operational and strategic benefits. This study highlights the strategic consequences of the different choices of implementation.     

Segmentation of the carotid intima-media region in B-mode ultrasound images

This paper proposes a new approach for the segmentation of both near-end and far-end intima-media regions of the common carotid artery in ultrasound images. The method requires minimal user interaction and is able to segment the near-end wall in arteries with large, hypoechogenic and irregular plaques, issues usually not considered previously due to the increased segmentation difficulty.     

A memetic algorithm for the multi-compartment vehicle routing problem with stochastic demands

The multi-compartment vehicle routing problem (MC-VRP) consists of designing transportation routes to satisfy the demands of a set of customers for several products that, because of incompatibility constraints, must be loaded in independent vehicle compartments. Despite its wide practical applicability the MC-VRP has not received much attention in the literature, and the few existing methods assume perfect knowledge of the customer demands, regardless of their stochastic nature. This paper extends the MC-VRP by introducing uncertainty on what it is known as the MC-VRP with stochastic demands (MC-VRPSD). The MC-VRPSD is modeled as a stochastic program with recourse and solved by means of a memetic algorithm. The proposed memetic algorithm couples genetic operators and local search procedures proven to be effective on deterministic routing problems with a novel individual evaluation and reparation strategy that accounts for the stochastic nature of the problem. The algorithm was tested on instances of up to 484 customers, and its results were compared to those obtained by a savings-based heuristic and a memetic algorithm (MA/SCS) for the MC-VRP that uses a spare capacity strategy to handle demand fluctuations. In addition to effectively solve the MC-VRPSD, the proposed MA/SCS also improved 14 best known solutions in a 40-problem testbed for the MC-VRP.     

Simple procedures of choice in multicriteria problems without precise information about the alternatives’ values

The additive model of multiattribute value theory is widely used in multicriteria choice problems. But often it is not easy to obtain precise values for the scaling weights or the alternatives’ value in each function. Several decision rules which require weaker information, such as ordinal information, have been proposed to select an alternative under these circumstances. We propose new decision rules and test them using Monte-Carlo simulation, considering that there is ordinal information both on the scaling weights and on the alternatives’ values. Results show the new rules constitute a good approximation. We provide guidelines about how to use these rules in a context of selecting a subset of the most promising alternatives, considering the contradictory objectives of keeping a low number of alternatives yet not excluding the best one.     

A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty

In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate the potential of the proposed multiobjective model and genetic algorithm.     

A framework for the definition of metamodels for Computer-Aided Software Engineering tools

Computer-Aided Software Engineering (CASE) tools support modeling-related activities in development projects. Given the variety of tools and functionalities, it is quite common to work with several tools in the same project. However, data cannot usually be exchanged between these tools without loss of information. Recent approaches address this model interchange problem using metamodels to characterize the involved information and transformations to export/import it. Nevertheless, most of these solutions focus on the abstract syntax of models. They fail to consider aspects such as the presentation of models or tool-specific information, which are either disregarded or represented in ad-hoc ways that make difficult their processing. In order to overcome these limitations, this paper introduces a framework to define metamodels of CASE tools and a process to carry out the model interchange using them. The proposed metamodels have a modular organization with several internal metamodels. Each of them is aimed at describing some specific information about content, structure and presentation for both models and tools. The paper illustrates this approach with a case study used for comparison with existing works for this problem.