LEGClust- a clustering algorithm based on layered entropic subgraphs.

Hierarchical clustering is a stepwise clustering method usually based on proximity measures between objects or sets of objects from a given data set. The most common proximity measures are distance measures. The derived proximity matrices can be used to build graphs, which provide the basic structure for some clustering methods. We present here a new proximity matrix based on an entropic measure and also a clustering algorithm (LEGClust) that builds layers of subgraphs based on this matrix, and uses them and a hierarchical agglomerative clustering technique to form the clusters. Our approach capitalizes on both a graph structure and a hierarchical construction. Moreover, by using entropy as a proximity measure we are able, with no assumption about the cluster shapes, to capture the local structure of the data, forcing the clustering method to reflect this structure. We present several experiments on artificial and real data sets that provide evidence on the superior performance of this new algorithm when compared with competing ones.     

Beam search algorithms for the single machine total weighted tardiness scheduling problem with sequence-dependent setups

In this paper, we consider the single machine weighted tardiness scheduling problem with sequence-dependent setups. We present heuristic algorithms based on the beam search technique. These algorithms include classic beam search procedures, as well as the filtered and recovering variants. Previous beam search implementations use fixed beam and filter widths. We consider the usual fixed width algorithms, and develop new versions that use variable beam and filter widths.     

A flexible semantic inference methodology to reason about user preferences in knowledge-based recommender systems

Recommender systems arose with the goal of helping users search in overloaded information domains (like e-commerce, e-learning or Digital TV). These tools automatically select items (commercial products, educational courses, TV programs, etc.) that may be appealing to each user taking into account his/her personal preferences. The personalization strategies used to compare these preferences with the available items suffer from well-known deficiencies that reduce the quality of the recommendations. Most of the limitations arise from using syntactic matching techniques because they miss a lot of useful knowledge during the recommendation process. In this paper, we propose a personalization strategy that overcomes these drawbacks by applying inference techniques borrowed from the Semantic Web. Our approach reasons about the semantics of items and user preferences to discover complex associations between them. These semantic associations provide additional knowledge about the user preferences, and permit the recommender system to compare them with the available items in a more effective way. The proposed strategy is flexible enough to be applied in many recommender systems, regardless of their application domain. Here, we illustrate its use in AVATAR, a tool that selects appealing audiovisual programs from among the myriad available in Digital TV.     

Synthesis of symmetric and asymmetric singly terminated elliptic ladder filters for multiplexing applications

An extension of the Cauer ladder development for synthesizing singly terminated filters with symmetric and asymmetric responses is presented. Basically, a driving‐point immittance including reactive constant elements is carried out in such a way that provides the transmission zeros. The reactive constant elements are introduced into the synthesis for two reasons. The first is to consider the possibility of the asymmetric position of transmission zeros in the real frequency axis. The second one is to obtain canonical forms, i.e. networks with the minimum number of elements in the case of symmetrical responses. To validate the proposed method, a filter with asymmetrical response has been synthesized, comparing different topologies for its use in multiplexers. This fact is illustrated with a Ku‐band elliptic response diplexer designed in H‐plane rectangular waveguide. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.     

Improved bushing models for general multibody systems and vehicle dynamics

The development and computational implementation, on a multibody dynamics environment, of a constitutive relation to model bushing elements associated with mechanical joints used in the models of road and rail vehicles is presented here. These elements are used to eliminate vibrations in vehicles, due to road irregularities, to allow small misalignment of axes, to reduce noise from the transmission, or to decrease wear of the mechanical joints. Bushings are made of a special rubber, used generally in energy dissipation, which presents a nonlinear viscoelastic relationship between the forces and moments and their corresponding displacements and rotations. In the methodology proposed here a finite element model of the bushing is developed in the framework of the finite element code ABAQUS to obtain the constitutive relations of displacement/rotation versus force/moment for different loading cases. The bushing is modeled in a multibody code as a nonlinear restrain that relates the relative displacements between the bodies connected with the joint reaction forces, and it is represented by a matrix constitutive relation. The basic ingredients of the multibody model are the same vectors and points relations used to define kinematic constraints in any multibody formulation. One particular, and relevant, characteristic of the formulation now presented is its ability to represent standard kinematic joints, clearance, and bushing joints just by defining appropriate constitutive relations. Spherical, revolution, cylindrical, and translational bushing joints are modeled, implemented, and demonstrated through the simulation of two multibody models of a road vehicle, one with perfect kinematic joints for the suspension sub-systems, and other with bushing joints. The tests conducted include an obstacle avoidance maneuver and a vehicle riding over bumps. It is shown that the bushing models for vehicle multibody models proposed here are accurate and computationally efficient so that they can be included in the vehicle models leading reliable simulations.     

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...     

Sensitive and Reversible Detection of Methanol and Water Vapor by In Situ Electrochemically Grown CuBTC MOFs on Interdigitated Electrodes

The in situ electrochemical growth of Cu benzene‐1,3,5‐tricarboxylate (CuBTC) metal–organic frameworks, as an affinity layer, directly on custom‐fabricated Cu interdigitated electrodes (IDEs) is described, acting as a transducer. Crystalline 5–7 µm thick CuBTC layers are grown on IDEs consisting of 100 electrodes with a width and a gap of both 50 µm and a height of 6–8 µm. These capacitive sensors are exposed to methanol and water vapor at 30 °C. The affinities show to be completely reversible with higher affinity toward water compared to methanol. For exposure to 1000 ppm methanol, a fast response is observed with a capacitance change of 5.57 pF at equilibrium. The capacitance increases in time followed diffusion‐controlled kinetics (k = 2.9 mmol s^?0.5 g^?1_CuBTC). The observed capacitance change with methanol concentration follows a Langmuir adsorption isotherm, with a value for the equilibrium affinity K _e = 174.8 bar^?1. A volume fraction f _MeOH = 0.038 is occupied upon exposure to 1000 ppm of methanol. The thin CuBTC affinity layer on the Cu‐IDEs shows fast, reversible, and sensitive responses to methanol and water vapor, enabling quantitative detection in the range of 100–8000 ppm.     

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.