A Multicriteria Decision Support Methodology for Annual Rehabilitation Programs of Water Networks

Abstract:   This article provides an overview of a multicriteria decision support methodology for annual rehabilitation programs of water networks. A first set of criteria is formulated for the purpose of comparing and ranking rehabilitation projects. Each proposed criterion is a measure of a particular impact of the condition of a pipe. The ELECTRE TRI method is implemented for defining rehabilitation priorities . Two reference profiles are used to define the limits of three categories associated with three increasing priority levels. With these two reference profiles, applying the ELECTRE TRI method to an asset stock ( a set of pipes that are candidates for rehabilitation ) means assigning each pipe to one of six possible priority groups. A second set of criteria, based on the concept of efficiency, is proposed for comparing alternative rehabilitation programs ( subsets of the asset stock ).     

BRAF Gene and Melanoma: Back to the Future

As widely acknowledged, 40–50% of all melanoma patients harbour an activating BRAF mutation (mostly BRAF V600E). The identification of the RAS–RAF–MEK–ERK (MAP kinase) signalling pathway and its targeting has represented a valuable milestone for the advanced and, more recently, for the completely resected stage III and IV melanoma therapy management. However, despite progress in BRAF-mutant melanoma treatment, the two different approaches approved so far for metastatic disease, immunotherapy and BRAF+MEK inhibitors, allow a 5-year survival of no more than 60%, and most patients relapse during treatment due to acquired mechanisms of resistance. Deep insight into BRAF gene biology is fundamental to describe the acquired resistance mechanisms (primary and secondary) and to understand the molecular pathways that are now being investigated in preclinical and clinical studies with the aim of improving outcomes in BRAF-mutant patients.     

A Survey of Optical Flow Techniques for Robotics Navigation Applications

Optical flow has been widely used by insects and birds to support navigation functions. Such information has appealing capabilities for application to ground and aerial robots, especially for navigation and collision avoidance in urban or indoor areas. The purpose of this paper is to provide a survey of existing optical flow techniques for robotics navigation applications. Detailed comparisons are made among different optical-flow-aided navigation solutions with emphasis on the sensor hardware as well as optical flow motion models. A summary of current research status and future research directions are further discussed.     

Probabilistic consensus clustering using evidence accumulation

Machine Learning - Clustering ensemble methods produce a consensus partition of a set of data points by combining the results of a collection of base clustering algorithms. In the evidence...     

Use of scanning probe microscopy to study the evolution of nanometer sized liquid structures

The evolution of the profile of nanometer sized water drops on a mica surface has been studied through hydration scanning probe microscopy. A time range from a few seconds down to a fraction of millisecond after the formation of the drop has been explored. This high time resolution has been obtained by sampling a series of statistically equivalent drops. This approach also avoids any probe interference during the drop evolution process.     

Empirical evaluation of an educational game on software measurement

Software measurement is considered important in improving the software process. However, teaching software measurement remains a challenging issue. Although, games and simulations are regarded powerful tools for learning, their learning effectiveness is not rigorously established. This paper describes the results of an explorative study to investigate the learning effectiveness of a game prototype on software measurement in order to make an initial judgment about its potential as an educational tool as well as to analyze its appropriateness, engagement and strengths & weaknesses as guidance for further evolution. Within the study, a series of experiments was conducted in parallel in three master courses in Brazil. Results of the study reveal that the participants consider the content and structure of the game appropriate, but no indication for a significant difference on learning effectiveness could be shown.

Questionnaire-based variability modeling for system configuration

Variability management is a recurrent issue in systems engineering. It arises for example in enterprise systems, where modules are configured and composed to meet the requirements of individual customers based on modifications to a reference model. It also manifests itself in the context of software product families, where variants of a system are built from a common code base. This paper proposes an approach to capture system variability based on questionnaire models that include order dependencies and domain constraints. The paper presents analysis techniques to detect circular dependencies and contradictory constraints in questionnaire models, as well as techniques to incrementally prevent invalid configurations by restricting the space of allowed answers to a question based on previous answers. The approach has been implemented as a toolset and has been used in practice to capture configurable process models for film post-production.

Optimal-tuning PID control of adaptive materials for structural efficiency

The objective of this paper was solving the optimization problem of lightweight stiffened structures modelled as a two-dimensional domain in an efficient computational way. The underlying premise was that mass should be distributed in an efficient way, so as to use a minimum amount of material to accomplish the mechanical function. This premise was expressed as a global, multi-objective optimization problem in which stiffness and mass were conflicting objectives. Alternative local evolution rules were implemented to update mass density or Young’s modulus at each step of the iterative procedure. The solution of the structural optimization problem was accomplished by a novel automatic procedure consisting of two consecutive stages of control and optimization. In the first stage of Proportional Integral Derivative (PID) control gains were manually selected whereas in the second stage the finding of optimal values of control gains, target, and cost indices was allowed. In this study a bone-like material was adopted and a thin slab was analysed as a sample problem.     

Graph-based quadratic optimization: A fast evolutionary approach

Quadratic optimization lies at the very heart of many structural pattern recognition and computer vision problems, such as graph matching, object recognition, image segmentation, etc., and it is therefore of crucial importance to devise algorithmic solutions that are both efficient and effective. As it turns out, a large class of quadratic optimization problems can be formulated in terms of so-called “standard quadratic programs” (StQPs), which ask for finding the extrema of a quadratic polynomial over the standard simplex. Computationally, the standard approach for attacking this class of problems is to use replicator dynamics, a well-known family of algorithms from evolutionary game theory inspired by Darwinian selection processes. Despite their effectiveness in finding good solutions in a variety of applications, however, replicator dynamics suffer from being computationally expensive, as they require a number of operations per step which grows quadratically with the dimensionality of the problem being solved. In order to avoid this drawback, in this paper we propose a new population game dynamics (InImDyn) which is motivated by the analogy with infection and immunization processes within a population of “players.” We prove that the evolution of our dynamics is governed by a quadratic Lyapunov function, representing the average population payoff, which strictly increases along non-constant trajectories and that local solutions of StQPs are asymptotically stable (i.e., attractive) points. Each step of InImDyn is shown to have a linear time/space complexity, thereby allowing us to use it as a more efficient alternative to standard approaches for solving StQPs and related optimization problems. Indeed, we demonstrate experimentally that InImDyn is orders of magnitude faster than, and as accurate as, replicator dynamics on various applications ranging from tree matching to image registration, matching and segmentation.