A Write-Based Solver for SAT Modulo the Theory of Arrays

The extensional theory of arrays is one of the most important ones for applications of SAT Modulo Theories (SMT) to hardware and software verification. Here we present a new T-solver for arrays in the context of the DPLL(T) approach to SMT. The main characteristics of our solver are: (i) no translation of writes into reads is needed, (ii) there is no axiom instantiation, and (iii) the T-solver interacts with the Boolean engine by asking to split on equality literals between indices. As far as we know, this is the first accurate description of an array solver integrated in a state-of-the-art SMT solver and, unlike most state-of-the-art solvers, it is not based on a lazy instantiation of the array axioms. Moreover, it is very competitive in practice, specially on problems that require heavy reasoning on array literals

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Adaptive optimization schemes for mobile VoIP applications Battery life and call quality aspects

In this thesis programmatic, application-layer means for better energy-efficiency in the VoIP application domain are studied. The work presented concentrates on optimizations which are suitable for VoIP-implementations utilizing SIP and IEEE 802.11 technologies. Energy-saving optimizations can have an impact on perceived call quality, and thus energy-saving means are studied together with those factors affecting perceived call quality. In this thesis a general view on a topic is given. Based on theory, adaptive optimization schemes for dynamic controlling of application's operation are proposed. A runtime quality model, capable of being integrated into optimization schemes, is developed for VoIP call quality estimation. Based on proposed optimization schemes, some power consumption measurements are done to find out achievable advantages. Measurement results show that a reduction in power consumption is possible to achieve with the help of adaptive optimization schemes.

Niche Differentiation and Fine-Scale Projections for Argentine Ants Based on Remotely Sensed Data

Modeling ecological niches of species is a promising approach for predicting the geographic potential of invasive species in new environments. Argentine ants (Linepithema humile) rank among the most successful invasive species: native to South America, they have invaded broad areas worldwide. Despite their widespread success, little is known about what makes an area susceptible - or not - to invasion. Here, we use a genetic algorithm approach to ecological niche modeling based on high-resolution remote-sensing data to examine the roles of niche similarity and difference in predicting invasions by this species. Our comparisons support a picture of general conservatism of the species' ecological characteristics, in spite of distinct geographic and community contexts

Minimization of the experimental workload for the prediction of pollutants propagation in rivers. Mathematical modelling and knowledge re-use

The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.

Engendering Group Support Based Foresight for Capital Intensive Manufacturing Industries - Case Paper and Steel Industry Scenarios by 2018

In recent times of global turmoil, the need for uncertainty management has become ever momentous. The need for enhanced foresight especially concerns capital-intensive industries, which need to commit their resources and assets with long-term planning horizons. Scenario planning has been acknowledged to have many virtues - and limitations - concerning the mapping of the future and illustrating the alternative development paths. The present study has been initiated to address both the need of improved foresight in two capital-intensive industries, i.e. the paper and steel industries and the imperfections in the current scenario practice. The research problem has been approached by engendering a problem-solving vehicle, which combines, e.g. elements of generic scenario process, face-to-face group support methods, deductive scenario reasoning and causal mapping into a fully integrated scenario process. The process, called the SAGES scenario framework, has been empirically tested by creating alternative futures for two capital-intensive industries, i.e. the paper and steel industries. Three scenarios for each industry have been engendered together with the identification of the key megatrends, the most important foreign investment determinants, key future drivers and leading indicators for the materialisation of the scenarios. The empirical results revealed a two-fold outlook for the paper industry, while the steel industry future was seen as much more positive. The research found support for utilising group support systems in scenario and strategic planning context with some limitations. Key perceived benefits include high time-efficiency, productivity and lower resource-intensiveness. Group support also seems to enhance participant satisfaction, encourage innovative thinking and provide the users with personalised qualitative scenarios.

Experimental analysis of optimization techniques on the road passenger transportation problem

Analyzing the state of the art in a given field in order to tackle a new problem is always a mandatory task. Literature provides surveys based on summaries of previous studies, which are often based on theoretical descriptions of the methods. An engineer, however, requires some evidence from experimental evaluations in order to make the appropriate decision when selecting a technique for a problem. This is what we have done in this paper: experimentally analyzed a set of representative state-of-the-art techniques in the problem we are dealing with, namely, the road passenger transportation problem. This is an optimization problem in which drivers should be assigned to transport services, fulfilling some constraints and minimizing some function cost. The experimental results have provided us with good knowledge of the properties of several methods, such as modeling expressiveness, anytime behavior, computational time, memory requirements, parameters, and free downloadable tools. Based on our experience, we are able to choose a technique to solve our problem. We hope that this analysis is also helpful for other engineers facing a similar problem

Optimization of methodology to analyze ascorbic and dehydroascorbic acid in vegetables

In this study, different solutions to extract vitamin C were tested. High-performance liquid chromatography was chosen and the conditions were based on isocratic elution in reverse phase column. Dehydroascorbic acid was determined indirectly after its reduction using dithiothreitol. The use of metaphosphoric acid to stabilize the vitamin C was shown to be required and it was necessary to neutralize the pH of the extract to apply dithiothreitol. The average recovery was 90% in collard and tomato samples. The presence of oil did not interfere in extraction and the methodology can be used to analyze stir fried vegetables.

Optimization of the carrot leaf dehydration aiming at the preservation of omega-3 fatty acids

The carrot leaf dehydration conditions in air circulation oven were optimized through response surface methodology (RSM) for minimizing the degradation of polyunsaturated fatty acids, particularly alpha-linolenic (LNA, 18:3n-3). The optimized leaf drying time and temperature were 43 h and 70 ºC, respectively. The fatty acids (FA) were investigated using gas chromatography equipped with a flame ionization detector and fused silica capillary column; FA were identified with standards and based on equivalent-chain-length. LNA and other FA were quantified against C21:0 internal standard. After dehydration, the amount of LNA, quantified in mg/100 g dry matter of dehydrated carrot leaves, were 984 mg.

Optimization of the use of carbon paste electrodes (CPE) for electrochemical study of the chalcopyrite

The use of carbon paste electrodes (CPE) of mineral sulfides can be useful for electrochemical studies to overcome problems by using massive ones. Using CPE-chalcopyrite some variables were electrochemically evaluated. These variables were: (i) the atmosphere of preparation (air or argon) of CPE and elapsed time till its use; (ii) scan rate for voltammetric measurements and (iii) chalcopyrite concentration in the CPE. Based on cyclic voltammetry, open-circuit potential and electrochemical impedance results the recommendations are: oxygen-free atmosphere to prepare and kept the CPE until around two ours, scan rates from 10 to 40 mV s-1, and chalcopyrite concentrations > 20%.

Production Cycle Optimization: Defining the Market Potential for a New Planning Tool

An optimization tool has been developed to help companies to optimize their production cycles and thus improve their overall supply chain management processes. The application combines the functionality that traditional APS (Advanced Planning System) and ARP (Automatic Replenishment Program) systems provide into one optimization run. A qualitative study was organized to investigate opportunities to expand the product’s market base. Twelve personal interviews were conducted and the results were collected in industry specific production planning analyses. Five process industries were analyzed to identify the product’s suitability to each industry sector and the most important product development areas. Based on the research the paper and the plastic film industries remain the most potential industry sectors at this point. To be successful in other industry sectors some product enhancements would be required, including capabilities to optimize multiple sequential and parallel production cycles, handle sequencing of complex finishing operations and to include master planning capabilities to support overall supply chain optimization. In product sales and marketing processes the key to success is to find and reach the people who are involved directly with the problems that the optimization tool can help to solve.

Optimization and practical implementation of ultrafast 2D NMR experiments

Ultrafast 2D NMR is a powerful methodology that allows recording of a 2D NMR spectrum in a fraction of second. However, due to the numerous non-conventional parameters involved in this methodology its implementation is no trivial task. Here, an optimized experimental protocol is carefully described to ensure efficient implementation of ultrafast NMR. The ultrafast spectra resulting from this implementation are presented based on the example of two widely used 2D NMR experiments, COSY and HSQC, obtained in 0.2 s and 41 s, respectively.

LOW COST ANALYZER FOR THE DETERMINATION OF PHOSPHORUS BASED ON OPEN-SOURCE HARDWARE AND PULSED FLOWS

The need for automated analyzers for industrial and environmental samples has triggered the research for new and cost-effective strategies of automation and control of analytical systems. The widespread availability of open-source hardware together with novel analytical methods based on pulsed flows have opened the possibility of implementing standalone automated analytical systems at low cost. Among the areas that can benefit from this approach are the analysis of industrial products and effluents and environmental analysis. In this work, a multi-pumping flow system is proposed for the determination of phosphorus in effluents and polluted water samples. The system employs photometric detection based on the formation of molybdovanadophosphoric acid, and the fluidic circuit is built using three solenoid micropumps. The detection is implemented with a low cost LED-photodiode photometric detection system and the whole system is controlled by an open-source Arduino Uno microcontroller board. The optimization of the timing to ensure the color development and the pumping cycle is discussed for the proposed implementation. Experimental results to evaluate the system behavior are presented verifying a linear relationship between the relative absorbance and the phosphorus concentrations for levels as high as 50 mg L-1.