MapScript: A map algebra programming language incorporating neighborhood analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.

A formal model of real-time program compilation

Program compilation can be formally defined as a sequence of equivalence-preserving transformations, or refinements, from high-level language programs to assembler code, Recent models also incorporate timing properties, but the resulting formalisms are intimidatingly complex. Here we take advantage of a new, simple model of real-time refinement, based on predicate transformer semantics, to present a straightforward compilation formalism that incorporates real-time constraints. (C) 2002 Elsevier Science B.V. All rights reserved.

A probabilistic analysis of Clostridium perfringens growth during food service operations

The purpose of this study was threefold: first, the study was designed to illustrate the use of data and information collected in food safety surveys in a quantitative risk assessment. In this case, the focus was on the food service industry; however, similar data from other parts of the food chain could be similarly incorporated. The second objective was to quantitatively describe and better understand the role that the food service industry plays in the safety of food. The third objective was to illustrate the additional decision-making information that is available when uncertainty and variability are incorporated into the modelling of systems. (C) 2002 Elsevier Science B.V. All rights reserved.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

The effectiveness of personalized smoking cessation strategies for callers to a Quitline service

Aim To assess the effectiveness of a program of computer-generated tailored advice for callers to a telephone helpline, and to assess whether it enhanced a series of callback telephone counselling sessions in aiding smoking cessation. Design Randomized controlled trial comparing: (1) untailored self-help materials; (2) computer-generated tailored advice only, and (3) computer-generated tailored advice plus callback telephone counselling. Assessment surveys were conducted at baseline, 3, 6 and 12 months. Setting Victoria, Australia. Participants A total of 1578 smokers who called the Quitline service and agreed to participate. Measurements Smoking status at follow-up; duration of cessation, if quit; use of nicotine replacement therapy; and extent of participation in the callback service. Findings At the 3-month follow-up, significantly more (chi(2)(2) = 16.9; P < 0.001) participants in the computer-generated tailored advice plus telephone counselling condition were not smoking (21%) than in either the computer-generated advice only (12%) or the control condition (12%). Proportions reporting not smoking at the 12-month follow-up were 26%, 23% and 22%, respectively (NS) for point prevalence, and for 9 months sustained abstinence; 8.2, 6.0, and 5.0 (NS). In the telephone counselling group, those receiving callbacks were more likely than those who did not to have sustained abstinence at 12 months (10.2 compared with 4.0, P < 0.05). Logistic regression on 3-month data showed significant independent effects on cessation of telephone counselling and use of NRT, but not of computer-generated tailored advice. Conclusion Computer-generated tailored advice did not enhance telephone counselling, nor have any independent effect on cessation. This may be due to poor timing of the computer-generated tailored advice and poor integration of the two modes of advice.

Use of Performance Measurement in the Public Sector: the case of the police service

Many public organisations have been under great pressure in recent years to increase the efficiency and transparency of outputs, to rationalise the use of public resources, and to increase the quality of service delivery. In this context, public organisations were encouraged to introduce the New Public Management reforms with the goal of improving the efficiency and effectiveness of the performance organisation through a new public management model. This new public management model is based on measurement by outputs and outcomes, a clear definition of responsibilities, the transparency and accountability of governmental activities, and on a greater value for citizens. What type of performance measurement systems are used in police services? Based on the literature, we see that multidimensional models, such as the Balanced Scorecard, are important in many public organisations, like municipalities, universities, and hospitals. Police services are characterised by complex, diverse objectives and stakeholders. Therefore, performance measurement of these public services calls for a specific analysis. Based on a nationwide survey of all police chiefs of the Portuguese police force, we find that employee performance measurement is the main form of measurement. Also, we propose a strategic map for the Portuguese police service.

MDAI: Model based Design in Automobile Industry

It is proposed a new approach based on a methodology, assisted by a tool, to create new products in the automobile industry based on previous defined processes and experiences inspired on a set of best practices or principles: it is based on high-level models or specifications; it is component-based architecture centric; it is based on generative programming techniques. This approach follows in essence the MDA (Model Driven Architecture) philosophy with some specific characteristics. We propose a repository that keeps related information, such as models, applications, design information, generated artifacts and even information concerning the development process itself (e.g., generation steps, tests and integration milestones). Generically, this methodology receives the users' requirements to a new product (e.g., functional, non-functional, product specification) as its main inputs and produces a set of artifacts (e.g., design parts, process validation output) as its main output, that will be integrated in the engineer design tool (e.g. CAD system) facilitating the work.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

Conceptual model for decomposing the value for the customer

Value has been defined in different theoretical contexts as need, desire, interest, standard /criteria, beliefs, attitudes, and preferences. The creation of value is key to any business, and any business activity is about exchanging some tangible and/or intangible good or service and having its value accepted and rewarded by customers or clients, either inside the enterprise or collaborative network or outside. “Perhaps surprising then is that firms often do not know how to define value, or how to measure it” (Anderson and Narus, 1998 cited by [1]). Woodruff echoed that we need “richer customer value theory” for providing an “important tool for locking onto the critical things that managers need to know”. In addition, he emphasized, “we need customer value theory that delves deeply into customer’s world of product use in their situations” [2]. In this sense, we proposed and validated a novel “Conceptual Model for Decomposing the Value for the Customer”. To this end, we were aware that time has a direct impact on customer perceived value, and the suppliers’ and customers’ perceptions change from the pre-purchase to the post-purchase phases, causing some uncertainty and doubts.We wanted to break down value into all its components, as well as every built and used assets (both endogenous and/or exogenous perspectives). This component analysis was then transposed into a mathematical formulation using the Fuzzy Analytic Hierarchy Process (AHP), so that the uncertainty and vagueness of value perceptions could be embedded in this model that relates used and built assets in the tangible and intangible deliverable exchange among the involved parties, with their actual value perceptions.

Logic programming and fuzzy Monte Carlo for distribution network reconfiguration

This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

A model for heterogeneous networks management and Performance evaluation

In general, modern networks are analysed by taking several Key Performance Indicators (KPIs) into account, their proper balance being required in order to guarantee a desired Quality of Service (QoS), particularly, cellular wireless heterogeneous networks. A model to integrate a set of KPIs into a single one is presented, by using a Cost Function that includes these KPIs, providing for each network node a single evaluation parameter as output, and reflecting network conditions and common radio resource management strategies performance. The proposed model enables the implementation of different network management policies, by manipulating KPIs according to users' or operators' perspectives, allowing for a better QoS. Results show that different policies can in fact be established, with a different impact on the network, e.g., with median values ranging by a factor higher than two.

A Model to Evaluate Vertical Handovers on JRRM

In a heterogeneous cellular networks environment, users behaviour and network deployment configuration parameters have an impact on the overall Quality of Service. This paper proposes a new and simple model that, on the one hand, explores the users behaviour impact on the network by having mobility, multi-service usage and traffic generation profiles as inputs, and on the other, enables the network setup configuration evaluation impact on the Joint Radio Resource Management (JRRM), assessing some basic JRRM performance indicators, like Vertical Handover (VHO) probabilities, average bit rates, and number of active users, among others. VHO plays an important role in fulfilling seamless users sessions transfer when mobile terminals cross different Radio Access Technologies (RATs) boundaries. Results show that high bit rate RATs suffer and generate more influence from/on other RATs, by producing additional signalling traffic to a JRRM entity. Results also show that the VHOs probability can range from 5 up to 65%, depending on RATs cluster radius and users mobility profile.

E-Learning as a shared service in shared services centers

Book Subtitle International Conference, CENTERIS 2010, Viana do Castelo, Portugal, October 20-22, 2010, Proceedings, Part II

Risk factors for cesarean section by category of health service

OBJECTIVE: To analyze the rate of cesarean section and differences in risk factors by category of health service, either public or private. METHODS: A cross-sectional study was carried out including all pregnant women in labor admitted to hospitals in the city of Rio Grande, Southern Brazil, between January 1 and December 31, 2007. A pre-coded and pre-tested questionnaire was used to collect on social, demographic, obstetric and newborn care information. Two regression models were constructed: one for public users and the other one for private ones. Poisson regression was used in each model in the multivariate analysis. Prevalence rates and 95% confidence intervals were calculated for each adjusted factor. RESULTS: The rate of cesarean section was 43% and 86% among public and private users. Sociodemographic factors and twin births have a more significant impact among public users as well as number of pregnancies (25% vs. 13% reduction in public and private users, respectively) and previous cesarean section (86% vs. 24% increase in public and private users, respectively). Prenatal care visits and hospital admissions affected the outcome only in women users of public services. CONCLUSIONS: Cesarean section rates were high in both groups studied, but it was twice as high among women cared in the private sector. Associated factors differ in magnitude by category of service used.