IT & C Projects Duration Assessment Based on Audit and Software Reengineering

This paper analyses the effect of applying the core elements of software engineering and reengineering, probabilistic simulations and system development auditing to software development projects. Our main focus is reducing software development project duration. Due to the fast changing economy, the need for efficiency and productivity is greater than ever. Optimal allocation of resources has proved to be the main element contributing to an increase in efficiency.Reengineering, audit, project duration assessment, Monte Carlo simulation

Creating Policy using Decision Support pattern for Software Project Management

Decision making for programming project management incorporates a fundamental part of compelling management. Decisions come from limitations considered over the meaning of a project. Decision making of this practice found with many difficulties went given elusive nature of programming tasks to the inadequacy of system model utilized. In this paper, a calculated multi-strategy recreation based system will be acquainted in a methodology with different cover levels of the decision structure over programming project management handle. The techniques utilized are incorporated towards a multi-strategy reproduction demonstrate. Each of These strategies only acknowledges particular part of programming project management. The system develops the way of decision making by a worldview which builds up the establishment for a key level understanding and strategic decision support for professionals. At the outcomes area, an ideal strategy for the structure will be exhibited

Uncertainty analysis in product service system: Bayesian network modelling for availability contract

There is an emerging trend of manufacturing companies offering combined products and services to customers as integrated solutions. Availability contracts are an apt instance of such offerings, where product use is guaranteed to customer and is enforced by incentive-penalty schemes. Uncertainties in such an industry setting, where all stakeholders are striving to achieve their respective performance goals and at the same time collaborating intensively, is increased. Understanding through-life uncertainties and their impact on cost is critical to ensure sustainability and profitability of the industries offering such solutions. In an effort to address this challenge, the aim of this research study is to provide an approach for the analysis of uncertainties in Product Service System (PSS) delivered in business-to-business application by specifying a procedure to identify, characterise and model uncertainties with an emphasis to provide decision support and prioritisation of key uncertainties affecting the performance outcomes. The thesis presents a literature review in research areas which are at the interface of topics such as uncertainty, PSS and availability contracts. From this seven requirements that are vital to enhance the understanding and quantification of uncertainties in Product Service System are drawn. These requirements are synthesised into a conceptual uncertainty framework. The framework prescribes four elements, which include identifying a set of uncertainties, discerning the relationships between uncertainties, tools and techniques to treat uncertainties and finally, results that could ease uncertainty management and analysis efforts. The conceptual uncertainty framework was applied to an industry case study in availability contracts, where each of the four elements was realised. This application phase of the research included the identification of uncertainties in PSS, development of a multi-layer uncertainty classification, deriving the structure of Bayesian Network and finally, evaluation and validation of the Bayesian Network. The findings suggest that understanding uncertainties from a system perspective is essential to capture the network aspect of PSS. This network comprises of several stakeholders, where there is increased flux of information and material flows and this could be effectively represented using Bayesian Networks

How much Detail is needed in Cost Estimation in an Economic Evaluation alongside a Clinical Trial to Optimise Evidence for Decisions?

Acquiring evidence to support decision making is expensive. Collecting resource use data alongside a randomised controlled clinical trial is particularly so due to the multidimensional nature of costs: different costs are incurred by different agencies with varying methods and systems to account for these. Trialists are faced with decisions over how to collect such data, in particular different ‘levels’ of detail are possible. For example, hospitalisations can be costed (1) on a top-down, per admission basis multiplied by a representative unit cost, (2) a bottom-up basis measuring every component of care such as nursing and medic time, investigations and other procedures and drugs used which are each multiplied by relevant unit costs, or (3) some intermediate level of aggregation. The top-down data will be less expensive to obtain but may be less accurate (biased and/or over- or under-estimation of uncertainty) compared with the bottom-up. I refer to these alternative methods as ‘data collection processes’. Currently such decisions are based on the judgement of the trialist(s). However, formal quantification of the added value of one data collection process versus another compared with the added cost would inform the efficient allocation of research resources. In this thesis I extend the use of value of information analysis to compare the incremental cost and benefit of one data process with another, further extending this to estimate the optimal mix of observations between two processes. Using an example dataset I find that the method is workable, requiring prior information on the relationship between the two processes which can be obtained from either a pilot or feasibility study or expert opinion. When incorporated with other concurrent developments in value of information analysis, the method has the potential to provide a decision analytic approach to the complete design of clinical trials

THE ROLE OF PROBABILISTIC INFORMATION ON AFFECTIVE PREDICTIONS: NEURAL AND SUBJECTIVE CORRELATES AS MODULATED BY INTOLERANCE OF UNCERTAINTY

Emotions have been recently reconsidered as interoceptive predictive models, “constructed” by the brain on the basis of contextual information and prior experience, with the aim to predict relevant stimuli or events, and to provide the organism with optimal resources for survival. Nevertheless, the specific mechanisms underlying the construction of affective predictions both at the neural and subjective experience level remain unclear. More specifically, both the role played by contextual information and prior experience on the one hand, and the potential interactions with dispositional characteristics such as Intolerance of Uncertainty (IU), which is considered a trans-diagnostic risk factor for affective disorders, on the other hand, have yet to be unraveled. The present thesis aimed to answer these open questions. As a first aim, we investigated how contextual information of different predictive value modulates the neural correlates of affective predictions construction. Second, we explored how prior probabilistic experience affects the construction of affective predictions at the subjective experience level. Third and last, we studied how individual differences in IU impact on the construction of affective predictions as a function of contextual information and prior experience. Taken together, this thesis contributes to untangling the dynamics of affective prediction construction at the neural and subjective experience level. Contextual information and prior experience were found to differently influence (depending on their predictive value), and to interact with IU, in shaping the neural correlates and the subjective experience of emotion along the construction of affective predictions. Thus, this work offers both a theoretical contribution to predictive models of emotion, by better clarifying the mechanisms subtending prediction construction at the neural and subjective experience levels, and potential clinical implications for the prevention and treatment of anxiety disorders, given the trans-diagnostic nature of IU as a risk factor for the development of affective psychopathology.Emotions have been recently reconsidered as interoceptive predictive models, “constructed” by the brain on the basis of contextual information and prior experience, with the aim to predict relevant stimuli or events, and to provide the organism with optimal resources for survival. Nevertheless, the specific mechanisms underlying the construction of affective predictions both at the neural and subjective experience level remain unclear. More specifically, both the role played by contextual information and prior experience on the one hand, and the potential interactions with dispositional characteristics such as Intolerance of Uncertainty (IU), which is considered a trans-diagnostic risk factor for affective disorders, on the other hand, have yet to be unraveled. The present thesis aimed to answer these open questions. As a first aim, we investigated how contextual information of different predictive value modulates the neural correlates of affective predictions construction. Second, we explored how prior probabilistic experience affects the construction of affective predictions at the subjective experience level. Third and last, we studied how individual differences in IU impact on the construction of affective predictions as a function of contextual information and prior experience. Taken together, this thesis contributes to untangling the dynamics of affective prediction construction at the neural and subjective experience level. Contextual information and prior experience were found to differently influence (depending on their predictive value), and to interact with IU, in shaping the neural correlates and the subjective experience of emotion along the construction of affective predictions. Thus, this work offers both a theoretical contribution to predictive models of emotion, by better clarifying the mechanisms subtending prediction construction at the neural and subjective experience levels, and potential clinical implications for the prevention and treatment of anxiety disorders, given the trans-diagnostic nature of IU as a risk factor for the development of affective psychopathology

Análisis de Correlaciones de Duraciones de Actividades en Proyectos de Túneles

In the area of Civil Engineering and Construction it is relevant to study the correlation between durations of different activities, in order to acquire information that allows optimizing performance of work cycles, as well as improving estimates of activity durations in future works. The data analyzed in this paper comes from activity cycles of tunneling works in Line 6 of Metro de Santiago. Once the correlations were obtained, one first goal was to propose the application of a statistical hypothesis test to determinate their level of confidence. A second goal was to present a formulation that employs these correlations to estimate the duration of an activity from a previous activity duration. The results from the first objective allow to perform comparative analysis depending on soil type, excavation pace and work shift, applying a level of confidence of 80%. It is observed that negative correlations can be associated to a better efficiency of the constructive process. The results from the second objective are validated through the application of the suggested formulation based on a bivariate normal distribution.En el rubro de la ingeniería civil y la construcción resulta de interés estudiar la correlación entre las duraciones de las distintas actividades, a fin de contar con información que permita optimizar los rendimientos de los ciclos de trabajo, lo mismo que mejorar las estimaciones de las duraciones de actividades para futuras obras. La información de duraciones de actividades proviene de ciclos de trabajo de la ejecución de túneles interestación de la Línea 6 del Metro de Santiago. Con las correlaciones obtenidas, un primer objetivo es proponer la aplicación de un estadístico de prueba para determinar su nivel de confianza. Un segundo objetivo es plantear una formulación que emplee estas correlaciones para estimar la duración de una actividad a partir de la duración de una actividad anterior. Los resultados del primer objetivo permiten realizar análisis comparativos según tipo de suelo, paso de excavación y turno, considerando un nivel de confianza del 80%. Se observa que correlaciones negativas se pueden asociar a una mayor eficiencia del proceso constructivo. Los resultados del segundo objetivo se reflejan mediante un ejemplo de aplicación de la formulación propuesta en base a la distribución normal bivariada

The Alcohol Hangover

The seeds and fruits (or their parts) of Iberoamerican crops have high nutritional and functional properties which could be utilized in a wide range of foods. The crops included in this book are amaranth (Amaranthus spp.), quinoa (Chenopodium quinoa), kañiwa (Chenopodium pallidicaule), chia (Salvia hispanica L.), Andean maize (Zea mays L.), moringa (Moringa oleifera), yvapuru (Plinia peruviana), kurugua (Sicana odorifera), sacha inchi (Plukenetia huayllabambana), camu camu (Myrciaria dubia), mango (Mangifera indica), tarwi (Lupinus mutabilis), peanut (Arachis hypogaea L.) and taro (Colocasia esculenta), all of them still underutilized. Their cultivation is low; nevertheless, in recent years, the worldwide demand for some of them has increased immensely, resulting in an increase in their production. The ancient Iberoamerican crops have been widely recognized for their nutritional value by food scientists and food producers because they contain high-quality proteins and large quantities of micronutrients such as minerals, vitamins and bioactive compounds. In addition, they are gluten-free, which makes them suitable for people suffering from various gluten intolerances. This book summarizes the large amount of investigations in this field in the last year and provides knowledge within all the relevant areas of food science. The editors hope that this book will contribute to an increased use of these products in human nutrition by consumers worldwide