942 resultados para Projects Analysis


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This study describes the pedagogical impact of real-world experimental projects undertaken as part of an advanced undergraduate Fluid Mechanics subject at an Australian university. The projects have been organised to complement traditional lectures and introduce students to the challenges of professional design, physical modelling, data collection and analysis. The physical model studies combine experimental, analytical and numerical work in order to develop students’ abilities to tackle real-world problems. A first study illustrates the differences between ideal and real fluid flow force predictions based upon model tests of buildings in a large size wind tunnel used for research and professional testing. A second study introduces the complexity arising from unsteady non-uniform wave loading on a sheltered pile. The teaching initiative is supported by feedback from undergraduate students. The pedagogy of the course and projects is discussed with reference to experiential, project-based and collaborative learning. The practical work complements traditional lectures and tutorials, and provides opportunities which cannot be learnt in the classroom, real or virtual. Student feedback demonstrates a strong interest for the project phases of the course. This was associated with greater motivation for the course, leading in turn to lower failure rates. In terms of learning outcomes, the primary aim is to enable students to deliver a professional report as the final product, where physical model data are compared to ideal-fluid flow calculations and real-fluid flow analyses. Thus the students are exposed to a professional design approach involving a high level of expertise in fluid mechanics, with sufficient academic guidance to achieve carefully defined learning goals, while retaining sufficient flexibility for students to construct there own learning goals. The overall pedagogy is a blend of problem-based and project-based learning, which reflects academic research and professional practice. The assessment is a mix of peer-assessed oral presentations and written reports that aims to maximise student reflection and development. Student feedback indicated a strong motivation for courses that include a well-designed project component.

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The financial and economic analysis of investment projects is typically carried out using the technique of discounted cash flow (DCF) analysis. This module introduces concepts of discounting and DCF analysis for the derivation of project performance criteria such as net present value (NPV), internal rate of return (IRR) and benefit to cost (B/C) ratios. These concepts and criteria are introduced with respect to a simple example, for which calculations using MicroSoft Excel are demonstrated.

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This book chapter represents a synthesis of the work which started in my PhD and which has been the conceptual basis for all of my research since 1993. The chapter presents a method for scientists and managers to use for selecting the type of remotely sensed data to use to meet their information needs associated with a mapping, monitoring or modelling application. The work draws on results from several of my ARC projects, CRC Rainforest and Coastal projects and theses of P.Scarth , K.Joyce and C.Roelfsema.

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This paper discusses the financial and economic analysis of prevention of needlestick accidents related to Occupational Health and Safety projects and presents the application to a case study involving a Hospital.

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Work-related musculoskeletal disorders (WMSDs) are among the most costly health problems that society is facing today. Prevention involves investments and it is important for organizations to make a cost ebenefit analysis of ergonomic projects. Return on prevention is a recent concern in the domain of occupational safety and health (OSH). There are many studies concerning the return on the prevention of WMSDs, in terms of the benefits for the organization in which the preventive measures are implemented. However, it is also important to perform an analysis of the impact of each measure on society (externalities). A model to perform a financial and economic costebenefit analysis related to OSH projects was developed and it was applied in the case of the prevention of WMSDs in a Portuguese hospital. An analysis of the accidents and corresponding costs has been made in six of the services of the hospital. Financial and an economic costebenefit analysis have been made and the benefitecost ratio (B/C) has been calculated. While the B/C financial ratio, considering only the benefits to the hospital, is around 2, the economic B/C ratio, taking into account all the external benefits that have been quantified, is higher than 14. Relevance to industry: Both the economic and the financial B/C ratio are important support tools for decision makers in public and private organizations, helping them to define which preventive measures should be implemented, taking into account the costs involved and the resulting quantified benefits, for the organization, for the workers and for the society.

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ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

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In Portugal, especially starting in the 1970s, women’s studies had implications on the emergency of the concept of gender and the feminist criticism to the prevailing models about differences between sexes. Until then, women had been absent from scientific research both as subject and as object. Feminism brought more reflexivity to the scientific thinking. After the 25th of April 1974, because of the consequent political openness, several innovating themes of research emerged, together with new concepts and fields of study. However, as far as gender and science relationship is concerned, such studies especially concentrate on higher education institutions. The feminist thinking seems to have two main objectives: to give women visibility, on the one hand, and to denunciate men’s domain in the several fields of knowledge. In 1977, the “Feminine Commission” is created and since then it has been publishing studies on women’s condition and contributing to the enhancement of the reflection of female condition at all levels. In the 1980s, the growing feminisation of tertiary education (both of students and academics), favoured the development of women’s studies, especially on their condition within universities with a special focus on the glass ceiling, despite the lack of statistical data by gender, thus making difficult the analysis of women integration in several sectors, namely in educational and scientific research activities. Other agglutinating themes are family, social and legal condition, work, education, and feminine intervention on political and social movements. In the 1990s, Women Studies are institutionalised in the academic context with the creation of the first Master in Women Studies in the Universidade Aberta (Open University), in Lisbon. In 1999, the first Portuguese journal of women studies is created – “Faces de Eva”. Seminars, conferences, thesis, journals, and projects on women’s studies are more and more common. However, results and publications are not so divulgated as they should be, because of lack of comprehensive and coordinated databases. 2. Analysis by topics 2.1. Horizontal and vertical segregation Research questions It is one of the main areas of research in Portugal. Essentially two issues have been considered: - The analysis of vertical gender segregation in educational and professional fields, having reflexes on women professional career progression with special attention to men’s power in control positions and the glass ceiling. - The analysis of horizontal segregation, special in higher education (teaching and research) where women have less visibility than men, and the under-representation of women in technology and technological careers. Research in this area mainly focuses on description, showing the under-representation of women in certain scientific areas and senior positions. Nevertheless, the studies that analyze horizontal segregation in the field of education adopt a more analytical approach which focuses on the analysis of the mechanisms of reproduction of gender stereotypes, especially socialisation, influencing educational and career choices. 1

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Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

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The CDIO Initiative is an open innovative educational framework for engineering graduation degrees set in the context of Conceiving – Designing – Implementing – Operating real-world systems and products, which is embraced by a network of worldwide universities, the CDIO collaborators. A CDIO compliant engineering degree programme typically includes a capstone module on the final semester. Its purpose is to expose students to problems of a greater dimension and complexity than those faced throughout the degree programme as well as to put them in contact with the so-called real world, in opposition to the academic world. However, even in the CDIO context, there are barriers that separate engineering capstone students from the real world context of an engineering professional: (i) limited interaction with experts from diverse scientific areas; (ii) reduced cultural and scientific diversity within the teams; and (iii) lack of a project supportive framework to foster the complementary technical and non-technical skills required in an engineering professional. To address these shortcomings, we propose the adoption of the European Project Semester (EPS) framework, a one semester student centred international capstone programme offered by a group of European engineering schools (the EPS Providers) as part of their student exchange programme portfolio. The EPS package is organised around a central module – the EPS project – and a set of complementary supportive modules. Project proposals refer to open multidisciplinary real world problems and supervision becomes coaching. The students are organised in teams, grouping individuals from diverse academic backgrounds and nationalities, and each team is fully responsible for conducting its project. EPS complies with the CDIO directives on Design-Implement experiences and provides an integrated framework for undertaking capstone projects, which is focussed on multicultural and multidisciplinary teamwork, problem-solving, communication, creativity, leadership, entrepreneurship, ethical reasoning and global contextual analysis. As a result, we recommend the adoption of the EPS within CDIO capstone modules for the benefit of engineering students.

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The objective of the thesis is to analyze the behaviour of the wind flow when it is passing beside the forest. To complete this analysis, a parametric study was done based upon generalized situations. Some abacus have been made, which are related to forest and wind characteristics. The abacus were compared with a particular real case, namely Alexandrovo (Bulgaria), where it was concluded that the applicability of the abacus in projects with complex terrain is low and they must be used, from a quantitative point of view, for flat terrain, being hc the most important parameter.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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The Corporate world is becoming more and more competitive. This leads organisations to adapt to this reality, by adopting more efficient processes, which result in a decrease in cost as well as an increase of product quality. One of these processes consists in making proposals to clients, which necessarily include a cost estimation of the project. This estimation is the main focus of this project. In particular, one of the goals is to evaluate which estimation models fit the Altran Portugal software factory the most, the organization where the fieldwork of this thesis will be carried out. There is no broad agreement about which is the type of estimation model more suitable to be used in software projects. Concerning contexts where there is plenty of objective information available to be used as input to an estimation model, model-based methods usually yield better results than the expert judgment. However, what happens more frequently is not having this volume and quality of information, which has a negative impact in the model-based methods performance, favouring the usage of expert judgement. In practice, most organisations use expert judgment, making themselves dependent on the expert. A common problem found is that the performance of the expert’s estimation depends on his previous experience with identical projects. This means that when new types of projects arrive, the estimation will have an unpredictable accuracy. Moreover, different experts will make different estimates, based on their individual experience. As a result, the company will not directly attain a continuous growing knowledge about how the estimate should be carried. Estimation models depend on the input information collected from previous projects, the size of the project database and the resources available. Altran currently does not store the input information from previous projects in a systematic way. It has a small project database and a team of experts. Our work is targeted to companies that operate in similar contexts. We start by gathering information from the organisation in order to identify which estimation approaches can be applied considering the organization’s context. A gap analysis is used to understand what type of information the company would have to collect so that other approaches would become available. Based on our assessment, in our opinion, expert judgment is the most adequate approach for Altran Portugal, in the current context. We analysed past development and evolution projects from Altran Portugal and assessed their estimates. This resulted in the identification of common estimation deviations, errors, and patterns, which lead to the proposal of metrics to help estimators produce estimates leveraging past projects quantitative and qualitative information in a convenient way. This dissertation aims to contribute to more realistic estimates, by identifying shortcomings in the current estimation process and supporting the self-improvement of the process, by gathering as much relevant information as possible from each finished project.

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Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

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This thesis applied real options analysis to the valuation of an offshore oil exploration project, taking into consideration the several options typically faced by the management team of these projects. The real options process is developed under technical and price uncertainties, where it is considered that the mean reversion stochastic process is more adequate to describe the movement of oil price throught time. The valuation is realized to two case scenarios, being the first a simplified approach to develop the intuition of the used concepts, and the later a more complete cases that is resolved using both the binomial and trinomial processes to describe oil price movement. Real options methodology demonstrated to be capable of assessing and valuing the projects options, and of overcoming common capital budgeting methodologies flexibility limitation. The added value of the application of real options is evident, but so is the method's increased complexity, which adversely influence its widespread implementation.

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Mestrado em Ciências Actuariais