976 resultados para Selection criterion


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Project selection is a complex decision making process that is not merely influenced by the technical aspects of the project. Selection of road infrastructure projects in the Indonesian public sector is generally conducted at an organisational level, which involves multiple objectives, constraints and stakeholders. Hence, a deeper understanding of the various organisational drivers that impact on such decisions, in particular organisational culture, is much needed for improving decision-making processes as it has been posited by some researchers that organisational culture can become either an enabler, or a barrier, to the process. One part of the cultural assessment undertaken as part of the research, identifies and analyses the cultural types of relevant and involved organisations in the decision making process. The organisational culture assessment instrument (OCAI) of Cameron and Quinn (2011) was utilized in this study and the data was taken from three selected provinces in Indonesia. The results can facilitate the surveyed (and similar) organisations to improve their performance by moving towards a more appropriate cultural typology that is arguably better suited to their operations and to improving their organisational processes to more closely align with their organisational vision, mission and objectives.

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The favourable scaffold for bone tissue engineering should have desired characteristic features, such as adequate mechanical strength and three-dimensional open porosity, which guarantee a suitable environment for tissue regeneration. In fact, the design of such complex structures like bone scaffolds is a challenge for investigators. One of the aims is to achieve the best possible mechanical strength-degradation rate ratio. In this paper we attempt to use numerical modelling to evaluate material properties for designing bone tissue engineering scaffold fabricated via the fused deposition modelling technique. For our studies the standard genetic algorithm was used, which is an efficient method of discrete optimization. For the fused deposition modelling scaffold, each individual strut is scrutinized for its role in the architecture and structural support it provides for the scaffold, and its contribution to the overall scaffold was studied. The goal of the study was to create a numerical tool that could help to acquire the desired behaviour of tissue engineered scaffolds and our results showed that this could be achieved efficiently by using different materials for individual struts. To represent a great number of ways in which scaffold mechanical function loss could proceed, the exemplary set of different desirable scaffold stiffness loss function was chosen. © 2012 John Wiley & Sons, Ltd.

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Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

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The question "what causes variety in organisational routines" is of considerable interest to organisational scholars, and one to which this thesis seeks to answer. To this end an evolutionary theory of change is advanced which holds that the dynamics of selection, adaptation and retention explain the creation of variety in organisational routines. A longitudinal, multi-level, multi-case analysis is undertaken in this thesis, using multiple data collection strategies. In each case, different types of variety were identified, according to a typology, together with how selection, adaptation and retention contribute to variety in a positive or negative sense. Methodologically, the thesis makes a contribution to our understanding of variety, as certain types of variety only become evident when examined by specific types of research design. The research also makes a theoretical contribution by explaining how selection, adaptation and retention individually and collectively contribute to variety in organisational routines. Moreover, showing that routines could be stable, diverse, adaptive and dynamic at the same time; is a significant, and novel, theoretical contribution.

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Facial expression is an important channel of human social communication. Facial expression recognition (FER) aims to perceive and understand emotional states of humans based on information in the face. Building robust and high performance FER systems that can work in real-world video is still a challenging task, due to the various unpredictable facial variations and complicated exterior environmental conditions, as well as the difficulty of choosing a suitable type of feature descriptor for extracting discriminative facial information. Facial variations caused by factors such as pose, age, gender, race and occlusion, can exert profound influence on the robustness, while a suitable feature descriptor largely determines the performance. Most present attention on FER has been paid to addressing variations in pose and illumination. No approach has been reported on handling face localization errors and relatively few on overcoming facial occlusions, although the significant impact of these two variations on the performance has been proved and highlighted in many previous studies. Many texture and geometric features have been previously proposed for FER. However, few comparison studies have been conducted to explore the performance differences between different features and examine the performance improvement arisen from fusion of texture and geometry, especially on data with spontaneous emotions. The majority of existing approaches are evaluated on databases with posed or induced facial expressions collected in laboratory environments, whereas little attention has been paid on recognizing naturalistic facial expressions on real-world data. This thesis investigates techniques for building robust and high performance FER systems based on a number of established feature sets. It comprises of contributions towards three main objectives: (1) Robustness to face localization errors and facial occlusions. An approach is proposed to handle face localization errors and facial occlusions using Gabor based templates. Template extraction algorithms are designed to collect a pool of local template features and template matching is then performed to covert these templates into distances, which are robust to localization errors and occlusions. (2) Improvement of performance through feature comparison, selection and fusion. A comparative framework is presented to compare the performance between different features and different feature selection algorithms, and examine the performance improvement arising from fusion of texture and geometry. The framework is evaluated for both discrete and dimensional expression recognition on spontaneous data. (3) Evaluation of performance in the context of real-world applications. A system is selected and applied into discriminating posed versus spontaneous expressions and recognizing naturalistic facial expressions. A database is collected from real-world recordings and is used to explore feature differences between standard database images and real-world images, as well as between real-world images and real-world video frames. The performance evaluations are based on the JAFFE, CK, Feedtum, NVIE, Semaine and self-collected QUT databases. The results demonstrate high robustness of the proposed approach to the simulated localization errors and occlusions. Texture and geometry have different contributions to the performance of discrete and dimensional expression recognition, as well as posed versus spontaneous emotion discrimination. These investigations provide useful insights into enhancing robustness and achieving high performance of FER systems, and putting them into real-world applications.

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The inquiries to return predictability are traditionally limited to conditional mean, while literature on portfolio selection is replete with moment-based analysis with up to the fourth moment being considered. This paper develops a distribution-based framework for both return prediction and portfolio selection. More specifically, a time-varying return distribution is modeled through quantile regressions and copulas, using quantile regressions to extract information in marginal distributions and copulas to capture dependence structure. A preference function which captures higher moments is proposed for portfolio selection. An empirical application highlights the additional information provided by the distributional approach which cannot be captured by the traditional moment-based methods.

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The identification of the primary drivers of stock returns has been of great interest to both financial practitioners and academics alike for many decades. Influenced by classical financial theories such as the CAPM (Sharp, 1964; Lintner, 1965) and APT (Ross, 1976), a linear relationship is conventionally assumed between company characteristics as derived from their financial accounts and forward returns. Whilst this assumption may be a fair approximation to the underlying structural relationship, it is often adopted for the purpose of convenience. It is actually quite rare that the assumptions of distributional normality and a linear relationship are explicitly assessed in advance even though this information would help to inform the appropriate choice of modelling technique. Non-linear models have nevertheless been applied successfully to the task of stock selection in the past (Sorensen et al, 2000). However, their take-up by the investment community has been limited despite the fact that researchers in other fields have found them to be a useful way to express knowledge and aid decision-making...

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Drosophila serrata is a member of the montium group, which contains more than 98 species and until recently was considered a subgroup within the melanogaster group. This Drosophila species is an emerging model system for evolutionary quantitative genetics and has been used in studies of species borders, clinal variation and sexual selection. Despite the importance of D. serrata as a model for evolutionary research, our poor understanding of its genome remains a significant limitation. Here, we provide a first-generation gene-based linkage map and a physical map for this species. Consistent with previous studies of other drosophilids we observed strong conservation of genes within chromosome arms homologous with D. melanogaster but major differences in within-arm synteny. These resources will be a useful complement to ongoing genome sequencing efforts and QTL mapping studies in this species

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The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.

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Pronounced phenotypic shifts in island populations are typically attributed to natural selection, but reconstructing heterogeneity in long-term selective regimes remains a challenge. We examined a scenario of divergence proposed for species colonizing a new environment, involving directional selection with a rapid shift to a new optimum and subsequent stabilization. We provide some of the first empirical evidence for this model of evolution using morphological data from three timescales in an island bird, Zosterops lateralis chlorocephalus. In less than four millennia since separation from its mainland counterpart, a substantial increase in body size has occurred and was probably achieved in fewer than 500 generations after colonization. Over four recent decades, morphological traits have fluctuated in size but showed no significant directional trends, suggesting maintenance of a relatively stable phenotype. Finally, estimates of contemporary selection gradients indicated generally weak directional selection. These results provide a rare description of heterogeneity in long-term natural regimes, and caution that observations of current selection may be of limited value in inferring mechanisms of past adaptation due to a lack of constancy even over short time-frames.

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Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.

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A new decision-making tool that will assist designers in the selection of appropriate daylighting solutions for buildings in tropical locations has been previously proposed by the authors. Through an evaluation matrix that prioritizes the parameters that best respond to the needs of tropical climates (e.g. reducing solar gain and protection from glare) the tool determines the most appropriate devices for specific climate and building inputs. The tool is effective in demonstrating the broad benefits and limitations of the different daylight strategies for buildings in the tropics. However for thorough analysis and calibration of the tool, validation is necessary. This paper presents a first step in the validation process. RADIANCE simulations were conducted to compare simulation performance with the performance predicted by the tool. To this end, an office building case study in subtropical Brisbane, Australia, and five different daylighting devices including openings, light guiding systems and light transport systems were simulated. Illuminance, light uniformity, daylight penetration and glare analysis were assessed for each device. The results indicate the tool can appropriately rank and recommend daylighting strategies based on specific building inputs for tropical and subtropical regions, making it a useful resource for designers.

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Complexes of the type \[M(phen)3](PF6)2 (M = Ni(II), Fe(II), Ru(II) and phen = 1,10-phenanthroline) were found to co-crystallize to form molecular alloys (solid solutions of molecules) with general formula \[MAxMB1–x(phen)3](PF6)2·0.5H2O in which the relative concentrations of the metal complexes in the crystals closely match those in the crystallizing solution. Consequently, the composition of the co-crystals can be accurately predicted and controlled by modulating the relative concentrations of the metal complexes in the crystallizing solution. Although they are chemically and structurally similar, complexes of the type \[M(bipy)3](PF6)2 (M = Ni(II), Fe(II), Ru(II) and bipy = 2,2′-bipyridine) display markedly different behavior upon co-crystallization. In this case, the resulting co-crystals of general formula \[MAxMB1–x(bipy)3](PF6)2 have relative concentrations of the constituent complexes that are markedly different from the relative concentrations of the complexes initially present in the crystallizing solution. For example, when the nickel and iron complexes are co-crystallized from a solution containing a 50:50 ratio of each, the result is the formation of some crystals with a higher proportion of iron and others with a higher proportion of nickel. The relative concentrations of the metal complexes in the crystals can vary from those in the crystallizing solutions by as much as 15%. This result was observed for a range of combinations of metal complexes (Ni/Fe, Ni/Ru, and Fe/Ru) and a range of starting concentrations in the crystallizing solutions (90:10 through to 10:90 in 10% increments). To explain this remarkable result, we introduce the concept of “supramolecular selection”, which is a process driven by molecular recognition that leads to the partially selective aggregation of like molecules during crystallization.

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In this paper we present substantial evidence for the existence of a bias in the distribution of births of leading US politicians in favor of those that have been the oldest in their cohort at school. This “relative age effect” has been proven to influence performance at school and in sports,but evidence on its impact on people’s vocational success has been rare. We find a marked break in the density of birthdate of politicians using a maximum likelihood test and McCrary’s (2008) nonparametric test. We conjecture that being relatively old in a peer group may create long term advantages which can create a significant role in the ability to succeed in a highly competitive environment like the race for top political offices in the USA. The magnitude of the effect we estimate is larger than what most other studies on the relative age effect for a broader (adult) population find, but is in general in line with studies that look at populations in high-competition environments.

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Evaluating the validity of formative variables has presented ongoing challenges for researchers. In this paper we use global criterion measures to compare and critically evaluate two alternative formative measures of System Quality. One model is based on the ISO-9126 software quality standard, and the other is based on a leading information systems research model. We find that despite both models having a strong provenance, many of the items appear to be non-significant in our study. We examine the implications of this by evaluating the quality of the criterion variables we used, and the performance of PLS when evaluating formative models with a large number of items. We find that our respondents had difficulty distinguishing between global criterion variables measuring different aspects of overall System Quality. Also, because formative indicators “compete with one another” in PLS, it may be difficult to develop a set of measures which are all significant for a complex formative construct with a broad scope and a large number of items. Overall, we suggest that there is cautious evidence that both sets of measures are valid and largely equivalent, although questions still remain about the measures, the use of criterion variables, and the use of PLS for this type of model evaluation.