Large space structures and systems in the space station era: A bibliography with indexes

Bibliographies and abstracts are listed for 1219 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1990 and December 31, 1990. The purpose is to provide helpful information to the researcher, manager, and designer in technology development and mission design according to system, interactive analysis and design, structural and thermal analysis and design, structural concepts and control systems, electronics, advanced materials, assembly concepts, propulsion, and solar power satellite systems

Advances in Possibilistic Clustering with Application to Hyperspectral Image Processing

Η ομαδοποίηση δεδομένων είναι μια εδραιωμένη μεθοδολογία ανάλυσης δεδομένων που έχει χρησιμοποιηθεί εκτενώς σε διάφορα πεδία εφαρμογών κατά τη διάρκεια των τελευταίων δεκαετιών. Η παρούσα διατριβή εστιάζει κυρίως στην ευρύτερη οικογένεια των αλγορίθμων βελτιστοποίησης κόστους και πιο συγκεκριμένα στους αλγόριθμους ομαδοποίησης με βάση τα ενδεχόμενα (Possibilistic c-Means, PCM). Συγκεκριμένα, αφού εκτίθενται τα αδύνατα σημεία τους, προτείνονται νέοι (batch και online) PCM αλγόριθμοι που αποτελούν επεκτάσεις των προηγουμένων και αντιμετωπίζουν τα αδύνατα σημεία των πρώτων. Οι προτεινόμενοι αλγόριθμοι ομαδοποίησης βασίζονται κυρίως στην υιοθέτηση των εννοιών (α) της προσαρμοστικότητας παραμέτρων (parameter adaptivity), οι οποίες στους κλασσικούς PCM αλγορίθμους παραμένουν σταθερές κατά την εκτέλεσή τους και (β) της αραιότητας (sparsity). Αυτά τα χαρακτηριστικά προσδίδουν νέα δυναμική στους προτεινόμενους αλγορίθμους οι οποίοι πλέον: (α) είναι (κατ' αρχήν) σε θέση να προσδιορίσουν τον πραγματικό αριθμό των φυσικών ομάδων που σχηματίζονται από τα δεδομένα, (β) είναι ικανοί να αποκαλύψουν την υποκείμενη δομή ομαδοποίησης, ακόμη και σε δύσκολες περιπτώσεις, όπου οι φυσικές ομάδες βρίσκονται κοντά η μία στην άλλη ή/και έχουν σημαντικές διαφορές στις διακυμάνσεις ή/και στις πυκνότητές τους και (γ) είναι εύρωστοι στην παρουσία θορύβου και ακραίων σημείων. Επίσης, δίνονται θεωρητικά αποτελέσματα σχετικά με τη σύγκλιση των προτεινόμενων αλγορίθμων, τα οποία βρίσκουν επίσης εφαρμογή και στους κλασσικούς PCM αλγορίθμους. Η δυναμική των προτεινόμενων αλγορίθμων αναδεικνύεται μέσω εκτεταμένων πειραμάτων, τόσο σε συνθετικά όσο και σε πραγματικά δεδομένα. Επιπλέον, οι αλγόριθμοι αυτοί έχουν εφαρμοστεί με επιτυχία στο ιδιαίτερα απαιτητικό πρόβλημα της ομαδοποίησης σε υπερφασματικές εικόνες. Τέλος, αναπτύχθηκε και μια μέθοδος επιλογής χαρακτηριστικών κατάλληλη για υπερφασματικές εικόνες.Clustering is a well established data analysis methodology that has been extensively used in various fields of applications during the last decades. The main focus of the present thesis is on a well-known cost-function optimization-based family of clustering algorithms, called Possibilistic C-Means (PCM) algorithms. Specifically, the shortcomings of PCM algorithms are exposed and novel batch and online PCM schemes are proposed to cope with them. These schemes rely on (i) the adaptation of certain parameters which remain fixed during the execution of the original PCMs and (ii) the adoption of sparsity. The incorporation of these two characteristics renders the proposed schemes: (a) capable, in principle, to reveal the true number of physical clusters formed by the data, (b) capable to uncover the underlying clustering structure even in demanding cases, where the physical clusters are closely located to each other and/or have significant differences in their variances and/or densities, and (c) immune to the presence of noise and outliers. Moreover, theoretical results concerning the convergence of the proposed algorithms, also applicable to the classical PCMs, are provided. The potential of the proposed methods is demonstrated via extensive experimentation on both synthetic and real data sets. In addition, they have been successfully applied on the challenging problem of clustering in HyperSpectral Images (HSIs). Finally, a feature selection technique suitable for HSIs has also been developed

The role of human capital in the private manufacturing sector productivity in the developing and transition economies.

This thesis principally seeks to provide empirical examination of the contribution of human capital, particularly in the form of education, to productivity at the micor level, through the lens of human capital and production theories, for a pooled sample of countries from the Middle East and North Africa (MENA), in comparison with both the Eastern Europe and Central Asia countries (ECA). This research mainly aims to establish substantive empirical evidence on the varying effects of human capital on growth, across regions. It also aims to investigate the role of human capital investment in the productivity gains, mainly through efficiency and labour productivity, in the formal private manufacturing sector, in the aforementioned regions. The thesis takes into account the variations in per capita income levels, based on the World Bank classifications of countries by income group. In addition, this research recognises and takes into account the heterogeneity which exists throughout the selected sample of countries. The main objective of evaluating the impact of human capital is to untangle the existing differences in the firms’ performance, partly on account of employing different workers with varying levels of education, with distinctive regional socio-economic changes, and different political conditions. The stochastic frontier analysis (SFA), as a fully parameterised model is used, in order to address and examine the determinants affecting production efficiencies, especially from a human capital point of view, and in the light of Vandenbussche, Aghion, and Meghir’s 2006 assumptions, on growth, distance to frontier, and composition of human capital, which remains untested in MENA and ECA at the firm-level. The SFA was applied following the approach of Caudill, Ford, and Gropper (1995) (CFG) by estimating and testing stochastic frontier production functions, assuming the presence of heteroscedasticity in the one-sided error term (inefficiency), and by following the approaches of Hadri (1999) for cross sectional data assuming the existence of heteroscedasticity in both error terms (the one-sided inefficiency term and the two-sided symmetric random noise), in order to obtain more accurate measures of technical efficiency. However, the rationale for this choice of the two different regions, is the heterogenous organisational structures, and the dissimilarities between production functions across economies in different developmental phases, which can be used as a suitable platform for analysing the distinctive effects of human capital composition on efficiency, and growth in each region in comparison with the other. In addition, the applied methodology also involves the incorporation of two matching methods consisting of a completely randomised experimental design, propensity score matching (PSM), and a fully blocked experimental design, Mahalanobis distance matching (MDM), using a cross-sectional firm level dataset, in order to examine the causal effects of formal training on productivity in MENA, and in ECA. The main conclusion of the empirical analysis suggests that highly-educated labour proxied by workers with tertiary education and those with university degree, appear to have a positive and statistically significant impact on efficiency in the two regions. Noting that the closer is the country to the frontier, the more important this level of human capital tends to be. As a country becomes closer to the frontier, it depends more on innovation and knowledge creation, which leads to the reallocation of labour from unskilled-complementary technology production activities, to skilled-prejudiced and technology-intensive activities. This result appears to confirm the association between high levels of human capital and growth, and chimes with the relevant literature about the link between human capital and growth in the developing and developed countries. It was also found that low-skilled labour component, denoted by workers who attended secondary school, seemed to have positive and statistically significant contribution to efficiency only in the less developed countries, such as MENA. This is due to the fact that the further the country is from the technological frontier, the more reliant the country becomes on imitation activities, and this seemed to corroborate the ideas posited in the literature about the sources of growth and the proximity to the world’s technological frontier. The low-skilled labour in the private manufacturing firms, in MENA, is positively associated with high levels of efficiency, and its impact appears to be significant, especially in high- technology firms. Although in the more affluent countries, such as the high-income economies in Eastern Europe, and the middle-income economies in ECA at large, the impact of secondary school workers gives the impression of being insignificant on efficiency. With respect to the intermediate-skilled labour, which is represented by the proportion of workers who have been trained in technical schools, or received on-the-job training, the maximum likelihood estimates point that their effects on efficiency have a propensity to be statistically insignificant, in MENA and ECA, in reducing the effects of inefficiency in firms’ performance. In fact, intermediate-skilled labour is found to have a positive and significant relationship with higher levels of inefficiency, especially in MENA. Put simply, it impedes efficiency improvements in the manufacturing firms, particularly, in the low and medium-technology plants in MENA. Furthermore, the effects of highly-skilled workers on efficiency were found to be positive and of a high level of significance in the low and medium-technology firms, and this is quite clear, especially, in the high-technology manufacturing firms in this region. All in all, the results of this study are in line, and compare well with the hypotheses of endogenous growth models of Lucas (1988) and Romer (1990), and with the assumptions of Benhabib and Spiegel (1994), that the economic growth is conditional on the human capital accumulation to improve efficiency and increase productivity in order to catch up with the technological frontier and shift it upward

Understanding and measuring the complex relationship between natural disasters and violence against children

Background:Violence against children is thought to increase after natural disasters, but evidence is limited. Methodological questions of how to measure possible associations are similarly unanswered. This thesis addresses these gaps by analyzing the relationship between natural disasters and violence against children, with emphasis on the 2010 Haitian earthquake,and by advancing design-based approaches for inference. Methods:The thesis is comprised of four related studies: (i) a systematic review and meta-analysis of the association between natural disasters and violence against children; (ii) a systematic review of pathways to violence; (iii) a matched-pairs analysis of violence against girls and boys after internal displacement from the 2010 Haitian earthquake; and (iv) a simulation comparing bias reduction properties and accuracy of matching designs,with sexual violence against girls displaced to a camp as the motivating example. The first two components synthesize background literature, the third component is empirical, and the fourth is methodological. Results: Themeta-analysis found no clear association or directional effect, albeit with a limited number of studies that exhibited methodological weaknesses. Further systematic review identified five pathways to violence. In delving into one aspect of exposure, internal displacement from the 2010 Haitian earthquake was not associated with long-term violence. Sensitivity analysis, however, indicated that sexual violence against girls and physical violence perpetrated by authority figures against boys were sensitive to Unobserved covariates. Full matching incorporating an instrumental variable can mitigate measured and unmeasured biases to increase the accuracy of inference. Conclusion:This thesis begins to elucidate and quantify the relationship between natural disasters and violence against children. The findings identify gaps in knowledge and pathways to violence for future study. Additional high-quality research is needed to unpack the complex relationship. The methods piloted in this thesis present promising tools, particularly after rapid-onset natural disasters and in resource scarce settings