Thesis (M.S.)--University of Wisconsin--Madison, 1983. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 344-348).

Thesis (M.S.)--University of Wisconsin--Madison, 1969. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--Ohio University, March, 1993. / Title from PDF t.p.

Colour forecasting is a sector of trend forecasting which is arguably the most important link in the product development process, yet little is known about it, the methodology behind its development or its accuracy. It is part of a global trend forecasting industry valued recently at $36bn, providing information which is developed commercially eighteen months to two years ahead of the season. Used throughout the garment supply chain, by the yarn and fibre manufacturers, the fabric mills, garment designers and retailers, it plays a pivotal role in the fashion and textile industry, but appears in many different forms. Colour forecasts were first commercially produced in 1917, but became more widely used during the 1970s, and in recent years digital versions of colour forecasts have become increasingly popular. The investigation aimed to establish the historical background of the industry, mindful of the considerable changes to fashion manufacturing and retailing in recent decades. For the purposes of the investigation, a period spanning 25 years was selected, from 1985 to 2010. In reviewing the available literature, and the methodologies currently used in developing forecasting information, it became clear that there was a view that the process is very intuitive, and thus a lack of in depth academic literature. This necessitated a considerable quantity of primary research in order to fill the gaps in the knowledge regarding the development, use and accuracy of colour forecasting. A mixed method approach to primary research was required to answer the aim of the thesis, namely to investigate how colour forecasts are compiled, and examine their use, influence and accuracy within the fashion and textiles industry, suggesting methods for developing more accurate forecasts in the future. Interviews were conducted with industry practitioners comprising forecasters, designers and retailers to better understand how colour was developed and used within industry. Two longitudinal studies were carried out with the two largest UK clothing retailers to map their development and use of colour palettes, and understand better how colour contributes to the critical path and supply chain. Two colour development meetings were observed, one with a commercial colour forecaster, the other with an industry association, and two colour archives were studied to establish whether or not any identifiable and predictable colour cycles existed. Data from the interviews and longitudinal studies were analysed using a grounded approach, and revealed some new insights into the influences upon the development of colour forecasts both commercially and from the retailer's perspective. The sell through rates of merchandise, EPOS analysis and range of practices between those interviewed and the two retailers studied provided an interesting insight into working practices and how colour forecasting information is changed when used by the retailers. It was found that a group of core colours existed, which were used season after season, and consistently demonstrated a high sell through rate, such as black, white, grey and navy. In order to establish whether or not colour cycles were consistently predictable in their repetition, two colour forecasting archives were assessed. If predictable colour cycles existed, they would be a useful tool in developing more accurate forecasts. Unfortunately this was not the case, as no clear colour cycles were found. However, the archive, together with evidence from the retailers demonstrated the 'lifecycle' of fashion colours was longer than expected, as they took time to phase in and out. It was concluded that in general the less fashion led brands used their own signature colours and were able to develop colour palettes far later in the product development timeline. This approach could be adopted more widely by retailers and designers as it was discovered that although accuracy rates for colour forecasts are generally accepted to be around 80%, the commercial forecasters provide colour update cards closer to the season where at least 40% of the colours are changed. Very early information, two years ahead of the season is no longer necessary in the contemporary fashion and textiles industry.

Dissertation (MCIS)--AUT University, 2009. / Includes bibliographical references. Also held in print (53 leaves : ill. ; 30 cm.) in the Archive at the City Campus (T 003 SHI)

Thesis (Ph.D.)--Baylor University, 2006. / Includes bibliographical references (p. 115-117).

Doctor of Philosophy / Department of Chemical Engineering / Bin Liu / In the course of mitigating our dependence on fossil energy, it has become an urgent issue to develop unconventional and innovative technologies based on renewable energy utilization for fuels and chemicals production. Due to the lack of fundamental understanding of catalytic behaviors of the novel chemical compounds involved, the task to design and engineer effective catalytic systems is extremely challenging and time-consuming. One central challenge is that an intricate balance among catalytic reactivity, selectivity, durability, and affordability must be achieved pertinent to any successful design. In this dissertation, density functional theory (DFT), coupled with modeling techniques derived from DFT, is employed to gain insights into molecular interactions between elusive intermediates and targeted functional catalytic materials for novel electrochemical and heterogeneous catalytic processes. Two case studies, i.e., electroreduction of furfural and step-catalysis for cyclic ammonia production, will be discussed to demonstrate the capability and utility of DFT-based theoretical modeling toolkits and strategies. Transition metal cathodes such as silver, lead, and nickel were evaluated for furfuryl alcohol and 2-methylfuran production through detailed DFT modeling. Investigation of the molecular mechanisms revealed that two intermediates, mh6 and mh7 from mono-hydrogenation of furfural, are the key intermediates that will determine the product formation activities and selectivities. Nickel breaks the trends from other metals as DFT calculations suggested the 2-methylfuran formation pathway is most likely different from other cathodes. In this work, the Brønsted–Evans–Polanyi relationship, derived from DFT energy barrier calculations, has been found to be particularly reliable and computationally efficient for C-O bond activation trend predictions. To obtain the solvation effect on the adsorptions of biomass-derived compounds (e.g., furfural and glycerol), influence of explicit solvent was probed using periodic DFT calculations. The adsorptions of glycerol and its dehydrogenation intermediates at the water-platinum surface were understood via various water–adsorbate, water–water, and water–metal interactions. Interestingly, the bond-order-based scaling relationship established in solvent-free environment is found to remain valid based on our explicit solvent models. In the second case study, step-catalysis that relies on manganese’s ability to dissociate molecular nitrogen and as a nitrogen carrier emerges as an alternative route for ammonia production to the conventional Haber-Bosch process. In this collaborative project, DFT was used as the primary tool to produce the mechanistic understanding of NH3 formation via hydrogen reduction on various manganese nitride systems (e.g., Mn4N and Mn2N). Both nickel and iron dopants have the potential to facilitate NH3 formation. A broader consideration of a wide range of nitride configurations revealed a rather complex pattern. Materials screening strategies, supported by linear scaling relationships, suggested the linear correlations between NHx (x=0, 1, 2) species must be broken in the development of optimal step catalysis materials. These fundamental findings are expected to significantly guide and accelerate the experimental material design. Overall, molecular modeling based on DFT has clearly demonstrated its remarkable value beyond just a validation tool. More importantly, its unique predictive power should be prized as an avenue for scientific advance through the fundamental knowledge in novel catalysts design.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 195-204). Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: Analogy, Design, Functional Modeling, Functional Reasoning, Knowledge Representation, Repertory Grid, SME, Structure Mapping Engine, AI in design. Includes bibliographical references (p.106).

Thesis (Ph. D.)--University of California, San Diego, 2006. / Title from first page of PDF file (viewed April 6, 2006). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 201-206).