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In the era of continuing development of electrical and computer technology, product design grow more complex and diversified. Design reuse and effective design integration thus become important ways to increase design productivity. For example, In system-on-chip designs, reusable silicon intellectual properties include micro processors, digital signal processing units, memories, bus designs, general design libraries, application-specific design libraries, and software design libraries. It is thus an important subject to develop, integrate, and reuse design libraries provided by different designers. In this thesis, we developed software design for our post research of attribute composition graph capable of representing integration organizations of design libraries. It includes software designs of attribute composition graph schema representation and editing, incremental composition organization instantiation based on macro definitions in an attribute composition graph schema, and design composition solving from existing constraint solver packages. With these functionalities, designers can effectively construct organizations of design libraries for intended application designs, and perform design reuse in real designs.

Design reuse and effective design integration is an important ways to increase design productivity. It is thus an important subject to develop, integrate and reuse design libraries provided by different designers. In this thesis, we developed software design of an instance graph expansion that can expand attribute composition graph instance from attribute composition graph schema. Designer can then effectively construct design organizations for application designs, and perform design reuse in real designs.

Understanding how consumers evaluate products is of great interest to market researchers. Different approaches focus on how consumers compare, combine or process attributes (Bettman, Luce and Payne 1998, 2008; Chen and Chaiken 1999; Cohen, Fishbein and Ahtola 1972). While attribute evaluation is clearly central to these approaches, what makes particular product attributes influential to consumers’ overall evaluation of the product is not entirely clear. One of the central goals of the current work is to examine why certain product attributes are appealing or unappealing, and to explore the implications of this for product evaluation research, including work on choice and persuasion, and more focused investigations on the role of trivial attributes. I structure this framework around two broad issues: First, I suggest that product evaluation is based on an attribute’s ability to fulfill a particular goal. Furthermore, I examine the specific processes by which activated goals influence the role of product features on the evaluation of the product itself. Specifically, I suggest that goals are more likely to influence the impact of product attributes on product evaluation when goals are activated and perceived to fit with the product. Second, I focus on three product related features within the consumption environment that are likely to activate certain goals, especially extra-consumption goals (i.e. goals that are not directly relevant to the function of the product, but that may nevertheless exert an important influence on product evaluation). Those aspects include the context in which the product is evaluated (e.g. choosing between multiple products versus evaluating an individual product), product category associations (e.g. fair trade and coffee), and even specific features of the product being evaluated (e.g. shampoo with “eco-friendly” ingredients). These aspects can activate goals that influence the role of the product’s specific features on overall evaluation. / Thesis (Ph.D, Management) -- Queen's University, 2010-11-29 16:55:13.751

In best-first top-down induction of decision trees, the best split is added in each step (e.g. the split that maximally reduces the Gini index). This is in contrast to the standard depth-first traversal of a tree. The resulting tree will be the same, just how it is built is different. The objective of this project is to investigate whether it is possible to determine an appropriate tree size on practical datasets by combining best-first decision tree growth with cross-validation-based selection of the number of expansions that are performed. Pre-pruning, post-pruning, CART-pruning can be performed this way to compare.

Ground Penetrating Radar (GPR) is a near surface geophysical method that has been used for applications including archaeological sites, groundwater contamination, and geological mapping. Though GPR has been used extensively, advancements on data processing had a great impact on data resolution. GPR is frequently used for shallow investigations because of the high resolution near the surface; however, it has limited depth of penetration and vertical bed resolution. Vertical resolution is proportional to frequency. The thickness of beds in the subsurface is conventionally resolved to one-fourth the wavelength of the central frequency. The vertical resolution at a central frequency of 200 MHz in a beach environment is approximately 17 cm; however, that value does not accurately represent fine-scale lamina and pinching out of beds, which can be an order magnitude or more than the current resolution. Complex trace analysis and spectral analysis have been used in seismic reflection for characterizing structures and stratigraphy. These "attributes" have been used to indicate hydrocarbon presence in industry. The same concept was applied to a theoretical GPR model and tested against actual data. The theoretical GPR model was created to simulate a case in which two ideal 0 degree phase Ricker wavelets merge. The wavelets constructively "add" together to create a composite wavelet with double amplitude. Applying a spectral analysis reveals that an attribute in the form of instantaneous phase and instantaneous frequency can be used to image the beds merging. The spectral analysis was applied to field data from North Padre Island National Seashore, Texas, to image "pinch-outs". Multiple survey arrays were collected using a 200 MHz frequency antenna to image internal dune structures. The results showed anomalous features at merging beds and contacts between interfaces. The results directly influence sedimentological and geomorphological interpretations of internal dune structure and can be used to better understand erosional processes in coastal sedimentary environments.

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Consumers are often confronted with incomplete product information. In such instances, they can eliminate the product from further consideration due to higher associated uncertainty or ask for more information. Alternatively, they can apply subjective theories about covariation to infer the value of missing attributes. This paper investigates the latter option in the context of sustainability and provides an in-depth exploration of consumers' inference formations. Drawing from rich qualitative data, it offers a conceptualization of the underlying relationships consumers use to infer product sustainability based on other product attributes. The study further assesses whether these findings can be captured in a quantifiable way. To this end, inferred sustainability is conceptualized as a formative second-order construct, thereby depicting the influence of inference-triggering product attributes. (authors' abstract)

In mature product markets competitive advantage is increasingly realised by the careful design and engineering of product attributes that emphasise a brand’s values. In the high-luxury automotive segment, user satisfaction appears to be particularly influenced by products that are perceived to be typical to the brand’s lineage. This research aims to explore the links between product specifications and the categorisation of the product as belonging to the brand, by studying the effect with the Bentley brand’s interiors. The research uses cognitive categorisation theory and related methodologies as a basis for understanding the cognitive processes that operate between the input of specific multisensory stimuli and assessments of typicality and therefore satisfaction. These processes are interpreted through Semantic Differentiation techniques in a number of studies of Bentley products and competitor vehicles. The results suggest that by identifying and defining a number of product properties, of varying importance, and measuring subject’s responses to them, brand-based categorisation effects can be visualised and quantified. The research investigates if these effects have been stable over time and finds that some patterns exist that might be used to predict how future products might be categorised. The benefits of the resulting assessment and measurement tool to the product development process appear to be at least two-fold; firstly, by informing the process, product specifications may be set and designs developed, that are considered more accurate, good and right for the brand, resulting in controlled development time and costs and increased consumer satisfaction. Secondly, by enabling the process, property strengths, weakness and competitive threats may be understood that facilitate experimental and actual design modifications to optimise brand distinctiveness.