Artificial neural networks, so far, have not been used for designing modular cells. Therefore, Self-organizing neural network (SONN) is used in the present research to design minicell-based manufacturing system. Two previously developed methods were studied and implemented using SONN model. Results obtained are compared with previous results to analyze the effectiveness of SONN in designing minicells. A new method is then developed with the objective to design minicells more effectively and efficiently. Results of all three methods are compared using machine-count and materialhandling as performance measuring criteria to find out the best method

Several content-based interfaces for music collection exploration rely on Self-Organizing Maps (SOMs) to produce 2D or 3D visualizations of music spaces. In these visualizations, perceptually similar songs are clustered together. The positions of clusters containing similar songs, however, cannot be determined in advance due to particularities of the traditional SOM algorithm. In this thesis, I propose a variation on the traditional algorithm named anchoredSOM. This variation avoids changes in the positions of the aforementioned clusters. Moreover, anchoredSOM allows users to personalize the music space by choosing the locations of clusters containing per- ceptually similar tracks. This thesis introduces SoundAnchoring, an interface for music collection exploration featuring anchoredSOM. SoundAnchoring is evaluated by means of a user study. Results show that SoundAnchoring offers engaging ways to explore music collections and build playlists. / Graduate / 0984 / 0413 / leandro.collares@gmail.com

Form-finding in Architecture looks at processes in nature to discover a more correct way in which to organize building. It is a study into the capability of discovering optimum form, dynamic adaptability, and exposes a set of unique relationships not relevant to Architecture previously. The beauty of these objects does not have to be designed. It is an emergent property of natural form. However, the wonder lies not in aesthetics, but in the manner in which natural forms come into being seemingly without a plan, at a multitude of scales, and in a vast array of materials. Alone, pattern in nature opens a vast array of potentialities for the study into new methods of architectural design. It is important to note that this inquiry will not be into the aesthetics of self-organized pattern, but the mathematical and procedural processes of formation itself. This study forms a set of principles, methodologies and tools for structuring a full-scale form-finding inquiry through the self-organization of pattern in nature. Following this inquiry one should be able to apply the organizational principles of patterning in nature, specifically breakdown patterns, to inform the programmatic design and layout of shopping malls. The rules set forth outline the formation of breakdown patterns, and the ordering of shopping malls. Through the use of parametric modeling software and computer programming language, sets of digital models efficiently explore of the vast number of potential pattern organizations by mimicking their formation in digital space. Through computational scripting, digital models also reveal formation changes due to the adaptation to site, circulatory loads, and spatial distribution, while still maintaining the laws of pattern formation.

This research explored the processing and properties of PNCs using a polyfurfural alcohol (PFA) matrix. The precursor for PFA, furfuryl alcohol (FA) is sourced from feedstocks rich in hemicellulose, such as corn cobs, oat hulls and wood. To exploit FA as a polymerizable solvent, cellulose whiskers (CW) and montmorillonite clay (MMT) were used as the nanoparticle phase. Results from PNC processing show that CW and MMT can be dispersed in the PFA matrix by means of insitu polymerization, without the use of surfactants or dilution in solvents. Both CW and MMT nanoparticles catalyze the polymerization of furfuryl alcohol (FA). Moreover, the insitu intercalative polymerization of FA in the interlayer galleries of MMT leads to the complete exfoliation of the MMT in the PFA matrix. CW and MMT both function as effective matrix modifiers, increasing the thermal stability of PFA nanocomposites compared to pure PFA polymer. The increased thermal stability is seen as significant increases in the onset of degradation and in residual weight at high temperature. This research also explored the surface functionalization of Cu, Ni and Pt substrates by self-assembly of a range of difunctional linker molecules. Characterization by XPS and PM-IRRAS indicate that diisocyanides and dicarboxylic acids both form chemically "sticky" surfaces after self-assembly on Cu and Ni. Sticky surfaces may provide a means of increasing nanoparticle dispersion in metal nanocluster filled PNCs, by increasing their interaction with the matrix polymer. Another potential application for sticky surfaces on Cu is in the ongoing miniaturization of circuit boards. The functionalization of Cu bond pad substrates with linker molecules may provide an alternate means of bonding components to their bond pads, with higher placement accuracy compared to solder bumps.

The demand for imported fruit in China has increased dramatically since it first appeared in Chinese markets around 1993. Although imported fruit is much more expensive than domestically produced fruit and people’s income is much lower in China than in developed countries, imported fruit still attracts many willing buyers. Conventional concepts such as meeting basic needs or increasing consumer awareness of the importance of fresh fruit to a healthy lifestyle cannot adequately explain this phenomenon, as there is an abundance of fresh, cheap, local produce available in almost every Chinese market. There must be other factors influencing buying behaviour. To explore these factors and to examine the dynamics of the market for imported fruit, this research adopted a mixed qualitative-quantitative methodology guided by the paradigm of phenomenology. The research examined the characteristics of imported fruit itself, criteria imposed by Chinese buyers on these characteristics, the intended uses of imported fruit and their associated consumption values. To shed light on the possible influence of socio-economic factors, the research also compared buyers from two Chinese cities, Guangzhou and Urumqi. The former is one of the most developed cities in China and the latter is regarded as among the more backward and conservative cities in China. The research identified ten attributes that appeal to Chinese buyers. Six relate to the fruit’s physical attributes: that it has better appearance and packaging, lower chemical residues, better or different taste, and freshness. The remaining four relate to symbolic attributes associated with the fruit: that it represents achievement, wealth, personality and social status. Five intended uses of imported fruit were identified: for gifts, self-consumption, children, aged parents and patients. Four consumption values underlying these intentions were also identified: symbolism, concern for health, meeting basic needs and hedonism. However, the research revealed that no single combination of intended use and consumption value drives the demand for imported fruit in the Chinese market. Most frequently, it is a mix of hedonic and symbolic values behind a range of different intended uses that stimulates demand. Pursuing hedonic and symbolic values also leads to the visual quality of imported fruit generally being the most appealing attribute to Chinese buyers, a pattern common to both Guangzhou and Urumqi. These findings make a significant contribution to empirical knowledge about Chinese consumer behaviour. Results provide valuable insights into the interrelationships among product attributes, intended uses, consumption values and cultural values, and would give essential guidance to the development of strategies to market imported fruit in China. The research also examined limitations of current analytical approaches to the study of consumer behaviour. It demonstrated that approaches based on neural networks and fuzzy logic could be used independently or combined with conventional statistical methods to improve the explanation of consumer behaviour in this case. A comparison was carried out between the most popular form of neural networks (feedforward networks) and multivariate statistical methods in terms of their ability to predict behavioural intention through consumers’ attitudes towards products. Results demonstrated that neural networks were capable of capturing nonlinear aspects of complex relationships and producing better predictions than conventional statistical models. To explore consumer cognitive patterns, the research also compared K-means clustering with a Self-organizing Map (SOM) neural network in terms of the ability to cluster consumers on the basis of perceptions towards imported fruit attributes. Results indicate a superior outcome when K-means is used in conjunction with SOM in clustering analysis: using SOM to determine the ‘natural’ numbers of clusters and using K-means to do clustering. Finally, to quantitatively evaluate the impact of consumption values, this research develops a new approach that combines Means-end Chain theory with fuzzy logic theory. Given the global importance of the Chinese market, the successful application of neural networks and fuzzy logic in this study of the behaviour of Chinese consumers purchasing imported fruit could have wider ramifications. If the approach were proven in other applications, it could significantly improve the ability to understand the demand for consumer goods in China.

The understanding of the emergent behaviour of complex systems is probably one of the most intriguing challenges in modern theoretical physics. In the present Thesis we use novel data analysis techniques and numerical simulations in order to shed some light on the fundamental mechanisms involved in their dynamics. We divide the main core of the research into three parts, each of which address a specific, and formally well defined, issue. In the first part, we study the processes of self - organization and herding in the evolution of the stock market. The data analysis, carried out over the fluctuations of several international indices, shows an avalanche - like dynamics characterized by power laws and indicative of a critical state. Further evidence of criticality relates to the behaviour of the price index itself. In this case we observe a power law decline with superimposed embedded log - periodic oscillations which are possibly due to an intrinsic discrete scale invariance. A stochastic cellular automata, instead, is used to mimic an open stock market and reproduce the herding behaviour responsible for the large fluctuations observed in the price. The results underline the importance of the largest clusters of traders which, alone, can induce a large displacement between demand and supply and lead to a crash. The second part of the Thesis focuses on the role played by the complex network of interactions that is created among the elementary parts of the system itself. We consider, in particular, the influence of the so - called " scale - free " networks, where the distribution of connectivity follows a power law, on the antiferromagnetic Ising model and on a model of stochastic opinion formation. Novel features, not encountered on regular lattices, have been pointed out. In the former case a spin glass transition at low temperatures is present while, in the latter, the turbulent - like behaviour emerging from the model is found to be particularly robust against the indecision of the agents. The last part is left for a numerical investigation of an extremal dynamical model for evolution / extinction of species. We demonstrate how the mutual cooperation between them comes to play a fundamental role in the survival probability : a healthy environment can support even less fitted species. / Thesis (Ph.D.)--School of Chemistry and Physics, 2006.

The demand for imported fruit in China has increased dramatically since it first appeared in Chinese markets around 1993. Although imported fruit is much more expensive than domestically produced fruit and people’s income is much lower in China than in developed countries, imported fruit still attracts many willing buyers. Conventional concepts such as meeting basic needs or increasing consumer awareness of the importance of fresh fruit to a healthy lifestyle cannot adequately explain this phenomenon, as there is an abundance of fresh, cheap, local produce available in almost every Chinese market. There must be other factors influencing buying behaviour. To explore these factors and to examine the dynamics of the market for imported fruit, this research adopted a mixed qualitative-quantitative methodology guided by the paradigm of phenomenology. The research examined the characteristics of imported fruit itself, criteria imposed by Chinese buyers on these characteristics, the intended uses of imported fruit and their associated consumption values. To shed light on the possible influence of socio-economic factors, the research also compared buyers from two Chinese cities, Guangzhou and Urumqi. The former is one of the most developed cities in China and the latter is regarded as among the more backward and conservative cities in China. The research identified ten attributes that appeal to Chinese buyers. Six relate to the fruit’s physical attributes: that it has better appearance and packaging, lower chemical residues, better or different taste, and freshness. The remaining four relate to symbolic attributes associated with the fruit: that it represents achievement, wealth, personality and social status. Five intended uses of imported fruit were identified: for gifts, self-consumption, children, aged parents and patients. Four consumption values underlying these intentions were also identified: symbolism, concern for health, meeting basic needs and hedonism. However, the research revealed that no single combination of intended use and consumption value drives the demand for imported fruit in the Chinese market. Most frequently, it is a mix of hedonic and symbolic values behind a range of different intended uses that stimulates demand. Pursuing hedonic and symbolic values also leads to the visual quality of imported fruit generally being the most appealing attribute to Chinese buyers, a pattern common to both Guangzhou and Urumqi. These findings make a significant contribution to empirical knowledge about Chinese consumer behaviour. Results provide valuable insights into the interrelationships among product attributes, intended uses, consumption values and cultural values, and would give essential guidance to the development of strategies to market imported fruit in China. The research also examined limitations of current analytical approaches to the study of consumer behaviour. It demonstrated that approaches based on neural networks and fuzzy logic could be used independently or combined with conventional statistical methods to improve the explanation of consumer behaviour in this case. A comparison was carried out between the most popular form of neural networks (feedforward networks) and multivariate statistical methods in terms of their ability to predict behavioural intention through consumers’ attitudes towards products. Results demonstrated that neural networks were capable of capturing nonlinear aspects of complex relationships and producing better predictions than conventional statistical models. To explore consumer cognitive patterns, the research also compared K-means clustering with a Self-organizing Map (SOM) neural network in terms of the ability to cluster consumers on the basis of perceptions towards imported fruit attributes. Results indicate a superior outcome when K-means is used in conjunction with SOM in clustering analysis: using SOM to determine the ‘natural’ numbers of clusters and using K-means to do clustering. Finally, to quantitatively evaluate the impact of consumption values, this research develops a new approach that combines Means-end Chain theory with fuzzy logic theory. Given the global importance of the Chinese market, the successful application of neural networks and fuzzy logic in this study of the behaviour of Chinese consumers purchasing imported fruit could have wider ramifications. If the approach were proven in other applications, it could significantly improve the ability to understand the demand for consumer goods in China.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 155-158).

Thesis (M.S.)--University of Nevada, Reno, 2007. / "May, 2007." Includes bibliographical references (leaves 62-64). Online version available on the World Wide Web. Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2007]. 1 microfilm reel ; 35 mm.

Thesis (M.C.S.)--Carleton University, 2004. / Includes bibliographical references (p. 127-131). Also available in electronic format on the Internet.