The study of multi-phase diffusion in three-component metallic systems

"This report was prepared by University of Florida, Gainesville, Florida, under USAF Contract no. F 33615-67-C-1227."

HUD rehabilitation energy guidelines for multi-family dwellings /

"September 1996."

Air pollution exposure and novel biomarkers of inflammation and cardiac stress in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Thesis (Master's)--University of Washington, 2016-06

Mode Localization in a Nearly Cyclic Symmetric System

Thesis (Ph.D.)--University of Washington, 2016-06

Minimum description length, regularisation and multi-modal data

Relationships between clustering, description length, and regularisation are pointed out, motivating the introduction of a cost function with a description length interpretation and the unusual and useful property of having its minimum approximated by the densest mode of a distribution. A simple inverse kinematics example is used to demonstrate that this property can be used to select and learn one branch of a multi-valued mapping. This property is also used to develop a method for setting regularisation parameters according to the scale on which structure is exhibited in the training data. The regularisation technique is demonstrated on two real data sets, a classification problem and a regression problem.

Minimum description length, regularisation and multi-modal data

Conventional feed forward Neural Networks have used the sum-of-squares cost function for training. A new cost function is presented here with a description length interpretation based on Rissanen's Minimum Description Length principle. It is a heuristic that has a rough interpretation as the number of data points fit by the model. Not concerned with finding optimal descriptions, the cost function prefers to form minimum descriptions in a naive way for computational convenience. The cost function is called the Naive Description Length cost function. Finding minimum description models will be shown to be closely related to the identification of clusters in the data. As a consequence the minimum of this cost function approximates the most probable mode of the data rather than the sum-of-squares cost function that approximates the mean. The new cost function is shown to provide information about the structure of the data. This is done by inspecting the dependence of the error to the amount of regularisation. This structure provides a method of selecting regularisation parameters as an alternative or supplement to Bayesian methods. The new cost function is tested on a number of multi-valued problems such as a simple inverse kinematics problem. It is also tested on a number of classification and regression problems. The mode-seeking property of this cost function is shown to improve prediction in time series problems. Description length principles are used in a similar fashion to derive a regulariser to control network complexity.

Classification and contextual enhancement of remotely sensed data

The aims of the project were twofold: 1) To investigate classification procedures for remotely sensed digital data, in order to develop modifications to existing algorithms and propose novel classification procedures; and 2) To investigate and develop algorithms for contextual enhancement of classified imagery in order to increase classification accuracy. The following classifiers were examined: box, decision tree, minimum distance, maximum likelihood. In addition to these the following algorithms were developed during the course of the research: deviant distance, look up table and an automated decision tree classifier using expert systems technology. Clustering techniques for unsupervised classification were also investigated. Contextual enhancements investigated were: mode filters, small area replacement and Wharton's CONAN algorithm. Additionally methods for noise and edge based declassification and contextual reclassification, non-probabilitic relaxation and relaxation based on Markov chain theory were developed. The advantages of per-field classifiers and Geographical Information Systems were investigated. The conclusions presented suggest suitable combinations of classifier and contextual enhancement, given user accuracy requirements and time constraints. These were then tested for validity using a different data set. A brief examination of the utility of the recommended contextual algorithms for reducing the effects of data noise was also carried out.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

Integrated manufacturing systems design in a multi-product company

Using a hydraulic equipment manufacturing plant as the case study, this work explores the problems of systems integration in manufacturing systems design, stressing the behavioural aspects of motivation and participation, and the constraints involved in the proper consideration of the human sub-system. The need for a simple manageable modular organisation structure is illustrated, where it is shown, by reference to systems theory, how a business can be split into semi-autonomous operating units. The theme is the development of a manufacturing system based on an analysis of the business, its market, product, technology and constraints, coupled with a critical survey of modern management literature to develop an integrated systems design to suit a specific company in the current social environment. Society currently moves through a socio-technical revolution with man seeking higher levels of motivation. The transitory environment from an autocratic/paternalistic to a participative operating mode demands systems parameters only found to a limited extent in manufacturing systems today. It is claimed, that modern manufacturing systems design needs to be based on group working, job enrichment, delegation of decision making and reduced job monotony. The analysis shows how negative aspects of cellular manufacture such as lack of flexibility and poor fixed asset utilisation are relatively irrelevant and misleading in the broader context of the need to come to terms with the social stresses imposed on a company operating in the industrial environment of the present and the immediate future.

Intra-cavity dynamics in high power mode-locked fiber lasers

A theoretical model allows for the characterization and optimization of the intra-cavity pulse evolutions in high-power fiber lasers. Multi-parameter analysis of laser performance can be made at a fraction of the computational cost.

Disentangle contextual and permanent individual motivations:an application to shopping behavior

Past studies resulted in conflicting definitions of consumer motivation. On the one hand, motivations are seen as the consumer’s characteristics that shape her general behavior (motivational trait). On the other hand, they are seen as contextual variables representing the reason why the individual is behaving specific to today’s context (motivational state). The objective of this research is to stress the difference between these two concepts and to understand the impact of each on consumer behavior. We applied our empirical study to shopping motivations; our results show a strong interaction between motivational trait and motivational state. Problem and Hypothesis On the one hand, Westbrook and Black (1985) consider shopping motivations as individual permanent characteristics. This concept is shared by other researchers (Rohm and Swaminathan 2004), which show that some shoppers are functional (they shop for convenience, information seeking, and time saving) while some others are hedonic (they shop for social interaction, bargain hunting and browsing). On the other hand, Kaltcheva and Weitz (2006) define motivations as a contextual orientation changing over time, depending on the situation, and show that contextual shopping motivations have a strong impact on shopping behavior. From our knowledge, no research specifically examined the respective impact of both these shopping motivation types. To deal with this issue, we used the notions of “traits” and “states” that have been largely used in marketing research to designate respectively a permanent characteristic of the individual and a temporary orientation of the consumer (Mowen 2000). The reversal theory (Apter 2001) suggests that two opposite states exist: the telic and the paratelic states. In the telic state, individuals set goals for themselves, must be disciplined to reach these goals, and do not behave in accordance with their personal trait. In the paratelic state, individuals are seeking arousal and enjoyment, do not set rules, and one could postulate that they act in accordance with their natural tendencies. Based on these considerations, we hypothesize the following process: in situations involving paratelic states, hedonic as well as functional individuals should behave according to their natural traits, whereas in situations involving telic states, hedonic people should inhibit their natural propensity to enjoy shopping and behave similarly to functional people. Hence, we postulate the following: Hypothesis: Compared to shoppers with functional motivational trait, shoppers with hedonic motivational trait will a) significantly display more hedonic shopping behavior intentions in a condition of paratelic motivational state, and b) not display more hedonic shopping behavior intentions in a condition a telic motivational state Empirical Research First, 108 participants were asked to fill a multi-items scale about their shopping habits, which actually measured their shopping motivational traits. This questionnaire allowed us to highlight four different dimensions in shopping motivational traits: social interaction, novelty/utility seeking, bargain hunting, and browsing. According to their scores on different items, participants were classified as functional or as hedonic on each of these four dimensions (a single individual may be hedonic on some dimensions and functional on others). Then, participants were then induced to adopt either a telic or a paratelic shopping motivational state while reading an appropriate scenario. Finally, participants were asked for their shopping behavior intentions in response to the shopping context. Four items were developed, corresponding to the four shopping motivational trait dimensions we found with our factor analysis. Results As we found four dimensions in shopping motivational trait, we set up four quasi-experimental designs to capture the entire phenomenon: for each dimension, a 2 (motivational trait) x 2 (motivational state) design was built, where the dependant variable was the shopping behavior element corresponding to the studied dimension. Four 2 x 2 Anovas were performed to assess the interaction between motivational trait and motivational state. Concerning the three dimensions - browsing, novelty/utility seeking, and bargain hunting- , in the paratelic state scenario participants with hedonic motivational trait displayed significantly more hedonic shopping behavior intentions than participants with a functional motivational trait (resp. F = 9.701, p = .003; F = 4.979, p = .03; F = 5.757, p = .02); and in the telic state scenario, there was no significant difference in behavior intentions between participants with hedonic or functional motivation trait. Each time, the interaction effect between motivational state and motivational trait was significant (resp. F = 4.859, p = .03; F = 3.314, p = .07; F = 2.98, p = .08). Concerning the fourth dimension, social interaction, shopping behavior intentions of participants with hedonic and with functional motivational traits were significantly different in the paratelic state scenario (F = 29.898, p <.000) as well as in the telic state scenario (F = 9.559, p = .003). However, the interaction effect showed that this behavioral difference was significantly stronger in the paratelic scenario. All these results support our research hypothesis. Discussion and Implications Our study provides consistent support for our hypotheses saying that there is an interaction effect between shopping motivational states and shopping motivational traits. The generalization of the results is strengthened by the study of four different shopping traits: social interaction, novelty/utility seeking, bargain hunting and browsing. As we proposed, when shopping in a goal-oriented state (telic state), behaviors of hedonic and functional shoppers do not differ significantly. Conversely, when shopping for a recreational reason (paratelic state), hedonic and functional shoppers behave significantly different. These results could explain why some previous studies concluded that shopping motivational traits had no impact on shopping behavior: they did not take into consideration the interaction between motivational trait and motivational state. Moreover, our study shows that marketing surveys performed by store managers to draw the personal profile of their customers must be crossed with contextual motivations in order to accurately forecast shopper behavior. Future Developments Our results can be explained by the self-control process, which pushes hedonic-trait shoppers to behave in a rather functional way in utilitarian situations. However, to be certain that this is the very process that occurs, we plan to add self-control perception scales to our existing measures. This is obviously the next step of this research.

PMD tolerance of 288 Gbit/s Coherent WDM and transmission over unrepeatered 124 km of field-installed single mode optical fiber

Low-cost, high-capacity optical transmission systems are required for metropolitan area networks. Direct-detected multi-carrier systems are attractive candidates, but polarization mode dispersion (PMD) is one of the major impairments that limits their performance. In this paper, we report the first experimental analysis of the PMD tolerance of a 288Gbit/s NRZ-OOK Coherent Wavelength Division Multiplexing system. The results show that this impairment is determined primarily by the subcarrier baud rate. We confirm the robustness of the system to PMD by demonstrating error-free performance over an unrepeatered 124km field-installed single-mode fiber with a negligible penalty of 0.3dB compared to the back-to-back measurements. (C) 2010 Optical Society of America

73.7 Tb/s (96 x 3 x 256-Gb/s) mode-division-multiplexed DP-16QAM transmission with inline MM-EDFA

Transmission of a 73.7 Tb/s (96x3x256-Gb/s) DP-16QAM mode-division-multiplexed signal over 119km of few-mode fiber transmission line incorporating an inline multi mode EDFA and a phase plate based mode (de-)multiplexer is demonstrated. Data-aided 6x6 MIMO digital signal processing was used to demodulate the signal. The total demonstrated net capacity, taking into account 20% of FEC-overhead and 7.5% additional overhead (Ethernet and training sequences), is 57.6 Tb/s, corresponding to a spectral efficiency of 12 bits/s/Hz.

Mode-division-multiplexed 3x112-Gb/s DP-QPSK transmission over 80 km few-mode fiber with inline MM-EDFA and blind DSP

We show transmission of a 3x112-Gb/s DP-QPSK mode-division-multiplexed signal up to 80km, with and without multi-mode EDFA, using blind 6x6 MIMO digital signal processing. We show that the OSNR-penalty induced by mode-mixing in the multi-mode EDFA is negligible.

Formation and characterization of ultra-sensitive surface plasmon resonance sensor based upon a nano-scale corrugated multi-layered coated D-shaped optical fiber

We present experimental results on the performance of a series of coated, D-shaped optical fiber sensors that display high spectral sensitivities to external refractive index. Sensitivity to the chosen index regime and coupling of the fiber core mode to the surface plasmon resonance (SPR) is enhanced by using specific materials as part of a multi-layered coating. We present strong evidence that this effect is enhanced by post ultraviolet radiation of the lamellar coating that results in the formation of a nano-scale surface relief corrugation structure, which generates an index perturbation within the fiber core that in turn enhances the coupling. We have found reasonable agreement when we modeling the fiber device. It was found that the SPR devices operate in air with high coupling efficiency in excess of 40 dB with spectral sensitivities that outperform a typical long period grating, with one device yielding a wavelength spectral sensitivity of 12000 nm/RIU in the important aqueous index regime. The devices generate SPRs over a very large wavelength range, (visible to 2 mu m) by alternating the polarization state of the illuminating light.