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Multi-Channel Retailing: Function of Consumers' Perceived Benefits and Costs and Retail Synergy

Multi-Channel Retailing: Function of Consumers' Perceived Benefits and Costs and Retail Synergy

Date: May 2003
Creator: Pookulangara, Sanjukta Arun
Description: This study investigated the consumers' intention towards multi-channel shopping and the function of synergy in a multi-channel retailing format (i.e., brick-and-mortar stores, catalogs, and the Internet). Two questionnaires were developed, one for the multi-channel consumers and the other for the multi-channel retailers. The structural equation modeling was used to predict the effect of shopping benefits and costs perceived from each channel on the consumer's purchase intention. Data analysis (N = 500) indicated that the purchase intentions were affected by different shopping benefit and cost variables. Qualitative analysis of retailers (N= 10) revealed that the retailers considered synergy to be an important part of their multi-channels. Also, there existed a high level of synergy among the existing three retail channels.
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A multi-dimensional entropy model of jazz improvisation for music information retrieval.

A multi-dimensional entropy model of jazz improvisation for music information retrieval.

Date: December 2005
Creator: Simon, Scott J.
Description: Jazz improvisation provides a case context for examining information in music; entropy provides a means for representing music for retrieval. Entropy measures are shown to distinguish between different improvisations on the same theme, thus demonstrating their potential for representing jazz information for analysis and retrieval. The calculated entropy measures are calibrated against human representation by means of a case study of an advanced jazz improvisation course, in which synonyms for "entropy" are frequently used by the instructor. The data sets are examined for insights in music information retrieval, music information behavior, and music representation.
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Multi-perspective, Multi-modal Image Registration and Fusion

Multi-perspective, Multi-modal Image Registration and Fusion

Date: August 2012
Creator: Belkhouche, Mohammed Yassine
Description: Multi-modal image fusion is an active research area with many civilian and military applications. Fusion is defined as strategic combination of information collected by various sensors from different locations or different types in order to obtain a better understanding of an observed scene or situation. Fusion of multi-modal images cannot be completed unless these two modalities are spatially aligned. In this research, I consider two important problems. Multi-modal, multi-perspective image registration and decision level fusion of multi-modal images. In particular, LiDAR and visual imagery. Multi-modal image registration is a difficult task due to the different semantic interpretation of features extracted from each modality. This problem is decoupled into three sub-problems. The first step is identification and extraction of common features. The second step is the determination of corresponding points. The third step consists of determining the registration transformation parameters. Traditional registration methods use low level features such as lines and corners. Using these features require an extensive optimization search in order to determine the corresponding points. Many methods use global positioning systems (GPS), and a calibrated camera in order to obtain an initial estimate of the camera parameters. The advantages of our work over the previous works are the following. ...
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The Multi-reference Correlation Consistent Composite Approach: A New Vista In Quantitative Prediction Of Thermochemical And Spectroscopic Properties

The Multi-reference Correlation Consistent Composite Approach: A New Vista In Quantitative Prediction Of Thermochemical And Spectroscopic Properties

Date: December 2011
Creator: Oyedepo, Gbenga A.
Description: The multi-reference correlation consistent composite approach (MR-ccCA) was designed to reproduce the accuracy of more computationally intensive ab initio quantum mechanical methods like MR-ACPF-DK/aug-cc-pCV?Z-DK, albeit at a significantly reduced cost. In this dissertation, the development and applications of the MR-ccCA method and a variant of its single reference equivalent (the relativistic pseudopotential ccCA method) are reported. MR-ccCA is shown to predict the energetic properties of reactive intermediates, excited states species and transition states to within chemical accuracy (i.e. ±1.0 kcal mol 1) of reliable experimental values. The accuracy and versatility of MR-ccCA are also demonstrated in the prediction of the thermochemical and spectroscopic properties (such as atomization energies, enthalpies of formation and adiabatic transition energies of spin-forbidden excited states) of a series of silicon-containing compounds. The thermodynamic and kinetic feasibilities of the oxidative addition of an archetypal arylglycerol ?-aryl ether (?-O-4 linkage) substructure of lignin to Ni, Cu, Pd and Pt transition metal atoms using the efficient relativistic pseudopotential correlation consistent composite approach within an ONIOM framework (rp-ccCA-ONIOM), a multi-level multi-layer QM/QM method formulated to enhance the quantitative predictions of the chemical properties of heavy element-containing systems larger than hitherto attainable, are also reported.
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A multi-state political process analysis of the anti-testing movement.

A multi-state political process analysis of the anti-testing movement.

Date: December 2006
Creator: DeMerle, Carol
Description: I applied McAdam's political process model for social movement analysis to examine the level of collective resistance to high stakes testing in California, Massachusetts, New York, South Carolina, and Texas from 1985 to 2005. Data on protest occurrences in those states were gathered from online news reports, anti-testing organization websites, and electronic interviews from individuals associated with the anti-testing movement. Variables used in the analysis included each state's key educational accountability legislation, political affiliations of state political leaders, state political leaders' support of accountability issues, student ethnicity profiles, poverty indicators, dropout rates, and collective bargaining laws. I examined the relationship between those variables and protest development in terms of the political process model's three components: framing processes, mobilizing structures, and political opportunity. I concluded California and Massachusetts, with their strong networks of anti-testing organizations, showed more instances of protest than any other state. Slightly fewer protests occurred in New York. Texas showed few instances of anti-testing protests and there were no reports of protests in South Carolina. There was evidence of framing efforts from both proponents and opponents of high-stakes testing, with proponents' framing efforts tending to be more covert. I found that anti-testing protests were primarily initiated by middle-class ...
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A Multi-Time Scale Learning Mechanism for Neuromimic Processing

A Multi-Time Scale Learning Mechanism for Neuromimic Processing

Date: August 1994
Creator: Mobus, George E. (George Edward)
Description: Learning and representing and reasoning about temporal relations, particularly causal relations, is a deep problem in artificial intelligence (AI). Learning such representations in the real world is complicated by the fact that phenomena are subject to multiple time scale influences and may operate with a strange attractor dynamic. This dissertation proposes a new computational learning mechanism, the adaptrode, which, used in a neuromimic processing architecture may help to solve some of these problems. The adaptrode is shown to emulate the dynamics of real biological synapses and represents a significant departure from the classical weighted input scheme of conventional artificial neural networks. Indeed the adaptrode is shown, by analysis of the deep structure of real synapses, to have a strong structural correspondence with the latter in terms of multi-time scale biophysical processes. Simulations of an adaptrode-based neuron and a small network of neurons are shown to have the same learning capabilities as invertebrate animals in classical conditioning. Classical conditioning is considered a fundamental learning task in animals. Furthermore, it is subject to temporal ordering constraints that fulfill the criteria of causal relations in natural systems. It may offer clues to the learning of causal relations and mechanisms for causal reasoning. The ...
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A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

A Multi-Variate Analysis of SMTP Paths and Relays to Restrict Spam and Phishing Attacks in Emails

Access: Use of this item is restricted to the UNT Community.
Date: December 2006
Creator: Palla, Srikanth
Description: The classifier discussed in this thesis considers the path traversed by an email (instead of its content) and reputation of the relays, features inaccessible to spammers. Groups of spammers and individual behaviors of a spammer in a given domain were analyzed to yield association patterns, which were then used to identify similar spammers. Unsolicited and phishing emails were successfully isolated from legitimate emails, using analysis results. Spammers and phishers are also categorized into serial spammers/phishers, recent spammers/phishers, prospective spammers/phishers, and suspects. Legitimate emails and trusted domains are classified into socially close (family members, friends), socially distinct (strangers etc), and opt-outs (resolved false positives and false negatives). Overall this classifier resulted in far less false positives when compared to current filters like SpamAssassin, achieving a 98.65% precision, which is well comparable to the precisions achieved by SPF, DNSRBL blacklists.
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Multi-year Operation Effect of Geothermal Heat Exchanger on Soil Temperature for Unt Zero Energy Lab

Multi-year Operation Effect of Geothermal Heat Exchanger on Soil Temperature for Unt Zero Energy Lab

Date: December 2013
Creator: Walikar, Vinayak P.
Description: Ground source heat pump (GSHP) uses earth’s heat to heat or cool space. Absorbing heat from earth or rejecting heat to the earth, changes soil’s constant temperature over the multiple years. In this report we have studied about Soil temperature change over multiple years due to Ground loop heat exchanger (GLHE) for Zero Energy Research Laboratory (ZØE) which is located in Discovery Park, University of North Texas, Denton, TX. We did 2D thermal analysis GLHP at particular Depth. For simulation we have used ANSYS workbench for pre-processing and FLUENT ANYS as solver. TAC Vista is software that monitors and controls various systems in ZØE. It also monitors temperature of water inlet/outlet of GLHE. For Monitoring Ground temperatures at various depths we have thermocouples installed till 8ft from earth surface, these temperatures are measured using LabVIEW. From TAC Vista and LabVIEW Reading’s we have studied five parameters in this report using FLUENT ANSYS, they are; (1) Effect of Time on soil Temperature change over Multi-years, (2) Effect of Load on soil temperature change over Multi-years, (3) Effect of Depth on soil temperature change over Multi-years, (4) Effect of Doubling ΔT of inlet and outlet of GLHE on soil temperature change over ...
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Multifractal Analysis of Parabolic Rational Maps

Multifractal Analysis of Parabolic Rational Maps

Date: August 1998
Creator: Byrne, Jesse William
Description: The investigation of the multifractal spectrum of the equilibrium measure for a parabolic rational map with a Lipschitz continuous potential, φ, which satisfies sup φ < P(φ) x∈J(T) is conducted. More specifically, the multifractal spectrum or spectrum of singularities, f(α) is studied.
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Multifractal Measures

Multifractal Measures

Date: May 1994
Creator: Olsen, Lars
Description: The purpose of this dissertation is to introduce a natural and unifying multifractal formalism which contains the above mentioned multifractal parameters, and gives interesting results for a large class of natural measures. In Part 2 we introduce the proposed multifractal formalism and study it properties. We also show that this multifractal formalism gives natural and interesting results when applied to (nonrandom) graph directed self-similar measures in Rd and "cookie-cutter" measures in R. In Part 3 we use the multifractal formalism introduced in Part 2 to give a detailed discussion of the multifractal structure of random (and hence, as a special case, non-random) graph directed self-similar measures in R^d.
Contributing Partner: UNT Libraries