Multilevel analyses in marketing research:differentiating analytical outcomes

Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

Advanced fibre gratings fabricated in standard and infrared glass fibres by ultraviolet and near-infrared-femtosecond lasers

In this thesis, I describe studies on fabrication, spectral characteristics and applications of tilted fibre gratings (TFGs) with small, large and 45° tilted structures and novel developments in fabrication of fibre Bragg gratings (FBGs) and long period gratings (LPGs) in normal silica and mid-infrared (mid-IR) glass fibres using near-IR femtosecond laser. One of the major contributions presented in this thesis is the systematic investigation of structures, inscription methods and spectral, polarisation dependent loss (PDL) and thermal characteristics of TFGs with small (<45°), large (>45°) and 45° tilted structures. I have experimentally characterised TFGs, obtaining relationships between the radiation angle, central wavelength of the radiation profile, Bragg resonance and the tilt angle, which are consistent with theoretical simulation based on the mode-coupling theory. Furthermore, thermal responses have been measured for these three types of TFGs, showing the transmission spectra of large and 45° TFGs are insensitive to the temperature change, unlike the normal and small angle tilted FBGs. Based on the distinctive optical properties, TFGs have been developed into interrogation system and sensors, which form the other significant contributions of the work presented in this thesis. The 10°-TFG based 800nm WDM interrogation system can function not just as an in-fibre spectrum analyser but also possess refractive index sensing capability. By utilising the unique polarisation properties, the 81 °-TFG based sensors are capable of sensing the transverse loading and twisting with sensitivities of 2.04pW/(kg/m) and 145.90pW/rad, repectively. The final but the most important contribution from the research work presented in this thesis is the development of novel grating inscription techniques using near-IR femtosecond laser. A number of LPGs and FBGs were successfully fabricated in normal silica and mid-IR glass fibres using point-by-point and phase-mask techniques. LPGs and 1st and 2nd order FBGs have been fabricated in these mid-IR glass fibres showing resonances covering the wavelength range from 1200 to 1700nm with the strengths up to 13dB. In addition, the thermal and strain sensitivities of these gratings have been systematically investigated. All the results from these initial but systematic works will provide useful function characteristics information for future fibre grating based devices and applications in mid-IR range.

A combination of cyclone and vert techniques for the management of construction projects

Many planning and control tools, especially network analysis, have been developed in the last four decades. The majority of them were created in military organization to solve the problem of planning and controlling research and development projects. The original version of the network model (i.e. C.P.M/PERT) was transplanted to the construction industry without the consideration of the special nature and environment of construction projects. It suited the purpose of setting up targets and defining objectives, but it failed in satisfying the requirement of detailed planning and control at the site level. Several analytical and heuristic rules based methods were designed and combined with the structure of C.P.M. to eliminate its deficiencies. None of them provides a complete solution to the problem of resource, time and cost control. VERT was designed to deal with new ventures. It is suitable for project evaluation at the development stage. CYCLONE, on the other hand, is concerned with the design and micro-analysis of the production process. This work introduces an extensive critical review of the available planning techniques and addresses the problem of planning for site operation and control. Based on the outline of the nature of site control, this research developed a simulation based network model which combines part of the logics of both VERT and CYCLONE. Several new nodes were designed to model the availability and flow of resources, the overhead and operating cost and special nodes for evaluating time and cost. A large software package is written to handle the input, the simulation process and the output of the model. This package is designed to be used on any microcomputer using MS-DOS operating system. Data from real life projects were used to demonstrate the capability of the technique. Finally, a set of conclusions are drawn regarding the features and limitations of the proposed model, and recommendations for future work are outlined at the end of this thesis.

Modelling manufacturing planning and control systems:the application of object-oriented principles and discrete-event simulation

Manufacturing planning and control systems are fundamental to the successful operations of a manufacturing organisation. 10 order to improve their business performance, significant investment is made by companies into planning and control systems; however, not all companies realise the benefits sought Many companies continue to suffer from high levels of inventory, shortages, obsolete parts, poor resource utilisation and poor delivery performance. This thesis argues that the fit between the planning and control system and the manufacturing organisation is a crucial element of success. The design of appropriate control systems is, therefore, important. The different approaches to the design of manufacturing planning and control systems are investigated. It is concluded that there is no provision within these design methodologies to properly assess the impact of a proposed design on the manufacturing facility. Consequently, an understanding of how a new (or modified) planning and control system will perform in the context of the complete manufacturing system is unlikely to be gained until after the system has been implemented and is running. There are many modelling techniques available, however discrete-event simulation is unique in its ability to model the complex dynamics inherent in manufacturing systems, of which the planning and control system is an integral component. The existing application of simulation to manufacturing control system issues is limited: although operational issues are addressed, application to the more fundamental design of control systems is rarely, if at all, considered. The lack of a suitable simulation-based modelling tool does not help matters. The requirements of a simulation tool capable of modelling a host of different planning and control systems is presented. It is argued that only through the application of object-oriented principles can these extensive requirements be achieved. This thesis reports on the development of an extensible class library called WBS/Control, which is based on object-oriented principles and discrete-event simulation. The functionality, both current and future, offered by WBS/Control means that different planning and control systems can be modelled: not only the more standard implementations but also hybrid systems and new designs. The flexibility implicit in the development of WBS/Control supports its application to design and operational issues. WBS/Control wholly integrates with an existing manufacturing simulator to provide a more complete modelling environment.

QoS guarantee with adaptive transmit power and message rate control for DSRC vehicle network based road safety applications

Quality of services (QoS) support is critical for dedicated short range communications (DSRC) vehicle networks based collaborative road safety applications. In this paper we propose an adaptive power and message rate control method for DSRC vehicle networks at road intersections. The design objective is to provide high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method an offline simulation based approach is used to find out the best possible configurations of transmit power and message rate for given numbers of vehicles in the network. The identified best configurations are then used online by roadside access points (AP) according to estimated number of vehicles. Simulation results show that this adaptive method significantly outperforms a fixed control method. © 2011 Springer-Verlag.

Photo-sketch synthesis and recognition based on subspace learning

This paper aims to reducing difference between sketches and photos by synthesizing sketches from photos, and vice versa, and then performing sketch-sketch/photo-photo recognition with subspace learning based methods. Pseudo-sketch/pseudo-photo patches are synthesized with embedded hidden Markov model. Because these patches are assembled by averaging their overlapping area in most of the local strategy based methods, which leads to blurring effect to the resulted pseudo-sketch/pseudo-photo, we integrate the patches with image quilting. Experiments are carried out to demonstrate that the proposed method is effective to produce pseudo-sketch/pseudo-photo with high quality and achieve promising recognition results. © 2009.

Adaptive power and rate control for QoS guarantee of DSRC based collaborative road safety applications

In this paper we propose an adaptive power and message rate control method for safety applications at road intersections. The design objectives are to firstly provide guaranteed QoS support to both high priority emergency safety applications and low priority routine safety applications and secondly maximize channel utilization. We use an offline simulation based approach to find out the best possible configurations of transmit power and message rate for given numbers of vehicles in the network with certain safety QoS requirements. The identified configurations are then used online by roadside access points (AP) adaptively according to estimated number of vehicles. Simulation results show that this adaptive method could provide required QoS support to safety applications and it significantly outperforms a fixed control method. © 2013 International Information Institute.

Rigid and non-rigid point-based medical image registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Hybrid approaches to estimating freeway travel times using point traffic detector data

The accurate and reliable estimation of travel time based on point detector data is needed to support Intelligent Transportation System (ITS) applications. It has been found that the quality of travel time estimation is a function of the method used in the estimation and varies for different traffic conditions. In this study, two hybrid on-line travel time estimation models, and their corresponding off-line methods, were developed to achieve better estimation performance under various traffic conditions, including recurrent congestion and incidents. The first model combines the Mid-Point method, which is a speed-based method, with a traffic flow-based method. The second model integrates two speed-based methods: the Mid-Point method and the Minimum Speed method. In both models, the switch between travel time estimation methods is based on the congestion level and queue status automatically identified by clustering analysis. During incident conditions with rapidly changing queue lengths, shock wave analysis-based refinements are applied for on-line estimation to capture the fast queue propagation and recovery. Travel time estimates obtained from existing speed-based methods, traffic flow-based methods, and the models developed were tested using both simulation and real-world data. The results indicate that all tested methods performed at an acceptable level during periods of low congestion. However, their performances vary with an increase in congestion. Comparisons with other estimation methods also show that the developed hybrid models perform well in all cases. Further comparisons between the on-line and off-line travel time estimation methods reveal that off-line methods perform significantly better only during fast-changing congested conditions, such as during incidents. The impacts of major influential factors on the performance of travel time estimation, including data preprocessing procedures, detector errors, detector spacing, frequency of travel time updates to traveler information devices, travel time link length, and posted travel time range, were investigated in this study. The results show that these factors have more significant impacts on the estimation accuracy and reliability under congested conditions than during uncongested conditions. For the incident conditions, the estimation quality improves with the use of a short rolling period for data smoothing, more accurate detector data, and frequent travel time updates.

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

A study of methods used to analyze total oil and polycyclic aromatic hydrocarbons in produced water: steps towards the validation of molecularly imprinted polymers for use in marine environmetns

Produced water is a by-product of offshore oil and gas production, and is released in large volumes when platforms are actively processing crude oil. Some pollutants are not typically removed by conventional oil/water separation methods and are discharged with produced water. Oil and grease can be found dispersed in produced water in the form of tiny droplets, and polycyclic aromatic hydrocarbons (PAHs) are commonly found dissolved in produced water. Both can have acute and chronic toxic effects in marine environments even at low exposure levels. The analysis of the dissolved and dispersed phases are a priority, but effort is required to meet the necessary detection limits. There are several methods for the analysis of produced water for dispersed oil and dissolved PAHs, all of which have advantages and disadvantages. In this work, EPA Method 1664 and APHA Method 5520 C for the determination of oil and grease will be examined and compared. For the detection of PAHs, EPA Method 525 and PAH MIPs will be compared, and results evaluated. APHA Method 5520 C Partition-Infrared Method is a liquid-liquid extraction procedure with IR determination of oil and grease. For analysis on spiked samples of artificial seawater, extraction efficiency ranged from 85 – 97%. Linearity was achieved in the range of 5 – 500 mg/L. This is a single-wavelength method and is unsuitable for quantification of aromatics and other compounds that lack sp³-hybridized carbon atoms. EPA Method 1664 is the liquid-liquid extraction of oil and grease from water samples followed by gravimetric determination. When distilled water spiked with reference oil was extracted by this procedure, extraction efficiency ranged from 28.4 – 86.2%, and %RSD ranged from 7.68 – 38.0%. EPA Method 525 uses solid phase extraction with analysis by GC-MS, and was performed on distilled water and water from St. John’s Harbour, all spiked with naphthalene, fluorene, phenanthrene, and pyrene. The limits of detection in harbour water were 0.144, 3.82, 0.119, and 0.153 g/L respectively. Linearity was obtained in the range of 0.5-10 g/L, and %RSD ranged from 0.36% (fluorene) to 46% (pyrene). Molecularly imprinted polymers (MIPs) are sorbent materials made selective by polymerizing functional monomers and crosslinkers in the presence of a template molecule, usually the analytes of interest or related compounds. They can adsorb and concentrate PAHs from aqueous environments and are combined with methods of analysis including GC-MS, LC-UV-Vis, and desorption electrospray ionization (DESI)- MS. This work examines MIP-based methods as well as those methods previously mentioned which are currently used by the oil and gas industry and government environmental agencies. MIPs are shown to give results consistent with other methods, and are a low-cost alternative improving ease, throughput, and sensitivity. PAH MIPs were used to determine naphthalene spiked into ASTM artificial seawater, as well as produced water from an offshore oil and gas operation. Linearity was achieved in the range studied (0.5 – 5 mg/L) for both matrices, with R² = 0.936 for seawater and R² = 0.819 for produced water. The %RSD for seawater ranged from 6.58 – 50.5% and for produced water, from 8.19 – 79.6%.

Integrated sensitivity analysis, calibration, and uncertainty propagation analysis approaches for supporting hydrological modeling

The successful performance of a hydrological model is usually challenged by the quality of the sensitivity analysis, calibration and uncertainty analysis carried out in the modeling exercise and subsequent simulation results. This is especially important under changing climatic conditions where there are more uncertainties associated with climate models and downscaling processes that increase the complexities of the hydrological modeling system. In response to these challenges and to improve the performance of the hydrological models under changing climatic conditions, this research proposed five new methods for supporting hydrological modeling. First, a design of experiment aided sensitivity analysis and parameterization (DOE-SAP) method was proposed to investigate the significant parameters and provide more reliable sensitivity analysis for improving parameterization during hydrological modeling. The better calibration results along with the advanced sensitivity analysis for significant parameters and their interactions were achieved in the case study. Second, a comprehensive uncertainty evaluation scheme was developed to evaluate three uncertainty analysis methods, the sequential uncertainty fitting version 2 (SUFI-2), generalized likelihood uncertainty estimation (GLUE) and Parameter solution (ParaSol) methods. The results showed that the SUFI-2 performed better than the other two methods based on calibration and uncertainty analysis results. The proposed evaluation scheme demonstrated that it is capable of selecting the most suitable uncertainty method for case studies. Third, a novel sequential multi-criteria based calibration and uncertainty analysis (SMC-CUA) method was proposed to improve the efficiency of calibration and uncertainty analysis and control the phenomenon of equifinality. The results showed that the SMC-CUA method was able to provide better uncertainty analysis results with high computational efficiency compared to the SUFI-2 and GLUE methods and control parameter uncertainty and the equifinality effect without sacrificing simulation performance. Fourth, an innovative response based statistical evaluation method (RESEM) was proposed for estimating the uncertainty propagated effects and providing long-term prediction for hydrological responses under changing climatic conditions. By using RESEM, the uncertainty propagated from statistical downscaling to hydrological modeling can be evaluated. Fifth, an integrated simulation-based evaluation system for uncertainty propagation analysis (ISES-UPA) was proposed for investigating the effects and contributions of different uncertainty components to the total propagated uncertainty from statistical downscaling. Using ISES-UPA, the uncertainty from statistical downscaling, uncertainty from hydrological modeling, and the total uncertainty from two uncertainty sources can be compared and quantified. The feasibility of all the methods has been tested using hypothetical and real-world case studies. The proposed methods can also be integrated as a hydrological modeling system to better support hydrological studies under changing climatic conditions. The results from the proposed integrated hydrological modeling system can be used as scientific references for decision makers to reduce the potential risk of damages caused by extreme events for long-term water resource management and planning.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

Periodic nonlinear Fourier transform for fiber-optic communications, Part I:theory and numerical methods

In this work, we introduce the periodic nonlinear Fourier transform (PNFT) method as an alternative and efficacious tool for compensation of the nonlinear transmission effects in optical fiber links. In the Part I, we introduce the algorithmic platform of the technique, describing in details the direct and inverse PNFT operations, also known as the inverse scattering transform for periodic (in time variable) nonlinear Schrödinger equation (NLSE). We pay a special attention to explaining the potential advantages of the PNFT-based processing over the previously studied nonlinear Fourier transform (NFT) based methods. Further, we elucidate the issue of the numerical PNFT computation: we compare the performance of four known numerical methods applicable for the calculation of nonlinear spectral data (the direct PNFT), in particular, taking the main spectrum (utilized further in Part II for the modulation and transmission) associated with some simple example waveforms as the quality indicator for each method. We show that the Ablowitz-Ladik discretization approach for the direct PNFT provides the best performance in terms of the accuracy and computational time consumption.

PCR-Based Analysis of Mitochondrial DNA Copy Number, Mitochondrial DNA Damage, and Nuclear DNA Damage.

Because of the role that DNA damage and depletion play in human disease, it is important to develop and improve tools to assess these endpoints. This unit describes PCR-based methods to measure nuclear and mitochondrial DNA damage and copy number. Long amplicon quantitative polymerase chain reaction (LA-QPCR) is used to detect DNA damage by measuring the number of polymerase-inhibiting lesions present based on the amount of PCR amplification; real-time PCR (RT-PCR) is used to calculate genome content. In this unit, we provide step-by-step instructions to perform these assays in Homo sapiens, Mus musculus, Rattus norvegicus, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Oryzias latipes, Fundulus grandis, and Fundulus heteroclitus, and discuss the advantages and disadvantages of these assays.