Background traffic modeling for large-scale network simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Hispanic orientalism: The literary development of a cultural paradigm, from medieval Spain to modern Latin America

This dissertation offers a novel approach to Hispanic Orientalism, developing a dynamic paradigm from its origins in medieval and Renaissance Iberia during the process of the Christian Reconquest, to its transatlantic migration and establishment in the early years of the Colony, from where it changed in late colonial and post-Independence Latin America, and onto modernity. ^ The study argues that Hispanic Orientalism does not necessarily imply a negative depiction of the Other, a quality associated with the traditional critique of Saidian Orientalism. Neither, does it entirely comply with the positivist approach suggested in the theoretical research of Said’s opponents, like Julia Kushigian. This dissertation also argues that sociopolitical changes and the shift in the discourse of powers, from imperial to non-imperial, had a significant impact of the development of Hispanic Orientalism, shaping the relationship with the Other. The methodology involves close reading of representative texts depicting the interactions of the dominant and dominated societies from each of the four historic periods that coincided with significant sociopolitical transformations in Hispanic society. Through an intercultural approach to literary studies, social history, and religious studies, this project develops an original paradigm of Hispanic Orientalism, derived from the image of the reinvented Semitic Other portrayed in the literary works depicting the relationship between the hegemonic and the subaltern cultures during the Reconquest period in Spain. Then, it traces the turn of the original paradigm towards reinterpretation during its transatlantic migration to Latin America through the analysis of the chronicles and travelogs of the first colonizers and explorers. During the transitional late colonial and early Independence periods Latin America sees a significant change in the discourse of powers, and Hispanic Orientalism reflects this oscillation between the past and the present therough the works of the Latin American authors from the seventeenth to the nineteenth centuries. Finally, once the non-imperial discourse of power established itself in the former Colony, a new modern stage in the development of Hispanic Orientalist paradigm takes place. It is marked by the desire to differentiate itself from the O(o)thers, as manifested in the works of the representatives of Modernism and the Boom.^

Sea-surface temperature reconstruction of sediment cores from the Skagerrak

We attempt a reconstruction of salinity levels of the central Baltic Sea based on diatom assemblages, the isotopic composition of organic matter and sedimentological expression of anoxia over the last 10 000 years. We use the data to investigate the dependence of salinity levels on climate evolution and isostasy. Changes in salinity of surface and deep waters were most pronounced from 8400 to approximately 5000 cal. BP. Density stratification between salty deep and fresher surface waters caused the frequent development of anoxic conditions and deposition of laminated sediments on large parts of the sea floor in the central Baltic Sea, and dramatic changes in organic carbon-accumulation rates. From 5000 to 3100 cal. BP, the salinity of the basin decreased, oxygenation of deep sea floors was improved, and fertility of the sea surface was significantly reduced. This is reflected by low accumulation rates of organic carbon in bioturbated sediments. Since 2800 cal. BP, salinity rose again and anoxic periods were more common. Even though the major steps in environmental evolution in the Baltic Sea coincide with known patterns of climatic change of the North Atlantic realm over the last 10 000 years, we find no conclusive evidence for synchronous changes or linear responses on submillennial timescales. However, we note that major variations in our salinity records agree with temporal patterns of reconstructed summer warmth and winter precipitation in southern Scandinavia. Both types of record suggest that climate in the mid-Holocene was far from stable. Our data also confirm that climate evolution over the late Holocene had significant impact on environmental conditions in the Baltic Sea.

Molecular epidemiology of sexually transmitted human papillomavirus in a self referred group of women in Ireland

Background: Human papillomavirus (HPV) causes cervical cancer and external genital warts. The purpose of this study is to document the genotype distribution of HPV in females aged between 18 and 34 who self-referred to an STI clinic with visible external genital warts (EGW). Scrapings were taken from visible external genital warts (EGW). These scrapings were analysed by PCR for the presence of HPV DNA. Positive samples were then genotyped by means of a commercially available assay (LiPA). A comparison of genotyping results determined by the LiPA assay and direct amplicon DNA sequencing was also performed. Results: Ninety-two patients out of 105 samples (88%) had detectable levels of HPV DNA. The majority of individuals with EGW (66%) showed the presence of two or more genotypes. The most common HPV genotypes present in the study population were HPV-6, HPV-11, HPV-16, HPV-18, HPV-33 and HPV-53. Potential effects of vaccination on HPV molecular epidemiology indicate that 40% of the patients could have been protected from the high risk genotypes HPV-16 and HPV-18.Conclusion: This is the first report of the molecular epidemiology of external genital warts in women aged between 18 and 34 from Ireland based on results from a LiPA assay. The study shows that most individuals are infected with multiple genotypes including those with high oncogenic potential and that the newly available HPV vaccines could have a significant impact on prevalence of the most common HPV genotypes in this study population.

Operational expenditure costs for wave energy projects and impacts on financial returns

This paper examines 'availability' and the input metrics of operational expenditure (OPEX) for wave energy projects and reports on a case study which assesses the impact of these inputs on project profit returns. Case study simulations modelled a 75 MW wave energy project at two locations; the west coast of Ireland and the north coast of Portugal. Access and availability with respect to weather windows at both locations are discussed and their impact on energy output and wave farm operations is quantified. The input metrics used to calculate OPEX of wave energy projects are defined as well as the impact of OPEX on project net present value (NPV) and internal rate of return (IRR). Results indicate that access and resultant availability factors have a significant impact on case study results by reducing energy output and correspondingly financial returns. Furthermore, the technology maturity level designated for a project also impacts on availability factors and consequently energy output and NPV. Case study profits proved to be very sensitive to annual OPEX, especially if overhaul and replacement costs were accounted for. As a result of the impact of 'availability' on project profit returns. Feed-in tariffs will need to be tailored to the location in question as well as the device technology maturity level, with case study simulations indicating that high FIT will be required to support early stage WEC projects. (C) 2012 Elsevier Ltd. All rights reserved.

Elucidating the Space-Time Structure of Low Level Warm Season Precipitation Processes in the Southern Appalachian Mountains Using Models and Observations

Light rainfall is the baseline input to the annual water budget in mountainous landscapes through the tropics and at mid-latitudes. In the Southern Appalachians, the contribution from light rainfall ranges from 50-60% during wet years to 80-90% during dry years, with convective activity and tropical cyclone input providing most of the interannual variability. The Southern Appalachians is a region characterized by rich biodiversity that is vulnerable to land use/land cover changes due to its proximity to a rapidly growing population. Persistent near surface moisture and associated microclimates observed in this region has been well documented since the colonization of the area in terms of species health, fire frequency, and overall biodiversity. The overarching objective of this research is to elucidate the microphysics of light rainfall and the dynamics of low level moisture in the inner region of the Southern Appalachians during the warm season, with a focus on orographically mediated processes. The overarching research hypothesis is that physical processes leading to and governing the life cycle of orographic fog, low level clouds, and precipitation, and their interactions, are strongly tied to landform, land cover, and the diurnal cycles of flow patterns, radiative forcing, and surface fluxes at the ridge-valley scale. The following science questions will be addressed specifically: 1) How do orographic clouds and fog affect the hydrometeorological regime from event to annual scale and as a function of terrain characteristics and land cover?; 2) What are the source areas, governing processes, and relevant time-scales of near surface moisture convergence patterns in the region?; and 3) What are the four dimensional microphysical and dynamical characteristics, including variability and controlling factors and processes, of fog and light rainfall? The research was conducted with two major components: 1) ground-based high-quality observations using multi-sensor platforms and 2) interpretive numerical modeling guided by the analysis of the in situ data collection. Findings illuminate a high level of spatial – down to the ridge scale - and temporal – from event to annual scale - heterogeneity in observations, and a significant impact on the hydrological regime as a result of seeder-feeder interactions among fog, low level clouds, and stratiform rainfall that enhance coalescence efficiency and lead to significantly higher rainfall rates at the land surface. Specifically, results show that enhancement of an event up to one order of magnitude in short-term accumulation can occur as a result of concurrent fog presence. Results also show that events are modulated strongly by terrain characteristics including elevation, slope, geometry, and land cover. These factors produce interactions between highly localized flows and gradients of temperature and moisture with larger scale circulations. Resulting observations of DSD and rainfall patterns are stratified by region and altitude and exhibit clear diurnal and seasonal cycles.

Essays in Empirical Operations Management: Bayesian Learning of Service Quality and Structural Estimation of Complementary Product Pricing and Inventory Management

This dissertation contributes to the rapidly growing empirical research area in the field of operations management. It contains two essays, tackling two different sets of operations management questions which are motivated by and built on field data sets from two very different industries --- air cargo logistics and retailing.

The first essay, based on the data set obtained from a world leading third-party logistics company, develops a novel and general Bayesian hierarchical learning framework for estimating customers' spillover learning, that is, customers' learning about the quality of a service (or product) from their previous experiences with similar yet not identical services. We then apply our model to the data set to study how customers' experiences from shipping on a particular route affect their future decisions about shipping not only on that route, but also on other routes serviced by the same logistics company. We find that customers indeed borrow experiences from similar but different services to update their quality beliefs that determine future purchase decisions. Also, service quality beliefs have a significant impact on their future purchasing decisions. Moreover, customers are risk averse; they are averse to not only experience variability but also belief uncertainty (i.e., customer's uncertainty about their beliefs). Finally, belief uncertainty affects customers' utilities more compared to experience variability.

The second essay is based on a data set obtained from a large Chinese supermarket chain, which contains sales as well as both wholesale and retail prices of un-packaged perishable vegetables. Recognizing the special characteristics of this particularly product category, we develop a structural estimation model in a discrete-continuous choice model framework. Building on this framework, we then study an optimization model for joint pricing and inventory management strategies of multiple products, which aims at improving the company's profit from direct sales and at the same time reducing food waste and thus improving social welfare.

Collectively, the studies in this dissertation provide useful modeling ideas, decision tools, insights, and guidance for firms to utilize vast sales and operations data to devise more effective business strategies.

Impurity profiling and synthesis of precursors to the hallucinogenic amphetamine DOB

DOB (4‐bromo‐2,5‐dimethoxyamphetamine) is a newly emerging hallucinogenic amphetamine that sparked serious health warnings in Ireland, following its first seizure back in 2003. Known more commonly as “snowball”, this drug is highly potent and may be used as a substitute to ecstasy (MDMA) and lysergic acid diethylamide (LSD). To date, the work carried out on the impurity profiling of DOB is limited in comparison to amphetamine, methamphetamine and MDMA. In this work, the impurity profile of 4‐bromo‐2,5‐dimethoxyphenyl‐2‐propanone (4‐Br‐2,5‐P2P) is explored. This ketone is a direct precursor to DOB. Its more versatile non‐bromo analogue, 2,5‐ dimethoxyphenyl‐2‐propanone (2,5‐P2P) is also examined, as in addition to DOB, it may be used in the synthesis of a range of several other hallucinogenic amphetamines. A number of different routes to both 2,5‐P2P and 4‐Br‐2,5‐P2P were investigated. For each of these routes, the impurities produced were carefully isolated. Following isolation, the impurities were fully characterised (by 1H‐NMR/13C‐NMR spectroscopy, IR, MS), in order to aid structure elucidation. Compounds not easily resolved by flash column chromatography were analysed by LC‐MS and/or independently synthesised for the purpose of attaining reference standards. Adaptation of the well‐known ‘phenylacetic acid route’ to synthesis of both 2,5‐P2P and 4‐Br‐2,5‐P2P, was found to provide low yields of the expected ketone products. Four impurities were isolated during the preparation of both ketones. The yield of one of these impurities (possessing a dibenzylketone core), was greatly influenced by the amount of acetic anhydride reagent used during the reaction. Having carried out the reaction with several different equivalents of acetic anhydride, it was found that formation of the ‘dibenzylketone’ could not be eliminated. This may increase its likelihood of being detected in the final drug product. The ‘Darzens route’, having very recently emerged as a synthetic route to amphetamine and MDMA precursors, was discovered to be a viable route for manufacture of 2,5‐P2P and 4‐Br‐2,5‐P2P. Despite execution of the reaction being more tedious, the route provides superior yields (≈50–60%) to those achieved using the ‘phenylacetic acid route’ (≈35–38%). Incorporation of a bromine atom (at the aromatic 4‐position) is required at some stage during synthesis of DOB. The bromination of many intermediates/starting materials was therefore also examined in detail. Bromination of the acid starting material 2,5‐dimethoxyphenylacetic acid (2,5‐PAA) was found to be clean and high yielding. This was in stark contrast to the bromination of the benzaldehyde starting material, the ketone precursor 2,5‐P2P and the dibenzylketone‐based impurity. Numerous brominated products were isolated from each of these reactions, many of which were novel compounds, and previously unreported as impurities in the literature. The unpredictable/nondescript nature of these brominations is likely to have a significant impact on the impurity profile of illicitly produced DOB.