Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

Evidence of climate variability and tropical cyclone activity from diatom assemblage dynamics in coastal southwest Florida

Estuaries are dynamic on many spatial and temporal scales. Distinguishing effects of unpredictable events from cyclical patterns can be challenging but important to predict the influence of press and pulse drivers in the face of climate change. Diatom assemblages respond rapidly to changing environmental conditions and characterize change on multiple time scales. The goals of this research were to 1) characterize diatom assemblages in the Charlotte Harbor watershed, their relationships with water quality parameters, and how they change in response to climate; and 2) use assemblages in sediment cores to interpret past climate changes and tropical cyclone activity. ^ Diatom assemblages had strong relationships with salinity and nutrient concentrations, and a quantitative tool was developed to reconstruct past values of these parameters. Assemblages were stable between the wet and dry seasons, and were more similar to each other than to assemblages found following a tropical cyclone. Diatom assemblages following the storm showed a decrease in dispersion among sites, a pattern that was consistent on different spatial scales but may depend on hydrological management regimes. ^ Analysis of sediment cores from two southwest Florida estuaries showed that locally-developed diatom inference models can be applied with caution on regional scales. Large-scale climate changes were suggested by environmental reconstructions in both estuaries, but with slightly different temporal pacing. Estimates of salinity and nutrient concentrations suggested that major hydrological patterns changed at approximately 5.5 and 3 kyrs BP. A highly temporally-resolved sediment core from Charlotte Harbor provided evidence for past changes that correspond with known climate records. Diatom assemblages had significant relationships with the three-year average index values of the Atlantic Multidecadal Oscillation and the El Niño Southern Oscillation. Assemblages that predicted low salinity and high total phosphorus also had the lowest dispersion and corresponded with some major storms in the known record, which together may provide a proxy for evidence of severe storms in the paleoecological record. ^

Hybrid multi-objective optimization and hybridized self-organizing response surface method

Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.

Optimization of transit transfer times: A system-wide approach

This dissertation presents a system-wide approach, based on genetic algorithms, for the optimization of transfer times for an entire bus transit system. Optimization of transfer times in a transit system is a complicated problem because of the large set of binary and discrete values involved. The combinatorial nature of the problem imposes a computational burden and makes it difficult to solve by classical mathematical programming methods. ^ The genetic algorithm proposed in this research attempts to find an optimal solution for the transfer time optimization problem by searching for a combination of adjustments to the timetable for all the routes in the system. It makes use of existing scheduled timetables, ridership demand at all transfer locations, and takes into consideration the randomness of bus arrivals. ^ Data from Broward County Transit are used to compute total transfer times. The proposed genetic algorithm-based approach proves to be capable of producing substantial time savings compared to the existing transfer times in a reasonable amount of time. ^ The dissertation also addresses the issues related to spatial and temporal modeling, variability in bus arrival and departure times, walking time, as well as the integration of scheduling and ridership data. ^

Mediational effects in cognitive behavioral treatment for anxiety disorders in children and adolescents

The current study examined whether variables that have been found to influence treatment outcome serve as mediators of a child and adolescent cognitive behavioral treatment (CBT) anxiety program at multiple time points throughout the intervention. The study also examined mediating variables measured at multiple time points during treatment to determine the time lags necessary for changes in the mediator variable to translate into changes on treatment gains. Participants were 168 youth (ages 6 to 16 years; 54% males) and their mothers who presented to the Child Anxiety and Phobia Program (CAPP) at Florida International University (FIU). Overall, results indicate that the mediators at multiple time points influenced youth anxiety in a fluctuating manner, such that a decrease in skills at one given session caused changes in youth anxiety at a later session. This dynamic between the mediator and outcome may be reflective of the process of therapeutic change and suggests that skills gained from session to session took time to exert their effect on youth anxiety. The methodology employed helps to elucidate how variables mediate treatment outcome in youth anxiety disorders.

Minimizing makespan for hybrid flowshops with batch, discrete processing machines and arbitrary job sizes

This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.

Long-Term Effects of Adding Nutrients to an Oligotrophic Coastal Environment

Management of ecological disturbances requires an understanding of the time scale and dynamics of community responses to disturbance events. To characterize long-term seagrass bed responses to nutrient enrichment, we established six study sites in Florida Bay, USA. In 24 plots (0.25 m2) at each site, we regularly added nitrogen (N) and phosphorus (P) in a factorial design for 7 years. Five of the six sites exhibited strong P limitation. Over the first 2 years, P enrichment increased Thalassia testudinum cover in the three most P-limited sites. After 3 years, Halodule wrightii began to colonize many of the P-addition plots, but the degree of colonization was variable among sites, possibly due to differences in the supply of viable propagules. Thalassia increased its allocation to aboveground tissue in response to P enrichment; Halodule increased in total biomass but did not appear to change its aboveground: belowground tissue allocation. Nutrient enrichment did not cause macroalgal or epiphytic overgrowth of the seagrass. Nitrogen retention in the study plots was variable but relatively low, whereas phosphorus retention was very high, often exceeding 100% of the P added as fertilizer over the course of our experiments. Phosphorus retentions exceeding 100% may have been facilitated by increases in Thalassia aboveground biomass, which promoted the settlement of suspended particulate matter containing phosphorus. Our study demonstrated that lowintensity press disturbance events such as phosphorus enrichment can initiate a slow, ramped successional process that may alter community structure over many years.

Periphyton as an indicator of restoration in the Everglades

Periphyton communities dominate primary production in much of the Florida Everglades wetland and therefore contribute to soil production, ecosystem metabolism and secondary production as well as the composition of dependent communities. Decades of research in the Everglades have supported research findings from other wetland types that cumulatively show that periphyton communities respond very rapidly to alterations in the two dominant drivers of wetland structure and function—hydrology and water quality. Hydrology controls periphyton productivity and composition by regulating moisture availability, substrate types available for colonization and supply of nutrients. Nutrients, particularly the limiting nutrient in this system, phosphorus (P), control levels of production and community composition. Because periphyton communities are well-established to be related to hydrology and water quality, an indicator was developed based on three periphyton attributes: abundance, quality (i.e., nutrient content) and community composition. This assessment tool offers a qualitative assessment of ecosystem response to potential changes in management activities at a time scale appropriate for active management. An example is provided of how the indicator can be used to assess the current water quality and hydrological conditions from high-density spatial surveys. Detected patterns of deterioration align with expectations derived from model predictions and known sources of nutrients and unnatural hydrologic regimes. If employed adaptively in ecosystem management, this tool can be used to both detect and react to change before the system has been irreparably altered.

Impacts of hurricanes on surface water flow within a wetland

Between 2001 and 2005, seven category 3 or higher major hurricanes made landfall within the US. The hydrologic impacts of these distinct climatic phenomena frequently occurring in wetland watersheds, however, are not well understood. The focus of this study was to evaluate the impacts of hurricane wind and rainfall conditions on water velocity and water elevations within the study wetland, the Florida Everglades. Specifically water velocity data was measured near two tree islands (Gumbo Limbo (GL) and Satin Leaf (SL)) and wind speed, water elevation, and rainfall were obtained from nearby wind observation stations. During the direct impacts of the hurricanes (Hurricanes Katrina and Wilma), water speed, flow direction, and hydraulic gradients were altered, and the extent of variation was positively related to wind characteristics, with significant alterations in flow direction at depth during Hurricane Wilma due to higher wind speeds. After the direct impacts, the longer lasting effect of hurricanes (time scale of a few days) resulted in altered flow speeds that changed by 50% or less. These longer lasting changes in flow speeds may be due to the redistribution of emergent vegetation.

Sediment accretion and organic carbon burial relative to sea-level rise and storm events in two mangrove forests in Everglades National Park

The goal of this investigation was to examine how sediment accretion and organic carbon (OC) burial rates in mangrove forests respond to climate change. Specifically, will the accretion rates keep pace with sea-level rise, and what is the source and fate of OC in the system? Mass accumulation, accretion and OC burial rates were determined via 210Pb dating (i.e. 100 year time scale) on sediment cores collected from two mangrove forest sites within Everglades National Park, Florida (USA). Enhanced mass accumulation, accretion and OC burial rates were found in an upper layer that corresponded to a well-documented storm surge deposit. Accretion rates were 5.9 and 6.5 mm yr− 1 within the storm deposit compared to overall rates of 2.5 and 3.6 mm yr− 1. These rates were found to be matching or exceeding average sea-level rise reported for Key West, Florida. Organic carbon burial rates were 260 and 393 g m− 2 yr− 1 within the storm deposit compared to 151 and 168 g m− 2 yr− 1 overall burial rates. The overall rates are similar to global estimates for OC burial in marine wetlands. With tropical storms being a frequent occurrence in this region the resulting storm surge deposits are an important mechanism for maintaining both overall accretion and OC burial rates. Enhanced OC burial rates within the storm deposit could be due to an increase in productivity created from higher concentrations of phosphorus within storm-delivered sediments and/or from the deposition of allochthonous OC. Climate change-amplified storms and sea-level rise could damage mangrove forests, exposing previously buried OC to oxidation and contribute to increasing atmospheric CO2 concentrations. However, the processes described here provide a mechanism whereby oxidation of OC would be limited and the overall OC reservoir maintained within the mangrove forest sediments.

Lake metabolism and the diel oxygen technique: State of the science

Significant improvements have been made in estimating gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) from diel, “free-water” changes in dissolved oxygen (DO). Here we evaluate some of the assumptions and uncertainties that are still embedded in the technique and provide guidelines on how to estimate reliable metabolic rates from high-frequency sonde data. True whole-system estimates are often not obtained because measurements reflect an unknown zone of influence which varies over space and time. A minimum logging frequency of 30 min was sufficient to capture metabolism at the daily time scale. Higher sampling frequencies capture additional pattern in the DO data, primarily related to physical mixing. Causes behind the often large daily variability are discussed and evaluated for an oligotrophic and a eutrophic lake. Despite a 3-fold higher day-to-day variability in absolute GPP rates in the eutrophic lake, both lakes required at least 3 sonde days per week for GPP estimates to be within 20% of the weekly average. A sensitivity analysis evaluated uncertainties associated with DO measurements, piston velocity (k), and the assumption that daytime R equals nighttime R. In low productivity lakes, uncertainty in DO measurements and piston velocity strongly impacts R but has no effect on GPP or NEP. Lack of accounting for higher R during the day underestimates R and GPP but has no effect on NEP. We finally provide suggestions for future research to improve the technique.

Evidence of the heterogeneous market hypothesis using wavelet multi -resolution analysis

In finance literature many economic theories and models have been proposed to explain and estimate the relationship between risk and return. Assuming risk averseness and rational behavior on part of the investor, the models are developed which are supposed to help in forming efficient portfolios that either maximize (minimize) the expected rate of return (risk) for a given level of risk (rates of return). One of the most used models to form these efficient portfolios is the Sharpe's Capital Asset Pricing Model (CAPM). In the development of this model it is assumed that the investors have homogeneous expectations about the future probability distribution of the rates of return. That is, every investor assumes the same values of the parameters of the probability distribution. Likewise financial volatility homogeneity is commonly assumed, where volatility is taken as investment risk which is usually measured by the variance of the rates of return. Typically the square root of the variance is used to define financial volatility, furthermore it is also often assumed that the data generating process is made of independent and identically distributed random variables. This again implies that financial volatility is measured from homogeneous time series with stationary parameters. In this dissertation, we investigate the assumptions of homogeneity of market agents and provide evidence for the case of heterogeneity in market participants' information, objectives, and expectations about the parameters of the probability distribution of prices as given by the differences in the empirical distributions corresponding to different time scales, which in this study are associated with different classes of investors, as well as demonstrate that statistical properties of the underlying data generating processes including the volatility in the rates of return are quite heterogeneous. In other words, we provide empirical evidence against the traditional views about homogeneity using non-parametric wavelet analysis on trading data, The results show heterogeneity of financial volatility at different time scales, and time-scale is one of the most important aspects in which trading behavior differs. In fact we conclude that heterogeneity as posited by the Heterogeneous Markets Hypothesis is the norm and not the exception.

Sediment Accretion and Organic Carbon Burial Relative to Sea-Level Rise and Storm Events in Two Mangrove Forests in Everglades National Park

The goal of this investigation was to examine how sediment accretion and organic carbon (OC) burial rates in mangrove forests respond to climate change. Specifically, will the accretion rates keep pace with sea-level rise, and what is the source and fate of OC in the system? Mass accumulation, accretion and OC burial rates were determined via 210Pb dating (i.e. 100 year time scale) on sediment cores collected from two mangrove forest sites within Everglades National Park, Florida (USA). Enhanced mass accumulation, accretion and OC burial rates were found in an upper layer that corresponded to a well-documented storm surge deposit. Accretion rates were 5.9 and 6.5 mm yr− 1 within the storm deposit compared to overall rates of 2.5 and 3.6 mm yr− 1. These rates were found to be matching or exceeding average sea-level rise reported for Key West, Florida. Organic carbon burial rates were 260 and 393 g m− 2 yr− 1 within the storm deposit compared to 151 and 168 g m− 2 yr− 1 overall burial rates. The overall rates are similar to global estimates for OC burial in marine wetlands. With tropical storms being a frequent occurrence in this region the resulting storm surge deposits are an important mechanism for maintaining both overall accretion and OC burial rates. Enhanced OC burial rates within the storm deposit could be due to an increase in productivity created from higher concentrations of phosphorus within storm-delivered sediments and/or from the deposition of allochthonous OC. Climate change-amplified storms and sea-level rise could damage mangrove forests, exposing previously buried OC to oxidation and contribute to increasing atmospheric CO2 concentrations. However, the processes described here provide a mechanism whereby oxidation of OC would be limited and the overall OC reservoir maintained within the mangrove forest sediments.