6 resultados para Complex problems

em Digital Commons at Florida International University


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Optimization of adaptive traffic signal timing is one of the most complex problems in traffic control systems. This dissertation presents a new method that applies the parallel genetic algorithm (PGA) to optimize adaptive traffic signal control in the presence of transit signal priority (TSP). The method can optimize the phase plan, cycle length, and green splits at isolated intersections with consideration for the performance of both the transit and the general vehicles. Unlike the simple genetic algorithm (GA), PGA can provide better and faster solutions needed for real-time optimization of adaptive traffic signal control. ^ An important component in the proposed method involves the development of a microscopic delay estimation model that was designed specifically to optimize adaptive traffic signal with TSP. Macroscopic delay models such as the Highway Capacity Manual (HCM) delay model are unable to accurately consider the effect of phase combination and phase sequence in delay calculations. In addition, because the number of phases and the phase sequence of adaptive traffic signal may vary from cycle to cycle, the phase splits cannot be optimized when the phase sequence is also a decision variable. A "flex-phase" concept was introduced in the proposed microscopic delay estimation model to overcome these limitations. ^ The performance of PGA was first evaluated against the simple GA. The results show that PGA achieved both faster convergence and lower delay for both under- or over-saturated traffic conditions. A VISSIM simulation testbed was then developed to evaluate the performance of the proposed PGA-based adaptive traffic signal control with TSP. The simulation results show that the PGA-based optimizer for adaptive TSP outperformed the fully actuated NEMA control in all test cases. The results also show that the PGA-based optimizer was able to produce TSP timing plans that benefit the transit vehicles while minimizing the impact of TSP on the general vehicles. The VISSIM testbed developed in this research provides a powerful tool to design and evaluate different TSP strategies under both actuated and adaptive signal control. ^

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By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER) Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

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The major barrier to practical optimization of pavement preservation programming has always been that for formulations where the identity of individual projects is preserved, the solution space grows exponentially with the problem size to an extent where it can become unmanageable by the traditional analytical optimization techniques within reasonable limit. This has been attributed to the problem of combinatorial explosion that is, exponential growth of the number of combinations. The relatively large number of constraints often presents in a real-life pavement preservation programming problems and the trade-off considerations required between preventive maintenance, rehabilitation and reconstruction, present yet another factor that contributes to the solution complexity. In this research study, a new integrated multi-year optimization procedure was developed to solve network level pavement preservation programming problems, through cost-effectiveness based evolutionary programming analysis, using the Shuffled Complex Evolution (SCE) algorithm.^ A case study problem was analyzed to illustrate the robustness and consistency of the SCE technique in solving network level pavement preservation problems. The output from this program is a list of maintenance and rehabilitation treatment (M&R) strategies for each identified segment of the network in each programming year, and the impact on the overall performance of the network, in terms of the performance levels of the recommended optimal M&R strategy. ^ The results show that the SCE is very efficient and consistent in the simultaneous consideration of the trade-off between various pavement preservation strategies, while preserving the identity of the individual network segments. The flexibility of the technique is also demonstrated, in the sense that, by suitably coding the problem parameters, it can be used to solve several forms of pavement management programming problems. It is recommended that for large networks, some sort of decomposition technique should be applied to aggregate sections, which exhibit similar performance characteristics into links, such that whatever M&R alternative is recommended for a link can be applied to all the sections connected to it. In this way the problem size, and hence the solution time, can be greatly reduced to a more manageable solution space. ^ The study concludes that the robust search characteristics of SCE are well suited for solving the combinatorial problems in long-term network level pavement M&R programming and provides a rich area for future research. ^

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Multi-problem youth undergoing treatment for substance use problems are at high behavioral risk for exposure to sexually transmitted infections (STIs), including human immunodeficiency virus (HIV). Specific risk factors include childhood adversities such as maltreatment experiences and subsequent forms of psychopathology. The current study used a person-centered analytical approach to examine how childhood maltreatment experiences were related to patterns of psychiatric symptoms and HIV/STI risk behaviors in a sample of adolescents (N = 408) receiving treatment services. Data were collected in face-to-face interviews at two community-based facilities. Descriptive statistics and Latent Profile Analysis (LPA) were used to (a) classify adolescents into groups based on past year psychiatric symptoms, and (b) examine relations between class membership and forms of childhood maltreatment experiences, as well as past year sexual risk behavior (SRB). ^ LPA results indicated significant heterogeneity in psychiatric symptoms among the participants. The three classes generated via the optimal LPA solution included: (a) a low psychiatric symptoms class, (b) a high alcohol symptoms class and (c) a high internalizing symptoms class. Class membership was associated significantly with adolescents’ self-reported scores for childhood sexual abuse and emotional neglect. ANOVAs documented significant differences in mean scores for multiple indices of SRB indices by class membership, demonstrating differential risk for HIV/STI exposure across classes. The two classes characterized by elevated psychiatric symptom profiles and more severe maltreatment histories were at increased behavioral risk for HIV/STI exposure, compared to the low psychiatric symptoms class. The high internalizing symptoms class reported the highest scores for most of the indices of SRB assessed. The heterogeneity of psychiatric symptom patterns documented in the current study has important implications for HIV/STI prevention programs implemented with multi-problem youth. The results highlight complex relations between childhood maltreatment experiences, psychopathology and multiple forms of health risk behavior among adolescents. The results underscore the importance of further integration between substance abuse treatment and HIV/STI risk reduction efforts to improve morbidity and mortality among vulnerable youth. ^

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Structural Health Monitoring (SHM) systems were developed to evaluate the integrity of a system during operation, and to quickly identify the maintenance problems. They will be used in future aerospace vehicles to improve safety, reduce cost and minimize the maintenance time of a system. Many SHM systems were already developed to evaluate the integrity of plates and used in marine structures. Their implementation in manufacturing processes is still expected. The application of SHM methods for complex geometries and welds are two important challenges in this area of research. This research work started by studying the characteristics of piezoelectric actuators, and a small energy harvester was designed. The output voltages at different frequencies of vibration were acquired to determine the nonlinear characteristics of the piezoelectric stripe actuators. The frequency response was evaluated experimentally. AA battery size energy harvesting devices were developed by using these actuators. When the round and square cross section devices were excited at 50 Hz frequency, they generated 16 V and 25 V respectively. The Surface Response to Excitation (SuRE) and Lamb wave methods were used to estimate the condition of parts with complex geometries. Cutting tools and welded plates were considered. Both approaches used piezoelectric elements that were attached to the surfaces of considered parts. The variation of the magnitude of the frequency response was evaluated when the SuRE method was used. The sum of the square of the differences was calculated. The envelope of the received signal was used for the analysis of wave propagation. Bi-orthogonal wavelet (Binlet) analysis was also used for the evaluation of the data obtained during Lamb wave technique. Both the Lamb wave and SuRE approaches along with the three methods for data analysis worked effectively to detect increasing tool wear. Similarly, they detected defects on the plate, on the weld, and on a separate plate without any sensor as long as it was welded to the test plate.

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Multi-problem youth undergoing treatment for substance use problems are at high behavioral risk for exposure to sexually transmitted infections (STIs), including human immunodeficiency virus (HIV). Specific risk factors include childhood adversities such as maltreatment experiences and subsequent forms of psychopathology. The current study used a person-centered analytical approach to examine how childhood maltreatment experiences were related to patterns of psychiatric symptoms and HIV/STI risk behaviors in a sample of adolescents (N = 408) receiving treatment services. Data were collected in face-to-face interviews at two community-based facilities. Descriptive statistics and Latent Profile Analysis (LPA) were used to (a) classify adolescents into groups based on past year psychiatric symptoms, and (b) examine relations between class membership and forms of childhood maltreatment experiences, as well as past year sexual risk behavior (SRB). LPA results indicated significant heterogeneity in psychiatric symptoms among the participants. The three classes generated via the optimal LPA solution included: (a) a low psychiatric symptoms class, (b) a high alcohol symptoms class and (c) a high internalizing symptoms class. Class membership was associated significantly with adolescents’ self-reported scores for childhood sexual abuse and emotional neglect. ANOVAs documented significant differences in mean scores for multiple indices of SRB indices by class membership, demonstrating differential risk for HIV/STI exposure across classes. The two classes characterized by elevated psychiatric symptom profiles and more severe maltreatment histories were at increased behavioral risk for HIV/STI exposure, compared to the low psychiatric symptoms class. The high internalizing symptoms class reported the highest scores for most of the indices of SRB assessed. The heterogeneity of psychiatric symptom patterns documented in the current study has important implications for HIV/STI prevention programs implemented with multi-problem youth. The results highlight complex relations between childhood maltreatment experiences, psychopathology and multiple forms of health risk behavior among adolescents. The results underscore the importance of further integration between substance abuse treatment and HIV/STI risk reduction efforts to improve morbidity and mortality among vulnerable youth.