Optimization of pavement maintenance and rehabilitation programming using shuffled complex evolution algorithm

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. ^

Practical secure information flow in programming languages

If we classify variables in a program into various security levels, then a secure information flow analysis aims to verify statically that information in a program can flow only in ways consistent with the specified security levels. One well-studied approach is to formulate the rules of the secure information flow analysis as a type system. A major trend of recent research focuses on how to accommodate various sophisticated modern language features. However, this approach often leads to overly complicated and restrictive type systems, making them unfit for practical use. Also, problems essential to practical use, such as type inference and error reporting, have received little attention. This dissertation identified and solved major theoretical and practical hurdles to the application of secure information flow. ^ We adopted a minimalist approach to designing our language to ensure a simple lenient type system. We started out with a small simple imperative language and only added features that we deemed most important for practical use. One language feature we addressed is arrays. Due to the various leaking channels associated with array operations, arrays have received complicated and restrictive typing rules in other secure languages. We presented a novel approach for lenient array operations, which lead to simple and lenient typing of arrays. ^ Type inference is necessary because usually a user is only concerned with the security types for input/output variables of a program and would like to have all types for auxiliary variables inferred automatically. We presented a type inference algorithm B and proved its soundness and completeness. Moreover, algorithm B stays close to the program and the type system and therefore facilitates informative error reporting that is generated in a cascading fashion. Algorithm B and error reporting have been implemented and tested. ^ Lastly, we presented a novel framework for developing applications that ensure user information privacy. In this framework, core computations are defined as code modules that involve input/output data from multiple parties. Incrementally, secure flow policies are refined based on feedback from the type checking/inference. Core computations only interact with code modules from involved parties through well-defined interfaces. All code modules are digitally signed to ensure their authenticity and integrity. ^

Reduced-parameter model of head-related transfer functions for synthesized spatial audio

Digital systems can generate left and right audio channels that create the effect of virtual sound source placement (spatialization) by processing an audio signal through pairs of Head-Related Transfer Functions (HRTFs) or, equivalently, Head-Related Impulse Responses (HRIRs). The spatialization effect is better when individually-measured HRTFs or HRIRs are used than when generic ones (e.g., from a mannequin) are used. However, the measurement process is not available to the majority of users. There is ongoing interest to find mechanisms to customize HRTFs or HRIRs to a specific user, in order to achieve an improved spatialization effect for that subject. Unfortunately, the current models used for HRTFs and HRIRs contain over a hundred parameters and none of those parameters can be easily related to the characteristics of the subject. This dissertation proposes an alternative model for the representation of HRTFs, which contains at most 30 parameters, all of which have a defined functional significance. It also presents methods to obtain the value of parameters in the model to make it approximately equivalent to an individually-measured HRTF. This conversion is achieved by the systematic deconstruction of HRIR sequences through an augmented version of the Hankel Total Least Squares (HTLS) decomposition approach. An average 95% match (fit) was observed between the original HRIRs and those re-constructed from the Damped and Delayed Sinusoids (DDSs) found by the decomposition process, for ipsilateral source locations. The dissertation also introduces and evaluates an HRIR customization procedure, based on a multilinear model implemented through a 3-mode tensor, for mapping of anatomical data from the subjects to the HRIR sequences at different sound source locations. This model uses the Higher-Order Singular Value Decomposition (HOSVD) method to represent the HRIRs and is capable of generating customized HRIRs from easily attainable anatomical measurements of a new intended user of the system. Listening tests were performed to compare the spatialization performance of customized, generic and individually-measured HRIRs when they are used for synthesized spatial audio. Statistical analysis of the results confirms that the type of HRIRs used for spatialization is a significant factor in the spatialization success, with the customized HRIRs yielding better results than generic HRIRs.

``This is your brain on drugs'': The public policy of anti -drug programming. An exploratory analysis of media and other sources of drug information for adolescents

In the 1980s, government agencies sought to utilize research on drug use prevention to design media campaigns. Enlisting the assistance of the national media, several campaigns were designed and initiated to bring anti-drug use messages to adolescents in the form of public service advertising. This research explores the sources of information selected by adolescents in grades 7 through 12 and how the selection of media and other sources of information relate to drug use behavior and attitudes and perceptions related to risk/harm and disapproval of friends' drug-using activities.^ Data collected from 1989 to 1992 in the Miami Coalition School Survey provided a random selection of secondary school studies. The responses of these students were analyzed using multivariate statistical techniques.^ Although many of the students selected media as the source for most of their information on the effects of drugs on the people who use them, the selection of media was found to be positively related to alcohol use and negatively related to marijuana use. The selection of friends, brothers, or sisters was a statistically significant source for adolescents who smoke cigarettes, use alcohol or marijuana.^ The results indicate that the anti-drug use messages received by students may be canceled out by media messages perceived to advocate substance use and that a more persuasive source of information for adolescents may be friends and siblings. As federal reports suggest that the economic costs of drug abuse will reach an estimated $150 billion by 1997 if current trends continue, prevention policy that addresses the glamorization of substance use remains a national priority. Additionally, programs that advocate prevention within the peer cluster must be supported, as peers are an influential source for both inspiring and possibly preventing drug use behavior. ^

A survey of music educator's understanding and use of advanced audio technology in their instructional methods and strategies

This study examines the correlation between how certified music educators understand audio technology and how they incorporate it in their instructional methods. Participants were classroom music teachers selected from fifty middle schools in Miami- Dade Public Schools. The study adopted a non-experimental research design in which a survey was the primary tool of investigation. The findings reveal that a majority of middle school music teachers in Miami-Dade are not familiar with advanced audiorecording software or any other digital device dedicated to the recording and processing of audio signals. Moreover, they report a lack of opportunities to develop this knowledge. Younger music teachers, however, are more open to developing up-to-date instructional methodologies. Most of the participants agreed that music instruction should be a platform for preparing students for a future in the entertainment industry. A basic knowledge of music business should be delivered to students enrolled in middle-school music courses.