Applied operational research with SAS

Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work. The book is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, project management decisions, printed circuit board assembly, and multiple criteria decision making. The text begins with the algorithms and methods for linear programming, integer linear programming, and goal programming models. It then describes the principles of several OR procedures in SAS. Subsequent chapters explain how to use these procedures to solve various types of OR problems. Each of these chapters describes the concept of an OR problem, presents an example of the problem, and discusses the specific procedure and its macros for the optimal solution of the problem. The macros include data handling, model building, and report writing. While primarily designed for SAS users in OR and marketing analytics, the book can also be used by readers interested in mathematical modeling techniques. By formulating the OR problems as mathematical models, the authors show how SAS can solve a variety of optimization problems.

Summary of the 9th Workshop on Models@run.time

The Models@run.time workshop (MRT) series offers a discussion forum for the rising need to leverage modeling techniques at runtime for the software of the future. MRT has become a mature research topic, which is, e.g., reflected in separate sessions at conferences covering MRT approaches only. The target venues of the workshops audience changed from workshops to conferences. Hence, new topics in the area of MRT need to be identified, which are not yet mature enough for conferences. In consequence, the main goal of this edition was to reflect on the past decade of the workshop's history and to identify new future directions for the workshop.

Adaptability of nonlinear equilibrum models to central planning

Linear multisectoral models have for long been applied in the Hungarian national economic planning. Price-quantity correspondences and interaction, however, cannot easily be taken into account in the traditional linear framework. Computable general equilibrium modelers in the West have developed techniques which use extensively price-quantity interdependences. However, since they are usually presented with the controversial strict neoclassical interpretation, the possibility of their adaptation to socialist planning models has been concaled. This paper reflects on some results of a research investigating the possible adaptation of eqailibrium modeling techniques to central planning models.

Alcohol use and sexual victimization among Hispanic college women

Sexual victimization of young women typically occurs within a context of alcohol use, such that women are more likely to be victimized on days on which they consume alcohol compared to days on which no alcohol is consumed. Additionally, most research on sexual victimization of women has focused on forced sexual acts; consequently, little is known about forms sexual victimization that college women typically experience, such as brief (e.g., unwanted touching) or verbally coerced experiences (e.g., doing sexual things to prevent a partner from leaving). Finally, there is a need for more research on the processes underlying college women's drinking and the specific mechanisms through which drinking increases risk for sexual victimization. This dissertation sought to replicate recent findings of a temporal association between alcohol use and sexual victimization, and to investigate whether or not binge use increased risk for victimization, within a sample of young Hispanic college women, using repeated-measures logistic regression. This study also aimed to identify and explore typologies of victimization experiences in order to better understand types of sexual victimization common among young college women. Finally, the validity of a model of alcohol use and sexual victimization was investigated using structural equation modeling techniques. The results confirmed and extended previous research by demonstrating an increase in the conditional probability of sexual victimization on days of alcohol consumption compared with days of no alcohol consumption, and on days of binge alcohol consumption compared with days of moderate alcohol consumption. Sexual victimization experiences reported in this study were diverse, and cluster analysis was used to identify and explore specific typologies of victimization experiences, including intimate relationship victimization, brief victimization with stranger, prolonged victimization with acquaintance, and workplace victimization. The results from structural equation modeling (SEM) analyses were complex and helped to illuminate the relationships between reasons for drinking, alcohol use, childhood sexual abuse, sexual victimization, psychopathology, and acculturation-related factors among Hispanic college women. These findings have implications for the design of university-based prevention and intervention efforts aimed at reducing rates of alcohol-related sexual victimization within Hispanic populations.

Correlates of voluntary HIV testing and counseling among middle aged and older Latinas

This study identifies and describes HIV Voluntary Counseling and Testing (VCT) of middle aged and older Latinas. The rate of new cases of HIV in people age 45 and older is rapidly increasing, with a 40.6% increase in the numbers of older Latinas infected with HIV between 1998 and 2002. Despite this increase, there is paucity of research on this population. This research seeks to address the gap through a secondary data analysis of Latina women. The aim of this study is twofold: (1) Develop and empirically test a multivariate model of VCT utilization for middle aged and older Latinas; (2) To test how the three individual components of the Andersen Behavioral Model impact VCT for middle aged and older Latinas. The study is organized around the three major domains of the Andersen Behavioral Model of service use that include: (a) predisposing factors; (b) enabling characteristics and (c) need. Logistic regression using structural equation modeling techniques were used to test multivariate relationships of variables on VCT for a sample of 135 middle age and older Latinas residing in Miami-Dade County, Florida. Over 60% of participants had been tested for HIV. Provider endorsement was found to he the strongest predictor of VCT (odds ration [OR] 6.38), followed by having a clinic as a regular source of healthcare (OR=3.88). Significant negative associations with VCT included self rated health status (OR=.592); Age (OR=.927); Spanish proficiency (OR=.927); number of sexual partners (OR=.613) and consumption of alcohol during sexual activity (.549). As this line of inquiry provides a critical glimpse into the VCT of older Latinas, recommendations for enhanced service provision and research will he offered.

The Influence of Phosphorus on Periphyton Mats from the Everglades and Three Tropical Karstic Wetlands

The distinctive karstic, freshwater wetlands of the northern Caribbean and Central American region support the prolific growth of calcite-rich periphyton mats. Aside from the Everglades, very little research has been conducted in these karstic wetlands, which are increasingly threatened by eutrophication. This study sought to (i) test the hypothesis that water depth and periphyton total phosphorus (TP) content are both drivers of periphyton biomass in karstic wetland habitats in Belize, Mexico and Jamaica, (ii) provide a taxonomic inventory of the periphytic diatom species in these wetlands and (iii) examine the relationship between periphyton mat TP concentration and diatom assemblage at Everglades and Caribbean locations. ^ Periphyton biomass, nutrient and diatom assemblage data were generated from periphyton mat samples collected from shallow, marl-based wetlands in Belize, Mexico and Jamaica. These data were compared to a larger dataset collected from comparable sites within Everglades National Park. A diatom taxonomic inventory was conducted on the Caribbean samples and a combination of ordination and weighted-averaging modeling techniques were used to compare relationships between periphyton TP concentration, periphyton biomass and diatom assemblage composition among the locations. ^ Within the Everglades, periphyton biomass showed a negative correlation with water depth and mat TP, while periphyton mat percent organic content was positively correlated with these two variables. These patterns were also exhibited within the Belize, Mexico and Jamaica locations, suggesting that water depth and periphyton TP content are both drivers of periphyton biomass in karstic wetland systems within the northern Caribbean region. ^ A total of 146 diatom species representing 39 genera were recorded from the three Caribbean locations, including a distinct core group of species that may be endemic to this habitat type. Weighted averaging models were produced that effectively predicted mat TP concentration from diatom assemblages for both Everglades (R2=0.56) and Caribbean (R2=0.85) locations. There were, however, significant differences among Everglades and Caribbean locations with respect to species TP optima and indicator species. This suggests that although diatoms are effective indicators of water quality in these wetlands, differences in species response to water quality changes can reduce the predictive power of these indices when applied across systems. ^

An evaluation of functional impairment among children with anxiety disorders

Despite a considerable progress in developing and testing psychosocial treatments to reduce youth anxiety disorders, much remains to learn about the relation between anxiety symptom reduction and change in youth functional impairment. The specific aims of this dissertation thus were to examine: (1) the relation between different levels of anxiety and youth functional impairment ratings; (2) incremental validity of the Children Global Assessment Scale (CGAS); (3) the mediating role of anxiety symptom reduction on youth functional impairment ratings; (4) the directionality of change between anxiety symptom reduction and youth functional impairment; (5) the moderating effects of youth age, sex, and ethnicity on the mediated relation between youth anxiety symptom reduction and change in functional impairment; and (6) an agreement (or lack thereof) between youths and their parents in their views of change in youth functional impairment vis-à-vis anxiety symptom reduction. ^ The results were analyzed using archival data set acquired from 183 youths and their mothers. Research questions were tested using SPSS and structural equation modeling techniques in Mplus. ^ The results supported the efficacy of psychosocial treatments to reduce the severity of youth anxiety symptoms and its associated functional impairment. Moreover, the results revealed that at posttreatment, youths who scored either low or medium on anxiety levels scored significantly lower on impairment, than youths who scored high on anxiety levels. Incremental validity of the CGAS was also revealed across all assessment points and informants in my sample. In addition, the results indicated the mediating role of anxiety symptom reduction with respect to change in youth functional impairment at posttest, regardless of the youth’s age, sex, and ethnicity. No significant findings were observed with regard to the bidirectionality and an informant disagreement vis-à-vis the relation between anxiety symptom reduction and change in functional impairment. ^ The study’s main contributions and potential implications on theoretical, empirical, and clinical levels are further discussed. The emphasis is on the need to enhance existing evidence-based treatments and develop innovative treatment models that will not only reduce youth’s symptoms (such anxiety) but also evoke genuine and palpable improvements in lives of youths and their families.^

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

A model of self -transformative identity development in troubled adolescent youth

Within the Stage II program evaluation of the Miami Youth Development Project's (YDP) Changing Lives Program (CLP), this study evaluated CLP intervention effectiveness in promoting positive change in emotion-focused identity exploration (i.e. feelings of personal expressiveness; PE) and a "negative" symptom of identity development (i.e. identity distress; ID) as a first step toward the investigation of a self-transformative model of identity development in adolescent youth. Using structural equation modeling techniques, this study found that participation in the CLP is associated with positive changes in PE (path = .841, p < .002), but not changes in ID. Increase in ID scores was found to be associated with increases in PE (path = .229, p < .002), as well. Intervention effects were not moderated by age/stage, gender, or ethnicity, though differences were found in the degree to which participating subgroups (African-American/Hispanic, male/female, 14-16 years old/17-19 years old) experience change in PE and ID. Findings also suggest that moderate levels of ID may not be deleterious to identity exploration and may be associated with active exploration. ^

A model of self-transformative identity development in troubled adolescent youth

Within the Stage II program evaluation of the Miami Youth Development Project's (YDP) Changing Lives Program (CLP), this study evaluated CLP intervention effectiveness in promoting positive change in emotion-focused identity exploration (i.e. feelings of personal expressiveness; PE) and a "negative" symptom of identity development (i.e. identity distress; ID) as a first step toward the investigation of a self-transformative model of identity development in adolescent youth. Using structural equation modeling techniques, this study found that participation in the CLP is associated with positive changes in PE (path = .841, p < .002), but not changes in ID. Increase in ID scores was found to be associated with increases in PE (path = .229, p < .002), as well. Intervention effects were not moderated by age/stage, gender, or ethnicity, though differences were found in the degree to which participating subgroups (African- American/Hispanic, male/female, 14-16 years old/17-19 years old) experience change in PE and ID. Findings also suggest that moderate levels of ID may not be deleterious to identity exploration and may be associated with active exploration.

Seismic Retrofitting of a Historic Structure with Limited Construction Documentation

Many buildings constructed during the middle of the 20th century were constructed with criteria that fall short of current requirements. Although shortcomings are possible in all aspects of the design, the inadequacies in terms of seismic design present a more pressing issue to human life. This risk has been seen in various earthquakes that have struck Italy recently, and subsequently, the codes have been altered to account for this underestimated danger. Structures built after these changes remain at risk and must be retrofitted depending on their use. This report centers around the Giovanni Michelucci Institute of Mathematics at the University of Bologna and the work required to modify the building so that it can withstand 60% of the current design requirements. The goal of this particular report is to verify the previous reports written in Italian and present an accurate analysis along with intervention suggestions for this particular building. The work began with an investigation into the previous sources and work to find out how the structure had been interpreted. After understanding the building, corrections were made where required, and the failing elements were organized graphically to more easily show where the building needed the most work. Once the critical zones were mapped, remediation techniques were tested on the top floor, and the modeling techniques and effects of the interventions were presented to assist in further work on the structure.

Memory-Based Attentional Guidance: A Window to the Relationship between Working Memory and Attention

Attention, the cognitive means by which we prioritize the processing of a subset of information, is necessary for operating efficiently and effectively in the world. Thus, a critical theoretical question is how information is selected. In the visual domain, working memory (WM)—which refers to the short-term maintenance and manipulation of information that is no longer accessible by the senses—has been highlighted as an important determinant of what is selected by visual attention. Furthermore, although WM and attention have traditionally been conceived as separate cognitive constructs, an abundance of behavioral and neural evidence indicates that these two domains are in fact intertwined and overlapping. The aim of this dissertation is to better understand the nature of WM and attention, primarily through the phenomenon of memory-based attentional guidance, whereby the active maintenance of items in visual WM reliably biases the deployment of attention to memory-matching items in the visual environment. The research presented here employs a combination of behavioral, functional imaging, and computational modeling techniques that address: (1) WM guidance effects with respect to the traditional dichotomy of top-down versus bottom-up attentional control; (2) under what circumstances the contents of WM impact visual attention; and (3) the broader hypothesis of a predictive and competitive interaction between WM and attention. Collectively, these empirical findings reveal the importance of WM as a distinct factor in attentional control and support current models of multiple-state WM, which may have broader implications for how we select and maintain information.

Using Helix-coil Models to Study Protein Unfolded States

An abstract of a thesis devoted to using helix-coil models to study unfolded states.\\

Research on polypeptide unfolded states has received much more attention in the last decade or so than it has in the past. Unfolded states are thought to be implicated in various

misfolding diseases and likely play crucial roles in protein folding equilibria and folding rates. Structural characterization of unfolded states has proven to be

much more difficult than the now well established practice of determining the structures of folded proteins. This is largely because many core assumptions underlying

folded structure determination methods are invalid for unfolded states. This has led to a dearth of knowledge concerning the nature of unfolded state conformational

distributions. While many aspects of unfolded state structure are not well known, there does exist a significant body of work stretching back half a century that

has been focused on structural characterization of marginally stable polypeptide systems. This body of work represents an extensive collection of experimental

data and biophysical models associated with describing helix-coil equilibria in polypeptide systems. Much of the work on unfolded states in the last decade has not been devoted

specifically to the improvement of our understanding of helix-coil equilibria, which arguably is the most well characterized of the various conformational equilibria

that likely contribute to unfolded state conformational distributions. This thesis seeks to provide a deeper investigation of helix-coil equilibria using modern

statistical data analysis and biophysical modeling techniques. The studies contained within seek to provide deeper insights and new perspectives on what we presumably

know very well about protein unfolded states. \\

Chapter 1 gives an overview of recent and historical work on studying protein unfolded states. The study of helix-coil equilibria is placed in the context

of the general field of unfolded state research and the basics of helix-coil models are introduced.\\

Chapter 2 introduces the newest incarnation of a sophisticated helix-coil model. State of the art modern statistical techniques are employed to estimate the energies

of various physical interactions that serve to influence helix-coil equilibria. A new Bayesian model selection approach is utilized to test many long-standing

hypotheses concerning the physical nature of the helix-coil transition. Some assumptions made in previous models are shown to be invalid and the new model

exhibits greatly improved predictive performance relative to its predecessor. \\

Chapter 3 introduces a new statistical model that can be used to interpret amide exchange measurements. As amide exchange can serve as a probe for residue-specific

properties of helix-coil ensembles, the new model provides a novel and robust method to use these types of measurements to characterize helix-coil ensembles experimentally

and test the position-specific predictions of helix-coil models. The statistical model is shown to perform exceedingly better than the most commonly used

method for interpreting amide exchange data. The estimates of the model obtained from amide exchange measurements on an example helical peptide

also show a remarkable consistency with the predictions of the helix-coil model. \\

Chapter 4 involves a study of helix-coil ensembles through the enumeration of helix-coil configurations. Aside from providing new insights into helix-coil ensembles,

this chapter also introduces a new method by which helix-coil models can be extended to calculate new types of observables. Future work on this approach could potentially

allow helix-coil models to move into use domains that were previously inaccessible and reserved for other types of unfolded state models that were introduced in chapter 1.

ThreeDimensional Epigraphic Recording at Stobi (Former Yugoslav Republic of Macedonia): Creating a Virtual Lapidarium

There is an increased need for 3D recording of archaeological sites and digital preservation of their artifacts. Digital photogrammetry with prosumer DSLR cameras is a suitable tool for recording epigraphy in particular, as it allows for the recording of inscribed surfaces with very high accuracy, often better than 2 mm and with only a short time spent in the field. When photogrammetry is fused with other computational photography techniques like panoramic tours and Reflectance Transformation Imaging, a workflow exists to rival traditional LiDAR­based methods. The difficulty however, arises in the presentation of 3D data. It requires an enormous amount of storage and end­user sophistication. The proposed solution is to use game­engine technology and high definition virtual tours to provide not only scholars, but also the general public with an uncomplicated interface to interact with the detailed 3D epigraphic data. The site of Stobi, located near Gradsko, in the Former Yugoslav Republic of Macedonia (FYROM) was used as a case study to demonstrate the effectiveness of RTI, photogrammetry and virtual tour imaging working in combination. A selection of nine sets of inscriptions from the archaeological site were chosen to demonstrate the range of application for the techniques. The chosen marble, sandstone and breccia inscriptions are representative of the varying levels of deterioration and degradation of the epigraphy at Stobi, in which both their rates of decay and resulting legibility is varied. This selection includes those which are treated and untreated stones as well as those in situ and those in storage. The selection consists of both Latin and Greek inscriptions with content ranging from temple dedication inscriptions to statue dedications. This combination of 3D modeling techniques presents a cost and time efficient solution to both increase the legibility of severely damaged stones and to digitally preserve the current state of the inscriptions.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model