Development of a Probabilistic Multi-Class Model Selection Algorithm for High-Dimensional and Complex Data

The development of quantifiable measures of uncertainty in forensic conclusions has resulted in the debut of several ad-hoc methods for approximating the weight of evidence (WoE). In particular, forensic researchers have attempted to use similarity measures, or scores, to approximate the weight of evidence characterized by highdimensional and complex data. Score-based methods have been proposed to approximate theWoE for numerous evidence types (e.g., fingerprints, handwriting, inks, voice analysis). In general, scorebased methods consider the score as a projection onto the real line. For example, the score-based likelihood ratio evaluates and compares the likelihoods of a score calculated between two objects in two density functions, based on sampling distributions of the score under two mutually exclusive propositions. Other score-based methods have been proposed [6, 7, 31, 82], which do not rely on such a ratio. This dissertation focuses on a class of kernel-based algorithms that fall in the latter group of score-based methods, and introduces a model that serves to complete the class of kernel-based algorithms initiated under NIJ Awards 2009-DN-BX-K234 and 2015-R2-CX-0028, which addressed the “outlier detection” and “common source” problems, by proposing a fully probabilistic model for addressing the “specific source” problem. This “specific source” problem is addressed in three progressive models: first, the problem is addressed for a pair of fixed sources; next, the two-class model is extended to consider multiple fixed sources; finally, a kernel-based model selection algorithm is developed to consider a single fixed source juxtaposed with multiple random sources. This class of algorithms relates pairs of high-dimensional, complex objects through a kernel function to obtain a vector of within-source and between-source scores, and capitalizes on the variability that exists within and between these sets of scores. The model makes no assumptions about the type or dimension of data to which it can be applied, and can be tailored to any type of data by modifying the kernel function at the core of the model. In addition, this algorithm provides a naturally probabilistic, multi-class, and compact alternative to current kernel-based pattern recognition methods such as support vector machines, relevance vector machines, and approximate Bayesian computation methods

Born in Service: Birth Experiences in Military vs. Civilian Hospitals

As women have increasingly entered the military or received health care as military dependents, the quintessential feminine experience of giving birth collides with an intensely masculine realm. This study examines if birth experiences differ between military and civilian health care facilities. Specifically, I interviewed women on perceived quality of care, the frequency of self-reported complications, and whether they reported an overall positive or negative birth experience during prenatal care, labor, and delivery. Results suggest that excellent care during delivery occurs in either environment. However, continuity of care (or lack thereof) and the lack of physical space exclusively for birth negatively affected the perceived quality of the birth experience for some military families. I discuss specific recommendations for how military facilities might improve the birth experience through small structural and organizational changes to positively affect the birth environment for women leading to better birth experience outcomes

Eliminating the lost time interval of law enforcement to active shooter events in schools

The Newtown Connecticut school attack at the Sandy Hook elementary school on December 14, 2012, was another example of the tragedy of mass murder. When a targeted attack occurs, the victims must await the arrival of law enforcement personnel to address the threat and stop the loss; this lost time interval results in extending the duration of a targeted attack until police can resist an attacker. In the absence of onsite personnel trained to resist an attacker, such as a school resource officer, students and staff are at the mercy of an attacker. This thesis asked the question: Can existing resources be leveraged to increase available capacities in actively resisting an active shooter in a targeted school attack to eliminate or reduce the lost time interval of law enforcement during an attack on an American school especially in low resource areas, such as rural and/or isolated communities. Case studies were completed to identify opportunities to reduce the loss incurred in these attacks with an emphasis on reducing the duration of an incident when prevention measures had failed. The value of collaboration and necessity to leverage resources in the public safety sector is well researched and critical resources with the capacity to operate in an offensive posture are available through planning and preparedness. Relationships can be developed between different domains and disciplines within a community to create a multidisciplinary environment of safety with the capacity to prevent or reduce loss through violence. Through these relationships, a culture can be created that combines strategies and tactics for prevention, as well as a response to these tragedies. A culture of security can replace vulnerability and result in a greater level of confidence in the ability to keep this nation’s schools safer.http://archive.org/details/eliminatinglostt1094547227Assistant Fire Chief, Omaha Fire Department, Omaha, NebraskaApproved for public release; distribution is unlimited

Concurrent Sessions B: Modeling and Design - 2-Dimensional Hydraulic Modeling of a Low-Head Dam Retrofit and Implications for Design

Adaptive Hydraulics (AdH) was used to model a recently constructed low-head dam retrofit project in which boulders were used to create a step-pool sequence that allows fish passage. AdH is a 2-dimensional hydraulic model developed by the US Army Corps of Engineers. Detailed survey data of the retrofit project was taken by using a 3D scanner during a dry period in which no water was flowing through the project. The 3D scanner is capable of creating an accurate 3D surface by generating points within millimeters of each other. AdH was used to model the existing retrofit project, and the results were compared to HEC-RAS results. HEC-RAS, a 1-dimensional hydraulic model that was also developed by the US Army Corps of Engineers, is often used in the design of in-stream structures and retrofit projects such as these because it is a well-known model, easy to use, and does an excellent job of predicting upstream impacts a project may cause; however one of its primary limitations is its inability to model localized velocities. The modeling effort with AdH provides a more detailed view of the hydraulics through all portions of the retrofit project in various flow conditions. In addition, various boulder spacing’s were modeled to determine impacts on velocities and forces that would act on individual boulders. Gaining a better understanding of localized velocities and forces enables the desktop design to incorporate a more natural boulder layout, which is beneficial for aesthetics. The natural boulder layout can also be used to create variable velocities through a given cross section at a given flow and could be used to target various fish species at various life stages in future designs

Braak Stage And Trajectory Of Cognitive Decline In Noncognitively Impaired Elders

In a previous cross-sectional study, we found that nondemented elderly participants from the Rush Religious Orders Study (RROS) displayed a wide range of Braak neurofibrillary tangle and amyloid plaque pathology similar to that seen in prodromal and frank Alzheimer\u27s disease. Here, we examined longitudinal changes in cognitive domains in subjects from this cohort grouped by Braak stage using linear mixed effects models. We found that the trajectory of episodic memory composite (EMC), executive function composite (EFC), and global cognitive composite scores (GCS: average of EMC and EFC scores) was significantly associated with age at visit over time, but not with Braak stage, apolipoprotein E (APOE) ε4 status or plaque pathology alone. By contrast, the combined effects of Braak stage, APOE status, and age at visit were strongly correlated with the trajectory of EMC, EFC and GCS performance over time. These data suggest that age and APOE ε4 status, rather than Alzheimer\u27s disease-related pathology, play a more prominent role in the trajectory of cognitive decline over time in this elderly nondemented population. However, the findings reported require confirmation in a larger cohort of cases