Parallel and distributed processing in high speed traffic monitoring

This thesis presents a parallel and distributed approach for the purpose of processing network traffic at high speeds. The proposed architecture provides the processing power required to run one or more traffic processing applications at line rates by means of processing full packets at multi-gigabits speeds using a parallel and distributed processing environment. Moreover, the architecture is flexible and scalable to future needs by supporting heterogeneous processing nodes such as different hardware architectures or different generations of the same hardware architecture. In addition to the processing, flexibility, and scalability features, our architecture provides an easy-to-use environment with the help of a new programming language, called FPL, for traffic processing in a distributed environment. The language and its compiler come to hide specific programming details when using heterogeneous systems and a distributed environment.UBL - phd migration 201

Access to and utilization of dental care services among children with special health care needs in the United States

OBJECTIVE: To evaluate access and utilization of both preventive and other dental care services among Children with Special Health Care Needs (CSHCN) in the US in 2005 and 2009. METHODS: We analyzed data for 81,082 CSHCN from the National Survey of Children with Special Health Care Needs (NS-CSHCN) 2005 and 2009. The three main dependent variables were: access to and utilization of dental care, and health insurance status. The independent variables were: gender, age, race/ethnicity, type of insurance, number of criteria met on the screener tool, federal poverty level (FPL), family structure, language, family work life, financial burden and out-of-pocket expenses. Bivariate and multivariate weighted analyses were conducted to evaluate the study outcomes. RESULTS: We found that CSHCN had a high degree of access and utilization of the dental care system in the US. In 2005, 98.2% and 99.03% of CSHCN had “very good to good” access to preventive dental care and other dental care, respectively, and in 2009, the access was 98.1% and 98.7% for both services, respectively. Further, in 2005, 92.9% and 90.4% “fully utilized” preventive dental care services and other dental care, respectively, while 91.9% and 84.7% of CSHCN “fully utilized” both services respectively in 2009. Barriers to access dental care were commonly seen among CSHCN of an older age (5-17 years old), other Non-Hispanics, those from low-income families, with complicated health conditions, living with single mothers, who were uninsured or publically insured, and having family out-of-pocket expenses of more than $250 for their health services. Low levels of utilization were found among non-Hispanic Blacks, Hispanics and other Non-Hispanics CSHCN, from low-income families, with complicated health conditions, who were uninsured or publically insured, having family out-of-pocket expenses of more than$250 for their health services and had other unmet specialist care needs. Hispanic CSHCN from low-income families were more likely to be uninsured. Family work life and family financial status were both significantly associated with access and utilization of dental care services in 2005 and 2009. CONCLUSION: Although the results of this study show that, in 2005 and 2009, CSHCN accessed and utilized both preventive and other dental care services at a high level, disparities still exist among some CSHCN

FACTORS THAT INFLUENCE BREAST CANCER DIAGNOSES IN VIRGINIA WOMEN 40-64 YEARS OLD WHO UTLIZED THE EVERY WOMAN’S LIFE PROGRAM 1998-2012

This dissertation examines sociodemographic determinants and preventive health behaviors among women 40-64 years of age who participated in the Virginia Department of Health’s Every Woman’s Life breast cancer screening program. Utilizing secondary data, this research sought to explore patterns of breast cancer incidence, mammography screening utilization and sources of health information among low-income women. The Virginia Department of Health provided a large sample size (N=34,942) on which to perform binary logistic regression analyses. Sociodemographic determinants and preventive health behaviors were analyzed as potential influencing factors in the diagnosis of breast cancer, the stage at the time of diagnosis and source of health information. Additionally, frequencies across all variables were explored and compared to state and national statistics, where appropriate. In this study, cancer and preventive health disparities reported in the literature persist within this sample of low income women. The binary regression analyses demonstrated that there are marginally worse outcomes for each level of decreasing income. Those with the most “wealth” were less likely to be diagnosed with invasive breast cancer and were more likely to obtain health information from a health provider. Additionally, it was determined that those without a prior mammogram were more likely to be diagnosed with breast cancer and the cancer was more likely to be invasive. The aims of the Every Woman’s Life program align with Affordable Care Act (2010) to strengthen health care and eliminate cancer disparities. Highlighting program characteristics and presenting these analyses allows policymakers, program officials and practitioners an opportunity to tailor health promotion activities while considering all tiers of influence

FIT-PROLOG : a functional/relational language comparison

The programming languages FIT and PROLOG are compared as examples of functional and relational programming, respectively. This leads to some proposals concerning both languages. As an introductory tutorial, PROLOG facts, questions, variables, conjunctions, and rules are reformulated in FIT. A natural equivalence between functions and relations is exploited for their interchangeable FIT use. An ESCVAL operator is proposed which causes relation calls to return values of request variables and thus permits their function-like nesting. Function calls with request variables are introduced, showing a sense in which FIT functions are more general than PROLOG relations. Higher-order functions and relations are demonstrated to be available in FIT but not in PROLOG. PROLOG structures and FIT compounds differ mainly in the fixed arity of the former and the variable length of the latter. FIT's compounds can also be interpreted as function calls that return themselves in normalized form. Pattern matching in PROLOG [FIT] treats list heads and tails asymmetrically [symmetrically] and doesn't [does] allow for non-deterministic results. While PROLOG generalizes pattern-data matching to pattern-pattern unification. FIT generalizes it to adapter-data fitting. PROLOG's Horn clauses in FIT become implicit fitters: Facts become special implicit adapters and rules become special implicit transformers; for PROLOG II constraints, transformers with LOCAL bodies or invocation adapters with COM[POSE-TRA]FO expressions can be used. While PROLOG interprets clauses in textual order, FIT interprets them in a specificity order which is modifiable by a SECURE operator. Although PROLOG's cut operator is not used in FIT, a proposal is made to distinguish the specification of clause ordering [by FIT's SECURE operator] and the specification of clause abandoning [by an EXCLUSIVE operator corresponding to 'initial'-restricted cuts]. EXCLUSIVE-marked COMFO-constrained rules are then used for functional and relational representations of guarded commands. A comparison of the list processing capabilities of both languages exemplifies how FIT's adapters can make relational programming more concise than PROLOG’s Horn clauses. The representation of sets as lists without duplicates leads to difficulties with PROLOG's standard intersection and union predicates, which can be overcome by representing them as the self-normalizing CLASS data structure in FIT. Possible reasons for the poor readability of Warren's PROLOG serialise predicate are discussed and an alternative FIT function is formulated which shows the inherent simplicity of this problem. McDermott's PROLOG quadrat predicate is transformed into a more concise and readable ESCVAL form, which in turn is transformed into a corresponding FIT ESCVAL form and into a functional FIT form. Fermat's equation is formulated relationally, showing that for principal reasons some relations can not be used in all ways allowed by PROLOG's notation, a problem that does not arise in a corresponding functional FIT formulation